PSI Journal 2015

PSI 2015

PSI ISSUE V

2015

PSI

The McGill Psychology Undergraduate Journal

Issue V March 2015

1

McGill Psychology Student´s Association

PSI ISSUE V

2015

Foreword Dear Reader, As many of you are probably aware, the Psychology Department at McGill exists under both the Faculty of Arts and the Faculty of Science. Yet, the department is far from divided; this speaks rather to the multifaceted nature of psychology both here and around the world.

This year’s edition of PSI highlights the diversity of psychological research at McGill. The research ranges from studies of disgust sensitivity in a pain laboratory, to the role of cultural identity in the motivations of students attending university. This year we have peppered the dense (but fascinating!) text with illustrations, for the enjoyment of Gestalt fans.

The potential for psychology to improve our lives–through mental health initiatives, education reform, and disease prevention–is astounding. Equally important is the insight psychology can give us into the forces that shape our own behaviours and emotions. My hope is that the research highlighted in our journal speaks to the impact psychology has on a global and micro scale. I am inspired to know that the current and future research of our undergraduates has the potential to shape our lives for the better.

Sincerely, Tess Wrobleski Journal Coordinator

McGill Psychology Student´s Association

2

PSI ISSUE V

2015

Acknowledgments The PSI Editorial Committee would like to thank: The Arts Undergraduate Society for providing us with the funding that has allowed us to print this journal.

The executives of the McGill Psychology Student’s Association for their ongoing support.

Nina Wang, for taking on the challenge of managing the PSI Blog.

Charlene Zhang, for her photographs of the editorial board members.

3

McGill Psychology Student´s Association

PSI ISSUE V

2015

Journal Committee 2014-2015 Journal Coordinator Tess Wrobleski Managing Editors Andrew Samo Catherine Guo Editor-in-Chief (Fall) Vanessa Sunahara Editorial Board Andrew Samo Catherine Guo Emma Stewart Hasagani Tissera Jack Lam Jeremy Laporte Nikita Mohan Portia Proctor Rebecca Kahn Saloni Singh Sara Perillo Sonja Chu Illustrator and Cover Art Eleanor Milman

McGill Psychology Student´s Association

4

PSI ISSUE V

2015

Contents C ognition an d Att ention

Intelligence impacts judgements in Biconditional Discrimination Settings • 06

Elsa Haoyou Yu

Flashing Faces: Is Social Orienting Automatic? • 17 Jaclyn Kirstiuk

Adolescents with type 1 diabetes are less likely to use spatial strategies when navigating in a virtual environment compared to their matched control • 28 Stephanie Polchtchikov

Pain

Disgust Sensitivity and Vasovagal Reactions during Exposure to Blood, Injection, and

Mutilation Stimuli • 38

Sophie Béland Perceived Injustice and Pain Outcomes in a Healthy Student Sample • 51 Tudor Vrinceanu

He alth

The Effect of Meditation Practice on Daily Mindfulness and Psychological Well-being • 61 Kimberly Carrière

Behavioural Modification Paper: Pathological Skin Picking • 71 Isabella Parks

C hi ld De velopment

Dropping Out of High School: Conditions, Causes and Potential Solutions (essay) • 78

Ariele Peterson The Relationship between Perinatal Maternal Mental Illness and Theory of Mind Development in their Children Ages 2-3 • 85 Vivian Gu

S o ci a l and Cu ltur a l

The Cross-Cultural Construct of PTSD Diagnoses: Implications for Refugee Populations

(essay) • 97 Beth Mansell Coming to Canada: Investigating the Effect of Cultural Saliency Among Bicultural sub- Saharan Africans • 105 Marilyn N. Ahun

5

McGill Psychology Student´s Association

PSI ISSUE V

2015

Intelligence impacts judgements in Biconditional Discrimination Settings Elsa Haoyou Yu* Supervisor: Andrew Baker *email: elsastudy2014@gmail.com

Abstract

In 2013 at McGill University, Canada, a recent study examined possible relationships between performance IQ scores and performance in a conditional learning test (Baker et al.). The results showed that participants who scored higher on the IQ tests were better at judging compound stimuli. Most importantly, the advantage of individuals who scored highly on the IQ test (the high intelligence group) was particularly strong when rule learning was required. This finding suggested that rule acquisition skills might have mediated the correlation between IQ scores and learning efficiency. In their study, Baker et al. employed a patterning discrimination design where stimuli predicted a different outcome when grouped together as opposed to when presented individually. However, whether high-intelligence individuals are better at associative learning in other settings remains unknown. To further examine the generality of the impact of intelligence on learning, we conducted a follow-up study using biconditional discriminations. 79 undergraduate students were recruited from McGill University, Canada. Resulting observations were that participants with higher scores on the composite measures of intelligence performed better in both simple and biconditional discriminations. This was consistent with the previous conclusion that IQ positively correlated with associative learning. However, neither the low nor high IQ group showed any evidence of internalizing the underlying biconditional rule. Therefore, we have good reasons to believe that rule learning skills do not fully explain the association between intellectual abilities and learning performance. These findings also challenge the propositional theories, which advocate that no associative learning could take place without forming explicit propositions. From a long-term perspective, our study will not only help us to better understand the role of intelligence in learning, but will also open new windows to studying the nature of human learning.

Keywords: intelligence; IQ; biconditional discrimination; pattern discrimination

Cognition and Attention

6

PSI ISSUE V Introduction The nature of human learning is by far one of the most controversial and intensely debated topics in cognitive psychology; it has evoked a century long struggle among researchers. Nonetheless, consensus seems to have been reached upon the role of learning as an important component of intelligence. Snydeman and Rothman (1988) define intelligence as the “ability to learn.” Similarly, Jensen (1989) believes that individual differences in learning can be thought of as differences in intelligence. While learning and intelligence are clearly closely related, how they impact each other remains unclear. First, researchers disagree as to which construct of intelligence drives its connection with learning. This is further complicated by the possibility that there are different types of learning.

The intention of this paper is to integrate three fundamental aspects of findings from our recent studies. The primary goal is to examine the impact of Performance IQ and fluid intelligence (Gf) on complex associative learning tasks. These tasks include a positive and negative pattern discrimination, in which a compound of two cues signals a different outcome than the individual elements of the compound, and a biconditional discrimination, in which compounds of different configurations of the same elements signal different outcomes. We will further discuss the role that rule acquisition, working memory and processing speed play in these learning tasks. Last but not least, we will report a study on biconditional discrimination that provides new evidence that human learning can be, at least partially, achieved without forming explicit propositions.

Early findings from many laboratory studies have shown only low to modest correlations between learning and intelligence. For example, simple pairedassociate tasks show a correlation of no more than 0.3 with IQ (Mackintosh, 2011). This suggests potential independence of associative learning and general intelligence; however, recent studies evince that relations between intelligence and associative learning depend on the type of learning task. This phenomenon was illustrated by Williams and Pearlberg’s 2006 study, in which they assessed learning using a three-term contingency test (a task in which the participant is required to make three different responses to every stimulus). The participant was then tested on the outcome that followed each stimulus-response pair. The authors directly compared this test with two frequently used laboratory learning tasks – free recall and paired-associate learning. They found that three-term contingency performance correlated significantly with

fluid intelligence (Gf) as measured by Raven’s Matrices scores, while paired-associate learning and free recall did not.

This lead us to wonder, why do specific learning tasks vary in their relationship to measures of intelligence? One possible interpretation of the failure of free recall and paired-associate learning to correlate significantly with Gf is that the complexity of the material determines how well the learning test predicts general ability (Estes, 1970). Specifically, cognitively demanding tasks are more strongly related to IQ scores, while tasks such as free recall and paired-associate do not correlate strongly with intellect. The three-contingency task is more complex in that the participant has to withhold an immediate response and use other cues or information to “decide” what is correct.

This type of cognitive “decision making” is also involved in the negative and positive patterning discriminations and biconditional discriminations used in our studies. All three tests are similar in that all the cues have multiple meanings. In positive and negative patterning discriminations, each of the two conditional stimuli (CS) individually signals an outcome whereas the compound of those same stimuli signals the opposite outcome. For instance, in positive patterning, two single stimuli are nonreinforced (A−, B−) whereas the compound of the same stimuli is reinforced (AB+). In negative patterning, the situation is reversed – elements are reinforced (A+, B+) whereas the compound is nonreinforced (AB−). In a biconditional learning test, stimuli are presented as pairwise compounds, half of which are reinforced and half not. If compounds AB and CD are reinforced (+), AD and BC will always be nonreinforced (–). Therefore, each element stimulus (A, B, C, or D) is presented within one reinforced compound and one nonreinforced compound. Neither negative patterning nor biconditional discrimination can be solved by simply distributing excitatory and/ or inhibitory associative strength among the CS’s themselves. Further cognitive “decision making” is thus required to predict whether a stimulus will be reinforced or nonreinforced.

In 2013, Baker et al. examined the relation between intelligence and performance on positive and negative patterning discriminations. The authors found that prediction accuracy positively correlated with fluid intelligence (Gf) measures. Participants scored generally better in element discriminations than in compounds. For the low Gf group, discriminating positive compounds from negative compounds did not improve with experience in contrast to discriminating individual positive or negative elements. The high Gf group, on the other hand, improved significantly and outperformed their counterpart in compound

7

Cognition and Attention

PSI ISSUE V discriminations by the end of the test. In short, both low and high intelligence groups may have performed equally well in the individual element versus compound discriminations but differed substantially in learning that the compounds from positive patterning were reinforced and those from negative patterning were not. These findings suggest that intelligence predicts learning performance. Additionally, they indicate that the strength of the relation between Raven’s scores and three-term contingency was not because of the unique characteristics of the task, but rather was due to its complexity and the subsequently high cognitive load.

What attributes of the increase in complexity of the task could drive its stronger association with intelligence? Unfortunately, few studies seem to have effectively addressed this question. Jensen (1998) suggested that individual laboratory intelligence tests probe only a narrow range of abilities. In order to generate a strong correlation between learning and intelligence, one must extract a general factor (intelligence) from a collection of learning tasks. Jensen’s conclusion, however, has been heavily criticized by researchers that have found significant evidence of general learning ability in individual tasks (Malmi, Underwood, & Carroll, 1979; Underwood, Boruch, & Malmi, 1978).

With the knowledge that simple processes of learning associations did not seem to relate to intellect under all circumstances, we proposed an alternative method to increase the magnitude of the relationship between IQ and associative learning in the positive and negative patterning discrimination study. The alternative method was to assess the ability of “learning to learn”.

“Learning to learn”, also referred to as transfer, is the practice of applying the knowledge gained in a training context to a similar yet different setting. In order to test their ability of “learning to learn”, we gave participants a series of transfer questions, where the outcome of the compound CS’s was masked by a question mark throughout the test. Positive transfer, for instance, was composed of two nonreinforced (–) element stimuli (A–, B–) and a compound of the same stimuli with unknown outcome (AB?). Similarly, in negative transfer, instead of A+, B+ and AB–, participants would now only see A+, B+ and AB (?). Transfer trials were designed to assess rule learning, for they could not be solved by mere memorization. Without any feedback to reveal whether the given prediction was correct, the only way of solving transfer problems was to infer the rule that compounds always predicted the opposite outcome to elements. Learning the rule was thus essential to task performance.

Further analyses revealed that fluid intelligence had no consistent main effect on training trials. On the contrary, in transfer trials, participants who scored higher

on Gf substantially outperformed their counterparts.

Interestingly, the degree of rule acquisition as assessed by retrospective self-reports correlated with scores on Letter Series (another standard measure of Gf). Thus, there were, good reasons to argue that superior rule learning ability may have mediated the correlation between high IQ and better performance in positive and negative patterning discriminations. We wished to further investigate the relationship between rule learning, discrimination performance and intelligence in the present study.

Another approach largely employed in studies of intelligence and associative learning is to assess the impact of subcomponents of general intelligence on learning performance. Processing speed and working memory have attracted the most attention in the cognitive literature. Jensen (1989) argues that the observed correlations between individual differences in learning can best be understood from the viewpoint of information processing theory. Unsworth (2010) suggests that many aspects of memory, including encoding, retrieval and monitoring the products of retrieval are also important for learning, and the variance in Gf accounted for by working memory should also be related to learning. Analyses from Williams and Pearlberg’s study (2006) indicate that the threeterm contingency correlates with Gf even when other mechanisms such as working memory are controlled.

Tamez later contradicts these findings and uncovers a significant correlation between the verbal three-term learning task and working memory (Tamez et al. 2008).

She later goes on to advocate that associative learning mediates the correlation between working memory and Gf (Tamez, Myerson and Hale, 2012).

The study on positive and negative patterning reported no significant main effect of processing speed on prediction accuracy. Both measures of working memory – Sentence Span and Dot Matrix, on the other hand, correlated with overall correct response (Baker et al. 2013). This was consistent with the belief that working memory plays a role in both learning and intelligence.

Thus, another goal of our current study was to examine whether speed and memory would similarly impact biconditional discriminations as it does to positive and negative patterning discriminations.

Method Participants Undergraduate students (68 female, 11 male, mean age = 20.4, S.D. = 1.4) participated through the McGill Psychology Department Participant Pool to obtain course extra credits. Previous involvement in research

Cognition and Attention

8

PSI ISSUE V in the same laboratory was the only criterion for change from question to question. Six minutes were exclusion. Upon entering the lab, all participants were allowed for this task. told of their right to discontinue testing at any time Mental Rotation. Mental Rotation assessed during the experiment; none chose to do so. visual-spatial ability. Participants viewed a drawing of a given object and then tried to find the same object in a set of four other dissimilar objects. The only difference Materials The experimental session contained a battery of between the original object and the answer would be intellectual tests and a biconditional learning task. that they were presented at different virtual rotations.

Tests were administered in groups and presented The test was divided into two parts, each requiring three to participants in the same fixed order. The entire minutes.

Visual Matching. The last paper-based intellectual procedure required 80 to 100 minutes; the first 50 to 60 minutes were used for the pencil and paper testing, after test was called Visual Matching. It contained rows of which 30 to 40 minutes were spent on the computer- numbers with two repeated numbers in each row. As based tasks. On arrival in the laboratory, participants a speed task, Visual Matching required participants to were asked to sit in front of the computer and given a circle the repeated numbers as fast as possible within consent form. Both oral and written instructions were the three-minute limit. After completing the written provided for each task, with an additional instruction tests, participants performed three computerized tasks, booklet for Raven’s Advanced Progressive Matrices. The including two working memory tests – Sentence Span and Dot Matrix – and the biconditional discrimination tests were timed individually.

The written intellectual tests consisted of task. The tests were programmed in RealBasic and 6 subtests given in the following order – Raven’s presented to participants on Mackintosh desktop Advanced Progressive Matrices, Coding Task, Mental computers. Each memory task took approximately 15 ‘Paper Folding’ Task, Letter Series, Mental Rotation, minutes.

Sentence Span. The first memory task performed and Visual Matching. was the Sentence Span task. Participants were tested on Raven’s Progressive Matrices. The Raven’s test –first published in 1938 – has been largely accepted their ability to comprehend text and at the same time as the prototypical measure of fluid intelligence (Gf) remember new pieces of information. Specifically, we (Raven, 1938). (Mackintosh, 2011). It is a nonverbal asked participants to read a sequence of sentences and group test of fluid intelligence in which the subject is judge whether each was true. Following each sentence, asked to identify the missing element in each test item a letter briefly appeared. The goal was to remember all to complete the pattern. All patterns used in our study the letters in the correct order. A trial might contain were presented in the form of 3x3 matrices. 15 minutes between four and eight sentences and each sentence would remain on the screen for only four seconds. were allowed to complete the 12 items.

Dot Matrix. Following the sentence span task, Coding. The Coding Task assessed processing participants performed the Dot Matrix task. A matrix speed. Participants observed boxes with numbers on equation was presented on each trial of the Dot Matrix the top of the sheet; each of the numbers was paired task.

Participants first verified whether the equation with a special symbol. The task was to transcribe the numbers into special marks and fill in as many empty was correct. Following each matrix equation, a grid containing a dot was briefly displayed. The task required boxes as possible within 90 seconds.

Paper Folding. Following the Coding Task was participants to recall at the end of each trial which the Mental Paper Folding task, which consisted of 30 grid spaces contained the dots presented earlier. Each patterns that could be folded into figures. Each question question consisted of a sequence of between two and had four figures to choose between. Participants were five equation-grid pairs.

Biconditional discrimination. The biconditional asked to decide which one of these figures could be discrimination task began with a brief review of the made from the pattern shown. They were given 12 instructions for the study on the computer screen. minutes for this test.

Letter Series. Together with Raven’s Matrices, Participants were instructed to learn about the Letter Series constituted the measurement of fluid associations between different pictures of foods and the intelligence. This exercise involved looking for patterns presence of a picture of a spider. Participants indicated across sets of letters. Each question had a total of five whether or not they expected the presence of the spider letter groups. Four of the five groups followed a certain by pressing keys on the keyboard. The “yes” key was rule. The goal was to identify, for each question, the randomly assigned to either A or L. Following each letter group that did not follow this rule. The rule could response, the system would reply by either “Correct +1 point!” or “Incorrect”. A salient picture of a red spider

9

Cognition and Attention

PSI ISSUE V represented the presence of the spider and the text “No Spider” indicated the absence of the spider. All testing cues were presented for a fixed duration of 1.5 seconds.

There were twenty kinds of foods throughout the test, including animal based, plant based, fruits and desserts. Different foods were used in Phase I and II. For further analyses, compounds used in Phase I will be referred to as AB+, AD–, CD+, CB–, EF+ and GH–, while cues appeared in Phase II as IJ+, IL–, KL+, KJ–, MN+ and OP– (see Table 1). In each phase, each compound was presented 16 times in random positions.

Transfer and Metatransfer. We introduced transfer and metatransfer trials to assess whether participants could learn the biconditional rule that if an individual food predicted one outcome (e.g. spider) in one compound configuration, it predicted the other outcome (e.g. no-spider) in the other configuration. In the transfer test, foods M, N, O and P from Phase II were each paired with an additional food (MQ, NR, OS, PT).

If, for example, a food from a formerly reinforced compound (e.g. cue M from Table 1) was presented in a new compound, the participant should deduce that this novel compound (e.g. MQ) should not be followed by a spider. Alternatively the participant might simply transfer his or her impression about the cue (e.g. M) that had been learned in Phase II and think that the novel compound was reinforced, indicating that he or she did not generalize the biconditional rule. For the metatransfer test, the novel elements Q, R, S, and T were then combined to form the metatranfer questions (QR? ST?). The predictiveness of the elements had been inferred in the transfer test, and two positive cues combined in a compound (e.g., ST) should be inferred to not be predictive of the spider and vice versa. On each of these trials, participants were asked to use a scale ranging from –100 to +100 to indicate the strength of association between the compound cues and the probability of the presence of a spider.

The elements E, F, G and H from Phase I, analogous to M, N, O and P in Phase II, were not employed in transfer sessions. Trials involving these cues were designed to ensure that the two phases matched for the number of stimuli, the number of trials, and the reinforcement rate. Furthermore EF+, GH–, MN+ and OP– also served as simple discriminations insofar as they were either completely reinforced or completely nonreinforced. Performance on these simple tasks therefore provided a baseline rate for assessing the relative difficulty of the biconditional discriminations.

At the end of the experiment, we assessed participant’s rule acquisition by asking them to write down whether they noticed any rule from the spider task and, if they had deduced a rule, to explain what it was. We then scored the comments on a scale of 0 to 2,

based on the following criteria: “0” = no expression of rule learning / expression of propositions based on features other than the patterning of the cues “1” = somewhat understanding of the relation between reinforcement and the patterning of the cues with no evidence of learning the biconditional rule “2” = full understanding of the biconditional rule Results Hypothesis 1. Performances on the biconditional trials rather than simple trials correlate with the composite measures of Performance IQ or fluid intelligence.

Standard scores (z-scores) were computed for each participant based on his or her performance on individual intellectual tests. We then averaged the z-scores across each pair of sub-tests to assess the participant’s ability on sub-components of intelligence, namely fluid intelligence (Gf), processing speed, visual spatial ability, and working memory. The average z-score across all sub-constructs was then calculated to provide the participant’s Performance IQ score. Participants were then categorized into high and low groups by median split based on these sets of standard scores, e.g. high fluid intelligence group vs. low fluid intelligence group.

The participants’ predictions were grouped into four blocks of four trials. To set up a criterion for evaluating the performance on the learning task, we used the difference in the proportion of predictions of the presence of the spider between the reinforced and nonreinforced trials. That is, CS+ minus CS–.

Participants, regardless of their overall Performance IQ, improved in the biconditional discriminations over trial. As shown in Figure 2, in general, the disparity between responses on CS+ and CS– increased over time. The two phases differed in that Phase I showed no significant difference between the high and low Performance IQ groups, while during Phase II participants with higher Performance IQ displayed a steeper learning curve than the low group.

A 2 x 2 x 4 analysis of variance (ANOVA) was carried out, with repeated measurements over two factors – Phase and Trial Block. The third independent factor was participants’ Performance IQ scores and the dependent variable was their learning performances on the biconditional discriminations. The ANOVA suggested a significant Phase x Trial Block x Performance IQ effect; F(3, 77) = 2.877, p < 0.05. Further t-tests (2-tailed) revealed a substantial group difference during Phase II, where participants from the high group significantly

Cognition and Attention

10

PSI ISSUE V outperformed in Trial Blocks 2, 3 and 4; the minimum t (77) = 2.33 over Trial Block 2, p < 0.05. It is thus suggested that the high performance IQ group improved faster than their counterpart during the second phase and outperformed throughout the phase. The impact of the composite scores of intelligence seemed to be particularly robust in Phase II compared to Phase I. A similar pattern emerged when participants were grouped by median split of fluid intelligence (Gf).

Although both groups seemed to predict the presence or the absence of the spider more accurately with experience, the high Gf group improved more in Phase II, excelling beyond its counterpart during the second half of the test (see Figure 3). The mixed 2-way ANOVA showed a significant interaction between Gf and Phase on the biconditional discriminations; F(1, 77) = 4.646, p < 0.05. Post-hoc t-tests indicated that during Trial Block 3 of Phase II there was a significant difference in performance between the high and low Gf groups; t (77) = 2.03, p < 0.05.

Some studies such as Williams and Pearlberg’s three-term contingency test (2006) have shown that intelligence only associates with complex associative learning tests and not simpler learning tasks.

Interestingly, our analyses suggested that participants with high performance intelligence not only did better in the biconditional discriminations but were also better in learning the simple compounds. That is, higher scores of Performance IQ predicted better performance in simple discriminations. Figure 4 shows that the supremacy of high Performance IQ group over the low group was more pronounced in Phase II, which is consistent with our findings concerning the biconditional discriminations.

During Phase II, participants with high Performance IQ more accurately discriminated the positive compounds from the negative and showed greater CS+ minus CS– values compared to their counterparts. A 2 x 2 x 4 ANOVA was carried out, with Phase, Trial Block and Performance IQ as the independent factors and the performances on simple discriminations as the dependent variable. The ANOVA revealed an interaction between Trial Block and Performance IQ on the simple discriminations; F(3, 77) = 3.631, p < 0.05.

According to post-hoc t-tests, participants with higher Performance IQ did significantly better during Trial Block 4 of Phase I and Trial Blocks 2 and 4 of Phase II; the minimum t (77) = 2.01 over Trial Block 4 of Phase I, p < 0.05. In conclusion, not only was Performance IQ predictive of learning on biconditional discriminations, it was also correlated with performance on simple discriminations.

Consistent with these findings concerning overall Performance IQ, fluid intelligence was also associated with superior performance on simple

discriminations. As Figure 5 suggests, although there was no significant difference between the high and low Gf groups during the first phase, participants with high Gf seemed to learn much faster from the beginning of the second phase and they maintained their superior performance towards the end of the test. According to the ANOVA, scores of fluid intelligence interacted with both phase (F(1,77) = 4.47, p < 0.05) and Trial Block (F(3, 75) = 3.70, p < 0.05). Post-hoc t-tests suggested that students who scored higher on fluid intelligence did better in discriminating the simple cues during the second and the fourth Trial Blocks of Phase II; the minimum t (77) = 2.36 over Trial Block 4, p < 0.05.

In short, fluid intelligence predicted both simple and biconditional discriminations.

Hypothesis 2. Rule-acquisition skills predict performance in biconditional leaning.

Transfer and metatransfer tests assessed whether participants could learn and apply the biconditional rule that if an individual cue predicted one outcome (e.g., spider) in one cue configuration, it predicted the other outcome (e.g., no spider) in the other configuration.

This was done by taking the elements from the simple discriminations from the second phase and presenting them in a compound with a novel food. Participants were then asked what was the chance of the new compound being followed by a spider. If, for example, a food from a formerly reinforced compound (e.g., cue M from Table 1) was presented in a new compound, the participant should deduce that this novel compound (e.g., MQ) should not be followed by a spider. Alternatively, the participants might simply transfer their impression about the cue that had been learned in Phase II, indicating that they did not generalize the biconditional rule. We also did a metatransfer test where the novel cues whose predictiveness had been inferred in the first transfer test were combined in a second transfer test.

For instance, two inferred positive cues combined in a compound (e.g., ST) should be inferred not to predict the spider.

We averaged participants’ ratings on the strength of association between the transfer cues and the probability of the presence of a spider. As Figure 6 shows, both compounds MQ– and RN–, which according to the biconditional rules should be associated with the absence of the spider, had average positive ratings of 20 – 30 of being reinforced. Similarly, both positive compounds OS+ and TP+ were rated as nonreinforced, being associated with the absence of the spider with a 30 – 35% chance. In the metatransfer test, compound QR, according to biconditional reasoning, predicted the presence of the spider (+) and RN the absence of the spider (–); ST predicted the absence of the

11

Cognition and Attention

PSI ISSUE V spider (–) and TP predicted the presence of the spider (+). None of the elements Q, R, S, or T had previously occurred in the training period and participants did not differentiate the positive compound from the negative compound (see Figure 6). Further analyses did not generate any significant effects of Performance IQ or Gf on performance in transfer tests. There seemed to be little difference between high and low IQ groups in transfer trials, either negative or positive.

Rule acquisition was further assessed by an openended question. Of the 79 participants, only one student was able to explicitly describe the biconditional rule. Five students scored 1 because they indicated, to a certain extent, patterning recognition but showed no evidence of identifying the biconditional rule. The remaining 73 participants did not report any relevant rule learning and scored 0. Because of the lack of variability in scores of rule learning, no statistical difference was detected between the low and high IQ participants. Therefore, we have good reasons to believe that rule learning skills do not fully explain the association between intellectual abilities and learning performance.

Discussion

acquisition is crucial for tests of fluid intelligence–such as Raven’s Matrices and Letter Series (Mackintosh, 2011)–superior rule learning may also be the reason why people with higher intelligence outperform in associative learning.

Our current analysis of the biconditional discrimination provides a different image concerning rule acquisition and associative learning. Performance on the transfer questions indicated that the participants seemed to generalize the training polarities of the cues rather than transfer the rule, which suggested difficulty in rule deduction. Despite the apparent absence of rule acquisition, this study observed sizable disparity between the high and low Performance IQ groups in discrimination performance. In other words, the association between IQ and associative learning remained robust even though no correlation between IQ and rule acquisition (transfer tests) could be found. While the previous study on positive and negative patterning indicated that high intelligence is advantageous when rule learning is essential, the current biconditional study shows that intelligence may also influence performance on tasks that do not depend on rule learning.

Rule acquisition and Propositional Theory These results concerning rule learning have meaningful implications on understanding the nature of human learning. Mitchell et al. (2009) propose that “learning does not take place outside of awareness; it requires cognitive resources, and it is affected by verbal instructions, rules, and deductive reasoning processes.”

Essentially, the propositional approach suggests that awareness is important or even necessary for learning and learning is anything but automatic or implicit.

Our results contradict Mitchel’s claims. That is, the majority of the participants seemed to have achieved better-than-chance performance without explicit awareness of the correct rule. In the biconditional setting, both verbal and non-verbal measures of rule acquisition indicated failure of rule learning. One may argue though that participants could have benefited from different propositional solutions other than the biconditional rule. Inability to articulate the single correct rule does not mean that participants did not form alternative propositions that may have resulted in their less than Rule Learning and Associative Learning perfect but better-than-chance performance. Indeed, For the previous study (Baker et al., 2013), the among those who scored 0 in the open-ended question, advantage of high fluid intelligence was most obvious some participants seemed to have followed their own on transfer trials, where rule learning was required. rules. Some relied on the colours of the foods, others the Participants with lower scores on Letter Series (a test flavour, or the number of the items, etc., despite the fact of fluid intelligence) seemed to have greater difficulty that these stimulus dimensions were counterbalanced. in transferring associations learned from training trials For instance, one student wrote: “…the only rule I could onto the new compounds. If accurate and rapid rule find was that the spider would appear if the two foods Cognition and Attention 12 Performance Intelligence, Biconditional Discrimination and Simple Discrimination Our current study on biconditional discriminations provides additional insights on how high Performance IQ relates to better learning. Participants performed better on the simple discriminations than the biconditional discriminations, which implies that the biconditional discriminations were harder to learn. Notably, higher Performance IQ accompanied superior performance in both biconditional and simple discriminations. The high group began to reliably outperform during the second phase of the task and the difference between the two groups kept growing throughout this phase. In short, higher Performance IQ appeared to be beneficial to simple and biconditional learning. This is consistent with the belief that intelligence has a positive impact on associative learning; however, it challenges the idea that only complex associative learning tasks correlate with intellect.

PSI ISSUE V would be eaten together and taste good.” Nevertheless, even when the criterion for rule acquisition is extended to any articulation of propositional reasoning, be it correct or incorrect, the results still do not support Michel’s propositional theory. 19 out of 73 participants previously counted as the non-rule learners left blanks in the comment section. 12 or more expressed explicitly that they did not find any rule, among whom one said: “I know I made other associations, I’m just not explicitly aware of what they are.” This suggests that the participants did not universally form either a correct or an incorrect propositional representation of the task even though they did “solve” it.

Although propositional reasoning may be involved in many aspects of learning, it is clearly not the exclusive mechanism behind all types of associative learning. Assuming people are able to articulate their awareness of propositional rules, as we did in our study, awareness appears to be a poor predictor of how well one learns or whether he or she can learn at all. The implications of these propositional theories are again hard to reconcile with propositional reasoning accounts.

Limitations and further investigations Multiple regression analyses should be performed on the present data set to clarify the contributions of the various constructs of intelligence. Also, to determine whether a biconditional discrimination task could better differentiate between high versus low IQ than the simple discriminations, we suggest further analyses on effect size. In brief, we would like to present this report to provide a stepping-stone for further investigations.

memory and processing speed, Intelligence, 37, 374 382.

Malmi, R. A., Underwood, B. J., & Carroll, J. B. (1979). The i

nterrelationships among some associative learning tasks. Bulletin of the Psychonomic Society, 13, 121– 123.

Mitchell, C. J., Houwer, J. D., & Lovibond, P. F. (2009).

The propositional nature of human associative learning. Behavioral and Brain sciences, 32, 183-246.

Tamez, E., Myerson, J., & Hale, S. (2012). Contributions of

associative learning to age and individual differences

in fluid intelligence. Intelligence, 40, 518-529.

Tamez, E., Myerson, J., & Hale, S. (2008). Learning, working

memory, and intelligence revisited. Behavioural Processes, 78, 240-245.

White, P. A. (2011) Causal judgements about two causal

candidates: accounting for occurrences, estimating

strength and the importance of interaction

judgements. Journal of Cognitive Psychology, 23(4), 485-506.

Whitlow, J. W., Jr. (2013). Negative Patterning and

Biconditional Discriminations in Human Causal

Reasoning: A Second Look. American Journal of Psychology, 126(1), 11-21.

Williams, B. A., & Pearlberg, S. L. (2006). Learning of three term contingencies correlates with Raven scores, but

not with measures of cognitive processing.

Intelligence, 34, 171-191.

References Estes, W. K. (1970). Learning theory and mental development.

New York, NY:Academic Press.

Harris, . A., & Livesey, El J. (2008). Comparing patterning

and biconditional discriminations in humans.

Journal of Experimental Psychology: Animal Behavior Processes, 34(1), 144-154.

Harris, J. A., Livesey E. J., Gharaei, S., & Westbrook, R. F.

(2008). Negative patterning is easier than a

biconditional discrimination. Journal of

Experimental Psychology: Animal Behavior Processes,

34(4), 494-500.

Jensen, A. R. (1989). The relationship between learning and intelligence. Learning and Individual Differences.

1(1), 37-62.

Kaufman, S. B., DeYoung, C. G., Gray, J. R., Brown, J.,

& Mackintosh, N. (2009). Associative learning

predicts intelligence above and beyond working

13

Cognition and Attention

PSI ISSUE V Appendix Table 1 Biconditional Cues: Reinforced & Nonreinforced Phase I Phase II Transfer Metatransfer AB+ IJ+ CD+ KL+ MQ? QR? ADILNR? ST? CBKJOS? EF+ MN+ PT? GHOP+ = reinforced cue, â&#x20AC;&#x201C; = nonreinfoced cue, ? = ambiguous

Table 1. Table 1 summarizes the combinations of foods during Phase I, Phase II, Transfer, and Metatransfer. Each letter represents one kind of food.

Figure 2. Impact of composite IQ on biconditional discrimination performance across trials and phases. Figure 2 compares participants with higher average composite scores on intelligence and those with lower performance IQ scores on biconditional discrimination across phases and trial blocks.

Cognition and Attention

14

PSI ISSUE V

Figure 3. Impact of Fluid Intelligence on Biconditional Discrimination. Figure 3 compares participants with higher fluid intelligence z-scores and those with lower intelligence z-scores on biconditional discrimination.

Figure 4. Impact of performance IQ scores on Simple Discrimination. Figure 4 compares performance on simple discriminations of participants with higher performance intelligence (black circles) and those with lower performance intelligence.

15

Cognition and Attention

PSI ISSUE V

Figure 5. Impact of Fluid Intelligence on Simple Discrimination. Figure 5 compares simple discrimination performance between participants with higher fluid intelligence versus those with lower fluid intelligence.

Figure 6. Performance in Transfer and Metatransfer Tests. Figure 6 illustrates the averaged ratings on the strength of association between the transfer cues and the probability of the presence of a spider.

Cognition and Attention

16

PSI ISSUE V

2015

Flashing Faces: Is Social Orienting Automatic?

Jaclyn Kirstiuk* Supervisors: Dana Hayward, Jelena Ristic *email: jaclyn.kirstiuk@gmail.com

Abstract Social orienting is a shift in human attention that occurs in response to social information. Research has cast doubt on the idea that social orienting is voluntary, but does this mean it is an automatic form of attention? To resolve this question, we paired a gaze cueing task with perceptual load. Perceptual load has been found to interfere with automatic attention; therefore, if social orienting is automatic, the pairing should hinder the typical social orienting effect found in the gaze cueing task. Otherwise, if social orienting is unique, the effect should remain intact across load. Our experiment contained two perceptual load conditions (No Load, High Load) with gaze cues and targets randomly presented in 50% of trials, resulting in four trial conditions: (Q1) cue present, target present; (Q2) cue absent, target present; (Q3) cue present, target absent; (Q4) cue absent, target absent. Further, Q1 was further broken down into: (Q1 Valid) cues that correctly direct attention towards the target and (Q1 Invalid) cues that incorrectly direct attention towards the target. This allowed us to observe any social orienting effect (i.e.

Q1 Valid) and altogether led to 5 total trial types. Finally, we determined whether individual differences in social competence (as measured by the autism spectrum quotient questionnaire ) predicted participantâ&#x20AC;&#x2122;s performance when a valid gaze cue was presented on screen. At a group level, we found no social orienting effects and no effect of eye gaze for either perceptual load condition. At an individual level, however, we found that the presence of eyes, when they correctly indicated the target, facilitated performance of individuals with high social competence and hindered the performance of individuals with low social competence. In sum, our findings failed to determine the attentional form of social orienting, but did exhibit the individual relationship that exists between social competence and whether helpful gaze for an individual is actually helpful or a hindrance.

Keywords: social orienting; perceptual load; automatic attention

17

Cognition and Attention

PSI ISSUE V Introduction

within the cueing task. The first is the informativeness of the cue with respect to the target. When the task is aimed at revealing voluntary attention, the cue informs participants about the location of the target – i.e., it predicts where the target will appear with high certainty (e.g., 80% of the time). When the task is aimed at revealing automatic attention, the cue does not inform participants about the location of the target – i.e., it predicts the location of the target at chance level.

The second variable is the stimulus-onset asynchrony (SOA), which refers to the amount of time between the presentation of the cue and that of the target. This delineates the time course of attention, in that voluntary attention is typically slow to arise (by 300ms) but sustained up to 1000ms, whereas automatic attention is quick to act (by 100ms) but short-lived, subsiding by 300-500ms after the cue presentation. Typically a range of stimulus-onset times between 100 and 1000ms is chosen.

When measuring voluntary attention, the task is designed to activate participants’ top-down processing.

The cue, typically an arrow, is centrally located and predictive of subsequent target locations. Participants are informed about its utility. The typical response time data show faster responses to valid trials as compared to invalid trials, which emerges for targets appearing 300ms after the presentation of the cue (Posner, 1980). This result is indicative of voluntary, top-down processing, because participants are told that the cue is meaningful and are thus using an effortful, more timeconsuming cognitive process to interpret the cue.

When measuring automatic attention, the task is designed to activate participants’ bottom-up processing.

Here, the cue is peripherally located and non-predictive of the target location, meaning the cue only predicts the location of the target correctly at chance level. The typical response time data show that orienting quickly occurs to the cue’s location , starting around 100ms after the presentation of the cue. This is followed by a period where, between 300-500ms, participants actually become faster to respond to invalid targets than valid ones (Posner & Cohen, 1984). These reaction time results are indicative of automatic, bottom-up processing, because participants are told that the cue is non-predictive and are thus are not using any effortful cognitive process to interpret the cue.

While these experimental procedures provided researchers with an ability to test how attention affects processing of simple sensory features, Friesen and Kingstone (1998) were among the first to apply this task to test whether social information, like eye gaze, also influences attention in a similar manner. The authors presented participants with a modified cueing task where a face with eyes deviated to the left or right served as an

Imagine you are talking with a cousin at a family reunion when you notice that your cousin’s gaze has shifted to something behind you. Instinctively you turn your head, and notice your flamboyant great aunt dancing wildly around the room. You then turn your head back to your cousin and both of you smile; the whole exchange taking place without any break in the current conversation.

This example illustrates the power of social orienting: the unique effect social information – such as the direction of a person’s gaze – has on an individual’s attentional shifts. Without it, such everyday-shared experiences would be nonexistent. It is intuitive that human eye gaze is a highly salient, attention-grabbing phenomenon (Kubayashi & Koshima, 1997); but how does it affect attention? In the present study, we set out to determine what characterizes social orienting in terms of its attentional mechanisms.

It has previously been postulated that there are two possible ways in which attention can be engaged, known as voluntary and automatic attention (Jonides, 1981; Posner 1980). Voluntary attention operates when individuals purposefully focus on an object or an event, such as looking at a clock to find out the time. Voluntary attention is considered a top-down process - a process that uses higher-level cognitive direction to encode the sensory input in detail. On the other hand, automatic attention acts as a bottom-up process, in which the sensory information draws attention by its salience, often in absence of higher-level cognitive control.

Automatic attention is at play when someone believes they are alone in a room, and a movement from the corner of their eye causes them to quickly scan where the movement occurred.

In the lab, a computerized cueing task (Posner, 1980) is often used to measure these two types of attention. First, a centrally located fixation cross or dot appears on the screen. This is followed by a cue display, typically directing attention to one of two possible locations. Finally after some time delay, a response target appears, and participants are asked to respond to its appearance as quickly as possible. Responses are typically collected via button press. This sequence results in two types of trials – valid and invalid. On a valid trial, the cue indicates the same location as the target. On an invalid trial, the cue indicates a different location than the one in which the target appeared. If attention is influenced by the cue, participants are faster and more accurate to respond to valid as opposed to invalid trials (Posner, 1980).

Typically, researchers test voluntary and automatic attention by manipulating two variables Cognition and Attention

18

PSI ISSUE V attentional cue. Participants were made aware that eye gaze direction was non-predictive of the target location, and were asked to respond to the target as quickly as possible by pressing a button on a standard computer keyboard. The results revealed that participants were always faster for valid targets relative to invalid targets, demonstrating the so-called social orienting effect.

However, the time course profile did not conform to either of the two known types of attention. In other words, the results did not resemble either voluntary or automatic attention. This is because, like automatic attention, social orienting emerged quickly by 100ms, but like voluntary attention, persisted for about 700ms.

This result, which has now been replicated numerous times (Frischen, Bayliss, & Tipper, 2007), did little to clarify the classification of social orienting in attention research.

To probe more into the nature of social attention, Hayward and Ristic (2013; see also Law, Langton, and Logie, 2010) recently pitted social attention directly against a voluntary, cognitive process in order to determine whether social orienting involved voluntary attentional control. In their experiment, the authors first engaged both social orienting and voluntary orienting in isolation. This was done by directing each type of attention to a different spatial location onscreen. Working memory load was then introduced to the task, where, in addition to performing the cueing task, participants were also asked to remember and report a random 5-digit sequence on each trial. The main question was whether an addition of a voluntary cognitive process, in this case, working memory load, would interfere with social orienting. They reasoned that if social orienting was under voluntary control, social orienting and working memory load processes would compete for the same cognitive resources, and as a result, the two would interfere with each other, i.e., performance for social orienting would suffer.

Otherwise, if social orienting was not under voluntary control, social orienting and working memory load could proceed in parallel without interference. Hayward and Ristic (2013) found that the addition of working memory load interfered with voluntary attention, as expected; however, working memory load did not affect social attention, leading the authors to conclude that social orienting was not under voluntary control.

It would be logical to deduce that social orienting is an automatic process, but several findings have caused many to speculate that social orienting may belong to a unique form of attention (Birmingham & Kingstone, 2009; Marotta, Lupiáñez, Martella, & Casagrande, 2012; Ristic & Kingstone, 2005). For one thing, humans are the only species that have a widely exposed white sclera surrounding the darker iris, making it easy to determine

where others are looking and communicate using such gaze signals (Kubayashi & Koshima, 1997). Others have noted that when there is choice to attend to either social eyes or other non-social directional cues like arrows, people will hardly look at arrows and attend significantly more to the social information conveyed by people and their eyes (Birmingham, Bischof, & Kingstone, 2009).

Bearing this in mind, we used a similar rationale as Hayward and Ristic (2013) to test if social orienting was automatic. To do so, we pitted social orienting against a process that is known to disrupt automatic orienting – more specifically, we pitted social orienting against perceptual load. Perceptual load is known to interact with automatic attention (Fu et. al., 2010) by disrupting bottom-up processing of salient stimuli.

If social orienting involves automatic attention, an addition of perceptual load would interfere with this process.

Perceptual load, in the context of a computer task, is the amount of visual information present on-screen.

In the low perceptual load condition, there is a minimal amount of stimuli on-screen, normally just displaying the target stimuli. A high perceptual load condition, in contrast, contains a number of distractor stimuli that may also share similarities to that of the target stimulus, making the target’s presence more difficult to discern.

Partly, task difficulty is caused by a lack of attentional capacity to perceptually process all the stimuli onscreen (Lavie, 1995). In low load conditions, therefore, the entire array is interpreted quickly because there is enough perceptual and attentional capacity to process everything on-screen. This is different from a high load manipulation where there is not enough perceptual and attentional capacity to process the entire array, causing the target to be interpreted at a slower rate and also causing selective attention of the array (i.e. not every distractor stimulus is attended to).

In the present study, we asked participants to complete a modified cueing task in which the eye gaze cue, visual distractors, and target were displayed on-screen for only 240ms. Participants were asked to respond to the presence or absence of the target as quickly and as accurately as possible under one of two perceptual load conditions: No Load or High Load.

Perceptual load was manipulated by the number and shape of the distractors on the screen.

Hypotheses: if social orienting was automatic, then an increase in perceptual load will cause participants to selectively attend to the target stimulus, causing the eye gaze cue to be ignored (i.e. no social orienting would occur). If social orienting was unique, then the social orienting effect would remain unaffected by perceptual load conditions. Furthermore, we were interested in determining if individual levels of social

19

Cognition and Attention

PSI ISSUE V competence, as measured by the Autism Spectrum Quotient (Baron-Cohen, Wheelwright, Skinner, Martin, & Clubley, 2001), could also explain the variability in social orienting. In sum, the present study aimed to test if social orienting engages automatic attention, as well as to uncover any individual performance effects in relation to levels of social competence.

Method Participants Forty-four (N=44) participants from McGill University and the Downtown Montreal area were recruited to complete the study (14 men, 30 women, Mage = 23.5, age range: 18–40 years). They were compensated $10 an hour for their time. Participants were randomly assigned to one of two experimental conditions (No Load, n = 22; High Load, n = 22) and were unaware of the purpose of the experiment. Testing occurred during one one-hour session.

Apparatus & Stimuli MiniMac computers with Mac OS X operating systems were attached to 16” CRT monitors. Responses were collected via standard computer keyboards. The stimulus display sequence was run using Matlab R2009b coding software and Psychtoolbox 3.0. Adobe Illustrator was used to create the computer-based stimuli.

Figure 1 shows an example of stimuli and possible trial types. All stimuli were black line drawings presented on a white background. The fixation cross, shown at the beginning of each trial, subtended 1.00 of visual angle (VA) in height and width. Stimuli also included a schematic face, with the outline of the face subtending 7.5° VA, the outlines of the eyes (1.0°), pupils (0.5°), a nose (0.2°), and a line representing the mouth (2.6°). Distractor circles (1.0°), distractor circles with gaps (size of gap: 0.25°), and half circles (1.0° x 0.5°) representing the target stimulus were presented on screen around the face. At the end of each trial, a question prompted participants for a response. (see Figure 1).

cue present and target absent (25%), (Q3) cue absent and target present (25%), and (Q4) both cue and target absent (25%). The Q1 trial type was further broken down into (Q1 Valid) when the gaze cue correctly directed attention to the target (i.e. eye gaze left, target appears on left side) and (Q2 Invalid) when the gaze cue incorrectly directed attention to the target (i.e. eye gaze left, target appears on right side).

Participants performed the experiment under one of two perceptual load conditions. Figure 2 illustrates the two load conditions. In the No Load condition, 4 distractor circles appeared, one of each above (subtending 6.5° from center), below (subtending 6.5° from center), to the left (subtending 7.5° from center), and to the right of the face (subtending 7.5° from center). In the High Load condition, 9 distractor circles with small gaps could appear anywhere on the screen around the face, subtending 6.5° and 7.5° from the screen’s center, with roughly equal numbers of distractors on the left and right of the screen, as well as on the top and bottom half of the screen.

In both load conditions, the target stimulus was randomly presented in one of two specific locations, either 7.5° to the left or 7.5° to the right of the vertical meridian and 1.5° above the horizontal meridian.

On each trial, the target stimulus appeared with its loop facing upwards or downwards (each orientation occurred an approximately equal number of times).

Gaze direction, when present, was non-predictive of where the target would appear, in that it only correctly predicted the direction of the target’s location at chance level, 50% of the time. (see Figure 2).

Procedure As shown in Figure 2, each trial began with the presentation of a fixation cross on screen for 1000ms, followed by the task display for 240ms. A final screen asking, “Target present/absent?” was displayed for 2000ms or until a response was made. The inter-trial interval (ITI) was 650ms.

Participants sat in a dimly lit room and completed 20 practice trials before going on to complete a total of 224 experimental trials equally distributed into 7 blocks. They were instructed to respond to the presence Design or absence of the target stimulus as quickly and as A 2x2 design was used to investigate the effects of accurately as possible, specifically by using the “V” and perceptual load on social orienting. Cue presence, “B” keys on a keyboard. The keys corresponding to each target presence, and cue validity were all within- response (present/absent) were counterbalanced across subjects, independent variables. Dependent variables participants. Participants were also informed that when were participants’ reaction times and accuracy scores. the gaze cue was present in the trial display, it was nonAs Figure 1B illustrates, the cue (in the form of pupils) predictive of a target location. After the computer task, and the target stimulus (in the form of a half-circle) participants completed the autism spectrum quotient were each present in 50% of the trials, resulting in 4 trial questionnaire (AQ). types: (Q1) cue present and target present (25%), (Q2) Cognition and Attention 20

PSI ISSUE V

The AQ is comprised of 50 questions and evaluates the degree to which an adult with normal intelligence displays autistic-like traits. Participants could receive either zero points or one point per question, depending on whether they agreed or disagreed with the question’s statement. For example, while completing the questionnaire participants had to decide whether they agreed or disagreed with the statement, “I would rather go to a library than a party.” Answers were counterbalanced so that half of the time, a “disagree” response resulted in one point, and the other half of the time, an “agree” response resulted in one point. A high overall score (i.e. many points) indicates likelihood that the respondent possesses autistic-like traits, and consequently suggests low social competence. On the other hand, low AQ scores (i.e. fewer points) suggest high social competence.

this condition separately using a mixed effects ANOVA with load and cue validity (valid, invalid) included as factors. As illustrated in Figure 3B, neither effects of load nor the effects of social orienting were reliable [Q1 valid: F(1,42)<2, p>0.3; Q1 invalid: F(1,42)<2, p>0.2]. Thus, no social orienting effects were found in either perceptual load condition despite load’s effective manipulation on reaction times across all trial types. (see Figure 3).

Analysis of eye gaze presence. Next we set out to test if the general presence of eye gaze affected participants target performance as a function of Perceptual Load. To do this, two mixed effects ANOVAs were run with Perceptual Load as the between-subjects variable and Cue Presence as the within-subjects variable. One analysis was run on target present trials (i.e., Q1 valid, Q1 invalid, Q2 no cue) and the other one Results was run on target absent trials (i.e., Q3 cue, Q4 no cue).

When the target was present, we found no significant Trials with reaction times (RTs) faster than 100ms main effects or interactions [all Fs<3, all ps>0.09]. When (anticipations) and slower than 1000ms (time outs) were the target was absent, similar nonsignficant results were removed from the final analysis. Anticipations and time also found [all Fs <2.3, all ps> 0.13]. Thus, at a group outs accounted for 4.97% and 1.19% of the experimental level, the presence of eyes did not affect participants’ trials, respectively, across the two load conditions. Trials RTs when determining whether the target was present with incorrect key presses (i.e. incorrectly identifying or not. whether the target was present or absent) were also removed from the analyses. Participants were 94.5% Individual Level Analyses accurate in both the No Load and High Load Conditions AQ Regressions. Finally, although we found no effect of (No Load, 94.5%; Load, 94.5%). eye gaze on performance at the group level, we had an a priori interest in whether individual differences in social competence, as measured by the AQ, would explain how Group Level Analyses All trial analysis. Mean correct Response Times (RTs) much the presence of eyes affected performance. To for each trial type were first subjected to a mixed quantify the effects of eyes while taking into account the effects ANOVA with Perceptual Load (No Load, High main effect of target presence, we calculated a difference Load) included as a between-subjects factor, and Trial score between Cue Present and Cue Absent trials for the Type (Q1 Valid, Q1 Invalid, Q2, Q3, and Q4) included Target Absent (i.e.; Q4 RTs – Q3 RTs) and Target Present as within-subjects factors. This analysis indicated a (i.e., Q2 RTs – Q1 valid RTs and Q2 RTs – Q1 invalid RTs) main effect of Trial Type [F(4,168)=38.5, p<0.001], conditions. A positive value would therefore indicate revealing that RTs were slowest for target-absent trials that the eyes had facilitated, or sped up performance, (i.e. Q3 and Q4). This finding is consistent with typical while a negative value would indicate that the eyes had visual search data, whereby participants are slower to hindered, or slowed down performance. As shown in determine that a target is absent from an array than they Figure 4A, when the target was absent, an individual’s are to determine that a target is present in an array (e.g., level of social competence did not reliably predict Chun & Wolfe, 1996). Furthermore, and as illustrated the facilitating effect of eye gaze looking at the target in Figure 3A, a significant interaction emerged between [F<0.5, p>0.4]. When the target was present, however, Perceptual Load and Trial Type [F(4,168)=23.8, social competence reliably related to the facilitory effect p<0.001], indicating that this difference between target of eyes looking at the correct target location. Indeed, validly indicated present and target absent trials was most pronounced in this effect was only present when eyes 2 the location of the target [valid: R =0.1; F(1,42)=4.5, the High Load condition. p<0.05;] as shown in Figure 4B, with marginal but To determine if social orienting was present unreliable effects for invalid trials as shown in Figure in Q1, in which the eye gaze cue was present and 2 alternated between left and right deviation, we analyzed 4C [invalid: R <0.09; F(1,42)<4.1, p>0.05]. Specifically, those individual who were high in social competence

21

Cognition and Attention

PSI ISSUE V were facilitated in their response times by valid eye gaze while those who were low in social competence were hindered by it. Thus, the data suggests that the level of social competence may affect individual performance for trials with targets in the presence of helpful gaze information. (see Figure 4).

Discussion In the present study, we aimed to resolve whether social orienting involved automatic attention. This was done by pairing a gaze cueing task with another task known to interfere with automatic processing: perceptual load. We hypothesized that if social orienting was an automatic process, adding perceptual load would suppress the typical social orienting effect. On the other hand, if social orienting was a unique attentional process, an addition of perceptual load should not interfere with social orienting, as the two would work in parallel. We also wanted to determine whether individual levels of social competence predicted the amount of facilitation that â&#x20AC;&#x153;helpful,â&#x20AC;? or valid, eye gaze provided for participants. This was accomplished with the use of the autism spectrum quotient questionnaire (AQ) as a measure of social competence. Although we did not find any significant effects of perceptual load, social orienting, or presence of eye gaze at a group level, we did uncover a relationship between individual AQ scores and the individual amounts of facilitation in performance from helpful gaze cues.

At the group level, there was a significant interaction between trial type and load, yet it was determined that this was mainly caused by the significant difference in reaction times between target-present and target-absent trials under High Load, reflecting that of a typical search task (e.g., Chun & Wolfe, 1996). Our second analyses consisted of two mixed effects ANOVAs, comparing only Q1 valid and invalid trials. This was run in order to determine whether we had obtained any significant social orienting effects in our experiment; however, none were found for either perceptual load condition. Also, although we found no effect of eye gaze direction on reaction times, we thought that perhaps there would be more of a general effect of cue presence on responses. Hence two repeated measures ANOVAs were run, separated by target presence. Neither targetpresent nor target-absent trials showed any general effect of cue presence. This suggests that performance was not affected by the cue, but solely by the presence of the target on screen.

At the individual differences level, however, we did find a significant relationship between social competence and the individual amounts of facilitation

caused by valid cue trials: participants high in social competence were facilitated by helpful gaze as they were faster to respond to targets that were gazed at (Q1) relative to targets in no gaze trials (Q2).

Conversely, helpful gaze hindered participants low in social competence, as they were slower to respond to targets that were gazed-at (Q1) relative to targets in no gaze trials (Q2). Taken together, these results seem to suggest that individual levels of social competence relate to performance, specifically when contrasting RTs for target-present trials that contain no cue and target-present trials that contain valid, helpful gaze.

This is congruent with previous research noting that those with low social competence have been found to also have weaker effects when exposed to helpful gaze (Bayliss, di Pellegrino, & Tipper, 2005).

Our task failed to determine whether social orienting was an automatic process, as we did not find a social orienting effect, even under the No Load condition. This suggests that there may be something about our manipulation itself that was not effective.

Specifically, perhaps the No Load condition with 4 items on screen was in fact more similar to low perceptual load, although it was strong enough to eliminate the social orienting effect. A future step would be to run the task with just one item (target or distractor) on screen and investigate whether a social orienting effect emerges. If it does, this suggests the automaticity of the attentional mechanisms at play while attending to social information, since higher perceptual load conditions as observed in our experiment, were otherwise unable to obtain a social orienting effect. Alternatively, there are at least two other possibilities as to why we failed to obtain a social orienting effect in our task.

First, the type of cueing task we utilized was modified, which could be the cause for the discrepancy between the results of a typical cueing task and that of our own. In our experiment, the cue and target were presented at the same time for a total of only 240 ms, while in the typical task, there is a noticeable SOA between the cue and target presentation, and often a longer amount of presentation time of each. It is plausible that the short display time, or the non-sequential display, may have resulted in a lack of processing time for the participants and thus a lack of social orienting.

Second, this was a hard test of social orienting. It is important to note that out of 224 trials, only 56 were from Q1 including the cue and the target. Out of these 56 trials, only 28 (12.5% of the experimental trials) had gaze cues that correctly directed attention to the target location. Other studies looking at social orienting by utilizing the cueing task, in comparison, have over a hundred cue-present trials for analysis (e.g., Langton & Bruce, 2010), leaving this experiment at a notable

Cognition and Attention

22

PSI ISSUE V disadvantage. This low prevalence of cue presence, and that of valid cue presence, may have removed any social orienting effect from appearing in our analyses. This hypothesis would be interesting to examine in future studies, as it may suggest that the mere presence of gaze cue within a task may affect how participants interpret it.

In consideration of these findings, proposed future directions in determining whether social orienting is automatic should still consider the perceptual load manipulation. As mentioned above, it is possible that our modified version of the gaze cueing task was just too modified to be directly compared to social orienting effects obtained with the typical gaze cueing task. Further, it is possible that our No Load condition did not allow the cue to be as perceptually salient as we had originally expected.

Altogether, this experiment sought to determine whether social orienting was automatic or unique by examining the effects of perceptual load on social orienting during a modified gaze cueing task. Due to the lack of a significant social orienting effect in both perceptual load conditions, our results failed to provide an answer. We did, however, find a relationship for individual differences of valid gaze facilitation and levels of social competence (as measured by the AQ): valid eye gaze helped those high in social competence, leading to faster responses to the target, while valid eye gaze hindered those low in social competence, leading to slower responses to the target. Albeit not a true social orienting effect in the classic sense, it hints that the effect may emerge under an effective perceptual load manipulation. In conclusion, further research is still required to address the dilemma of social orienting: is it truly automatic.

References Baron-Cohen, S., Wheelwright, S., Skinner, R., Martin, J., & Clubley, E. (2001). The autism-spectrum quotient (AQ): evidence from Asperger syndrome/highfunctioning autism, males and females, scientists and mathematicians. Journal of Autism and Developmental Disorders, 31(1) 5-12 Bayliss, A. P., di Pellegrino, G., & Tipper, S. P. (2005).

Sex differences in eye gaze and symbolic cueing of attention. Quarterly Journal of Experimental Psychology, 58(4), 631-650 Birmingham, E., Bischof, W. F., & Kingstone, A. (2009). Get real! Resolving the debate about equivalent social stimuli. Visual Cognition, 17:6-7, 904-924 Birmingham, E. & Kingstone, A. (2009). Human social attention: A new look at past, present and future investigations. The Year in Cognitive Neuroscience: Annals of the New York Academy of Sciences, 2009,

118-140 Chun, M. M. & Wolfe, J. M. (1996). Just say no: how are visual searches terminated when there is no target present?

Cognitive Psychology, 30, 39-78 Friesen, C. K., & Kingstone, A. (1998). The eyes have it!

Reflexive orienting is triggered by nonpredictive gaze. Psychological Bulletin Review, 5, 490-495 Frischen, A., Bayliss, A. P., & Tipper, S. P. (2007). Gaze cueing of attention: visual attention, social cognition, and individual differences. Psychological Bulletin, 133(4), Reflexive orienting is triggered by nonpredictive gaze. Psychological Bulletin Review, 5, 490-495 Frischen, A., Bayliss, A. P., & Tipper, S. P. (2007). Gaze cueing of attention: visual attention, social cognition, and individual differences. Psychological Bulletin, 133(4), 694-724 Fu, S., Huang, Y., Luo, Y., Wang, Y., Fedota, J., Greenwood, P. M., & Parasuraman, R. (2010). Early interaction between perceptual load and involuntary attention: An event-related potential study. NeuroImage, 48(1), 191-199 Hayward, D. A., & Ristic, J. (2013). The uniqueness of social attention revisited: working memory load interferes with endogenous but not social orienting.

Experimental Brain Research, 231, 405-414 Jonides, J. (1981). Voluntary versus automatic control over the mind’s eye’s movement. in J. B. Long & A. D. Baddeley (Eds) Attention and Performance Vol. IX (pp.

187-203). Hillsdale, NJ: Erlbaum Kobayashi, H., & Koshima, S. (1997). Unique morphology of the human eye. Nature, 387, 767-768 Langton, S. R. H., & Bruce, V. (2010). Reflexive visual orienting in response to the social attention of others. Visual Cognition, 6(5), 541-567 Lavie, N. (1995). Perceptual load as a necessary condition for selective attention. Journal of Experimental Psychology: Human Perception & Performance, 21, 451-468 Law, A. S., Langton, S. R. H., Logie, R. H. (2010). Assessing the impact of verbal and visuospatial working memory load on eye-gaze cueing. Visual Cognition 18, 14201438 Marotta, A., Lupiáñez, J., Martella, D., & Casagrande, M. (2012). Eyes versus arrows as spatial cues: two qualitatively different modes of attentional selection.

Journal of Experimental Psychology: Human Perception and Performance, 38(2), 326-335 Posner, M. I. (1980). Orienting of Attention. Quarterly Journal of Experimental Psychology, 32, 3-25 Posner, M. I., & Cohen, Y. (1984). Component s of Visual Orienting in Bourma, H; Bouwhuis, D. Attention and performance S: Control of language processes. Hillsdale, NJ: Erlabaum. pp 531-36 Ristic, J., & Kingstone, A. (2005). Taking control of reflexive social attention. Cognition, 94(3), B55-B65

23

Cognition and Attention

PSI ISSUE V Appendix Figure 1. Examples of the Task Display

Note. Examples of the task display. Figure 1a. An example of a cue present, target present trial display under the No Load condition. Figure 1b. All possible trial types as observed under the No Load condition. Altogether, cues and targets were present in 50% of trials, leading to 4 general trial conditions: (Q1) target present, cue present; (Q2) target present, cue absent; (Q3) target absent, cue present; and (Q4) target absent, cue absent. (stimuli not drawn to scale) Figure 2. Sample Sequence of Events for a Single Trial

Note. A sample sequence of events for a single trial, one for each perceptual load condition. Figure 2a. A valid gaze, No Load trial. Figure 2b. A gaze absent, target present High Load trial. (stimuli not drawn to scale)

Cognition and Attention

24

PSI ISSUE V Figure 3. Trial RT Analyses as a Function of Load

3A. All trial analysis

3B. Q1 trial analysis: valid and invalid trials

Note. Trial RT analyses as a function of load. 3a. All trial analysis. Significant differences found in RTs between target absent and target present trials under High Load. 3b. Q1 trial analysis: valid and invalid trials. No significant differences in RTs found, consequently showing no social orienting effects.

25

Cognition and Attention

PSI ISSUE V Figure 4. Regressions using AQ to predict the effect of eye gaze 4A. Target absent trials

4B. Target present trials, valid gaze

Figure 4 is continued on the next page.

Cognition and Attention

26

PSI ISSUE V

4C. Target present trials, invalid gaze

Figure 4. Regressions using AQ to predict the effect of eye gaze. In relation to AQ score, a mean difference value (ms) for RTs of No Cue (no eyes) trials subtracted by Cue trials (eyes) was calculated, reflecting facilitation or inhibition of performance due to the cue.

4a. Effect of cue on target absent trials. 4b. Effect of valid cues on target present trials. 4c.

Effect of invalid cues on target present trials.

27

Cognition and Attention

PSI ISSUE V

2015

Adolescents with type 1 diabetes are less likely to use spatial strategies when navigating in a virtual environment compared to their matched control Stephanie Polchtchiko* Supervisor: Dr. Veronique Bohbot *email: stephanie.polchtchikov@mail.mcgill.ca Abstract Diabetes Mellitus type 1, a juvenile onset disease characterized by lack of insulin production, has been implicated in cognitive deficits in episodic and spatial memory. Healthy individuals will spontaneously use a spatial or response strategy when solving a virtual navigation task. In accordance with previous research showing the critical role of the hippocampus in spatial memory, it is thought that healthy individuals rely on the hippocampus when faced with a virtual navigation task. It is hypothesized that individuals with type 1 diabetes will be less reliant on the hippocampus when faced with a virtual navigation task and will favor a hippocampus-independent response strategy. Thirteen right-handed adolescents with type 1 diabetes, age 14 to 17, and fourteen controls, matched in age, were tested on their navigational strategies. Short term memory, long term memory, verbal memory and visuospatial abilities were assessed through neuropsychological tasks. We found that adolescents with late onset type 1 diabetes and no history of hypoglycemic attacks did not significantly differ from their matched control in performance on neuropsychological tasks. However, individuals with type 1 diabetes tended to favor a response strategy when completing the virtual navigation task. This indicates less reliance on the hippocampus when navigating the task. Lack of spatial strategy use has been associated with reduced hippocampal function, which is a risk factor for cognitive impairments such as Alzheimerâ&#x20AC;&#x2122;s disease.

Keywords: spatial memory; navigation; Type I Diabetes; hippocampus; caudate nucleus.

Acknowledgments I am very grateful for the help and guidance I received from Nadia Andruchow in data collection and analysis. I would like to thank Dr. Veronique Bohbot and the Memory and Motion laboratory for their support. Dr. Laurent Legault and the Diabetes Clinic have been very helpful in participant recruitment.

Cognition and Attention

28

PSI ISSUE V Introduction Insulin dependent Diabetes Mellitus, more commonly known as Type 1 diabetes (T1D), is hypothesized to be caused by an autoimmune destruction of the pancreas (Hershey et al., 2005). Studies have linked cognitive deficits in T1D with early onset of the disease (Ack et al., 1961; Ryan, 1988; 1999; Rovet et al., 1987) and severe hypoglycemic episodes, caused by a low blood sugar level (Hershey et al., 2005; Perantie et al., 2008) and poor maintenance of the disease (Northam et al., 2001; Ryan, 2004). The hippocampal region is vulnerable to low blood glucose levels (Hershey et al., 2010), which is characteristic of T1D. Cases of low blood glucose levels occur most commonly with an over-administration of insulin, a hormone that is vital to metabolizing sugar in the blood (Ryan, 1999). Indeed, neuroimaging technologies have demonstrated smaller grey matter in the hippocampus (Antenor-Dorsey et al., 2007; Hershey et al. 2010), as well as irregular axonal connections in the superior temporal region (Kodl et al. 2008) of patients with T1D when compared to healthy controls. With the hippocampus playing a crucial role in episodic and spatial memory (Bird & Burgess, 2008; Bohbot et al., 2007), T1D persons may exhibit alterations in spatial memory and learning.

When navigating in a virtual environment, an individual will spontaneously use one of two navigational memory systems: the hippocampusdependent spatial strategy or the response strategy (Iaria et al., 2003; Bohbot et al., 2004, 2007). The hippocampus is involved in allocentric spatial navigation (Zhang & Ekstrom, 2013; O’Keefe & Nadel, 1978), which allows an individual to use spatial information flexibly. In contrast, the rigid response strategy is mediated by the caudate nucleus, and is characterised by a robust mechanism that operates with response-stimulus associations.

(Bayley et al., 2007). There is a positive correlation between gray matter in the hippocampus and spatial learning, while response learning is associated with increased gray matter in the caudate nucleus (Bohbot et al., 2007). Furthermore, the two systems seem to act in a competitive manner, meaning an individual will spontaneously favor either the spatial or the caudate nucleus (Bohbot et al., 2007). The two systems cannot act simultaneously.

In healthy young adults, there is an even proportion of individuals who spontaneously use the spatial strategy to those who use a response strategy

(Bohbot et al., 2012; Iaria et al., 2003). The objective of the present study is to determine if adolescents with T1D will exhibit the same distribution of response and spatial strategies. We hypothesize that due to the impact of T1D on the hippocampus, young adults with T1D will be more likely to spontaneously use the response strategy when navigating in a virtual environment.

Although the effects of being hippocampusindependent may not be prevalent with our age group, the use of the hippocampus is necessary for healthy aging. Studies have demonstrated that a decrease in hippocampal volume is a risk factor for cognitive dysfunction, including Alzheimer’s disease (Convit et al., 1997). Furthermore, Bohbot et al. (2012) showed through functional magnetic resonance imaging (fMRI) that hippocampus use declines with aging in a healthy population, which may lead to a decline in hippocampal function. If adolescents with T1D show an inclination to disfavor hippocampal use, this might signal neurocognitive problems with aging.

Materials and Methods Participants Thirteen teenagers with T1D (8 females and 5 males, with a mean age of 16 ± 0.82) and fourteen healthy young adults (11 females and 3 males, with a mean age of 16.07 ± 1.14) took part in the study. All participants were right-handed and between 14 to 17 years of age. Participants were screened for any history of neurological or psychiatric disorders. Informed consent was obtained from both the participant and their legal guardian in a manner approved by the local ethics committee.

Diabetic group. Thirteen individuals with T1D were recruited from the Diabetes Clinic at the Montreal Children’s Hospital, in affiliation with Dr. Laurent Legault. The participants did not have a history of severe hypoglycemia. To avoid alterations in blood sugar during testing, blood glucose levels were measured before.

Control group. Fourteen control subjects were recruited from the waiting area of the Montreal Children’s hospital and through word of mouth.

Tests Neuropsychological Tests. Impulsivity, self-esteem, and perceived stress were determined with the Barratt Impulsivity Scale, Rosenberg Self-Esteem Scale, and

29

Cognition and Attention

PSI ISSUE V Perceived Stress Scale, respectively. The Rey Auditory Verbal Learning Test (RAVLT) was administered as a standard neuropsychological memory test, assessing verbal learning, short term and long term verbal memory. The Rey-Osterrieth Complex Figure assessed visuospatial cognition, as well as short and long term visual memory. The Digit Span was used to assess memory.

Virtual Navigational Tasks. Two computer-based navigation tasks (Unreal Tournament, Epic Games Inc., Raleigh NC) were used as virtual navigational tasks.

One was administered at the beginning of the study session, and one was administered at the end. The order of presentation was counterbalanced between sessions.

Recombined Pairs Virtual Task. The task consists of a center platform from which branch out 12 pathways. At the end of each pathway, there are stairs that lead to a small pit. Six of the 12 pathways have an object located in the pit, while the other six are empty.

The position of the object does not change throughout the task. The maze is surrounded by a rich landscape, containing both proximal and distal landmarks. During the first phase of the task, the 12 pathways are presented in pairs of two. Within each pair, one pathway always contains an object and the other is always empty. The pathways outside of this pair are blocked by tall walls.

The participant is repeatedly presented the same six pairs of pathways, in a random order, with the goal of memorizing where the object is located within each pair.

If they entered a pathway containing no object, they would know it was the other pathway that contained the object. One trial consists of presenting all six pairs of pathways. In order to reach criterion and move on to the next phases, the participant had to visit 11 “object” pathways within two consecutive trials. A minimum of six trials are administered.

The probe phase, also known as Stage 2, was aimed at dissociating the strategies used by the participant when memorizing where the objects are located. The pathways are recombined into four new pairs, still with one pathway containing an object, and the other being empty. The goal of the task remained the same: to choose the “object” pathway. The probe phase necessitates knowledge of the spatial relationship between the “object” pathways and the landscape; thus, it requires participants to demonstrate spatial flexibility in order to successfully complete the task. The participant must show flexibility in maneuvering the information they learned from phase 1.

The final phase (phase 3) consists of all pathways being accessible, meaning they are no longer blocked by walls. The participant must retrieve all six objects located at the end of the stairs, in the small pit.

4/8 Virtual Task. The 4 on 8 virtual task consists of an eight arm radial maze, surrounded by a landscape (mountains, a tree and a rock). At the end of each arm, there was a staircase leading to a small pit, where an object was situated. The task consisted of a minimum of five trials, divided into two parts. Participants started the trial from the center of the platform. In Part 1 of the trial, four of the eight paths were blocked by barriers.

The participants must visit all the accessible pathways and collect the object located in the small pit. They must remember which pathways they had visited, because in Part 2, all pathways are accessible and the participants must retrieve the objects located at the end of the previously blocked pathways. In order to move on to the probe trial, the participant must complete Part 2 successfully, and complete a minimum of three trials.

During the probe trial, the landscape was removed. The participants had the same task of retrieving the object located at the end of the previously blocked pathways. Performing poorly on the probe trial indicated that the individual relied heavily on the landscape when navigating. These individuals memorized the paths in relation to the landmarks, and with no landmarks to guide their navigation, spatial learners were more likely to enter paths at random. Participants who were not impaired during the probe trial were most likely using a response strategy during the task, which is not reliant on the spatial environment. After the probe trial, we administered one trial similar to the previous three to detect if participants would shift their strategy after the probe trial. Verbal reports were taken after completing the 4/8 Visual Task to better assess the strategy used by the participant. The verbal reports were recorded, transcribed and rated by two experimenters.

Onset of Diabetes. Within our diabetic group, the age of diagnosis is considered late onset T1D with a mean of 8.64 ± 1.6.

Results Neuropsychological Tasks. An independent samples t-test was performed to compare the two groups (individuals with T1D and their matched control) for their perceived stress, impulsivity and self-esteem in terms of the

Cognition and Attention

30

PSI ISSUE V scores received for the Perceived Stress Scale, Barratt Impulsivity Scale and the Rosenberg Self-Esteem Scale, respectively. The t-test yielded no significant result between diabetic individuals and their matched-control in terms of stress, impulsivity, and self-esteem, with p > 0.05 (Table 1). Therefore, the groups did not differ in terms of their impulsivity, self-worth or stress.

There was no difference between participants with T1D and control in their measure of short-term memory, long-term memory, verbal memory and visuospatial abilities, attributed with the RAVLT, ReyOsterrieth Complex Figure and the digit span (Table 1).

The independent samples t-test did not yield significant results, therefore the two groups had similar cognitive abilities when performing the visual navigational tasks.

Recombined Pairs Virtual Task. All participants were able to reach criteria. Performance on the probe trial was used to assess group differences. Diabetic patients did slightly worse, with a mean of 58.65 ± 25.63 % correct pathways taken, than the control group, with a mean of 73.23 ± 21.84 % correct pathways (Figure 1). However, an independent samples t-test found no significant difference between the performance of diabetic individuals and their matched control (p>0.05).

An independent samples t-test was performed to assess the group differences in performance on the third phase of the recombined pairs virtual task. No significant difference was found (p>0.05). Figure 2 illustrates the difference between the control group, with a mean of 80.95 ± 20.53 % of objects collected, compared to the diabetic group, with a mean of 73.08 ± 12.21 % of objects collected.

4/8 Virtual Maze. A 2-way independent groups ANOVA was used to assess the impact of strategy and diabetic/ control on the number of rotational errors during the probe phase. During the probe trial, the landscape surrounding the maze was removed; therefore participants who used a spatial strategy were more likely to make rotational errors while completing the task. The ANOVA yielded a significant main effect of strategy use in relation to rotational errors (p=0.001). This reaffirms the assumption that spatial learners will make more mistakes on the probe trial than response learners. No significant effect was found between the diabetic group and the control group in terms of rotational errors (p=0.245). In other words, the diabetic group, with a mean of 0.154 ± 0.39 rotational errors, did not differ significantly from the control group, with a mean of 0.429 ± 0.51 rotational errors, when completing the

probe trial (Figure 3) No significant interaction between group and strategy was found (p=0.451).

Verbal reports were used to assess the strategy of the participant. Within the control group, there was about a 1:1 ratio of spatial to response learners, as predicted (with 43 % spatial and 57 % response learners). Within the diabetic group, there was an increase in response learners with a 4:1 ratio (with 23% spatial and 77% response learners). Figure 4 demonstrates this comparison. The verbal reports reaffirmed that rotational errors were mostly made by spatial learners. Diabetics that used the response strategy made no rotational errors, whereas only one control made a rotational error using response strategy.

Two participants using a spatial strategy made no rotational errors, one respectively from each group.

Discussion In the present study, we assessed the spontaneous strategy used when navigating in a virtual environment among young adults, aged 14 to 17, with T1D compared to a healthy control group that was matched in age and sex. Studies have shown that individuals with T1D show signs of cognitive deficit (Hershey et al., 2012; Ryan, 1999). With this study, we aimed to further investigate this phenomenon with emphasis on hippocampal function, which is vital for a healthy aging process (Bohbot et al., 2012).

The diabetic group did not differ significantly on measures of short-term memory, long-term memory, verbal memory, and visuo-spatial ability, or on selfesteem, stress or impulsivity scores (Table 1). The virtual navigational tasks did not yield statistically significant group differences. With the 4/8 virtual maze, the probe trial removed all landmarks from the landscape.

Individuals that used a spatial strategy were impaired in their performance, and demonstrated rotational errors; however, those who did not extensively use the relationship between the landscape and the maze when navigating in the 4/8 used a response strategy and did not show any rotational errors. The presence of rotational errors in spatial learners when compared to the lack of rotational errors in response learning showed significance (p<0.001). This result confirms that the strategy assessment of participants with the use of verbal reports was correct. The 4/8 probe trial did not reveal any significant differences in rotational errors between these two groups, indicating that the diabetic group did

31

Cognition and Attention

PSI ISSUE V not differ in strategy preference when compared with findings. Within our diabetic group, no individuals the control group. However, from verbal reports, we reported experiencing a severe hypoglycemic attack. We found 77% of the diabetic group spontaneously used did not record mild hypoglycemic attacks, as low blood a response strategy, compared to only 57% of control glucose happens regularly among T1D individuals and subjects (Figure 4). are not always registered; however, prior to our study,

Functional neuroimaging demonstrates a we ensured the participantâ&#x20AC;&#x2122;s blood glucose levels were correlation between hippocampal activity and the use of within normal range, by taking note of their last blood a spatial learning strategy, while activity in the caudate glucose reading and time. nucleus corresponds with response memory learning Children who develop T1D prior to the age of (Bohbot et al., 2004). The hippocampus and the five appear to be more severely impaired in cognitive caudate nucleus are in competition, showing a negative functions than children who experience a later onset correlation in size (Bohbot et al., 2004). In other words, of diabetes (Ack et al., 1961; Ryan, 1999; Holmes & spatial learners show increased gray matter volume Richman, 1985; Rovet et al., 1987). This implies that there in the hippocampus correlates and decreased gray is more susceptibility for hippocampal impairments matter volume in the caudate; an inverse correlation due to low blood glucose earlier on in life. In our study, is seen in response learners. The opposite effect was only one diabetic fell within this critical period. The seen with response learners (Bohbot et al., 2004). The mean age of diagnosis was 8.64 Âą 1.6 years old. Studies 4:1 ratio of response to spatial learners in the diabetic regarding late onset T1D have been inconsistent, with group suggests that T1D young adults are less likely some reporting no evidence on cognitive dysfunction to use the hippocampus when navigating in a virtual (Wolters et al., 1996; Rovet & Alvarez, 1997) and other environment. This result is not reflected in the general researchers noting deficits in learning and memory with healthy young adult population that tends to show a no attribution to hypoglycemia (Northam et al., 1998).

50/50 trend of strategy use (Iaria et al., 2003). The control Rovet & Ehrlich (1990) tested children within group mimicked this finding, with about a 1:1 ratio in a year of acquiring T1D. No changes in visuomotor, spatial to response learners. Therefore, the majority of memory or attention abilities were found. Holmes and the diabetic participants used a response strategy that Richman (1985) reported that cognitive differences depends on their caudate nucleus during the 4/8 virtual were found in children only after seven years of diabetes navigation task, instead of the hippocampal-dependent onset. Perhaps neuropsychological deficits as a result spatial strategy. of T1D take time to manifest and will be noticed in Previous studies have demonstrated adulthood. These deficits could be caused by poor longhippocampal dysfunction among T1D patients. Severe term metabolic control. hypoglycemia and early onset of diabetes are believed The diabetic population of our study did not to be implicated in these cognitive deficits. Cognitive have a record of severe hypoglycemic episodes or early damage as a result of severe hypoglycemic episodes onset of diabetes (with the exception of one participant). is associated with atrophy of hippocampal neurons Being adolescents, long term effects of poor T1D (Languren et al., 2013; Perantie et al., 2011). The harmful maintenance has not yet affected them. The hypothesis metabolic state of severe hypoglycemia negatively that cognitive deficits have not had time to manifest impacts memory and performance on visuospatial in youth with T1D could account for the comparable tasks (Hershey et. al, 2004, 2005; Ryan, 1999; Auer et al., measures observed between healthy adolescents and 1989; Chalmers et al., 1991). Children who experienced diabetics in neuropsychological tasks, such as the at least one severe hypoglycemic episode were impaired RAVLT, Rey-Osterrieth Complex Figure and the digit in a spatial working memory task when compared to span. This indicates that the groups did not vary in their T1D children who have not experienced hypoglycemia short term, long term, verbal and visuospatial memory.

(Hershey et al., 1998). Ryan (2004) claimed that Although our study did not present significant mild hypoglycemic attacks, which occur frequently results, there were more response learners with the within the diabetic population, could over time affect T1D group, which was composed of adolescents with performance on neuropsychological tasks that require late onset T1D and no history of severe hypoglycemia planning, decision making, attention to detail, visual (Figure 4). Hippocampal dysregulations , such as a scanning, or rapid responding; however, studies have decrease in gray matter (Perantie et al., 2007) and not been extensively conducted to confirm these Cognition and Attention 32

PSI ISSUE V irregular axonal connections (white matter) (AntenorDorsey et al., 2011; Kodl et al., 2008) have been shown with T1D youth through neuroimaging techniques.

Many aging cognitive deficits, such as Alzheimerâ&#x20AC;&#x2122;s disease, are due to reductions in the temporal lobe, including the hippocampus (Convit et al., 1997). No studies have been conducted to confirm hippocampal reductions in aging T1D individuals.

The relatively small sample size in this study could account for the lack of significant data. Due to the limitation of our sample size, we could not analyze trends within groups, such as the strategies employed by early onset compared to late onset diabetics. Our study did not include diabetics who have had severe hypoglycemic attacks, which is believed to be the most plausible explanation for neuropsychological deficits (Northam et al, 2001). Furthermore, our subject pool was biased towards adolescents who were willing to volunteer their time for participation. This may indicate that the T1D adolescents who participated are more interested in the effects of their condition and may pay more attention to their blood sugar levels than potential participants who showed no interest in the study.

Clinic at the Childrenâ&#x20AC;&#x2122;s Hospital. This is partially due to the fact that few participants were willing to volunteer their time for the study. We recommend trying to reach a larger range of adolescents through ads, with the Diabetes Children Foundation, as well as MCHAM. In order to encourage participation, the ad should express the rewarding aspects of study participation, such as opportunity to see the research that is currently being conducted on memory and T1D. This will allow the study to reach more than just the outgoing participants willing to volunteer their time. Finally, parents should be engaged in the recruitment process.

We noticed that the parents were often more interested in the study than their teenagers, and encouraged the parents to participate, who in turn encouraged their children to take part. However, the ethics of informed consent should not be violated, meaning it is up to the consenting adolescent, as well as the parents, to choose to participate or not.

The study session location should remain constant, although this proved to be another obstacle.

Participants were unwilling to come to the Memory and Motion laboratory located at the Douglas Mental Health Institute. Therefore, testing was done at the Childrenâ&#x20AC;&#x2122;s Hospital or at McGill University. We recommend Future Experimentation keeping the testing environment free of distractions, such as cell phones or background noise.

Studies on the difference in cognitive function between Finally, hypoglycemic episodes should healthy and diabetic adolescents have not been cohesive. be assessed by their physician. For this study, we Our study did not confirm any neuropsychological deficits in short term, long term, verbal or visuospatial determined the presence of hypoglycemic episodes memory, as previously seen by Rovet et al. (1993), through questioning the participant and, in certain Hershey et al. (1997), and Northam et al. (2001). In cases, their parents. Often participants with T1D were unaware if they had exhibited such an episode. Getting order to replicate these findings, more participants are needed. A third group consisting of hypoglycemic confirmation from the treating physician would lessen diabetics should be added in order to further advance the errors made in their assumptions. the study.

A cross examination between age of onset and References hypoglycemic attacks among T1D adolescents should be examined, provided that there are enough participants. Ack M, Miller I, Weil WB (1961). Intelligence of children with diabetes mellitus. Pediatrics; Age of diabetes onset and hypoglycemia are two factors 28:764-770. that have been shown to decrease cognitive function (Hershey et al., 2012; Rovet et al., 1993). To our best Anthony-Dorsey JAV, Meyer E, Rutlin J, Perantie DC, White

NH, Arbelaez AM, Shimony JS, Hershey T (2013). knowledge, no studies have extensively looked at a White matter microstructural integrity in youth correlation between onset of T1D and hypoglycemic with type 1 diabetes. attacks. It would be interesting to see if hypoglycemic Diabetes; 62(2):581-589. attacks occur more often in individuals with early onset Auer RN, Hugh J, Cosgrove E, Curry B (1989).

T1D.

Neuropathological findings in three cases of profound hypoglycemia. Clin Neuropathol; 8:63-68.

The greatest challenge of this study was recruitment which was undertaken at the Diabetes Bayley PJ, Frascino JC, Squire LR (2005). Robust habit

33

Cognition and Attention

PSI ISSUE V

learning in the absence of awareness and independent of the medial temporal lobe. Nature; 436:550-553.

Bird CM, Burgess N (2008). The hippocampus and

memory: insights from spatial processing.

Nature Reviews Neuroscience; 9:182-194.

Bohbot VD, McKenzie S, Konishi K, Fouquet C, Kurdi V,

Schachar R, Boivin M, Robaey P (2012). Virtual navigation strategies from childhood to senescence: evidence for changes across the life span. Front Aging Neurosci; 4:28.

Bohbot VD, Petrides M, Iaria G (2004). Hippocampal

function and spatial memory: evidence from

functional neuroimaging in healthy participants

and performance of patients with medial temporal

lobe resections. Neuropsychology; 18(3):418-425.

Bohbot VD, Lerch J, Thorndycraft B, Iaria G, Zijdenbos AP

(2007). Gray matter differences correlate with spontaneous strategies in a human virtual navigation task. J. Neurosci; 27(38):10078-10083.

Chalmers J, Risk MTA, Kean DM, Grant R, Ashworth B,

Campbell IW (1991). Severe amnesia after hypoglycemia: clinical, psychometric and magnetic resonance imaging correlations.

Diabetes Care; 4:922-925.

Convit A, De Leon MJ, Tarchich C, De Santi S, Tsui W,

Rusinek H (1997). Specific hippocampal volume

reductions in individuals at risk for Alzheimer’s disease. Neurobiol Aging; 18:131-138.

Hershey T, Lillie R, Sadler M, White NH (2004). A

prospective study of severe hypoglycemia and long-term spatial memory in children with type 1 diabetes. Pediatr Diabetes; 5:63-71.

Hershey T, Perantie DC, Warren SL, Zimmerman EC, Sader

M, White NH (2005). Frequency and timing of

severe hypoglycemia affects spatial memory in

children with type 1 Diabetes. Diabetes Care; 28:2372-2377.

Hershey T, Perantie DC, Wu J, Weaver PM, Black KJ, White

NH (2010). Hippocampal volumes in youth with

type 1 diabetes. Diabetes. 59(1): 236-241.

Holmes CS, Richman LC (1985). Cognitive profiles of

children with insulin-dependent diabetes. J Dev

Behav Pediatr; 6:323-326.

Iaria G, Peptrides M, Dagher A, Pike B, Bohbot VD (2003).

Cognitive strategies dependent on the hippocampus

and caudate nucleus in human navigation:

Variability and change with practice. Journal of Neuroscience; 23:5945-5952.

Kodl CT, Franc DT, Rao JP, Anderson FS, Thomas W,

Mueller BA, Lim KO, Seaquist ER 2008).

Diffusion tensor imaging identifies deficits in white

matter microctructure in subjects with type

1 diabetes that correlate with reduced

neurocognitive function. Diabetes; 57(11):3089 3089.

Languren G, Montiel T, Julio-Amilpas A, Massieu L

(2013). Neuronal damage and cognitive impairment

with hypoglycemia : An integrated view. Neurochem Int; 63(4):331-343.

Northam EA, Anderson PJ, Jacobs R, Hughes M, Warne GL,

Werther GA (2001). Neuropsychological profiles

of children with type 1 diabetes 6 years after disease onset. Diabetes Care; 24:1541-1546.

Northam EA, Anderson PJ, Werther GA, Warne GI, Adler

RG, Andrewes D (1998). Neuropsychological

complications of IDDM in children 2 years after

disease onset. Diabetes Care 21: 379-384.

O’Keefe J, Nadel L (1978). The hippocampus as a cognitive

map. Oxford, England: Oxford University Press.

Perantic DC, Koller JM, Weaver PM, Lugar HM, Black KJ,

White NH, Hershey T (2011). Prospectively

determined impact of type 1 diabetes on brain

volume during development. Diabetes; 60(11):3006 3014.

Perantie DC, Lim A, Wu J, Weaver P, Warren SL, Sadler M,

White NH, Hershey T (2008). Effects of prior

hypoglycemia and hyperglycemia on cognition in

children with type 1 diabetes mellitus. Pediatr Diabetes; 9:87-95.

Rovet JF, Alvarez M (1997). Attentional functioning in

children and adolescents with IDDM. Diabetes Care; 20: 803-810.

Rovet JF, Ehrlich RM (1999). The effect of hypoglycemic

seizures on cognitive function in children with

diabetes: A 7-year prospective study. Journal of Pediatrics; 134:503-506.

Rovet JF, Ehrlich RM, Hoppe M (1987). Intellectual deficits

associated with early onset of insulin-dependent

diabetes mellitus in children. Diabetes Care; 10:510 515.

Ryan CM (2004). Does moderately severe hypoglycemia

cause cognitive dysfunction in children? Pediatr Diabetes; 5:59-62.

Ryan CM (1999). Memory and metabolic control in children. Diabetes Care; 22:1239-1241.

Ryan CM (1988). Neurobehavioral complications of type

1 diabetes. Examination of possible risk factors.

Diabetes Care; 11:86-93.

Squire LR (1992). Memory and the hippocampus: A

synthesis from findings with rats, monkeys and humans. Psychological Review; 99:195-231.

Wolters CA, Yu SL, Hagen JW, Kail R (1996). Short term memory and strategy use in children with

insulin-dependent diabetes mellitus. Journal of

Consulting and Clinical Psychology; 64:1397-1405.

Zhang H & Ekstrom A (2013). Human neural systems

Cognition and Attention

34

PSI ISSUE V

underlying flexible forms of allocentric spatial representation. Hum Brain Mapp; 34(5):1070-1087.

Appendix Table 1: Demographic and performance on neuropsychological test comparison between T1D and control group.

T1D Control p value n 13 14 Age 16 (0.8165) 16.07 (1.14) 0.853 Age of Onset 8.64 (1.6) Perceived Stress Scale 23 (6.45) 23.67 (4) 0.798 Self Esteem Scale 19.92 (2.99) 19.64 (3) 0.81 Impulsivity Non-Planning 26.38 (5.58) 24.54 (3.94) 0.394 Motor 25.38 (6.44) 22 (3.76) 0.119 Attention 19 (3.81) 19.69 (3.54) 0.653 Total 69.46 (12.69) 66.23 (9.1) 0.5 RAVLT 5 trial Score 55.62 (7.56) 54.93 (8.23) 0.824 Interference 11.23 (2.35) 11.79 (2.32) 0.543 Delayed 11.54 (2.88) 12 (2.48) 0.658 Recognition 13.85 (1.52) 12.79 (2.83) 0.242 Rey-O Figure Immediate 32.56 (3.83) 34.56 (1.51) 0.169 Delayed 25.13 (5.95) 24 (7.89) 0.702 Digit Span 17.07 (4.07) 19.36 (3.52) 0.131 Note. There was no significant difference in age between groups. Both T1D and their matched-control performed in a similar manner in all measures of neuropsychological function.

Figure 1: Comparison of the percent of total correct responses for Recombined Pairs probe.

Note. No significant group differences were found between the percent of correct pathways taken by T1D individuals and their matched control during the probe trial of recombined pairs.

Cognition and Attention 35

PSI ISSUE V Figure 2 :Comparison of percent of total correct pathways taken for Recombined Pairs Phase 3.

Note. No significant effect was found between the percent of correct pathways taken in phase 3 of recombined pairs by T1D adolescents and their matched control.

Figure 3: Group comparison of the number of rotational errors for 4/8 probe.

Note. No significant group difference was found between the number of rotational errors made in 4/8 probe (p=0.245)

Cognition and Attention

36

PSI ISSUE V

Figure 4: Strategy distribution within each group for 4/8

Note. Percent of participants using a spatial or response strategy in each group in the 4/8 Virtual Maze. 77% of T1D individuals used a response strategy compared to 57% of healthy subjects. 23% of T1D participants employed a spatial strategy compared to 43% of healthy control.

37

Cognition and Attention

PSI ISSUE V

2015

Disgust Sensitivity and Vasovagal Reactions During Exposure to Blood, Injection, and Mutilation Stimuli Sophie BĂŠland* Supervisor: Dr. Blaine Ditto *email: sophiebeland@gmail.com

Abstract Vasovagal reactions (VVR) occur frequently in contexts that involve blood, injections and injuries (BII) and are related to medical avoidance and delays in health care seeking. Support for similarities between the hypothesized physiological profiles of disgust and VVR has promoted the idea that disgust sensitivity may play a role in the risk of BII-related fainting. However, to date, research has yielded mixed findings. The aim of this study was to clarify the disgust-faint relationship by presenting participants with two videos depicting images of blood draw/injections and mutilation. Physiological and self-report measures of VVR were obtained from 29 volunteers after watching both videos. As predicted, higher disgust sensitivity was associated with more selfreported vasovagal symptoms, after controlling for sex. However, contrary to predictions, disgust sensitivity was consistently associated with higher heart rate. Results are discussed in terms of other possible psychophysiological mechanisms that may underlie the disgust sensitivity-faint relationship.

Keywords: vasovagal reactions; BII phobia; disgust-sensitivity

Pain

38

PSI ISSUE V Introduction Vasovagal reactions involve a sudden drop in blood pressure and heart rate that cause a decrease in cerebral perfusion and leave one with feelings of weakness, lightheadedness and dizziness; in the case of a sufficient lack of oxygen being directed to the brain, vasovagal reactions may result in a loss of consciousness or fainting, i.e., vasovagal syncope (France, Ditto, France & Himawan, 2008; Graham, 1961). Vasovagal reactions can occur during excessive physical stress such as bouts of pain or orthostasis (Moya et al., 2009).

However, one common but less understood trigger of this physiological inhibitory response seems to be the experience of intense psychological states, in the absence of any physical traumas or triggers. These vasovagal responses due to intense psychological states are experienced at a uniquely high frequency in settings where blood, injections and injuries are involved and by individuals who suffer from blood-injection-injury (BII) phobia, an anxiety disorder characterised by an excessive fear and avoidance of these stimuli (American Psychiatric Association, 2013; Olatunji & Sawchuk, 2005; Ost, 1992). In the general population, up to 15% of individuals have previously reported fainting in the presence of blood or injury, and a recent demographic report of blood donors reveals that approximately 90% of blood donors experience light symptoms of faintness during blood draws (Dubuc & Germain, 2013; Page, 1994). Moreover, data from an epidemiological study of medical students revealed that almost half of those who reported previous fainting episodes attributed them to emotions or situations that involved venipuncture or blood draws (Ganzeboom, Colman, Reitsma, Shen & Wieling, 2003). Within the context of anxiety disorders, the experience of fainting in the presence of phobic-relevant stimuli also seems to be unique to BII phobias. Indeed, Connolly, Hallam and Marks (1976) demonstrated that past fainting history during exposure to phobic relevant situations in phobic individuals was only reported by those with a diagnosis of BII phobia, suggesting that these strong inhibitory reactions differentiate BII phobia from other specific phobias.

The occurrence of vasovagal reactions in BII settings has significant implications among both healthy populations and individuals who suffer from BII phobia. This is because fear of vasovagal reactions has been found to discourage dental care, immunization and other preventive care (Kleinknecht & Lenz, 1989) and is associated with medical avoidance and delays in health care seeking among those with BII phobia (Kleinknecht, Thorndike & Walls, 1996; Page, 1994).

Moreover, France, Rader and Carlson (2005) found

that blood donorsâ&#x20AC;&#x2122; experience of moderate to severe vasovagal symptoms is associated with a 50% reduction in the likelihood of subsequent blood donation, regardless of the donorâ&#x20AC;&#x2122;s previous donation experience.

In light of the distinctive nature of fainting symptoms brought on by phobic reactions to BII stimuli, Olatunji et. al proposed that the avoidance and fear of BII stimuli in some individuals is driven by a fear of fainting, as well as fear of the potential embarrassment and sensations occurring after the fainting episode (Olatunji, Williams, Sawchuk & Lohr, 2006). Indeed, studies have shown that more than half of the negative cognitions experienced by BII phobics concern the fear of fainting and that higher levels of fear are seen in individuals who have a past fainting history (Kleinknecht, 1988; Ost, 1992). Hence, the common fainting response in BII phobia, which parallels the vasovagal reactions observed in medical settings, carries significant health implications as there is evidence that it may be the foundation of maladaptive phobic BII fears and that it promotes the avoidance of medical care and blood donation.

A greater understanding of the psychophysiological mechanism that links the perception of BII stimuli with vasovagal reactions could aid the development of BII phobia treatments aimed at reducing phobic reactions among those for whom fainting is a salient aspect of their BII fear.

Further, given that only 2.4% of the Quebec population has given blood in the past year (Dubuc & Germain, 2013), uncovering the psychophysiological risk factors for experiencing vasovagal reactions would aid the identification of individuals who are more prone to experience them during blood donation and inform preventive interventions to improve the safety and frequency of blood donations.

The singularity of BII phobic reactions and the consistent observation that vasovagal reactions occur in settings involving BII stimuli suggest that the perception of blood, injection and injury triggers a specific psychophysiological response that gives rise to vasovagal symptoms. Given the central role of fainting in BII phobias and the wide-ranging implications of vasovagal reactions in the context of BII, many researchers have attempted to delineate the psychophysiological mechanism that underlies these reactions. Recently, authors have explored the possibility of the role of specific evolutionary adaptations (Diehl, 2005), hereditary factors (Page & Martin, 1998) and, importantly, the role of emotions (Page, 1994).

It is well known that emotions are capable of eliciting strong and specific physiological changes in the body, as demonstrated by the clearly differentiated physiological correlates of different emotions such as anger and sadness (Schaefer, Nils, Sanchez & Philippot,

Pain 39

PSI ISSUE V 2010). It is thus reasonable to suggest that because of the high prevalence of vasovagal reactions experienced

by BII phobics, that an intense fearful reaction to BII may underlie fainting symptoms. Indeed, fear and anxiety prior to blood donation has been consistently found to predict vasovagal reactions (Ditto, Gilchrist, & Holly, 2012; Viar, Etzel, Ciesielski, & Olatunji, 2010).

However, although there is an association between fear and fainting in BII situations, this emotion alone cannot explain the full variance in fainting symptoms (Ditto et al., 2012; Kleinknecht et al., 1996; Lerma, A., Lerma, C., Marquez, Cardenas, & Hermosillo, 2013).

Indeed, if excessive fear was the emotion that mediated the relationship between BII stimuli and fainting, then presumably this fainting response would be observed in other anxiety and phobic disorders. However, fainting is only rarely seen in other specific phobias (Connolly et al., 1976). Additionally, the physiological profile of fear seems to be at odds with the physiological correlates of vasovagal reactions; while the former is associated with an increase in blood pressure and heart rate (Hayashi et al., 2009; Kreibig, Wilhelm, Roth, & Gross, 2007), the latter is associated with a prominent drop in both of these cardiovascular indicators (Engel, 1978).

Another influential theory on the role of emotion in BII-related fainting seems to be more in line with the observed physiological profile of vasovagal reactions.

Despite some ongoing debates that suggest that it may be more heterogeneous (Ritz, Meuret, & Simon, 2013), BII-related fainting has been characterised by some as a “diphasic” response (Graham, 1961; Page, 1994). In some studies, measures of individuals’ physiological activity while they are exposed to BII stimuli reveal an initial rise in sympathetic nervous system activity (SNS), indicated in part by a rise in blood pressure and heart rate (Page, 2003; Marks, 1988; Ritz et al., 2013). This increased arousal, characteristic of a stressresponse, is followed by a subsequent drop in blood pressure and heart rate, corresponding to an increase in parasympathetic nervous system (PNS) activity. The PNS and SNS work in counterbalance, such that high activity in one system triggers an opposing increase in the other system in order to maintain physiological balance. Because the human body cannot sustain high levels of arousal for an extended period of time, blood pressure and heart rate is lowered back to normal levels through the activation of the PNS. However, during BII fainting, this opposing PNS activity has been found to be exaggerated, leading to abnormally low heart rate and blood pressure levels, which may prevent oxygen from being directed to the brain and cause a vasovagal syncope (Graham, 1961; Olatunji & Sawchuk, 2005).

According to some, this over-activation may be the result of strong feelings of disgust (Page, 2003).

Pain

Disgust has been described as a “highly visceral emotion” that has a protective function because it promotes the withdrawal from potentially contaminating objects in the environment (Eckart, Sturm, Miller & Levenson, 2012; Woody & Teachman, 2000). Disgust is also associated with a distinct physiological profile that corresponds to PNS activation: slowing of heart rate, gastrointestinal activation and enhanced saliva production (de Jong, van Overveld & Peters, 2011; Levenson, 1992; Woody & Teachman, 2000). Page (2003) argues that BII stimuli, unlike other types of stimuli, are able to elicit both fear and disgust and that these two emotions underlie the diphasic nature of vasovagal reactions. Accordingly, he argues that the initial rise in blood pressure seen prior to fainting symptoms is caused by increased fear or anxiety at the sight of blood, injections or injuries. Paired with strong feelings of disgust, the rise in PNS activity that opposes the initial SNS-mediated fear “sums” with the disgust-initiated PNS activation, resulting in a vasovagal reaction (Page, 2003). Hence, the sum of the homeostatic and the disgust-mediated rise in parasympathetic activity leads blood pressure and heart rate levels to drop lower than normal levels, and results in feelings of faintness.

Based on this theory, Page (2003) predicted that individuals who experience high levels of disgust at the sight of BII stimuli and who are higher on trait disgust sensitivity (the propensity to experience strong feelings of disgust to disgust-eliciting stimuli) are more likely to experience faintness. Furthermore, because he argues that blood stimuli should elicit more disgust than injection stimuli, he predicts that the association between disgust and fainting symptoms will be stronger during exposure to blood as opposed to injectionrelated stimuli. Page’s predictions were supported by a study in which he showed that diphasic changes in diastolic blood pressure from high to low, distinctive of a vasovagal reaction, were more pronounced in individuals who were highly disgust sensitive, as opposed to low on disgust sensitivity, when he exposed them to blood and mutilation related images (Page, 2003). However, this response was not replicated when he exposed the same individuals to injection related stimuli. This suggests that disgust sensitivity is associated with stronger vasovagal responses, especially during exposure to blood/mutilation stimuli, which is in line with Page’s theory.

The proposal that there is a relationship between disgust sensitivity and vasovagal symptoms is also supported by findings that levels of disgust sensitivity predict self-reported physiological responses to films depicting graphic medical procedures, such as amputations (Valentiner, Hood, Hawkins 2005). The experience of disgust during exposure to BII stimuli,

40

PSI ISSUE V as opposed to a trait measure of disgust sensitivity, has also been associated with vasovagal reactions. In a study conducted by Ayala, Meuret and Ritz (2010), respiratory dysregulation, a physiological indicator that has been associated with the onset of syncope episodes, was examined as individuals were exposed to a surgery film. The authors found that disgust ratings of the film were consistently related to indicators of respiratory dysregulation, such as unstable breathing.

In addition, Ayala et al. (2010) found that participants who experienced signs of fainting when watching the surgery film reported particularly strong feelings of disgust. This supports the idea that disgust may be involved in the triggering of vasovagal reactions.

Another line of research findings which supports the theory that disgust underlies BII-related faintness comes from studies of BII phobia. In studying phobic reactions to different phobic-relevant stimuli, researchers have found that disgust, and not fear, is the dominant emotional response of BII phobics when they are shown fear relevant stimuli (Olatunji, Lohr, Sawchuk, & Patten, 2007; Tolin, Lohr, Sawchuk & Lee, 1997). This is in contrast with other specific phobias: for example, spider phobics’ primary emotional response to images of spiders is fear (Sawchuk, Lohr, Westendorf, Meunier, & Tolin, 2002). These findings suggest that what seems to distinguish blood, injections and injuries in terms of the emotional reactions they provoke is that they elicit feelings of disgust. Hence, the theory of disgust is given strength by the fact that both a dominant disgust response and strong vasovagal reactions are unique in BII phobia.

Although there is support for the role of disgust in vasovagal reactions, not all researchers have found evidence for this relationship. In one study, Gerlach, Spellmeyer, Vogeler, Hustler and Stevens (2006) obtained physiological measures of vasovagal symptoms, such as blood pressure and heart rate, and found that they were not related to participant’s experience of disgust while undergoing a blood draw procedure. However, the absence of a significant relationship might be explained by the fact that 90% of their sample chose not to look at the injection procedure. Hence, the lack of visual perception of BII stimuli may have failed to elicit sufficiently strong reactions in participants. In another study, Kleinknecht, R., Kleinknecht, E., and Thorndike (1997) found that past history of fainting and fainting symptoms were inversely related to disgust sensitivity.

On the other hand, the interpretation of these findings is limited by the fact that the authors did not experimentally induce disgust by presenting participants with BIIrelated stimuli and used measures of fainting symptoms that were based solely on subjective recall. In studies of blood donor samples, faintness symptoms during

blood draw and fainting history have not been found to be related to the experience of disgust or disgust sensitivity (Viar et al., 2010; Vossbeck-Elsebusch & Gerlach, 2012). However, a limitation of these studies is that they did not include a measure of disgust sensitivity to “mutilation” or “animal-reminder” domains (for example, see Vossbeck-Elsebusch & Gerlach, 2012; Vossebeck-Elsebusch, Steinigeweg, Vogele & Gerlach, 2012), which are domains of disgust sensitivity that have been shown to be uniquely related to BII phobia and fainting symptoms (Olatunji & Sawchuk, 2005; Valentiner et al., 2005). Hence, the inconsistent methodology of previously conducted studies does not permit definite conclusions about the role of disgust in BII-related faintness.

The contradictory findings in the literature may be due to the type of stimuli that was used in these studies. Whereas findings that provide support for a relationship between disgust and vasovagal reactions are primarily based on studies in which the stimuli used were salient blood and mutilation images (e.g. a surgery film; Ayala, et al., 2010; Valentiner et al., 2005) several studies’ results that fail to support the relationship were obtained in the context of blood donation (Gerlach et al., 2006; Viar et al., 2010; Vossbeck-Elsebusch & Gerlach, 2012). If the type of stimuli used plays a role in the contradictory findings reported in the literature, then this inconsistency does not go against Page’s (2003) prediction that the relationship between disgust and fainting symptoms should be seen during exposure to more salient blood and mutilation stimuli as opposed to injection stimuli. Because we know that vasovagal responses are stronger during exposure to blood stimuli as opposed to injection stimuli, and that blood phobics have a greater fainting history than injection phobics, the role of disgust in BII-related fainting may be specific to certain BII domains, such as blood and mutilation (Gilchrist & Ditto, 2012; Ost, 1992).

Given these mixed findings, the aim of the present study was to further examine the relationship between individual differences in disgust sensitivity and vasovagal symptoms when subjects are exposed to two films related to two different BII domains: 1) blood draw/injections, and 2) blood/mutilation. Indicators of vasovagal reactions were obtained using measures of heart rate after each video and self-reported vasovagal symptoms. Consistent with Page’s theory (2003), it was predicted that individuals high in disgust sensitivity would experience more vasovagal symptoms and steeper decreases in heart rate after watching the BII videos, than individuals low in disgust sensitivity.

Furthermore, it was hypothesized that the association between disgust sensitivity would interact with stimuli type, such that when exposed to the blood and

41 Pain

PSI ISSUE V mutilation stimulus, more disgust sensitive individuals would report higher levels of vasovagal symptoms and experience larger decreases in heart rate compared to when they are exposed to an injection and blood draw stimulus.

Methods Participants Recruitment of participants was done through online classified ads targeted at the general public and university students. Respondents were screened and excluded if they indicated any neurological or cardiovascular illnesses, if English was not their first or second language, and if they were not aged between 18-30 years old. 29 participants met the aforementioned eligibility criteria and signed informed consent. The final sample consisted of 29 undergraduate students and young adult community volunteers (8 males and 21 females) aged 18 to 30 years old (M=22.3; SD=3.5).

Materials Demographic questionnaire. A short demographic survey was administered along with the baseline selfreport measures and included questions on sex and age.

Stimuli. Four videos expected to elicit different emotional reactions were presented in a counterbalanced order, each lasting between 3.5 to 5 minutes on a laptop computer. An additional video serving as a neutral stimulus was shown first to all participants and consisted of a short documentary about a sustainability project on McGill University campus. Two of the four videos were BII-related stimuli. A scene from the movie The Exorcist (Friedkin & Blatty, 1973) was used as the injection/blood draw stimulus. In the scene, a medical doctor first gives an injection to a young girl and inserts a catheter in her neck in a medical setting, with blood spilling. The other BII-related stimulus consisted of an educational video of a heart surgery (Ritz, Wilhelm, Gerlach, Kullowatz, & Roth, 2005), and served as a mutilation/blood stimuli.

As part of the larger study, two other videos with no relevance to BII were presented to elicit non-BII-related disgust (a scene from the movie Trainspotting depicting images of a dirty toilet; Schaefer et al., 2010) and fear (a scene from the movie The Shining in which a man chases his wife and his child with an axe; Schaefer et al., 2010). In the present investigation, only responses to the baseline video and the two BII-related videos were used in analyses.

Disgust Emotion Scale (DES; Olatunji, Sawchuk, de Jong & Lohr, 2007). The DES was used to measure participant’s disgust sensitivity. The DES assesses sensitivity to disgust across five domains:

Pain

Animals, Injections and Blood Draws, Mutilation and Death, Rotting Foods and Smells. In this self-report questionnaire, participants rate 30 situations according to how much disgust or repugnance they would experience if they were directly exposed to them on a 5 point Likert scale, from 0 (“No disgust or repugnance at all”) to 4 (“Extreme disgust or repugnance”). Items include statements such as “A bottle of your blood” and “The smell of vomit”. Total scores on the DES are calculated by summing scores obtained on each item.

The DES has previously demonstrated good internal reliability with a Cronbach’s alpha of 0.90 and high item-total correlations for 29 out of 30 items ranging from 0.31 to 0.62 (Olatunji, Sawchuk, de Jong & Lohr, 2007).

Blood Donations Reactions Inventory (BDRI; France, France, Roussos, Ditto, 2004) A subjective measure of vasovagal symptoms was obtained using the BDRI. The BDRI is a self report measure which asks participant to rate, on a 6-point Likert scale, the extent to which they experienced symptoms associated with vasovagal reactions while watching the videos, from 0 (“not at all”) to 5 (“extremely”). Symptoms included are dizziness, lightheadedness, weakness, facial flush, visual disturbance, difficulty hearing, rapid or pounding heartbeat, sweating, rapid or difficult breathing, and nausea. Following recommendations from France, Ditto, France and Himawan (2008), only scores from four of the previous symptoms were analysed: weakness, lightheadedness, dizziness and faintness. In their factor analysis, France et al. (2008) showed that these items provide the best measure of symptoms that predict the risk of vasovagal syncope. Scores on the 4-item BDRI has demonstrated good concurrent validity, with higher scores predicting significantly more fainting episodes in samples of blood donors (France et al., 2008).

Furthermore, the 4-item BDRI has demonstrated high internal consistency, with Cronbach’s alpha ranging from 0.93-0.96 (France et al., 2008).

Heart rate. Repeated measurements of heart rate were obtained at baseline and approximately 1 minute after the end of each video using an automatic ambulatory Accutor® monitor pulse oximeter (Accutorr Plus, Data Scope Corp., Mont Vale, NJ, USA) with the cuff attached to the upper dominant arm.

Procedure Participants who met criteria for the study attended one testing session lasting approximately 80 minutes and were tested individually. Upon the scheduling of a session, participants were asked to refrain from vigorous physical activity on the day of testing and to refrain from smoking, drinking of caffeinated beverages or eating for two hours before the start of

42

PSI ISSUE V the experiment. In order to be more comfortable when connected to the physiological equipment, they were advised to wear a short-sleeved shirt. After providing informed consent, participants were attached to the physiological equipment and administered the baseline questionnaires which included the demographic survey and the DES. After completing the baseline questionnaires participants were presented the neutral stimulus (documentary), followed by the four emotional videos that were presented in a counterbalanced order.

To ensure that participants habituated to the laboratory conditions and to the physiological equipment, a baseline measure of their heart rate was obtained 5 minutes after they started completing the baseline questionnaires. Three other heart rate measurements were obtained approximately 1 minute before the end of each video. At the end of each video, participants rated how much fear and disgust they experienced while watching them on a 7-point Likert scale from 0 (“not at all”) to 6 (“extremely”), and reported the symptoms they experienced during the videos by completing the BDRI. All participants were given 20$ compensation for their time. All research procedures were approved by the McGill University Institutional Review Board.

sensitivity” or “high disgust sensitivity” group if they obtained DES scores lower than or higher than 40.5, respectively. Where appropriate, mean disgust scores, 4-item BDRI scores and HR are reported for the different groups and are represented in the figures. The alpha level was set to p < 0.05 for all statistical tests.

Results Manipulation Checks Self-reported symptoms. A 2 (Sex: male, female) X 3 (Video: documentary, exorcist, surgery) ANOVA of BDRI scores yielded a strong significant main effect of Video, F (2,54) = 11.36, p < .001, due to the higher BDRI scores obtained after the exorcist and surgery videos, but not after the documentary video. The main effect of Sex and the Sex by Video interaction were not significant.

Heart rate. To investigate the effect of video on heart rate, a 2 (Sex: male, female) X 4 (Time: baseline, documentary, exorcist, surgery) ANOVA of heart rate was conducted. The ANOVA yielded a significant main effect of time, F (3,72) = 4.21, p = .016. Significant decreases in heart rate from baseline to the BII videos (exorcist, surgery) were observed. However, the decrease in heart rate from baseline to the documentary video was not significant. The main effect of Sex and the Sex by Time interaction were not significant. Combined with the fact that testing had to be interrupted for one participant because of a strong vasovagal reaction (verbally reported feelings of nausea, lightheadedness and faintness) to the BII videos, which was associated with a marked decrease in heart rate from baseline (74 beats per minute) to the exorcist and surgery video (66 and 50 beats per minute, respectively), the previous analyses suggest that the videos used in the study elicited sufficient, although generally mild, vasovagal symptoms.

Emotional responses. Two 2 Sex (male, female) X 3 Video (documentary, exorcist, surgery) X DES (entered as a continuous variable) repeated measures GLMs were performed on disgust and fear responses. The GLM of disgust ratings yielded a significant main effect of DES, F (1, 25) = 38,53, p = .002, and a significant Video by DES interaction, F (2, 25) = 6,79, p = .015. Comparisons of mean disgust ratings of high disgust sensitivity and low disgust sensitivity groups indicated the high disgust sensitivity group experienced more disgust than the low disgust sensitivity group during the exorcist and surgery video, respectively (see Figure 1). However, the two groups did not differ in their disgust responses to the documentary video. The main effect of Sex and the Video by Sex interaction were not significant.

Overview of Statistical Analyses Scores on the 4-item BDRI completed after each video (documentary, exorcist, surgery) were calculated for each participant and log-transformed to reduce the positive skew of the distribution. Total DES score at baseline was also calculated for each participant. To ensure that the stimuli used in the study elicited the expected emotional and physiological reactions, several analyses of variance (ANOVAs) were conducted to examine the effect of video on heart rate and vasovagal symptoms, with sex entered as a between-subjects factor in all analyses.

In order to allow for the analysis of both categorical and continuous variables, analyses of the effects of disgust sensitivity were conducted as general linear models (GLMs). Sex (male, female) and disgust sensitivity (continuous) were included as independent variables in all analyses. To compare the effects of disgust sensitivity on BDRI scores obtained after watching the different videos, a repeated measures factor with 3 levels of video (documentary, exorcist, surgery) was added to the GLM. To investigate the effects of disgust sensitivity on heart rate, a repeated measures factor with 4 levels of time (baseline, documentary, exorcist, surgery) was added to the GLM. For illustration purposes, groups categorised as low and high in total disgust sensitivity were formed using median splits of participants’ scores on the DES scale. Individuals were categorised in the “low disgust

43 Pain

PSI ISSUE V The GLM of fear ratings also yielded a strong significant main effect of DES, F (1, 25) = 41,99, p = .00, and a significant Video by DES interaction, F (2, 25) = 8,48, p = .007. Mean comparisons of fear ratings of high disgust sensitivity and low disgust sensitivity groups indicated the high disgust sensitivity group experienced more fear than the low disgust sensitivity group during the exorcist and surgery video, respectively. However, the two groups did not differ in their fear responses to the documentary video (M=1, SD= 0, for both groups).

The main effect of Sex and the Video by Sex interaction were not significant.

Relationship between disgust sensitivity and vasovagal reactions Self-reported symptoms. A 2 Sex (male, female) X 3 Video (documentary, exorcist, surgery) X DES (treated as a continuous variable) GLM of BDRI scores produced a significant main effect of disgust sensitivity on selfreported vasovagal symptoms, F(1,24) = 7.33, p = .012.

In general, individuals higher in disgust sensitivity reported more vasovagal symptoms on the BDRI compared to individuals lower in disgust sensitivity (Figure 2). While the Video by DES interaction was not significant, the overall association was due mainly to a significant correlation between disgust sensitivity and surgery video BDRI score, r = .39, p = 0.42. The correlation between disgust sensitivity and exorcist video BDRI score approached significance, r =. 36, p = .059. On the other hand, the correlation between disgust sensitivity and documentary video DBRI score was not significant, r = .23, p = .22. This suggests that the main effect of disgust sensitivity on self-reported vasovagal symptoms was not due to a general reporting bias of high disgust sensitivity individuals because scores on the DES were not significantly correlated with symptoms during the neutral stimulus, though this possibility cannot be excluded. The relationship between disgust sensitivity and self reported symptoms appears to have occurred when participants were exposed to relevant disgust-eliciting stimuli.

Heart Rate. A 2 Sex (male, female) X 4 Time (baseline, documentary, exorcist, surgery) X DES (treated as a continuous variable) GLM on heart rate yielded a significant main effect of disgust sensitivity, F (1,21) = 4.56, p = 0.45. As can be seen in Figure 3, this was due mainly to higher baseline heart rate in high disgust sensitivity participants followed by somewhat larger drops in heart rate, although there was no significant Time by DES interaction. The significantly higher mean heart rate of the high disgust sensitive participants was maintained throughout the study.

Pain

Discussion The role of disgust in vasovagal reactions experienced in the context of blood injections and injuries has been hypothesized because of the emotion’s corresponding physiological correlates. However, to date, research has yielded mixed findings. Accordingly, the effect of individual differences in disgust sensitivity on selfreported vasovagal symptoms and heart rate during exposure to videos of injections/blood draw and mutilation/blood were investigated. It was predicted that higher levels of disgust sensitivity would be associated with higher levels of vasovagal symptoms during exposure to BII stimuli as opposed to a neutral stimulus.

The results of the study partly support the hypothesis.

While higher disgust sensitivity was associated with the report of more vasovagal symptoms, this relationship did not vary as a function of video, as indicated by the failure to find a significant interaction between disgust sensitivity and video type. This suggests that the role of disgust sensitivity may not be specific to BII-related stimuli as high disgust sensitive individuals seemed to report more vasovagal symptoms regardless of the video that was shown, which may indicate a reporting bias on the part of high disgust sensitive individuals. On the other hand, the investigation of separate correlations between disgust sensitivity and vasovagal symptoms at each video condition showed that while the correlation between disgust sensitivity and symptoms reported after the neutral video was not significant, the correlation between the two measures approached significance, and was significant during the blood draw/injection and the blood/mutilation stimuli, respectively. It is possible that the inclusion of more participants in the study would provide more statistical power to detect a significant interaction.

The failure to find that the disgust sensitivitysymptom relationship varied as a function of video is also contrary to our prediction that the effect of disgust sensitivity on vasovagal symptoms would be greater during exposure to blood/mutilation stimuli compared to injection/blood draw stimuli. Alternatively, the fact that both BII videos depicted salient images of blood and blood spilling may account for this lack of a difference.

It may be that the role of disgust sensitivity in faintness elicited by BII stimuli is fully accounted for by the fact that blood alone is capable of eliciting sufficiently strong disgust responses. This is consistent with the finding that nonphobic individuals are significantly more likely to report vasovagal symptoms after watching a video of a blood draw compared to an identical video depicting a saline injection, suggesting that the basis of vasovagal reactions is “in the blood” (Gilchrist & Ditto, 2012).

Interestingly in their study, Gilchrist and Ditto (2012)

44

PSI ISSUE V did not find that disgust sensitivity was associated with self-reported symptoms after watching either video.

Perhaps their use of shorter and milder BII videos, as well as their use of a different scale to measure disgust sensitivity account for this inconsistency.

Contrary to the hypothesis, disgust sensitivity was associated with higher heart rate which was mainly a result of the significantly higher heart rates of disgust sensitive individuals at baseline, although this difference was also maintained throughout the study.

This suggests that individuals who are more sensitive to disgust may experience more anticipatory anxiety at the prospect of watching disgust-eliciting videos, as well as more arousal in general. However, it does not support the hypothesis that the effect of disgust sensitivity on vasovagal symptoms is mediated by the theorised heart rate reducing effects of disgust reactions. Nevertheless, there may be alternative explanations to these findings.

The idea that disgust may play a role in vasovagal reactions is based on the proposal that BII-related fainting is diphasic. However, this diphasic response has not been observed in all studies. In fact, recent evidence suggests that an activation of the cardiovascular system such as an increase in blood pressure and heart rate, as opposed to a deactivation, is the most common physiological profile of BII phobics when they are exposed to a surgery film (Ritz et al., 2013; Sarlo, Buodo, Munafo, Stegagno, & Palomba, 2008). Given that disgust sensitivity was associated with both more subjective vasovagal symptoms and higher heart rate, it may be that rather than reflecting strong disgust responses, the higher self-reported vasovagal symptoms reported by disgust sensitive individuals may be indicative of their generally higher arousal and reactivity to disgusteliciting stimuli. Indeed, the fact that high disgust sensitive subjects reported not only more disgust, but more fear to the videos suggests that the effect of disgust sensitivity on reactions to BII stimuli is not specific to disgust. It is also possible that when rating the statements included on the DES, individuals may not reliably make the distinction between the disgust and general arousal that they would experience given the exposure to the proposed situations on the scale. This, in turn, reduces the confidence that we have that the results obtained from the DES really measure sensitivity to the experience of disgust to disgust-eliciting stimuli, and not a generalised emotional response.

The possibility that the role of disgust sensitivity is its arousal-enhancing effect on reactions to BII stimuli is also consistent with findings that suggest that the relationship between faintness and disgust sensitivity is mediated by BII fears (Kleinknecht et al., 1997; Olatunji, Williams, Sawchuk, & Lohr, 2006; VossbeckElsebusch & Gerlach, 2012). Consequently, the lack of

a distinction between the effects of fear and disgust on vasovagal reaction may reflect the fact that the role of emotions in vasovagal reaction is simply related to their effects on increases in arousal. The idea that the role of disgust sensitivity reflects a generally heightened arousal is also supported by evidence from a recent fMRI study that BII phobics who are also characterised by higher disgust sensitivity display reduced activity in the brain regions associated with cognitive emotion regulation when exposed to phobic-relevant stimuli (Hermann, 2007). The authors suggest that the phobic reactions in disgust sensitive BII phobics may be a result of reduced automatic control over their disgust reactions which may result in abnormally strong feelings of arousal and fear to these stimuli.

Alternatively, it is possible that other physiological mechanisms may mediate the effect of the interplay between disgust sensitivity and fear on BII-related fainting symptoms. In a sample of blood phobics, hyperventilation caused by deep breathing was shown to be associated with higher levels of vasovagal symptoms (Ritz, Wilhelm, Meuret, Gerlach, & Roth, 2009). Similarly, reactions to disgusting stimuli have been associated with breath holding (Boiten, 1998) and dysregulated breathing (Ayala et al., 2010). It is therefore possible that the effect of disgust sensitivity on selfreported vasovagal symptoms may be accounted for by the dysregulated breathing engaged in by individuals who experience strong emotional reactions to BII stimuli.

Taken together, these findings suggest that disgust sensitivity plays a role in the symptoms that individuals experience while exposed to BII stimuli.

However, the finding that disgust sensitivity was related to higher fear ratings and with higher heart rate casts doubt on the idea of a role of disgust in the decrease in heart rate that underlies vasovagal reactions. Instead, the role of disgust in BII related vasovagal reactions may be that, when combined with generally more anxiety/fear and lower cognitive emotion regulation, this creates a specific type of arousal that leads individuals to engage in certain coping behaviours, such as breathing deeper, which themselves trigger the physiological response that lead to vasovagal reactions. The frequent fainting experienced by BII phobics may therefore be a result of both their greater arousal during BII exposure as well as the way they physically cope with this arousal. These physical coping behaviours may also be performed by individuals during blood donation. On the other hand, not all blood donors and BII phobics who faint are disgust sensitive or are highly fearful. Kleinknecht, Kleinknecht and Thorndike (1997) suggested that there may be different types of fainters such as â&#x20AC;&#x153;escape faintersâ&#x20AC;? who experience fainting symptoms because

45 Pain

PSI ISSUE V of strong emotions, and “essential fainters” who report no more fear or disgust prior to fainting (Kleinknecht, Lenz, Ford, & De Berard, 1990). If this is the case, then this suggests the need for individualized approaches to the way that fainting is prevented in BII phobics and blood donors (Ritz et al., 2013).

Limitations and Future Directions

related fainting. Because BII phobics are characterised by more disgust sensitivity, this vulnerability could be targeted as part of treatments aimed at reducing phobic reactions. Future research should nevertheless attempt to replicate these findings in a sample of BII phobics and examine whether the same pattern of responses are found. Moreover, future research should further explore the role of hyperventilation responses not only in BII phobics but also in blood donors. Finally, given that disgust sensitivity was also associated with more fear responses, it would be worthwhile to develop more reliable tools to clearly delineate whether disgust sensitivity measures general arousal to disgust-eliciting stimuli, including BII stimuli, as opposed to actual propensity to physically and emotionally experience disgust.

Although the results of this study provide additional evidence for a role of disgust sensitivity in vasovagal reactions experienced in the context of BII stimuli, the results need to be interpreted in the light of the study’s methodological limitations. First, the sample of the study was small and consisted mostly of healthy young females. Therefore, the results of the study may not be generalizable to the larger population. However, the effect of sex was nonsignificant in all analyses and a significant effect of disgust sensitivity and a trend References toward a significant interaction of disgust sensitivity with video were found, suggesting that these effects American Psychiatric Association (2013).Diagnostic and statistical manual of mental disorders: DSMmay be stronger if the study was replicated with a larger sample. Second, the nature of the different BII stimuli 5. Washington, D.C: American Psychiatric might have confounded the results. The video used for Association. the injection/blood draw stimuli was a theatrical scene Ayala, E., Meuret, A., & Ritz, T. (2010). Confrontation with blood and disgust stimuli precipitates borrowed from a famous horror movie. Because the

respiratory dysregulation in blood-injectionparticipants knew that they would watch a scene from

injury phobia. Biological Psychology, 84, 1, this movie, this might have led them to experience more 88-97.doi:http://dx.doi.org/10.1016/j. anticipatory anxiety prior to watching the film based on biopsycho.2010.02.004 their knowledge that the movie contains scary scenes. Boiten, F. (1998). The effects of emotional behaviour Therefore, participants’ emotional and physiological on components of the respiratory cycle. reactions to the movie scene may not have reflected Biological Psychology, 49, 29-51. reactions to the injection/blood draw images contained Bravo, M., Kamel, H., Custer, B., & Tomasulo, P. (2011). Factors associated with faintingin the video but their emotional reaction to the famous

before, during and after whole blood donation. movie itself. Likewise, the surgery clip that was used as

Vox Sanguinis, 101, 303-312. doi: http://dx.doi. the mutilation stimulus was educational in nature and

org/10.1111/j.1423-0410.2011.01494.x this might have diminished the potential fear and disgust reactions that would have been elicited if pure images of Connolly, J., Hallam, R., & Marks, I. (1976). Selective

association of fainting with blood-injuryblood and mutilated bodies had been used. In the future, illness fear. Behavior Therapy, 7, 1, 8-13. studies should employ more standardised BII videos to de Jong, P., van Overveld M., Peters, M. (2011). control for these possible confounds. A third limitation Sympathetic and parasympathetic responses concerns the use of a single measurement of heart rate to a core disgust video clip as a function to detect vasovagal reactions. This may have limited our of disgust propensity and disgust sensitivity.

Biological Psychology, 88, 174-179. doi: http:// ability to detect significant decreases in heart rate from dx.doi.org/10.1016/j.biopsycho.2011.07.009 baseline. Based on the fact that vasovagal reactions may occur only instances after BII exposure (Bravo, Kamel, Diehl, R. (2005). Vasovagal syncope and Darwinian Custer & Tomasulo, 2011), future studies should collect fitness. Clinical Autonomic Research, 15, 2, 126129. doi : http://dx.doi.org/10.1007/s10286multiple measures of heart rate over the video exposure

005-0244-0 period as well as after BII exposure to examine more Ditto, B., Gilchrist, P., & Holly, C. (2012). Fear-related specific changes in heart rate over time.

predictors of vasovagal symptoms during Despite these limitations, the finding that blood donation: it’s in the blood. Journal of disgust sensitivity had an effect on both emotional and Behavioral Medicine, 35, 4, 393-9. doi : http:// dx.doi.org/10.1007/s10865-011-9366-0 physiological responses to BII stimuli suggests that it is a relevant factor to consider in the prevention of BII Dubuc, S., Germain, M.. (2013). Hema-Quebec: Pain

46

PSI ISSUE V

Rapport demograpique annuel (2012-2013).

Retrieved from http://www.hema-quebec.qc.ca/

userfiles/file/Rapport%20

d%C3%A9mographique%202012-2013.pdf Eckart, J., Sturm, V., Miller, B., Levenson, R.. (2012).

Diminished disgust reactivity in behavioural

variant frontotemporal dementia.

Neuropsychologia, 50, 5, 786-790. doi: http://

dx.doi.org/10.1016/j.

neuropsychologia.2012.01.012 Engel, G. L. (1978). Psychologic stress, vasodepressor

(vasovagal) syncope, and sudden death. Annals

of Internal Medicine, 89, 403-412.

France, C. R., Ditto, B., France, J. L., & Himawan,

L. K. (2008). Psychometric properties

of the Blood Donation Reactions Inventory: a

subjective measure of presyncopal reactions

to blood donation. Transfusion, 48, 9,

1820-1826. doi : http://dx.doi.org/10.1111/

j.1537-2995.2008.01831.x France C.R., France, J. L., Roussos, M., Ditto, B. (2004).

Mild reactions to blood donation predict a

decreased likelihood of donor return.

Transfusion and Apheresis Science, 30, 1, 17-22. doi : http://dx.doi.org/10.1016/j.

transci.2003.08.014 France, C., Rader, A., and Carlson, B. (2005). Donors

who react may not come back: Analysis of

repeat donation as a function of phlebotomist

ratings of vasovagal reactions. Transfusion and

Apheresis Science, 33, 2, 99-106.

Friedkin, W. (Director), Blatty, W. (Writer). (1973). The Exorcist [Motion picture]. United States:

Warner Bros.

Ganzeboom, K. S., Colman, N., Reitsma, J. B., Shen,

W. K., & Wieling, W. (2003). Prevalence and

triggers of syncope in medical students. The

American Journal of Cardiology, 91, 8,

1006-1008. doi: http://dx.doi.org/10.1016/

S0002-9149(03)00127-9 Gerlach, A., Spellmeyer, G., Vogele, C., Huster, R.

& Stevens, S. (2006). Blood-injury phobia with

and without a history of fainting :

Disgust sensitivity does not explain the fainting response. Psychosomatic Medicine, 68, 2,

331-339. doi : http://dx.doi.org/10.1097/01.

psy.0000203284.53066.4b Gilchrist, P. & Ditto, B. (2012). The effects of blood draw and injection stimuli on the vasovagal response. Psychophysiology, 49, 815-920. doi:

http://dx.doi.org/10.1111/j.1469-8986.20

12.01359.x Graham, D. T. (1961). Prediction of fainting in blood donors. Circulation, 23, 901-906 Hayashi, N., Someya, N., Maruyama, T., Hirooka, Y.,

Endo, M., & Fukuba, Y. (2009). Vascular r

esponses to fear-induced stress in humans.

Physiology and Behavior, 98, 441-446.

Hermann, Schafer, Walter, Stark, Waitl, & Schienle

(2007). Diminished prefrontal cortex activity

in blood-injection-injury phobia. Biological Psychology, 75, 124-130.

Kleinknecht, R., & Lenz, J. (1989). Bloog/injury fear,

fainting and avoidance of medically-related

situations: A family correspondence study.

Behaviour Research and Therapy, 27, 537-547.

Kleinknecht, R. (1988). Specificity and psychosocial

correlates of blood/injury fear and fainting,

Behaviour Research and Therapy, 26, 303–309 Kleinknecht, R., Kleinknecht E., and Thorndike R.

(1997). The role of disgust and fear in blood

and injection-related fainting symptoms: A

structural equation model. Behavior, Research

and Therapy, 35,12, 1075-1087.

Kleinknecht R, Lenz J, Ford G, & De Berard S. (1990).

Types and correlates of blood/injury-related

vasovagal syncope. Behaviour Research and Therapy, 28, 289–95 Kleinknecht, R., Thorndike, R., Walls, M. (1996).

Factorial dimensions and correlates of blood,

injury, injection and related medical fears:

cross validation of the medical fear survey.

Behavavior, Research and Therapy, 34, 4, 323 331.

Kreibig, S., Wilhelm, F., Roth, W., & Gross, J. (2007)

Cardiovascular, electrodermal, and respiratory

response patterns to fear- and sadness-inducing films. Psychophysiology, 44, 787-806.

Lerma, A., Lerma, C., Marquez, M. F., Cardenas,

M., & Hermosillo, A. G. (2013). Correlation

of syncopal burden with anxiety symptoms

score in recurrent vasovagal syncope. International Journal of Cardiology, 166, 1, 266-267. doi: http://dx.doi.

org/10.1016/j.ijcard.2012.09.105 Levenson, R. W.. (1992). Autonomic nervous system

differences among emotions. Psychological Science, 3, 1, 23-27.

Marks, I. (1988). Blood-injury phobia: a review. The

American Journal of Psychiatry, 145, 10, 1207 1213.

Moya, A., Sutton, R., Ammirati, F., Blanc, J., Brignole,

M., Dahm, J. B., … Wieling, W.. (2009).

Guidelines for the diagnosis and management

of syncope (version 2009). European Heart Journal, 20, 2631–71. doi : http://dx.doi.

org/10.1093/eurheartj/ehp298 Olatunji, B., Lohr, J., Sawchuk, C., & Patten, K. (2007).

Fear and disgust responding to heterogeneous

blood-injection-injury stimuli : Distinctions

from anxiety symptoms. Journal of Psychopathology

and Behavioral Assessment, 29, 1, 1-8. doi :

http://dx.doi.org/10.1007/s10862-006-9025-x Olatunji, B. & Sawchuk, C. (2005). Disgust :

Characteristic features, social manifestations,

and clinical implications. Journal of Social and

47 Pain

PSI ISSUE V

Clinical Psychology, 24,7, 932-962.

Olatunji, B., Sawchuk, C., de Jong, P., Lohr, J. (2007).

Disgust sensitivity and anxiety disorder

symptoms: Psychometric properties of the

Disgust Emotion Scale. Journal of

Psychopathology and Behavioral Assessment, 29, 115-124. doi : http://dx.doi.org/10.1007/

s10862-006-9027-8 Olatunji, B., Williams, N., Sawchuk, C., & Lohr,

J. (2006). Disgust, anxiety and fainting

symptoms associated with blood-injection injury fears: a structural model. Journal of

Anxiety Disorders, 20, 23-41 Ost, L. G. (1992). Blood and injection phobia:

background and cognitive, physiological,

and behavioral variables. Journal of Abnormal Psychology, 101, 1, 68-74.

Page, A. C. (1994). Blood-injury phobia. Clinical

Psychology Review, 14, 443-461.

Page, A. C. (2003). The role of disgust in faintness

elicited by blood and injection stimuli. Journal

of Anxiety Disorders, 17, 45-58. doi : http://

dx.doi.org/10.1016/S0887-6185(02)00169-X Page, A., & Martin, G. (1998). Testing a genetic

structure of blood-injury-injection fears. American Journal of Medical Genetics, 81, 377-384.

Ritz, T., Meuret, A. & Simon, E. (2013) Cardiovascular

activity in blood-injection-injury phobia

during exposure: Evidence for diphasic

response patterns? Behavior Research and Therapy, 51, 460-468 Ritz, T., Wilhelm, F. H., Gerlach, A. L., Kullowatz,

A., & Roth, W. T. (2005). End-tidal pCO2

in blood phobics during viewing of

emotion- and disease-related films.

Psychosomatic Medicine, 67, 4.

Ritz, T., Wilhelm, F., Meuret, A., Gerlach, A., & Roth,

W. (2009). Do blood phobia patients

hyperventilate during exposure by breathing

faster, deeper, or both? Depression and Anxiety,

26, E60-E67.

Sapolsky, R. M. (2004). Stroke, heart attacks and

voodoo death. In R. Sapolsky (Eds.), Why

zebras don’t get ulcers (pp.37-56). New York:

Times Books.

Sarlo, M., Buodo, G., Munafò, M., Stegagno, L., &

Palomba, D. (2008). Cardiovascular

dynamics in blood phobia: Evidence for a

key role of sympathetic activity in vulnerability

to syncope. Psychophysiology, 45, 6, 1038-1045 Sawchuk, C., Lohr, J., Tolin, D., Lee, T., Kleinknecht,

R. (2000) Disgust sensitivity and contamination

fears in spider and blood-injection-injury phobias. Behaviour,Research and Therapy, 38, 753-762.

Sawchuk C.N., Lohr J.M., Westendorf D.H., Meunier

S.A., Tolin D.A. (2002). Emotional Responding

to fearful and disgusting stimuli in specific

Pain

phobics. Journal of Behaviour Research

and Therapy, 40, 9, 1031-1046. doi : http://

dx.doi.org/10.1016/S0005-7967(01)00093-6 Schaefer, A., Nils, F., Sanchez, X., & Philippot, P.

(2010). Assessing the effectiveness of a large

database of emotion-eliciting films: A

new tool for emotion researchers. Cognition

& Emotion, 24, 7, 1153-11. doi : http://dx.doi.

org/10.1080/02699930903274322 Tolin, D., Lohr, J., Sawchuk, C., & Lee, T. (1997).

Disgust and disgust sensitivity in blood injection-injury and spider phobia. Behaviour

Research and Therapy, 35, 949–953. doi : http:// dx.doi.org/10.1016/S0005 7967(97)00048-X Valentiner, D., Hood, J., & Hawkins, A. (2005).

Fainting history, disgust sensitivity, and

reactions to disgust-eliciting film stimuli. Personality and Individual Differences, 38, 6, 1329-1339. doi : http://dx.doi.

org/10.1016/j.paid.2004.08.015 Viar, M. A., Etzel, E. N., Ciesielski, B. G., & Olatunji,

B. O. (2010). Disgust, anxiety, and vasovagal

syncope sensations: A comparison of injection fearful and nonfearful blood donors. Journal of

Anxiety Disorders, 24, 8, 941-945. doi :

http:// dx.doi.org/10.1016/j.janxdis.

2010.06.021 Vossbeck-Elsebusch, A. N., & Gerlach, A. L. (2012).

The relation between disgust-sensitivity,

blood-injection-injury fears and vasovagal

symptoms in blood donors: Disgust sensitivity

cannot explain fainting or blood donation related symptoms. Journal of Behavior Therapy

and Experimental Psychiatry, 43, 1, 607-613. doi: http://dx.doi.org/10.1016/j.

btep.2011.08.005 Vossbeck-Elsebusch, A., Steinigeweg, K., Vogele,

C., Gerlach, A. (2012). Does disgust increase

parasympathetic activation in individuals

with a history of fainting? A

psychophysiological analysis of disgust stimuli

with and without blood-injection-injury association. Journal of Anxiety Disorders,

26, 849-858. doi: http://dx.doi.org/10.1016/j.

janxdis.2012.07.003 Woody, S., & Teachman, B. (2000). Intersection

of disgust and fear: Normative and pathological views. Clinical Psychology, 7, 3, 291-311. doi:

http://dx.doi.org/10.1093/clipsy.7.3.291

48

PSI ISSUE V Appendix

Figure 1. Mean disgust level reported after each video (documentary, exorcist, surgery) by participants who obtained the highest scores (â&#x2030;Ľ41; high disgust sensitivity) and the lowest scores (â&#x2030;¤ 40; low disgust sensitivity) on the DES.

49 Pain

PSI ISSUE V

Figure 2. Self-reported vasovagal symptoms on the 4-item BDRI in log-transformed units obtained by participants who obtained the highest scores (â&#x2030;Ľ41; high disgust sensitivity) and the lowest scores (â&#x2030;¤ 40; low disgust sensitivity) on the DES.

Figure 3. Mean heart rate (beats per minute) by disgust sensitivity group (low vs. high)

Pain

50

PSI ISSUE V

2015

Perceived Injustice and Pain Outcomes In a Healthy Student Sample Tudor Vrinceanu* Supervisor: Professor Michael Sullivan *email: vrinceanu.tudor@gmail.com

Abstract The primary aim of this paper was to validate the Trait Injustice Experience Questionnaire (T-IEQ) in a healthy student sample using a cold pressor paradigm. For this purpose, the 12-item questionnaire was administered to 74 healthy adults, along with the measure of pain catastrophizing, anger, depression, and anxiety. All of the questionnaires were administered twice: before and after the cold pressor test. During the cold pressor test, selfreport measures of pain intensity and displays of pain behavior were calculated. The results showed that the T-IEQ was significantly correlated to measures of pain catastrophizing and depression, and it was only marginally correlated to anger, anxiety, protective pain behavior, and pain intensity. When looking only at the highest quartile of respondents on the T-IEQ, there was a significant relationship between perceived injustice and protective pain behavior and total pain behavior. The results of the present study provide first empirical evidence suggesting that a general propensity to perceive the world as unfair may also be associated with pain outcomes, anxiety, depression, and anger. Theoretical implications are discussed.

Keywords: perceived injustice; pain catastrophizing; pain behavior; cold pressor; pain Acknowledgements I would like to thank professor Michael Sullivan, and the graduate student Esther Yakobov for their advice and feedback while working on this research project.

51

Pain

PSI ISSUE V

Recent studies suggest that perceived injustice might also influence mental health of patients with As humans, we have always been concerned with pain; chronic pain. One study examined individuals who consequently, we have tried to better understand why we sustained whiplash injuries and developed postfeel pain, what causes pain, and how we can minimize traumatic stress (PTSD) symptoms. They found that it. The biopsychosocial approach to pain suggests that individuals who scored highly on the measure of no single factor (e.g., biological) can sufficiently explain perceived injustice were less likely to recover from pain (Engel, 1981). Extant clinical and experimental the PTSD symptoms compared to individuals who research suggests that psychological variables play an scored low on perceived injustice. (Sullivan, Thibault, important role in pain related outcomes (e.g., pain et al., 2009). Another study that looked at depressive severity, pain behaviors; Mavros et al., 2011; Williamson symptoms and perceived injustice found an interaction et al., 2008). Support for the biopsychosocial model between perceived injustice and pain severity also derives from studies showing that psychological predicted depressive symptoms independently of pain variables such as pain catastrophizing, fear, anxiety and catastrophizing (Scott & Sullivan, 2012). In other words, depression contribute to the experience and expression individuals who scored high on pain severity reported of pain, even when controlling for medical status or worse symptoms of depression if they perceived their stimulus characteristics (Sullivan, Rogers & Kirsch, life condition with an elevated sense of injustice. These findings suggest that there might be a relationship 2001). between perceived injustice and mental health.

Emerging research identified perceived injustice Perceived injustice has also been shown to be as one psychological variable that is implicated in pain related to the display of pain behavior in individuals outcomes in individuals with pain conditions. Perceived injustice has been described as an appraisal process who sustained whiplash injuries (Sullivan, Davidson, et characterized by the severity and irreparability of loss, al., 2009). Pain behavior is an observable behavior that and a sense of unfairness and attributions of blame individuals engage in as a result of experiencing pain.

(Sullivan et al., 2008). The scale has been validated in Those behaviors are detected through facial expressions, both injury populations (e.g. occupational or motor body posture, activity avoidance, rubbing the affected vehicle injuries; Scott, Trost, Millioto et al., 2013; area, and vocalization (Sullivan, Scott and Trost, Sullivan et al., 2008) and in non-injury populations 2012). The measure of pain behavior can be divided in with chronic pain (Scott, Trost, Bernier, et al., 2013; two components: communicative pain behavior and Yakobov et al., 2014). Previous research demonstrated protective pain behavior (Sullivan, Scott & Trost, 2012). that the scale was correlated with pain severity, fear of The first subcategory is comprised of all pain behavior movement, depression, physical disability, and pain that is meant to communicate information to an observer about the distress caused by pain (for example catastrophizing (Sullivan et al., 2008). facial expressions, and verbal or paraverbal expressions;

Emerging research suggests that perceived Deyo, Prkachin & Mercer, 2004; Graig, 2004). The injustice is implicated in pain and disability outcomes protective pain behavior subcategory is comprised of all in individuals with musculoskeletal injuries, actions that are meant to reduce pain, prevent further fibromyalgia, arthritis and osteoarthritis (Sullivan et injury and promote healing (e.g. guarding, holding, al., 2008; Cebolla, Luciano, DeMarzo, Navarro-Gil, & rubbing; Wall, 1999). In a study, Sullivan, Davidson Campayo, 2013; Douard, 1991; Yakobov, Scott, Stanish, et al. (2009) found that perceived injustice was related et al., 2014). A study byYakobov et al. (2014) found that to the display of protective pain behavior but not to pre-surgery values of perceived injustice on the IEQ communicative pain behavior. predicted the presence of pain and disability one year Research to date has proceeded from the after the arthroplasty surgery, even after controlling assumption that perceptions of injustice arise from an for baseline ratings of pain severity, physical disability, and pain catastrophizing. While it is still unclear how incident, injury or illness that is associated with loss perceived injustice impacts pain outcomes, Scott and or suffering, and the perceptions of injustice were not colleagues (2013) proposed that anger may be one of the present prior to the index incident, injury or illness. As mechanisms by which a sense of unfairness augments a result, it remains unclear whether perceived injustice pain in individuals with chronic musculoskeletal pain. occurs in relation to an event accompanied by pain and losses, or whether this construct may underlie Pain

52 Introduction

PSI ISSUE V a more stable trait. In other words, it is possible that perceptions of injustice may also reflect a trait-like dimension characterized by a propensity to experience stressful situations as a violation of justice principles.

For instance, a limited amount of research suggested that some individuals are more sensitive to perceived injustice (Schmitt et al., 2005; Schmitt et al., 2010).

Individuals might differ in the degree to which they see themselves as experiencing more negative life situations than others (e.g., violation of distributive justice), the degree to which they feel punished undeservedly (e.g., violation of retributive justice), or the degree to which they have been insufficiently compensated for their suffering (e.g., violation of compensatory justice).

Should individual differences exist in the propensity to experience stressful situations as unjust, it is possible that the perceptions of injustice might have been present prior to injury. Accordingly, showing that levels of perceived injustice vary across individuals even prior to an index event (such as a stressful situation, an injury or the onset of a debilitating illness) would invite caution in the interpretation of results of research that only assess perceptions of injustice after the onset of injury or illness. Since existing measures are worded in relation to a loss event such as injury or illness, to address the question of trait perceived injustice the item content of the IEQ would need to be modified. T-IEQ has been created in order to serve this purpose.

The main purpose of this study was to validate the perceived injustice scale in a sample of healthy individuals using a cold pressor paradigm. Building on previous research on perceived injustice in the context of chronic pain we hypothesized that perceived injustice in healthy individuals will be also positively correlated with measures of pain catastrophizing, anger, anxiety and depression. We also expect that perceived injustice will be associated with higher reports of pain intensity, and increased displays of pain behaviour.

during the procedure ( (a) personal history of medical condition associated with persistent pain such as migraine headaches or back pain, (b) history of angina, heart disease, diabetes, or other cardiovascular disorder, (c) diagnosis of Raynaudâ&#x20AC;&#x2122;s Syndrome or history of frostbite, and (d) women who are pregnant or nursing) were screened out. The procedure lasted approximately 1 hour and subjects were compensated $15 CAD for their participation. The study was approved by the Research Ethics Board of McGill University, Montreal, Quebec, Canada. Informed consent was obtained from all participants.

Stimuli Cold Pressor Task. The participants had to immerse their non-dominant arm in a container filled with circulating cold water for 60 seconds while seated (water temperature between 3 and 7 degrees Celsius).

The participants did not know the duration of the cold water immersion, and they were deceptively told that the water immersion test would be stopped once their heart rate reached baseline level. During the 60 second immersion participants were asked by a recorded voice to rate their pain level on a 10-point Likert scale every 20 seconds. The ending of the task was signaled by the recorded voice telling the participants to remove their arm from the water.

Measures Perceived Injustice. Trait Injustice Experience Questionnaire (T-IEQ) is a 12-item scale that measures the extent to which individuals experience different thoughts concerning the sense of unfairness in relation to their life on a 5-point scale. The scale is based on the Injustice Experience Questionnaire which has been validated in a population with painful conditions (Sullivan, 2008).

Pain Catastrophizing. The Pain Catastrophizing Scale (PCS; Sullivan, Bishop & Pivik, 1995) is a 13-item Methods scale examining the extent to which participants have a catastrophic cognition when experiencing pain on Participants a 5-point Likert scale. The PCS is composed of three The sample used for this study was comprised of 74 subscales (magnification, rumination, helplessness) healthy adults (43 female, 31 male) between the age of and it is known to be associated with measures of pain 18 and 53 (M = 23.75, SD = 6.80). The participants were intensity and disability. The scale has a high degree of recruited with the help of advertisements on McGill validity and has been shown to be a reliable measure of Universityâ&#x20AC;&#x2122;s classifieds web-page, and potential subjects catastrophic thinking about pain. were screened during a phone interview. Participants State Mood Measure (SMM; McNair, Lorr, & with medical conditions that could be aggravated Droppleman, 1981). Participants were asked to rate the

53 Pain

PSI ISSUE V extent to which they felt angry, irritated, tense, nervous, and sad on a 6-point Likert scale. For the purpose of this study a shorter version of the questionnaire was administered including only the items dealing with depression, anger, and anxiety.

Pain Behavior. For the coding of pain behavior, participants were recorded with consent during the cold pressor task with two cameras positioned in front of them. One camera provided a full-body view of the participant, and the second camera provided a close-up of the face of the participant. The participants were also audiotaped during the cold pressor task. The procedure used for coding pain behavior was modeled after a system developed by Keefe and Block (1982). Each video was divided into six cycles: the first cycle started with the moment when the participant was instructed to introduce his arm in the water and lasted until he or she touched the water; the second cycle started when the participant touched the water and lasted until he or she was asked the first pain rating (approximately 20 seconds); the third cycle lasted from the first pain rating until the second pain rating (20 seconds); the fourth cycle lasted from the second pain rating until the third pain rating (20 seconds); the fifth cycle was comprised of the 5 seconds following the third pain rating; and the sixth cycle was comprised of the 30 seconds after the third pain rating (or until the participant was interrupted by the experimenter). The coders analyzed the recordings for pain behaviors after being trained with the use of a manual developed for this study. The indices of pain behavior were calculated by adding up all the time durations of pain behavior.

Procedure The study took place in a university psychology laboratory. After reading and signing the consent form, which informed the participants that the study explores the physical and cognitive factors associated with pain, the subjects were asked to complete a set of questionnaires (demographics, PCS, T-IEQ, and SMM).

After this, the participants were left alone in the room to perform the cold pressor test. After completing the task, the participants answered a second set of questionnaires (PCS, T-IEQ, and SMM) and they also had to estimate the time that they spent with their arm immersed in the cold pressor. Participants were reminded that they could discontinue the study at any point without loss of compensation.

Pain

Results Table 1 shows sample characteristics based on gender.

Analyses of variance revealed that the only gender difference in the sample was that of age (F(1,71) = 7.53, p < .01). The mean age for males (M = 25.6, SD = 8.9), was significantly higher than the mean age for females (M = 22.4, SD = 4.5). For all other variables, there was a non-significant mean difference between males and females.

Bivariate correlational analysis (Table 2) shows that the perceived injustice questionnaire was significantly correlated with measures of pain catastrophizing (r = .59, p < .001), and depression (r = .27, p < .05). Results also revealed that perceived injustice was marginally correlated with protective pain behavior (r = .21, p < .08) with pain ratings during the cold pressor test (r = .20, p < .09) with anger (r = .21, p < .07) and with anxiety symptoms (r = .21, p < .08). This means that individuals who score high on the perceived injustice scale display more protective pain behavior, rate higher levels of pain during the cold pressor test, feel more angry, and have more anxiety symptoms.

Moreover, in a sample of individuals who scored in the top 25% on the T-IEQ (N = 18), protective pain behavior and total pain behavior were significantly correlated with perceived injustice (Table 3). In a first regression analysis perceived injustice explained 32% of the variation in protective pain behavior (F(1,16) = 7.56, p < .05; r2 = .32; standardized beta = .57). That means that for every unit increase in perceived injustice the protective pain behavior would also increase by 0.57 units. Perceived injustice is also significant in predicting total pain behavior (F(1,16) = 5.26, p < .05) by explaining 25% of the variation (r2 = .25, standardised beta = .50).

The results show no significant relationship between perceived injustice and communicative pain behavior.

All the pain-related questionnaires were administered both pre- and post-cold pressor test, and test-retest reliability measures (Table 4) show that all the questionnaires were significantly reliable.

The results show that the T-IEQ had the strongest correlation coefficient (r = .92, p < .01) which means it has the highest stability pre- and post-immersion.

Further psychometric tests showed that the T-IEQ has high internal consistency (Îą = .89).

54

PSI ISSUE V Discussion The objective of the present study was to validate the Trait Injustice Experience Questionnaire (T-IEQ) in a healthy student population. It was hypothesized that perceived injustice is positively correlated with pain catastrophizing, depression, anxiety, and anger. It was also expected that perceived injustice would be related to higher display of pain behavior and higher ratings of pain intensity during the cold pressor test.

The T-IEQ has been adapted from the IEQ, a scale that assesses perceived injustice in the individuals suffering from painful conditions. In the context of pain and injury, perceived injustice was associated with depression and pain outcomes (Sullivan, Davidson, et al., 2009; Scott, Trost, Bernier et al., 2013). The results of the present research suggest that perceiving life with a sense of unfairness is also associated with poor mental and pain related outcomes.

The results of the study are consistent with previous research demonstrating a positive relationship between perceived injustice, pain catastrophizing, as well as symptoms of anxiety and depression (Sullivan et al. 2008, Sulivan, Thibault et al., 2009; Scott & Sullivan, 2009). Also, consistent with previous studies (Scott, et al., 2013; Sullivan, Davidson et al., 2009), the results of the present study indicate that perceived injustice had a marginally significant association with anger, pain intensity, and protective pain behavior. Moreover, when examining a sample of individuals that scored in the highest quartile on the T-IEQ, perceived injustice was significantly associated with the display of protective pain behavior and total pain behavior during the cold pressor test. The results of the present study expand on previous research by showing that the perceived injustice scale can be used in a healthy population.

A particularly robust correlation between perceived injustice and pain catastrophizing has been reported in previous research (Sullivan et al., 2008) and was also observed in the present study. Pain catastrophizing is a negative cognitive-affective response characterized by excessive and exaggerated focus on the fearful aspects of a painful experience, magnification of painful experience and feelings of helplessness when dealing with painful situations (Sullivan, Bishop, & Pivik, 1995). Studies have shown that individuals scoring high on pain catastrophizing report higher ratings of pain, display more pain behavior, have more negative expectancies about pain, feel helpless in

dealing with pain, pay more attention to pain sensations and ruminate more (Sullivan et al., 2011). Sullivan and colleagues suggested that perceived injustice and pain catastrophizing might influence poor mental and pain outcomes through shared mechanisms (Sullivan, 2011).

For example, it was speculated that individuals scoring high on pain catastrophizing have an increased attention to pain sensations (Arntz, Dreesen, & Merckelbach, 1991; McCracken, 1997) and similarly, individuals scoring high on perceived injustice could have an increased focus on pain losses, which could in turn influence the presence of depressive symptoms. It was suggested that the overlap between pain catastrophizing and perceived injustice can also be due to one of the subscales of perceived injustice (Sullivan, 2011). More precisely, the dimension of severity/irreparability of loss might be related to a catastrophic cognition, and therefore might overlap with pain catastrophizing.

However, the second subscale of perceived injustice, blame/unfairness, is unique to perceived injustice.

The present finding showing a marginal correlation between perceived injustice and anger is consistent with previous research suggesting the importance of this emotional state in individuals who score high on perceived injustice (Scott, Trost, Bernier et al., 2013). Indeed, social psychology research suggests that anger is a natural response to perceived injustice (Scott et al., 2013). Additionally, previous research in the context of pain and disability - where pain-related losses are more apparent - provides further support for the idea that anger is one pathway by which perceived injustice impacts pain. The results of our study suggest that anger may also be related to perceived injustice in healthy individuals.

Replicating previous research, perceived injustice was also associated with depression and anxiety. In individuals with persistent musculoskeletal pain, perceived injustice has been previously found to mediate the relationship between pain and depressive symptoms (Scott and Sullivan, 2012). Even though there is no clear evidence linking anxiety and perceived injustice, some studies have linked pain catastrophizing and stress-related variables such as anxiety, fear, depression (Sullivan, Thorn et al., 2001). The results of this study provide evidence for a marginal relationship between perceived injustice and anxiety.

In the present study we also found a trend relating perceived injustice with protective pain behavior and pain intensity ratings. Moreover, the individuals who

55 Pain

PSI ISSUE V scored in the top quartile on perceived injustice also low power of the statistical analyses. Replication of this displayed significant levels of pain behavior during a study with a larger sample and lower water temperature painful task. Those findings expand on previous research is warranted to bolster the reliability and validity of conducted with individuals with whiplash injuries the present findings. Lower temperature may result in (Sullivan, Davidson et al., 2009). In that study, it was a more intense pain during the cold pressor test, and found the perceived injustice was associated with pain subsequently, individuals more sensitive to pain stimuli intensity ratings and pain behavior in individuals with would report more intense pain and would display whiplash injuries. Our findings suggest that perceived more pain behavior. Moreover, future research should injustice is also an important predictor of pain behavior also analyze whether communicative pain behavior can in a healthy sample. Healthy individuals who did not vary as a function of the level of perceive injustice if a experience a painful state (or accident) still vary in their confederate is present during the painful task. level of perceived injustice and, as a result, vary on the Despite the limitations, this was the first study amount of pain behavior displayed. In this study as well to examine a trait-like characteristic of perceiving the as in previous research, protective pain behavior appears world as unfair in relation to poor pain outcomes, anger, to be more relevant than communicative pain behavior and mental distress. The associations between variables in relation to perceived injustice (Sullivan, Davidson et observed in the study suggest that the results go in the al., 2009). One reason for this finding might have been direction of the hypotheses, such that perceiving the related to the procedure of the study. During the cold world and life experiences with an elevated sense of pressor test, participants were alone in the room, which injustice is marginally associated with pain severity and may have caused them to display less communicative pain behaviors during the cold pressor test. Perceived pain behavior, although they were aware of being filmed injustice was also associated with depression, and a during the task. Communicative pain behavior consists trend was observed with measures of anxiety and anger. of pain behavior that can communicate to other people Whereas previous research focused on the role of IEQ the painful state of an individual, and may include on pain outcomes in pain and injury related context, the verbal and nonverbal vocalization, facial pain behavior; results of the present study provide the first empirical Sullivan, Davidson et al., 2009). Since the participants evidence suggesting that a general propensity to were alone in the room during the immersion, it is perceive the world as unfair may also be associated with possible that they focused more on protective pain pain outcomes, anxiety, depression, and anger. Future behavior that is meant to protect the affected area, in research is needed to explore the relationship between order to lower the pain, or reduce the probability of these variables and investigate whether T-IEQ and IEQ future injury. Future research needs to explore whether augment pain through similar mechanisms. the association between perceived injustice and communicative pain behavior will become significant References in a presence of a confederate.

Overall, the results of the present study suggest Arntz, A ., Dreesen, L., & Merckelbach, H. (1991). Attention, that in healthy individuals, the propensity to perceive not anxiety, influences pain. Behavior Research and the world as unjust is associated with higher pain ratings Therapy, 29, 41 – 50. and the increased frequency of display of pain behavior Bradfield, M., & Aquino, K. (1999). The effects of blame during a painful task. These results have theoretical attribution and offender libanleness on implications in our understanding of pain perception. forgiveness and revenge in the workplace. Journal of Whereas previous research examined the role of Management, 25(5), 607-631 perceptions of unfairness and poor pain and mental Burns, J. W., Holly, A., Quartana, P., Wolff, B., Gray, E., health outcomes in the context of painful condition Bruehl, S. (2008). Trait anger management style and injury (i.e., state-like), it appears that trait-like moderates effects of actual (‘‘state’’) anger regulation characteristics of perceiving the world as unfair are also on symptom- specific reactivity and recovery among implicated in poor pain and mental health outcomes.

chronic low back pain patients. Psychosomatic The present study is not without limitations.

Medicine, 70, 898–905.

The sample size was small and water temperature in Cebolla, A., Luciano, J. V., DeMarzo, M. P., Navarro-Gil, M., the cold pressor was not cold enough, ranging from 3-7 & Campayo, J. G. (2013). Psychometric properties of degrees Celsius. Those confounds could have resulted in the Spanish version of the mindful attention Pain

56

PSI ISSUE V

awareness scale (MAAS) in patients with fibromyalgia. Health and Quality of Life Outcomes, 11, 6. doi: 10.1186/1477-7525-11-6 Craig, K. D. (2004). Social communication of pain enhances

protective functions: a comment on Deyo,

Prkachin and Mercer (2004). Pain. 107, 5–6.

Deyo, K. S., Prkachin, K. M., & Mercer, S. R. (2004).

Development of sensitivity to facial expression of

pain. Pain, 107, 16–21.

Douard, J. (1991). Chronic illness: A problem of passive injustice. The Journal of Clinical Ethics, 2(3), 153–156.

Engel, G. L. (1981). The clinical application of the

biopsychosocial model. Journal of Medicine and

Philosophy, 6(2), 101-124.

Exline, J. J., Worthington, Jr. E. L., Hill, P., & McCullough, M.

E. (2003). Forgiveness and justice: A research

agenda for social and personality psychology.

Personality and Social Psychology Review, 7(4), 337 348.

Ferrari, R., & Schrader, H. (2001). The late whiplash

syndrome: a biopsychosocial approach.

Journal of Neurology, Neurosurgery and Psychiatry, 71, 722 – 726.

Keefe, F., & Block, A. (1982). Development of an observational

method for assessing pain behavior in chronic pain

patients. Behavior Therapy, 13, 363–375.

Mavros, M. N., Athanasiou, S., Gkegkes, I. D., Polyzos, K. A.,

Peppas, G., & Falagas, M. E. (2011). Do psychological

variables affect early surgical recovery. Plos one, 6(5).

doi: 10.1371/journal.pone.0020306 McCracken, L. M. (1997). “Attention” to pain in persons with

chronic pain: A behavioral approach. Behavioral Therapy, 28, 271 – 284.

McNair, P. M., Lorr, M., & Droppleman, L. F. (1981). POMS

manual (2nd ed.). San Diego: Educational and Industrial Testing Service.

Rodero, B., Luciano, J. V., Montero-Marin, J., Casanueva, B.,

Palacin,J. C., Gili, M., … Garcia-Campayo, J.

(2012). Perceived injustice in fibromyalgia:

Psychometric characteristics of the Injustice

Experience Questionnaire and relationship with

pain catastrophizing and pain acceptance.

Journal of Psychosomatic Research, 73, 86-91.

Schmitt, M., Baumert, A., Gollwitzer, M., & Maes, J. (2010).

The Justice Sensitivity Inventory: Factorial Validity,

Location in the Personality Facet Space, Demographic

Pattern, and Normative Data. Social Justice Research, 23, 211-238 Schmitt, M., Gollwitzer, M., Maes J, & Arbach, D. (2005).

Justice Sensitivity: Assessment and Location in the

Personality Space. European Journal of Psychological

Assessment, 21, 202-211.

Scott, W., & Sullivan, M. J. L. (2012). Perceived injustice

moderates the relationship between

pain and depression among individuals with

persistent musculoskeletal pain. Pain Research and Management, 17, 335-340.

Scott, W., & Trost, Z., Bernier, E., & Sullivan, M. J. L. (2013).

Anger differentially mediates the

relationship between perceived injustice and chronic

pain outcomes. Pain, 154(9), 1691- 1698.

Scott, W., & Trost, Z., Milioto, M., & Sullivan, M. J. L. (2013).

Further validation of a measure of injury-related injustice perceptions to identify risk for occupational disability: A prospective study of individuals with whiplash injury. Journal of Occupational Rehabilitation, 23(4), 557-565.

Sullivan, M. J. L., Adams, H., Horan, S., Mahar, D., Boland,

D., & Gross, R.(2008). The role of perceived injustice

in the experience of chronic pain and disability:

Scale development and validation. Journal of

Occupational Rehabilitation, 18(3), 249 – 261.

Sullivan, M. J. L., Adams, H., Martel, M. O., Scott, W., &

Wideman, T. H. (2011). Catastrophizing and

perceived injustice: Risk factors for the transition to

chronicity following whiplash injury. Spine, 36, S244 – S249.

Sullivan, M. J. L., Bishop, S. R., & Pivik, J. (1995). The Pain

Catastrophizing Scale: Development and validation. Psychological Assessment, 7, 524-532.

Sullivan, M. J. L., Davidson, N., Garfinkiel, B., Siriapaipant,

N., & Scott, W. (2009). Perceived injustice is a

ssociated with heightened pain behavior and

disability in individuals with whiplash injuries.

Psychological Injury and Law, 2, 238 – 247.

Sullivan, M. J. L., Rodgers, W. M., & Kirsch, I. (2001).

Catastrophizing, depression and

expectancies for pain and emotional distress. Pain, 91, 147-154.

Sullivan, M. J. L., Scott W., & Trost Z. (2012). Perceived

injustice: A risk factor for problematic pain outcomes. Clinical Journal of Pain, 28, 484–488.

Sullivan, M. J. L., Thibault, P., Simmonds, M., Milioto, M.,

Cantin, A-P., & Velly, A. M. (2009). Pain, perceived

injustice and the persistence of post-traumatic

stress symptoms during the course of

rehabilitation for whiplash injuries. Pain, 145, 325 – 331.

Sullivan, M. J. L., Thorn, B., Haythornthwaite, J.A., Keefe, F.,

Martin, M., Bradley, L.A.,

57 Pain

PSI ISSUE V Lefebvre, J.C. (2001). Theoretical perspectives on the relation between catastrophizing and pain.

Clinical Journal of Pain, 17, 52 â&#x20AC;&#x201C; 64.

Thompson, L. Y., Snyder, C. R., Hoffman, L., Michael, S. T.,

Rasmussen, H. N., Billings, L. S., Heinze, L.,

Neufeld, J. E., Shorey, H. S., Roberts, J. C, & Roberts,

D. E. (2005). Dispositional forgiveness of self,

others, and situations. Journal of Personality 73:

313- 359.

Wall, P. (1999). Pain: The Science of Suffering. London:

Weidenfelfd and Nicolson.

Williamson E., Williams M., Gates S., & Lamb, S. E. (2008).

A systematic literature review of psychological factors and the development of late whiplash syndrome. Pain, 135(1-2), 20-30. doi: 10.1016/j.pain.2007.04.035 Yakobov, E., Scott, W., Stanish, W., Dunbar, M., Richardson,

G., & Sullivan, M. J. L. (2014).

The role of perceived injustice in the prediction of pain and function following total knee arthroplasty. Pain, 155, 2040â&#x20AC;&#x201C;2046.

Yakobov, E., Scott, W., Tanzer, M., Stanish, W., Dunbar, M.,

Richardson, G., Sullivan. M. J. L. (2014). Validation

of the injustice experiences questionnaire adapted

for use with patients with severe osteoarthritis of

the knee. Journal of Arthritis, 3(2), 130. doi: 10.4172/2167-7921.1000130

Pain

58

PSI ISSUE V Appendix Table 1: Sample Characteristics Variables

Women (n=43)

Men (n=31)

P

Total Sample

Age PPB CPB TPB IEQ PCS PAIN DEP ANGR ANX 4.3

22.4 (4.5) 59.3 (32.2) 28.4 (18.9) 87.7 (41.6) 9.2 (7.1) 16.7 (10.1) 6.8 (1.5) 3.1 (4.3) 2 (3.5) 4.3 (5.7)

25.6 (8.9) 50.7 (27.6) 24.5 (195.)

75.2 (38.3) 10.3 (7.6) 14.9 (8.8) 6.2 (2) 3 (3.4) 2.2 (3.4) 3.7 (4.5)

.05 ns ns ns ns ns ns ns ns ns

23.8 (6.8) 55.7 (30.5) 26.6 (19.1) 82.5 (40.5) 96.7 (7.3) 16 (9.6) 6.5 (1.8) 3.1 (3.9) 2.1 (3.8) 4.1 (5.2)

Note. N = 73. PPB= Protective Pain Behaviour; CPB = Communicative Pain Behaviour; TPB = Total Pain Behaviour; IEQ = Injustice Experience Questionnaire; PCS = Pain Catastrophizing Scale; PAIN = Total pain ratings during the cold pressor test; DEP = Depression; ANGR = Anger; ANX = Anxiety.

Table 2: Correlations among pre-cold pressor test pain-related psychological measures 1. T-IEQ 2.PPB 3.CPB 4.TPB 5.PCS 6.PAIN 7.DEP 8.ANGR 9.ANX

1

2

3

4

5

6

7

8

.21† .60 .18 .59** .20† .27* .21† .21†

.30* .89** .45 .28* -.08 -.07 .01

.70** .09 .40** .13 .10 .21

.08 .40** .01 .00 .11

.05 .33** .21 .37**

.09 . 16 .19

.78** .73 **

.55**

Note. N= 73. PPB= Protective Pain Behaviour; CPB = Communicative Pain Behaviour; TPB = Total Pain Behaviour; IEQ = Injustice Experience Questionnaire; PCS = Pain Catastrophizing Scale; PAIN = Total pain ratings during the cold pressor test; DEP = Depression; ANGR = Anger; ANX = Anxiety. *p <.05, **p < .01, †p < .10

59 Pain

PSI ISSUE V Table 3: Predictability of Pain Behaviour using the top 25% of perceived injustice

PPB CPB TPB

Beta .57 .22 .50

R² .32 .05 .25

F 7.56* .78 5.26*

Note. N = 18. PPB = Protective Pain Behaviour; CPB = Communicative Pain Behaviour; TPB = Total Pain Behaviour. Standardized Betas are reported. *p < .05

Table 4: Test-retest correlations for pain-related psychological measures

T-IEQ 1 & T-IEQ 2 PCS 1 & PCS 2 DEP1 & DEP2 ANGR 1 & ANGR 2 ANX 1 & ANX 2

Pearson R .92** .72** .51** .46** .65**

IEQ 1 = Injustice Experience Questionnaire pre-cold pressor test; IEQ 2 = Injustice Experience Questionnaire post-cold pressor test; PCS 1 = Pain Catastrophizing Scale pre-cold pressor test; PCS 2 = Pain Catastrophizing Scale post-cold pressor test; DEP 1 = Depression rating pre-cold pressor test; DEP 2 = Depression rating postcold pressor test; ANGR 1 = Anger rating pre-cold pressor test; ANGR 2 = Anger rating post-cold pressor test; ANX 1 = Anxiety rating pre-cold pressor test; ANX 2 = Anxiety rating post-cold pressor test; *p <.05, **p < .01

Pain

60

PSI ISSUE V

The Effect of Meditation Practice on Daily Mindfulness and Psychological Well-being

Kimberly Carrière* Supervisor: Dr. Bärbel Knäuper *email: *kimberly.carriere@mail.mcgill.ca Keywords: mindfulness; MBSR; meditation; well-being

Health 61 and Well-being

PSI ISSUE V in formal meditation practice. Formal meditation practice teaches participants to respond mindfully, The purpose of the current study was to clarify the role which involves deliberately redirecting attention to of meditation practice in a mindfulness-based program. the present moment in an open and non-conceptual Specifically, we tested whether the amount of meditation way. In the MBSR program, participants are taught a practice throughout the 8 weeks of the program was variety of meditation exercises (e.g., body scan, sitting associated with psychological well-being outcomes. meditation, gentle yoga and walking yoga) to develop Our sample consisted of 76 adults enrolled in a clinical their abilities to respond mindfully. Mindfulness-based Mindfulness-Based Stress Reduction (MBSR) program. programs (Kabat-Zinn, 1990, Segal, Williams, Teasdale, This is an 8-week intervention aimed at reducing 2001), borrowing principles from Buddhist traditions stress. Participants recorded measures of mindfulness, (e.g., Goldstein & Kornfield, 2001), are based on the perceived stress, well-being and meditation practice assumption that deliberate mindfulness meditation times throughout the intervention. We hypothesized practice leads to an increased ability to automatically that greater amounts of meditation practice would be respond mindfully in daily life. This increase in daily related to increases in daily mindfulness, an increase application of mindfulness may allow individuals in positive affect, and a decrease in perceived stress to manage their stress and well-being by becoming and negative affect. Results unexpectedly showed the less reactive and judgmental towards difficult life accumulated meditation practice was not significantly experiences (Keng et al., 2011).

There is strong empirical support for the claim related to changes in outcome variables. MindfulnessBased Interventions are founded on the assumption that that mindfulness interventions lead to improvements in accumulated meditation practice is a necessary condition a wide range of physical and mental health conditions. for increases in psychological well-being. Our finding In a comprehensive meta-analysis conducted by Khoury that meditation practice has no effect on psychological et al. (2013), mindfulness-based interventions have outcomes in an MBSR setting may suggest otherwise. If been shown to reduce anxiety, depression, and stress. our null finding is further supported in future studies Effect-size estimates suggest that these interventions and further analyses, then daily meditation practice are moderately effective in pre-post comparisons may not be as fundamental in providing increases in (Hedgeâ&#x20AC;&#x2122;s g = .55) and waitlist comparisons (Hedgeâ&#x20AC;&#x2122;s g = .53), although smaller effects were obtained when psychological benefits as previously expected. comparing mindfulness-based therapies with other active treatments (Hedgeâ&#x20AC;&#x2122;s g = .33). Additionally, Introduction mindfulness interventions have also been shown to improve psychological well-being (see Keng, Smoski & Over the past two decades, there has been an increased Robins, 2011 for a review of the literature). interest in mindfulness and its use as a form of clinical While most mindfulness intervention research intervention. Since then, multiple mindfulness- has tested the efficacy of these interventions, there is oriented interventions have been developed, such as considerably less research on the mechanisms that are the Mindfulness-Based Stress Reduction program thought to be responsible for the beneficial effects of these (MBSR), an 8-week group-based intervention program programs. Among studies testing mechanisms involved that includes extensive mindfulness meditation training in mindfulness interventions, it has been shown with (Kabat-Zinn, 1990). The purpose of the program is to considerable reliability that individuals who participate teach mindfulness, commonly defined as an awareness in mindfulness-based interventions score higher on that arises from engaging in a process of intentionally trait mindfulness measures after the intervention than directing attention to the present moment in a non- before (Anderson et al., 2007; Michalak et al., 2008; judgmental way (Kabat-Zinn, 1994). These programs Shapiro et al., 2007) suggesting that, as the program are based on ancient Buddhist practices, yet have claims, trait mindfulness might be responsible for the been secularized and adapted to modern life (Kabat- beneficial outcomes of MBSR programs. Furthermore, Zinn, 2011). These mindfulness-based programs this increase in self-reported trait mindfulness has are founded on the assumption that mindfulness is been found to correlate with improvements in various mostly learned experientially by regularly engaging psychological outcomes, such as increased levels of life satisfaction and pleasant affect (Brown & Ryan, 2003), as Health and Well-being 62 Abstract

PSI ISSUE V well as decreased levels of perceived stress (Shapiro et al., 2005), anxiety (Anderson et. al., 2007), and depressive symptoms (Sephton et al., 2007). More recently, using daily diaries, Lacaille et al. (in preparation) found that as the program progresses, MBSR participants report a steady daily increase in use of mindful responses during the day. This increase was found to be associated with decreases in perceived stress and negative affect, and increases in positive affect.

Although the current literature partly supports the hypothesized workings of these interventions, it remains unclear whether formal meditation practice increases mindfulness or well-being, which are two independent constructs. A systematic review of the mindfulness intervention literature by Vettese, Toneatto, Stea, Nguyen, and Wang (2009) found discrepancies in the findings of different correlational studies investigating the relationship between measures of meditation practice and mindfulness intervention outcomes. Out of the 98 studies reviewed, approximately one-quarter (N = 24) investigated the relationship between meditation practice and measures of psychological health. Out of these 24 studies, just over half (N =13) demonstrated partial support for the association between the extent of meditation practice and psychological benefits. Additionally, two longitudinal studies to date have tested whether increases in mindfulness explain the relationship between meditation practice and psychological benefits.

After measuring pre and post scores of participants enrolled in an 8-week MBSR program, Carmody and Baer (2008) showed increases in levels of mindfulness and psychological wellbeing, as well as decreases in levels of stress, chronic pain, and anxiety. Increases in mindfulness were found to mediate the relationship between meditation practice and improvements in psychological distress and perceived stress. In other words, these findings suggest that meditation practice leads to increases in daily mindfulness, which is turn leads to decreased levels of stress and improved psychological functioning. However, in a more recent study, Baer, Carmody, and Hunsinger (2012) were unable to replicate this mediation effect.

These authors did not find a significant relationship between the extent of meditation practice and changes in mindfulness or perceived stress. Vettese et al. (2009) suggest that this discrepant finding is perhaps explained by unreliable dependent measures of meditation practice. Specifically, both Carmody and Baer, and Baer et al., recorded practice times with handwritten daily

logs or retrospective weekly logs that were collected before the start of each MBSR weekly session. Relying on participants to track their practice daily, return the completed log, and remember their daily practice at the end of the week may result in incomplete, inaccurate, and unreliable data on mediation practice. Collecting desirable behaviour retrospectively also renders the reports vulnerable to social desirability effects (McAullife et al., 2010). Thus, despite theoretical claims, the importance of meditation practice in mindfulnessbased programs is unclear based on currently available data. It cannot yet be ruled out that the effectiveness of the program in increasing well-being and mindfulness is due to other non-active ingredients of the intervention such as weekly group support, psycho-education about stress and mindfulness, in addition to expert instruction with the expectation of improvement.

Given the emphasis placed on daily meditation practice in MBSR programs, it is important to shed light on this issue and to examine more closely whether accumulated meditation practice is indeed associated with increases in daily mindfulness and well-being. In the current study, we attempt to improve the validity and reliability of self-reported meditation practice measure by asking participants to report their mediation practice in daily diaries immediately after meditating via an online questionnaire. Additionally, we assess the extent to which participants respond mindfully and experience psychological wellbeing in their daily life daily throughout the program. Collecting this information daily improves the reliability of selfreports (e.g., reduces cognitive biases; Bolger, Davis, & Rafaeli, 2003) as well as their validity (e.g., improves ecological validity; Almeida, 2005). This increased reliability and validity of self-reported data should help clarify whether mediation practice has an effect on learning mindfulness and experiencing psychological benefits from the programs. Based on what is claimed in these programs, we hypothesize that accumulated meditation practice will be associated with increases in daily mindfulness, an increase in positive affect, and a decrease in perceived stress and negative affect.

Methods Participants Participants for the study were recruited from a group of adults who were enlisted in an 8-week MindfulnessBased Stress Reduction (MBSR) program at a private

63 Health and Well-being

PSI ISSUE V psychological clinic. These individuals sought therapeutic relief from various stress related problems.

The research component was incorporated into the already existing MBSR program. Data collection is ongoing, and so far, 76 participants (60 females) took part in the study. The age, ethnicity, and occupational status of the participants is summarised in Table 1.

Procedure After verbally expressing interest in participating in the study, participants were sent an email containing links to the online consent form and a pre-program questionnaire that assessed demographic information and baseline levels of meditation practice, mindfulness, self-control, and wellbeing. Before the first MBSR session, participants were informed about the study’s requirements. During this period, participants registered their smartphones for a service that would prompt them with signals to daily reports for the duration of the study.

Every night for eight weeks, participants received a text message with an embedded link to a brief online questionnaire regarding their daily activities.

Participants were asked to report the extent to which they responded mindfully during the day, their levels of stress, and their affect, as well as the duration and type of their meditation practice that day. After the final (eighth) MBSR session, they also completed a post-questionnaire that assessed the same variables as the pre-questionnaire. During this period, participants were compensated for their time and debriefed as a group. Participants received up to $50 in compensation.

The amount was contingent on the amount of surveys that the participant completed during the study. Ethics approval was obtained from the university’s Research Ethics Board.

Materials Baseline Questionnaire. A baseline questionnaire was administered prior to the first session and assessed demographic variables, trait mindfulness and trait selfcontrol.

Demographic information. The demographics questionnaire included questions about basic demographic information including age, gender, ethnicity, employment status, income and marital status.

The questionnaire also assessed previous meditation experience (e.g., length of practice, type of meditation, status of current practice) and social desirability

(Reynolds, 1982) to be used as control variables in the analyses.

Trait mindfulness. Mindfulness was measured with a modified version of the Mindfulness Process Questionnaire ([MPQ]; Erisman & Roemer, 2012). The MPQ is an 8-item questionnaire that assesses the extent to which participants attempt or practice mindfulness, as well as their ability to bring their attention back to the present moment when their attention is elsewhere.

Four shortened items from the MPQ were used in our study. This new measure was called “Mindful Responding Questionnaire” (MRQ). Questions in the MRQ include: “When I was critical of myself or others, I let go of judgments to become more accepting instead” and “When my mind was caught up in thoughts I let go of them and brought my awareness back to the present moment.” Participants rated the accuracy of the following statements with a 10-point Likert scale from 1 (rarely) to 10 (often).

Perceived stress (PSS-10). Perceived stress was measured by the Perceived Stress Scale (PSS-10; Cohen, Kamark, & Mermelstein, 1988). The PSS-10 is the most widely used scale for measuring perceived stress. Items of the PSS-10 include: “In the LAST WEEK, how often have you felt confident about your ability to handle your personal problems” and “In the LAST WEEK, how often have you felt unable to control the important things in your life?” Participants rated the accuracy of the statements using a 5-point Likert scale that ranged from 1 (never) to 5 (very often).

Affect (I-PANAS-SF). Affect was measured by a shortened version of the Internationally Reliable Positive and Negative Affect Schedule (I-PANAS-SF; Thompson, 2007). The I-PANAS-SF is composed of two 10-item mood scales. One measures positive affectivity and the other measures negative affectivity. In the current study, ten of the I-PANAS-SF items were selected, comprised of five positive and five negative affectivity items. Such items include: “In the LAST WEEK, to what extent did you feel attentive?” and “In the LAST WEEK, to what extent did you feel ashamed?” Participants rated the accuracy of the following statements using a 5-point Likert scale that ranged from 1 (never) to 5 (always).

Daily Questionnaire. Every night for eight weeks a questionnaire was administered that assessed meditation practice and mindfulness responding.

Meditation practice. Participants reported the amount of time they spent meditating (in minutes)

Health and Well-being

64

PSI ISSUE V and the type of meditation practiced. Specifically, participants answered the questions: “TODAY, did you practice formal meditation?” and “TODAY, for how many minutes did you practice the following meditations? (Body Scan, Sitting Meditation, Yoga, Loving-Kindness Meditation, Other Meditation).”

Participants also rated the extent to which they adhered to the meditation instructions using a 10-point Likert scale ranging from 1 (very little) to 10 (very much).

Mindfulness. Daily mindful responding was assessed using the Mindful Responding Scale (MRS, Lacaille et al., 2014). The Mindful Responding Scale is a 4-item questionnaire modified from the MPQ (Erisman & Roemer, 2012) and is sensitive to daily changes in mindfulness skills learned while participating in a mindfulness-based intervention. Sample MRS items include: “TODAY, when I was critical of myself or others, I let go of judgments to become more accepting instead” and “TODAY, when my mind was caught up in thoughts, I let go of them and brought my awareness back to the present moment.” Participants rated the accuracy of the following statements with a 10-point Likert scale that ranged from 1 (rarely) to 10 (often).

Perceived Stress. Daily perceived stress was assessed using a 4-item version of the Perceived Stress Scale (PSS; Cohen, Kamarck, & Mermelstein, 1983).

The PSS measures the degree to which situations in a person’s life are appraised as stressful. Items include: “TODAY, to what extent did you feel upset because of something that happened unexpectedly?” and “TODAY, to what extent did you feel confident about your ability to handle your personal problems?” Participants rated the accuracy of the following statements with a 10-point Likert scale ranging from 1 (very little) to 10 (very much).

Affect. Daily positive and negative affect was assessed using the 10-item International Positive and Negative Affect Schedule Short Form (I-PANAS-SF; Thompson, 2007). Participants rated the extent to which they experienced positive affect and negative affect throughout the day using a 10-point Likert scale ranging from 1 (very little) to 10 (very much). Items include: “TODAY, to what extent did you feel upset?” and “TODAY, to what extent did you feel alert?”

Results Sample Demographics. So far, we have collected data from 76 participants (nfemales = 60) out of a target sample size of N = 100. The demographic information is listed in Table 1.

Predicting Change from the First Month of the Intervention to the Second. Means and standard deviations for all study variables, as well as their correlational relationships are presented in Tables 2 and 3.

In order to test our hypothesis that accumulated meditation practice predicts increases in daily mindfulness and positive affect and a decrease in perceived stress, we conducted regression analyses. In order to test the time precedence (a necessary condition for causality) between meditation practice and outcome variables, we examined the relationship among variables between the first and second halves of the program.

Specifically, mediation practice scores (in minutes) were summed for the first half of the program (day 1 to 25) and the scores of outcome variables (mindfulness, perceived stress, negative affect, positive affect) were averaged for the second half of the program (day 26 to 50).

Because time series data tend to be serially correlated (similar to itself from one time point to the next) the average scores of outcomes during the first half of the program were used as control variables. This was done to assesses whether accumulated meditation practice in the first half of the program (Time 1) predicted unique variance in outcomes variables in the second half of the program (Time 2) apart from the accounted variance of outcomes in the first half of the program. We hypothesize that when controlling for outcomes in the first half of the program, meditation practice in the first half of the program will uniquely predict outcomes in the second half of the program.

Mindfulness. The first of these regressions examined the ability of accumulated meditation practice in the first half of the program (Time 1) to predict increases in mindfulness in the second half of the program (Time 2). When mindfulness at Time 1 was entered in the first step, the model was significant (Adj R2 = .72, F = 183.09, p < .001). When entering accumulated meditation practice scores from Time 1 in the second step, the model did not significantly improve (ΔR2 =

Health 65 and Well-being

PSI ISSUE V .00, ΔF = 0.042, p = .839). With both predictors in the model, mindfulness at Time 1 remained a significant predictor of mindfulness at Time 2, while accumulated meditation practice was not (see Table 2 for statistics of regression analyses).

Perceived stress. The second model examined the ability of accumulated meditation practice in the first half of the program (Time 1) to predict decreases in perceived stress in the second half of the program (Time 2). When perceived stress at Time 1 was entered in the first step, the model was significant (Adj R2= .648, F = 133.65, p < .001). When entering accumulated meditation practice scores from Time 1 in the second step, the model did not significantly improve (ΔR2= .00, ΔF = 0.009, p =.927). Perceived stress scores at Time 1 were thus the only significant predictor in the final model.

Negative affect. The third model examined the ability of accumulated meditation practice in the first half of the program (Time 1) to predict decreases in negative affect in the second half of the program (Time 2). When negative affect scores at Time 1 were entered in the first step, the full model was significant (Adj R2= .449, F = 59.71, p < .001). When accumulated meditation practice scores from Time 1 were added in the second step, the model was no longer significant (ΔR2= .003, ΔF = 0.386, p = .536). Negative affect scores at Time 1 were thus the only significant predictors in the final model.

Positive affect. The final model examined the ability of accumulated meditation practice in the first half of the program (Time 1) to predict increases in positive affect in the second half of the program (Time 2). When positive affect scores at Time 1 were entered in the first step, the full model was significant (Adj R2= .696, F=165.61, p < .001). When accumulated meditation practice scores from Time 1 were entered in the second step, the model was no longer significant (Δ R2 = .00, ΔF = 0.011, p = .916). Positive affect scores at Time 1 were thus the only significant predictor in the final model.

Predicting Pre-Post Intervention Change. We did not find that accumulated meditation practice in the first half of the MBSR intervention predicted outcomes in the second half. Given that the MBSR is an 8-week intervention that involves meditation practice throughout the program, it is possible that half of the program is not sufficient to show a significant effect

of meditation practice. To test whether accumulated mediation practice (during the entire intervention) is predictive of change in outcomes (mindfulness, perceived stress, positive affect and negative affect) we separated participants into three groups based on the sum of their meditation practice across the program (in minutes). Based on participants’ total meditation amount, we separated participants into three groups (low: < 33%, medium: 33-66%, high: > 66%) to examine whether the amount of meditation practice was related to changes in outcomes. Changes in outcomes were calculated by subtracting the mean of the first week (day 1 to 7) from the mean of the last week (day 44 to 50). Due to the fact that participants were not randomly assigned to specific conditions, this analysis represents a quasi-experimental design analysis, and thus will not establish causality.

We first tested the hypothesis that “accumulated meditation practice over the entire MBSR program would lead to a significant increase in mindfulness”. To test this hypothesis, we conducted a 2 (Time: First week, Last week by 3) (Meditation practice: low, medium, high) mixed ANOVA, with Time as the repeatedmeasures factor and Meditation practice as the between-subject factor, and with average mindfulness scores as the dependent measure. The ANOVA revealed a significant effect of Time, F(1, 64) = 12.64, p < .001, η2 = .39, showing an increase in mindfulness scores from pre-intervention to post-intervention. However, contrary to expectations, the Time by Meditation interaction was not statistically significant, F (2, 64) = 1.65, p = .20, partial η2= .05. Accumulated meditation practice times were therefore not related to changes in mindfulness scores from pre- to post-measurement. We then tested whether accumulated practice would lead to a significant decrease in perceived stress. To test this hypothesis, we conducted a 2 (Time: First week, Last week) by 3 (Meditation practice: low, medium, high) mixed ANOVA, with Time as the repeated-measures factor and meditation practice as the between-subject factor, and with average perceived stress scores as the dependent measure. The ANOVA revealed a significant effect of Time, F (1, 64) = 13.87, p < .001, η2= .18, showing a decrease in perceived stress scores from preto post-intervention. However, contrary to expectations, the Time by Meditation practice interaction was not statistically significant, F (2, 64) = 0.034, p = .98 partial η2= .001. Accumulated meditation practice times were therefore not related to changes in perceived stress scores from pre to post intervention. We then tested whether

Health and Well-being

66

PSI ISSUE V accumulated practice would lead to significant decreases in negative affect. To test this hypothesis, we conducted a 2 (Time: First week, Last week) by 3 (Meditation practice: low, medium, high) mixed ANOVA, with Time as the repeated-measures factor and meditation practice as the between-subject factor, and with average negative affect scores as the dependent measure. The ANOVA revealed a significant effect of Time, F (1, 64) = 21.51, p < .001, η2= .26, showing a decrease in perceived stress scores from pre- to post-intervention. However, contrary to expectations, the Time by Meditation practice interaction was not statistically significant, F (2, 64) = 0.034, p = .176, partial η2 = .005. Accumulated meditation practice times were therefore not related to pre- to post-changes in negative affect scores. Finally, we tested whether accumulated practice would lead to significant decreases in negative affect. To test this hypothesis, we conducted a 2 (Time: First week, Last week) by 3 (Meditation practice: low, medium, high) mixed ANOVA, with Time as the repeated-measures factor and meditation practice as the between-subject factor, and with average perceived positive affect scores as the dependent measure. The ANOVA revealed a significant effect of Time, F(1, 64) = 8.96, p < .01, partial η2 = .12, showing a decrease in perceived stress scores from pre- to post-intervention. However, contrary to expectations, the Time by Meditation practice interaction was not statistically significant, F(2, 64) = 0.97, p = .385, partial η2 = .03. Accumulated meditation practice times were therefore not related to pre- to postintervention changes in positive affect.

Discussion The purpose of the current study was to clarify the role of meditation practice in a mindfulness-based program.

Specifically, we tested whether the amount of meditation practice throughout the 8 weeks of the program was associated with psychological well-being outcomes. We hypothesized that greater amounts of meditation practice would be related to increases in daily mindfulness, an increase in positive affect, and a decrease in perceived stress and negative affect. To test our hypothesis, we first conducted a regression analysis that examined whether the amount of meditation practice in the first half of the program (day 1 to day 25) was related to scores in outcome variables in the second half of the program (day 26 to 50). Contrary to our hypothesis, we found that the amount of meditation practice in

the first half of the program was not significantly related to outcomes in the second half of the program.

Given that the MBSR is an 8-week intervention that involves meditation practice throughout the program, it is possible that half of the program is not sufficient to show a significant effect on meditation practice. In order to test whether mediation practice over the entire MBSR program predicted change in outcome variables from the first week of the program to the last week of the program, we conducted a 2 (Time: First week, Last week) by 3 (Meditation practice: low, medium, high) mixed ANOVA. Results unexpectedly showed no difference in changes of outcome variables based on different amounts of meditation practice (low, medium, high) across the entire intervention.

Although it did not support our hypothesis, this null finding is consistent with other research showing the lack of relationship between meditation practice and outcomes (e.g., Baer, Carmody & Hunsinger, 2012; Rosenkranz et al., 2013). We expected that accumulated meditation practice would be associated with wellbeing outcomes because a basic assumption of mindfulnessbased interventions is that regular formal meditation practice is necessary to benefit from the program.

While the finding of the lack of relationship between accumulated meditation practice time and changes in daily mindfulness and outcome variables may be valid, there are a few caveats in this study that are worth noting. First, it is possible that only measuring the quantity of meditation practice paints an incomplete picture. Perhaps it is rather the quality of meditation practice that has an effect on outcome variables. To clarify whether quality of meditation practice is an important factor in the relationship between meditation practice and psychological wellbeing, future investigations should use instruments that can assess the quality of meditation practice, such as the Toronto Mindfulness Scale (Lau et al., 2006). Second, the lack of a correlation between meditation practice and change in outcomes may be attributed to the analyses we used, which only permitted us to investigate between-person level changes. More complex analyses were beyond the scope of this thesis. Additionally, our analyses were limited to investigating the total effects of meditation practice on change in outcomes. It is possible that if we had investigated whether meditating on one day predicts changes in outcomes on the next day, at the within-person level, we would have found a relationship between meditation practice and outcome variables. Future investigations should test these

67 Health and Well-being

PSI ISSUE V relationships using multi-level statistics.

Although these alternative explanations may partly account for the lack of a relationship between meditation practice and outcomes, one strength of the current study was its attempt to reduce the bias in reporting on meditation practice, which was a limitation of previous research. That is, participants in our study reported meditation practice immediately after their meditations on a time-stamped online questionnaire, which reduced memory biases. This is important given that unreliable measures of meditation practice have been identified as a crucial reason for the mixed findings regarding the association between meditation practice and psychological well-being. Despite the fact that we used an improved measure of meditation practice, we still did not find a relationship between the amount of meditation practice and changes in outcome variables. If these null findings are maintained when measuring the quality of practice and using multi-level analyses, while still using a trustworthy meditation practice measure, this should be taken as strong evidence for the lack of effects of meditation practice on psychological wellbeing. As another method of investigation to clarify the role of meditation practice in MBSR interventions, future studies could use experimental designs in which meditation practice time and quality are manipulated.

Mindfulness-Based Interventions are founded on the assumption that accumulated meditation practice is a necessary condition for increases in psychological well-being. Our finding that meditation practice has no effect on psychological outcomes in an MBSR setting may suggest otherwise. If our null finding is further supported in future studies and further analyses, then daily meditation practice may not be as fundamental in providing increases in psychological benefits as previously expected. If this is in fact the case, then mindfulness-based interventions could become more accessible to individuals who would not have previously taken such courses due to the burdens of daily meditation practice.

References Almeida, D.M. (2005). Resilience and vulnerability to daily stressors assessed via diary methods. Current Directions in Psychological Science. 14 (2), 64–68. doi: 10.1111/j.0963-7214.2005.00336.x Anderson, N. D., Lau, M. A., Segal, Z. V., and Bishop, S. R. (2007). Mindfulness-based stress reduction and attentional control. Clinical Psychology

Psychotherapy. 14 (6), 449–463. doi: 10.1002/ cpp.544 Baer, R. A, Carmody J., & Hunsinger, M. (2012). Weekly change in mindfulness and perceived stress in a mindfulness-based stress reduction program.

Journal of Clinical Psychology, 68 (7), 755-765. doi:10.1002/jclp.21865 Bolger, N., Davis, A., & Rafaeli, E. (2003). Diary methods: Capturing live as it is lived. Annual Review of Psychology, 54 (8), 579–616.

Brown, K. W., & Ryan, R. M. (2003). The Benefits of being Present: Mindfulness and Its Role in Psychological Well-Being. Journal of Personality and Socail Psychology, 84 (4), 822-848. doi: 10.1037/00223514.84.4.822 Carmody, J., & Baer, R. A. (2008). Relationships between mindfulness practice and levels of mindfulness, medical and psychological symptoms and wellbeing in a mindfulness-based stress reduction program. Journal of Behavioural Medicine, 31 (1), 23-33. doi: 10.1007/s10865-007-9130-7 Cohen, S., Kamarck, T., & Mermelstein, R. (1983). A global measure of perceived stress. Journal of Health and Social Behavior, 385–396.

Goldstein, J. & Kornfield, J. (2001) Seeking the heart of wisdom: The path of insight meditation. Boston: Shambhala.

Kabat-Zinn, J. (1990). Full Catastrophe Living: Using the Wisdom of Your Mind to Face Stress, Pain and Illness. New York: Dell Publishing.

Kabat-Zinn, J. (1994). Mindfulness meditation for everyday life. NewYork: Hyperion.

Kabat-Zinn, J. (2011). Mindfulness: diverse perspectives on its meaning, origins, and multiple applications at the intersection of science and dharma.

Contemporary Buddhism, 12 (1), 1-18. doi: 10.1080/14639947.2011.564811 Keng, S. L., Smoski, M. J., & Robins, C. J. (2011). Effects of mindfulness on psychological health: a review of the literature. Clinical Psychology Review, 31(6), 1041-1056. doi: 10.1016/j.cpr.2011.04.006 Khoury, B., Lecomte, T., Fortin, G., Masse, M., Therien, P., Bouchard, V., Chapeau, M.A., Paquin, K., & Hofmann, S. (2013). Mindfulness-based therapy: A comprehensive meta-analysis. Clinical Psychology Review, 33 (6), 763-771. doi: 10.1016/j. cpr.2013.05.005 McAuliffe, T.M, DiFranceisco, W., Reed, R. R. (2010).

Low numeracy predicts reduced accuracy of retrospective reports of frequency of sexual behaviour. AIDS Behavaiour, 14 (6), 1320-1329. doi.

10.1007/s10461-010-9761-5 Michalak J, Heidenreich T, Meibert P, & Schulte D.

Health and Well-being

68

PSI ISSUE V (2008). Mindfulness predicts relapse/recurrence in major depressive disorder after mindfulnessbased cognitive therapy. Journal of Nervous and Mental Disease, 196 (8), 630â&#x20AC;&#x201C;633. doi: 10.1097/ NMD.0b013e31817d0546 Segal, V. Z.,Williams, J.M.G., Teasdale, J. D. MindfulnessBased Cognitive Therapy for Depression: A New Approach to Preventing Relapse. New York: Guilford Press.

Shapiro, S. L., Brown, K., Biegel, G. (2007). Self-care for health care professionals: Effects of MBSR on mental wellbeing of counseling psychology students. Training and Education in Professional Psychology, 1, 105â&#x20AC;&#x201C;115. doi: 10.1037/1931-3918.1.2.105 Shapiro, S. L., Astin, J. A., Bishop, S. R., & Cordova, M.

(2005). Mindfulness-Based Stress Reduction

for Health Care Professionals: Results from

a Randomized Trail. International Journal of

Stress Management, 12 (2), 164-176. doi:

10.1037/1072-5245.12.2.164 Thompson, E. (2007). Development and validation of

an internationally reliable short-form of the

positive and negative affect schedule (PANAS).

Journal of Cross-Cultural Psychology, 38(2), 227-242.

Vettese, L. C, Toneatto, T., Stea, J. N., Nguyen, L.,

& Wang, J. J. (2009). Do Mindfulness

Mediation Participants do their Homework?

A Review of Empirical Evidence. Journal

of Cognitive Psychotherapy, 23 (3), 198-225. doi:10.1891/0889-8391.23.3.198

69 Health and Well-being

PSI ISSUE V Table 1: Demographic Information Variable Gender Age Ethnicity Marital Status Education Employment Status Previous Meditation Experience Previous Meditation Typeab Previous Meditation Amounta Current Meditation Statusa

Female Male 18-29 30-39 40-49 50 or older Caucasian Other Prefer not to answer Married Never married Other Prefer not to answer Bachelor degree Graduate degree Other Prefer not to answer Employed Student Other Yes No Mindfulness meditation Yoga Prayer or other religious meditations Other Less than a month 1-12 months More than 1 year Currently practicing Not currently practicing

N 60 16 6 29 21 20 66 5 5 30 32 12 2 30 32 12 2 61 8 7 58 18 36 22 12 25 10 30 17 23 34

% 79 21 8 38 28 26 87 7 7 39 42 16 3 39 42 16 3 80 11 10 76 24 62 38 21 33 17 51 29 40 59

Table 2: Regression Analyses between Meditation Practice and Outcome Variables Days 1 to 25 Days 26-50 Week 1 Week 7 Meditation practice (minutes) 343.75 (273.80) 376.67 (311.31) MRS 5.32 (1.16) 5.95 (1.35) 5.11 (1.35) 6.19 (1.47) PSS 4.36 (1.16) 3.98 (1.38) 4.46 (1.29) 3.78 (1.56) NA 3.11 (1.01) 2.72 (1.33) 3.20 (1.08) 2.43 (1.16) PA 5.91 (1.26) 6.16 (1.30) 5.80 (1.34) 6.26 (1.45) Note. MRS = Daily Mindfulness, PSS = Perceived Stress, NA = Negative Affect, PA = Positive Affect Table 3: Correlations between Meditation Practice and Outcome Variables at Time 1 (1 to 25 days) and Time 2 (26 to 50: days) Â 1 2 3 4 5 6 7 8 9 1. Meditation (Time 1) 2. Meditation Time 2) .80** 3. MRS (Time 1) .48** .51** 4. MRS (Time 2) .41** .48** .85** 5. PSS (Time 1) -.40** -.36** -.65** -.55** 6. PSS (Time 2) -.31** -.29* -.61** -.71** .81** 7. NA (Time 1) -.43** -.42** -.36** -.32** .66** .49** 8. NA (Time 2) -.33** -.35** -.34** -.52** .41** .67** .68** 9. PA (Time 1) .24* .30* .66** .59** -.70** -.58** -.38** -.30** 10. PA (Time 2) .22 .31* .71** .77* -.58** -.71** -.29* -.41** .84** Note. MRS = Daily Mindfulness, PSS = Perceived Stress, NA = Negative Affect, PA = Positive Affect * p < .05, **p < .01

Health and Well-being

70

PSI ISSUE V

2015

Behaviour Modification Research Paper: Pathological Skin Picking Isabella Parks* *email: isabella.parks@mail.mcgill.ca

Keywords: behaviour modification, MBSR; pathological skin picking Introduction Pathological skin picking has only recently gained increased attention in the realm of psychological disorders, after its inclusion in the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM5). While there have been many studies examining the condition under the names of “neurotic excoriation,” “compulsive picking,” and “dermatillomania,” the new DSM has finally categorized “Excoriation Disorder” under the section titled “Obsessive Compulsive and Related Disorders”. Criteria include “recurrent skin picking resulting in skin lesions” and “repeated attempts to decrease or stop skin picking.” The lifetime prevalence is estimated at 1.4% of the general population (American Psychiatric Association, 2013).

The disorder is not usually characterized by obsessions or preoccupations, but rather preceded by various emotional states like anxiety and boredom. Individuals may engage in the activity in a focused or automatic way, where a focused pathology uses the behaviour as a distraction or coping mechanism, while an automatic pathology unconsciously employs the mechanism (Wather et al., 2009).

Excoriation disorder has been found to have a negative impact on social functioning. In a study assessing such a relationship, one half of the sample with chronic skin picking experienced social withdrawal, and one fifth reported that they were largely housebound (Arnold et al., 1998). Social embarrassment, avoidance, lowered leisure activity participation and negative impact on quality of life have also been shown to be associated with the condition (Odlaug, Kim & Grant, 2009). Physical consequences of the disorder may include infections, skin lesions, scarring and physical disfigurement (Odlaug & Grant, 2008).

Previous efforts to modify skin-picking behaviours have included Acceptance and Commitment Therapy (ACT; Twohig et al., 2006), Cognitive-Behavioural Therapy (CBT; Schuck, Keijsers, & Rinck, 2010), and HabitReversal Training (HRT; Teng, Woods, & Twohig, 2006; Twohig & Woods, 2001). Acceptance-Enhanced Behaviour Therapy (AEBT; Flessner, Busch, Heideman, & Woods, 2008) has also been developed, which includes aspects of both ACT and HRT. These treatments share many common intervention techniques, including: selfmonitoring, awareness training, competing response training, practicing mindfulness exercises, and cognitive restructuring. All treatments obtained large effect sizes for reduced severity of skin picking, and positive effects on psychosocial functioning. Across all of the studies, the treatment gains were maintained at follow-up, even after brief interventions.

The goal of this intervention was to attempt to use several of the above mentioned methods to discontinue my pathological skin picking behaviour (labeled so because it has not been formally diagnosed as excoriation disorder). Included were self-monitoring techniques, mindfulness-based stress reduction (MBSR), competing response training, and cognitive restructuring, and are described in the “methods” section. These were selfadministered over the course of one week following a week of monitoring normal skin picking occurrences.

Overall, the frequency and severity of my skin picking declined, but did not completely stop. Several limitations are addressed to explain the reason for this. Implications for my findings and future directions are outlined in the “discussion” section.

Health 71 and Well-being

PSI ISSUE V Methods Subject I am a 20-year-old female student at McGill University without any history of mental illness or severe health issues. I have been picking my skin for approximately six and a half years.

Pre-Intervention Self-monitoring is commonly used in self-control behaviour modification plans (Lootens & NelsonGray, 2010), including the ones cited above. In this intervention, self-monitoring was performed for ten days prior to treatment, with detailed recordings of each skin picking occurrence and its antecedents. This process was done after both singular and lengthy skinpicking sessions.

Intervention Self-monitoring was continued throughout the intervention, though with less detail than preintervention. A blank sheet of paper was placed on the bathroom wall, upon which I would write, “scar” every time I entered the bathroom. Should I pick my skin, I would write the time and date of occurrence as well (see implementation intentions below for further explanation). I found it unnecessary to document urges to pick, since I wanted this monitoring to become habitual, and keeping it brief would make that easier.

Mindfulness-based stress reduction (MBSR) was incorporated into the treatment program after reviewing the pre-intervention skin picking data. I determined that my habit was of the “focused” kind, meaning that it is used as a stress coping mechanism (as seen in the frequencies of emotions experienced during picking, see Table 1). MBSR involves becoming aware and focusing on current stressors and being mindful of the negative emotions that may result. It has been associated with enhanced self-awareness and positive outcomes on many well-being constructs (Brown & Ryan, 2003). MBSR was used to target and cope with stressors that would otherwise lead to a need to engage in the skin picking behaviour. To implement this, I would stand back from the mirror any time I began a picking session, take one minute to breathe slowly, clench my fists (a technique used in Habit Reversal Training; Teng et al., 2006), and process my thoughts (also part of the implementation intentions I developed, see below).

Competing response training was used as a behavioural intervention. This was incorporated by creating as implementation intention statements, which

are used to bridge the “intention-behaviour gap” in behaviour change by forming “if/then” contingency statements: if a certain behaviour occurs, then an action must be taken (Gollwitzer, 1999). These were tailored towards my individual situation, and included: “if I enter the bathroom, then I must write the word ‘scar’ on a piece of paper next to the mirror” (the “scar” would serve as a reminder for the consequences of my actions); “if I feel the urge to pick a pimple, then I will engage in positive self-talk” (see “cognitive restructuring” section below); “if I pick a pimple, and acknowledge the distress associated with it, then I will step back from the mirror, breathe slowly, clench my fists, and process my thoughts”; “if I go on a picking ‘binge’ I will write down the time of the occurrence on the paper and be restricted from using concealer the next time I leave the house.” Another competing response included holding something in my hands so as to not subconsciously pick at my face while doing a non-interactive activity (i.e., holding a pen while doing readings for class). Finally, I made an active effort to spend more time away from home, since this is where most skin picking took place, according to the results of my pre-intervention (see below). These activities were not recorded, since the behaviours are too irregular and incommensurable.

Cognitive restructuring was used throughout the intervention to target improving my self-efficacy.

Over the many years I have been skin picking, I have often used negative self-talk after skin picking “binges,” criticizing my self-control abilities. I postulated that it would be beneficial to restructure my thoughts by focusing on positive self-talk in order to regain belief in my abilities to control the behaviour. I would engage in this self-talk whenever I felt myself tempted to pick, saying to myself statements such as “I am in control,” “I will overcome this,” “I am making progress,” and “I am excellent at exercising self-control in many other areas of my life.”

Measures The Skin Picking Scale (SPS; Keuthen et al, 2001) was used pre- and post-intervention to assess skin picking frequency and severity. The scale consists of 6 items, each scored on a 5-point severity scale, ranging from 0 (none) to 4 (extreme), resulting in a score from 0 to 24.

The cut-off score of 7 differentiates severe self-injurious behaviour from non-self-injurious skin pickers. The scale can be seen in Figure 1.

Photographs were taken pre- and postintervention to assess overall appearance changes and scar severity rated on a scale from 0 (clear skin) to 4 (extremely red). These were rated two three independent research assistants and myself.

Health and Well-being

72

PSI ISSUE V Skin Picking Scale Pre-intervention, I scored of 19 out of 24 on the SPS. Post-intervention, I received a score of 10 out of 24, Pre-Intervention I identified my bathroom as the most common location thus still at a severe self-injurious level. of skin picking; doing school work, socializing, and eating, as well as feelings of boredom or anxiety as Photograph Severity antecedents to the behaviour; and observed that skin Pre-intervention photograph severity levels were picking frequency increased on days where I spent more unanimously agreed upon a score of 3 out of 4 by all time at home (see Figure 2). In general, skin pickers do three raters. The post-intervention photograph was not pick in the presence of others (APA, 2013), so this rated as “0” in severity by the two assistants, and “1” finding was not surprising. An example from the data- by myself. The photographs were not included for recording sheet can be seen in Figure 3. personal reasons.

Results

Intervention Adherence It was difficult to maintain engaging in positive selftalk prior to picking (in accordance with the cognitive restructuring intervention), as negative self-talk has been very automatic for me for the several years I have been skin picking. However, taking the time to step back from the mirror after picking seemed beneficial to my emotional wellbeing, since I felt less guilty for engaging in skin picking, despite my inability to use self-talk to prevent the picking in the first place.

Additionally, once I began picking, I occasionally succumbed to the “abstinence violation effect”, defined by losing control and allowing myself to succumb to old behavioural practices after a minor violation of selfimposed rules (Marlatt & Gordon, 1985).

Skin Picking Frequency Pre-intervention skin picking frequency per day averaged 3.1 times a day, with a range of one to seven picks. Over the course of the pre-intervention week, a total of 31 picking sessions were recorded. Postintervention, picking frequency averaged 2.1 a day, ranging from zero to four picks. The total number of picks over this time period was twenty-one (21). Figure 4 shows pre- and post-intervention daily frequency of skin picking, while Figure 5 shows how pre- and postintervention skin picking averages compared. It must be noted that the number of picks decreased throughout the course of post-intervention, which may lead one to assume further progress could have been made past the end of data collection.

Figure 3 displays the relationship between hours away from home and skin picks during the ten days pre- and post-intervention. While the overall amount of picks was lower post-intervention, this graph suggests that such a finding may be the direct result of the greater number of hours away from home during post-intervention.

Limitations While the data outlined in the figures below may show promising outcomes for the behaviour modification treatment, no statistical analyses were done. Many methods were administered at once, therefore it is hard to isolate which one shows the most promise. The behaviour was only monitored for one week, making it hard to determine whether the skin picking frequency before and after intervention was significantly different.

All of the strategies used made me more aware of the severity of my behaviour and the emotional issues that underlie a majority of my skin picking, however, I am still engaging in this behaviour daily.

The sessions are noticeably shorter but my skin is still being damaged. While all of the cited interventions have shown large effect sizes, I believe the unavailing results of this behaviour modification program are largely due to the fact that I carried out the treatment myself.

CBT, ACT, HRT, and AEBT all included a component where the researchers gave training sessions to the participants in order to teach behavioural or cognitive restructuring techniques. Since excoriation disorder is indeed classified as a DSM-5 disorder, it should receive the same clinical assistance as another disorder that requires behavioural change. Therefore, carrying out a program by oneself may prove ineffective.

A large limitation across all studies of skin picking behaviour that could be observed is the use of the SPS to measure treatment success. It is a highly subjective measure of skin picking severity, with each item scored on a scale of 0 to 4 without a firm definition of the value of these numbers. Especially since I evaluated myself, the scoring of my own skin picking severity may be largely biased and inaccurate.

Looking retrospectively on my data collection, I realize I should have included the length of the sessions, as I personally noticed the length of sessions decreasing throughout the intervention. However, this data would have been hard to collect, as I am often unaware of the

73 Health and Well-being

PSI ISSUE V onset of my skin picking, and only partway through do I realize I have been engaging in the activity for an extended amount of time. It should be noted that pre-intervention, I would make this realization and continue regardless, but post-intervention, I would stop picking, engage in self-talk and perform a competing response.

Social support was included as a component in the treatment program developed by Teng et al. (2006). I chose to exclude this factor since its effects were not discussed in enough detail to prove its necessity in treatment. However, it may prove beneficial to obtain positive reinforcement from friends when adhering well to the intervention.

Discussion Despite the above limitations, finding any difference in behaviour after such a short period of time and within such unideal conditions provides promise for future improvements. The fact that I was able to see changes after applying these treatment conditions on my own may give hope to others for implementing other behavioural interventions without professional help. When establishing a set goal for oneself, humans are capable of remarkable change, including self-improvement.

As for future directions, I plan on making another deliberate attempt to eliminate my skin picking behaviour when I live in an apartment with roommates, who I will enlist as help. This will hopefully result in a better outcome.

References American Psychiatric Association. (2013). Obsessivecompulsive and related disorders. In Diagnostic and statistical manual of mental disorders (5th ed.).

Arnold, L. M., McElroy, S. L., Mutasim D. F., Dwight, M. M., Lamerson, C. L., & Morris, E. M. (1998).

Characteristics of 34 adults with psychogenic excoriation. Journal of Clinical Psychiatry, 59(10), 509-14.

Brown, K. W., & Ryan, R. M. (2003). The benefits of being present: mindfulness and its role in psychological well-being. Journal of Personality and Social Psychology. 84(4), 822-848.

Flessner, C. A., Busch, A. M., Heideman, P. W., & Woods, D. W. (2008). Acceptance-enhanced behavior therapy (AEBT) for trichotillomania and chronic skin picking: exploring the effects of component sequencing. Behavior Modification, 32 (5), 57994.

Gollwitzer, P. M. (1999). Implementation Intentions:

Strong Effects of Simple Plans. American Psychologist. 54(7), 492-503.

Keuthen, N. J., Wilhelm, S., Deckersbach, T., Englehard, I. M., Forker, A. E., Baer, L., & Jenike, M. A. (2001). Skin Picking Scale: Scale construction and psychometric analyses. Journal of Psychosomatic Research, 50(6), 337-341.

Lootens, C. M., & Nelson-Gray, R. O. (2010). SelfMonitoring. Corsini Encyclopedia of Psychology, 1-2.

Marlatt, G. A., & Gordon, J. R. (1985). A Cognitive Behavioural Model of the Relapse Process.

Relapse Prevention: Maintenance Strategies in the Treatment of Addictive Behaviors, New York: Guilford Press.

Odlaug, B. L., & Grant, J. E. (2008). Clinical characteristics and medical complications of pathologic skin picking. General Hospital Psychiatry, 30(1), 61-6.

Odlaug B. L., Kim SW, Grant JE. (2010). Quality of life and clinical severity in pathological skin picking and trichotillomania. Journal of Anxiety Disorders, 24(8), 823–829.

Schuck, K., Keijsers, G. P., & Rinck, M. (2010). The effects of brief cognitive-behaviour therapy for pathological skin picking: a randomized comparison to wait-list control, Behavior Research and Therapy. 49(1), 11-17.

Teng, E. J., Woods, D. W., & Twohig, M. P. (2006).

Habit reversal as a treatment for chronic skin picking: a pilot investigation. Behaviour Modification, 30(4), 411-422.

Twohig, M. P., Hayes, S. C., & Masuda, A. (2006). A preliminary investigation of acceptance and commitment therapy as a treatment for chronic skin picking, Behaviour Research and Therapy.

44(10), 1513-1522.

Twohig, M. P., & Woods, D. W. (2001). Habit reversal as a treatment for chronic skin picking in typically developing adult male siblings, Journal of Applied Behavior Analysis. 2 (34), 217-220.

Wather, M. R., Flessner, C. A., Conelea, C. A., & Woods, D. W. (2009). The Milwaukee Inventory for the Dimensions of Adult Skin Picking (MIDAS): initial development and psychometric properties. Journal of Behavior Therapy and Experimental Psychiatry, 40(1), 127-35.

Health and Well-being

74

PSI ISSUE V Appendix

Table 1: Pre-Intervention Characteristics and Antecedents of Skin Picking Sessions Time of day Morning: 1

Meal timing Before: 1

Mood beforea Sad: 1

Activity beforeb Work: 6

Thoughts during Anxiety: 6

Afternoon: 2

After: 9

Apathetic: 1

Social: 4

Problem solving: 3

Evening: 4

Content: 4

Food: 5

Guilty: 8

Bedtime: 3

Bored: 9

Bathroom: 3

Relief: 3

Anxious: 6

Class: 2

Hungry: 2

Grooming: 3

Happy: 0

Nothing: 0

Note. Multiple items were selected in each data collection for mood before, activity before, and thoughts during.

Figure 1. Skin Picking Scale (SPS)

75 Health and Well-being

PSI ISSUE V

Figure 2. Hours away from home in relation to number of times picked a day during pre-intervention and postintervention

Figure 3. Items recorded during each skin picking session, from pre-intervention data recording sheet

Health and Well-being

76

PSI ISSUE V

Figure 4. Skin picking frequency during pre-intervention and post-intervention

Figure 5. Average number and standard deviation of skin picks during pre-intervention and post-intervention

Health and Well-being 77

PSI ISSUE V

2015

Dropping Out of High School: Conditions, Causes, and Potential Solutions Ariele Peterson* *email: ariele.peterson@mail.mcgill.ca

Abstract

This essay discusses significant factors that cause students to drop out of high school and examines models for improving graduation rates. Factors contributing to non-completion include deficiencies in early childhood education; studentâ&#x20AC;&#x2122;s motivation and value of school based on their perceived levels of competency; and push, pull, and fall out factors concerning how a student drops out of school. These factorsâ&#x20AC;&#x2122; connections with race and socio-economic status are also discussed. Finally, several models including the third wave of school improvement reforms, minority-centered schools, and high school intervention programs are analysed as potential solutions to improving graduation rates. An emphasis on comprehensive, national early childhood education programs and support networks for underprivileged families are also recommended. The essay concludes that a combination of several models is likely necessary to best address the many factors that contribute to studentâ&#x20AC;&#x2122;s decisions to drop out of school.

Keywords: education; dropping out; socio-economic status; education reform

Child Development

78

PSI ISSUE V Introduction Failing to complete high school (commonly referred to as “dropping out”) is a decision that has lasting consequences throughout an individual’s life. High school dropouts are more likely to be imprisoned, impoverished, unemployed, divorced or single parents and to be less healthy than their peers who have graduated (Bridgeland, Dilulio & Morison, 2006). Yet, year after year a significant percentage of high school students stop attending high school before graduation. This essay will examine the many factors that influence students’ decisions to drop out as well as the circumstances that enable, force, or encourage them to leave school. It will further examine potential solutions and improvements for effectively promoting school completion.

Literature Review Dropout Prevention Starts in Early Childhood Countless studies have shown that early childhood development has a significant and lasting impact on a student’s learning abilities and future success in the classroom. Jensen’s research on child development has determined that 90% of brain development occurs before the age of five, making this time frame crucial in forming the foundations necessary for academic success (Jensen, 1998). In fact, children who receive high quality early childhood education are less likely to repeat grades, demonstrate higher levels of academic achievement, require fewer special needs programs, and exhibit a higher level of commitment to high school graduation (Hammond, Linton, Smink & Drew, 2007).

Dropping out of high school has increasingly been linked to the accumulation of educational risk factors starting from an early age and in a student’s previous schooling.

Risk factors that start before a child enters kindergarten - including smaller vocabularies, slower language processing speeds, and less at-home literary support - can snowball throughout elementary and middle school, and even determine whether or not a student will graduate. As such, an emphasis should be placed on an early childhood curriculum that is nurturing, consistent, and stimulating, to ensure that children are prepared to start school (Stegelin, 2004). Furthermore, it is important to identify risk factors in children as soon as they enter school, to ensure they do not fall even further behind.

It seems to be a common misconception amongst many parents that children learn basic skills such as reading, writing, counting and telling time, once they enter school. However, children receiving

high quality early childhood education are actually beginning to learn these skills at home and in preschool from birth to five years of age. As such, these children entering kindergarten are already well on their way to reading, writing, and counting, which are all essential abilities for later grades. On the other hand, children who have not had as much exposure to these skills are starting school already behind their peers.

The cycle of unprepared and undereducated children entering school is perpetuated by the unfortunately high numbers of lower socio-economic status families who cannot, due to lack of time, resources or ability, provide high quality early childhood education. In a seminal study by Hart and Risley, they found that by the age of 3 years old, children from privileged families have heard an average of 30 million more words than their underprivileged counterparts.

Additionally, they determined that these children matched their parent’s interaction styles, language and vocabulary use. Finally, they found that this language mastery at age 3 predicted achievement levels in grade 3 at school (Hart & Risley, 2003). The latter finding is significant, as others have noted that literacy at grade 3 is an important educational milestone that if not met, can be predictive of dropping out of high school later on (Annie E. Casey Foundation, 2010).

In another important study, Anne Fernald measured children’s language skills by testing their language processing speed and measuring the amount of words toddlers of higher versus lower socioeconomic status (SES) had learned between the ages of 18 and 24 months. The results indicated that, at 18 months, toddlers from higher SES families could identify the correct object 200 milliseconds faster than their lower SES counterparts (Fernald et al, 2013). This difference in mental processing speed reflects a large gap that does not close between the two groups with age. What’s more, at 24 months, the children of the lower SES group have barely reached the processing speed that their higher SES peers reached at 18 months. As well, the study discovered that between 18 and 24 months the higher SES group had added 260 new words to their vocabulary while the lower had only added 30 new words (Fernald et al, 2013).

These differences in language processing and vocabulary skills at such an early age reflect the dramatic effects that parent-provided early childhood education can have on a child’s future development. With this in mind, national dropout prevention center notes the importance of early literacy development for later academic success. Children learn the fundamentals of reading, such as cognitive and language skills before they reach school age and these abilities upon entering school determine the likelihood of having to repeat

79

Child Development

PSI ISSUE V a grade in the future (National Dropout Prevention Center/Network, 2009). Repeating grades greatly increases the likelihood of dropping out in future years.

If underprivileged children continue to start school with significantly slower language processing skills and a smaller vocabulary, they are likely to have more difficulty reading and to read less well than their peers. This can result in a learning gap that, if left unaddressed, will only increase with age. Lack of early childhood language skills, the resulting learning gap between children who have received comprehensive early childhood education and those who have not, and the subsequent danger of repeating grades are highly interrelated. What’s more, these factors become more predictive of high school non-completion when examined in relation to meeting critical educational milestones.

Mastery of reading by grade 3 is an example of a critical milestone in education. At this age, children “should have transitioned from learning to read to reading to learn” (Annie E. Casey Foundation, 2010), in order to keep up with curriculum and work expectations in higher grades. By grade 6 to 8, poor academic performance in Math and English as well as low reading scores, absenteeism, and disengagement from school become strong predictors of future dropouts (Kennelly & Monrad, 2007).

Children entering school with less developed language processing abilities and vocabulary are less likely than their more prepared peers, to meet crucial milestones in their elementary education. Given this important connection, it is all the more crucial to identify and support students who are behind in literacy and language processing from an early age, in order to prevent an accumulation of educational difficulties in later years that could become factors that encourage, enable or motivate a student to drop out of highschool.

with positive academic outcomes (Stewart, 2008).

In their research on achievement and motivation in school, Wigfield and Eccles also discuss the importance of Alfred Bandura’s theory of self-efficacy to their research on valuing educational achievement (Wigfield & Eccles, 2000). Alfred Bandura found selfefficacy to be crucial in performance accomplishments, self-regulation, achievement strivings, growth of intrinsic interests, and career pursuits (Bandura, 1982). He also notes the correlation between low self-efficacy and poor coping mechanisms, elevated arousal levels, stress, despondency, and resignation to failure experiences (Bandura, 1982). Bandura identifies several “underminers” of personal efficacy that can negatively affect performance and one’s beliefs in their own competency. These include situational factors such as the mere presence of a highly confident individual, being assigned a subordinate role, or being labeled as inferior. Bandura’s research on self-efficacy ties into studies on student motivation to achieve in school, as an instilled sense of incompetence from situational factors can have a dramatic impact on a student’s performance accomplishments. In fact, Bandura notes that subjects perform tasks they are skilled at less well when their incompetence is implied by factors such as labeling inferiority. Furthermore, in experiments in which subjects are made to focus on the strange or unusual in learning a new task rather than the familiar and routine, they also underperform (Bandura, 1982).

The impact of perceived incompetence can negatively affect student performance and learning. A student’s ability to perform tasks well directly relates to their perception of positive academic outcomes, which in turn positively affects their attachment, involvement, and commitment to school.

In their research, Wigfield and Eccles examine “how children’s expectancies for success, ability beliefs, and subjective values change across the school years; and how these beliefs and values relate to children’s performance and activity choice” (Wigfield & Eccles, 2000). Their findings show that children’s belief in their abilities and the value they place on these activities decreases throughout childhood into early adolescence (Wigfield & Eccles, 2000). In relation to performance and activity choice, they found that: “Even when previous performance is controlled, children’s beliefs about their ability and expectancies for success are the strongest predictors of subsequent grades in math, predicting those outcomes more strongly than either previous grades or achievement values. Second, children’s subjective task values are the strongest predictors of children’s intentions to keep taking math and actual decisions to do so.” (Wigfield & Eccles, 2000).

Their findings suggest that beliefs and expectancies

Motivation and Valuing Education Research has shown that a student’s motivation to continue school and to engage in the learning process is highly dependent on their self-esteem and perceived competency in academic endeavors. Wigfield and Eccles’ research indicates that students’ confidence in their abilities decrease as they grow into early adolescence.

They note that when students believe themselves less competent in an area of study, they will place less value on it and their effort to learn or practice this devalued academic subject will decrease as well (Wigfield & Eccles, 2000). This leads to a cycle of incompetency causing devaluation and a subsequent lack of effort to improve, leading to further incompetency. Building on this concept, Stewart determined in his research that student effort (qualified as school attachment, involvement, and commitment) is highly correlated Child Development

80

PSI ISSUE V play a significant role in children’s achievement and continued commitment to academic activities. As such, these beliefs and expectancies should be positively reinforced in schools through confidence-building techniques, modeling, and gradual building on simple tasks to achieve larger goals.

Pushed, Pulled, or Falling Out of School There are many factors that cause, influence, or contribute to a student’s decision to drop out of school.

Jordan et al describe some of these in terms of “push” or “pull” factors that exert pressures on students to dropout.

Push factors are characterised by adverse situations within the school leading to consequences such as poor test results, attendance issues and disciplinary measures (Jordan et al, 1994). “Pull” factors are characterised by personal factors in the student’s life that divert them from completing school, such as marriage, pregnancy, employment, financial issues or family needs (Jordan et al, 1994).

In addition, Watt and Roessingh have defined the term “falling out of school” to describe when a student’s insufficient academic achievement and progress result in apathy and disillusionment. Falling out is not an active decision but rather a culmination of insufficient personal and educational support and subsequent disengagement that results in students leaving school rather than being forced out (Watt & Roessingh, 1994).

Building on Jordan et al’s research, Bradley and Renzulli’s work examines the impact of socioeconomic factors on pushing or pulling out of school for AfricanAmerican and Hispanic students. They acknowledge that a large part of dropping out is related to less available resources and therefore class plays a significant role (Bradley & Renzulli, 2011). However, they note several competing theories that suggest there is a cultural factor in being an underprivileged minority that leads to lower attainment rates in schools.

In their findings, Bradley and Renzulli’s data demonstrates the powerful impact of SES on the likelihood of black students being pushed or pulled out of school in comparison to white students, thus supporting the theory that it is class, and not race, that is predictive of drop-out rates. However, they note “an all or nothing argument of “class not race” obscures the way class and race combine to cause advantages and disadvantages for students in different contexts.”

(Bradley & Renzulli, 2011). They also found that Latino students were no more likely to be pushed out of school than white students when SES was controlled for, but that they were more likely than white students to be pulled out, even when SES and school poverty were controlled for (Bradley & Renzulli, 2011). As such,

the authors argue that it is the complex interactions between class and race that contribute to dropping out, rather than simply class-based factors.

Linking Early Childhood Education, SES, and Push, Pull, Fall-Out Factors The several salient factors to dropping out of high school discussed in this paper are highly intertwined and mutually reinforcing. Children of lower socioeconomic status are less likely to receive high quality early childhood education than their more privileged peers.

They have on average heard millions of fewer words than their higher socioeconomic counterparts and have much slower language processing abilities (Hart & Risley, 2003). Studies have demonstrated that children’s reading competence is correlated with their home literacy environment, such as the number of books owned, and parental concern (Aikens & Barbarin, 2008).

However, lower SES families are less likely to have the time and available resources to provide these benefits to their children. As well, studies show that only 36% of parents in the lowest-income quintile read to their children compared to 62% of parents in the highestincome quintile, suggesting a disparity in parental proactivity in the provision of a quality home literacy environment (Coley, 2002). As such, underprivileged children do not enter school with adequate foundations in literacy and numeracy and are beginning school already behind the standard levels.

Starting school behind only further exacerbates the likelihood of dropping out later on. Studies have demonstrated that students are likely to place less value on activities in which they perceive themselves as incompetent and also to put less effort into their completion and mastery. Students who begin school behind are more likely to perceive themselves as incompetent from an early age, a feeling which only worsens with age and with increasing grade levels (Wigfield & Eccles, 2000). Feelings of incompetency and apathy can lead to deviant or high-risk behaviours eventually resulting in students being pushed out of school by expulsion or other disciplinary measures.

As well, students with lower SES are more likely to be pulled out of school due to financial issues and more likely to miss large amounts of school to an extent where they cannot catch up if they do return (Jordan et al, 1994). Further, low achievement levels and a lack of engagement in school can perpetuate the apathy and disillusionment of students that leads them to gradually “fall out” of school (Watt & Roessingh, 1994).

In addition to student’s familial and individual circumstances, underprivileged schools also play a significant role in determining a student’s likelihood of dropping out. Studies have shown that a teacher’s years

81

Child Development

PSI ISSUE V of experience and quality of training is correlated with student achievement (Gimbert, Bol, & Wallace, 2007), yet often the teachers with the least experience teach in low SES schools. Being enrolled in a school with high numbers of low-income students or being from a lowincome family also increase the likelihood of punitive forms of discipline (Sefa Dei, 2008), which increases the likelihood of being pushed out of school.

Models for Improvement There are many theories on how to alleviate high school dropout rates, most of which necessarily address the need to improve schools and increase student support in order to overcome deep-rooted and long-term socioeconomic disadvantages. Sefa Dei suggests an Afri-centric schooling model –– prioritising African American students but applicable to any minority group – which would concentrate resources and curriculum on meeting minorities’ specific educational requirements (2008). Finally, Christenson and Thurlow discuss the effectiveness of high school intervention programs on graduation rates and student performance, which could be implemented alongside other school reform models to provide supplemental support (2007).

Hopkins and Reynolds suggest a third wave of school improvement model, building on the previous first wave of unsystematic and inconsistent attempts at organisational change and school self-evaluation and the second wave, which focused on on the interaction between school improvement and “school effectiveness communities” (2001).

Hopkins and Reynolds outline the three phases of school improvement since the late 1980s with particular emphasis on the third wave of educational change. The authors note that in a study of five school systems with first and second wave style reforms in the US, Australia, and New Zealand, only one school system, that of Chicago, showed any improvement under a performance-based reform strategy. This is the context in which they introduce the third wave of education, a model seeking to build on the limited successes of previous reform strategies by focusing more on student outcomes than changes to school processes (Hopkins & Reynolds, 2001). Characteristics of the third wave include an emphasis on teachers’ instructional behaviours, implementing “best practice” research, capacity-building in schools through staff development and a commitment to vision building, ensuring programs are consistently implemented, and providing the training and resources to implement these techniques (Hopkins & Reynolds, 2001).

Hopkins and Reynolds note the various requirements for effective education in low SES schools, such as teacher behaviours, involving students actively in the

learning process and involving staff in the improvement plans. They also note that there are different kinds of underprivileged schools that require different reforms; the most serious being the “stuck” schools, which are essentially schools in which teachers work in isolation with low student achievement and no clear definition for the work to be done (Hopkins & Reynolds, 2001).

These schools require leadership changes such as new administration rather than mere changes in leadership style.

It is an unfortunate fact that low socioeconomic status, poor educational performance and race are often intertwined, thus it is important to seek models addressing educational deficits for underprivileged minorities. Sefa Dei’s model of Afri-centric schooling is designed to directly address these challenges by focusing on the issue of at-risk, underprivileged African American students. (Sefa Dei, 2008). Sefa Dei argues that black and minority education must emphasise the importance of personhood and identity, be tailored to cultural learning styles, and cultivate a sense of community and responsibility amongst learners. He notes that current educational systems in Canada disadvantage minorities by using one-size fits all curriculums, rigid school disciplinary measures, and top-down authority structures that alienate and disenfranchise students voices, particularly those already at-risk or in need of educational assistance (Sefa Dei, 2008). In response to these issues, Sefa Dei posits that in order to effectively teach underprivileged minorities, school must be perceived as a community. His proposed Afri-centric school would empower minority students by providing the right to self-definition, through a culturally inclusive curriculum and course material relevant to its students lived experiences.

Christenson and Thurlow examine the effectiveness of high school intervention programs on student’s school completion and performance.

They emphasise the importance of first establishing personal and emotionally engaging relationships with the students in order to create a support network and assist them in their interpersonal relations. They then propose a shift to academic supports such as tutoring and specialised courses before attempting to change alterable behaviours such as attendance. They note that there is a consensus that successful interventions go beyond improving attendance, by helping students and families engage with the school, teachers and peers.

However, successful intervention components include the personalisation of education to fit each students’ individual needs, and to allow for relationship building.

As well, the authors note the need for a high intensity of interventions that include everyday assistance, counseling and programs rather than sporadic tutoring

Child Development

82

PSI ISSUE V and limited counseling (Christenson & Thurlow, 2007).

However, many of these models focus primarily on later interventions or “Band-Aid” solutions that do not target the early causes of factors that contribute to dropping out. Given the numerous studies pointing to the importance of high quality early childhood education it seems that much more should be done to ensure young children are prepared to enter school and that they have the necessary foundations of literacy and numeracy. Further, interventions should potentially begin earlier than high school, with programs in place to assist elementary school children who display risk factors for dropping out and who do not meet basic milestones in academic progress such as reading by a certain age. Christensen and Thurlow note that to ensure these interventions have a lasting positive impact on student attendance and commitment to school, they must be designed specifically for the individual student.

Crucially, they must be intensive, and establish a connection of trust and support between the pupil and their school before focusing on academic improvement.

(Christenson & Thurlow, 2007).

Finally, the availability of programs, resources and information to parents with young children, particularly those with low SES backgrounds, should be drastically expanded to propagate the importance of vocabulary skills and language processing from birth to 5 years old, as well as reading to children daily from an early age. Parents should be aware of the necessity and have the capacity to supplement their children’s in-school education with a foundational interest and practice in literacy. Preschool programs for children ages three and four should be provided for free or be heavily subsidized to underprivileged children.

These programs should also emphasise basic literacy and numeracy, such as the alphabet, counting and vocabulary expansion.

Conclusion In conclusion, poor quality early childhood education, low self-efficacy, and perceived incompetence as well as push, pull, and fall out factors all play significant roles in students dropping out of high school. Amongst the models to address this issue and encourage graduation are the third wave of school improvement, which emphasises a shift in focus from changing school processes to changing student outcomes. As well, Sefa Dei’s proposed minority centered schooling model, which shifts the educational mandate to prioritise and empower minority culture, in order for students to control their own identities through a diverse, inclusive curriculum and school environment. Further, the

effectiveness of programs for high school interventions are analysed through Christensen and Thurlow’s research.

Clearly, there is no one “best practice” or most effective model to encourage an increase in school commitment and graduation rates. Rather, it is a combination of supports, programs, and interventions as well as internal, context-specific school improvement programs and a nation-wide commitment to fostering and disseminating the importance of education from an early age that will make the difference.

References Aikens, N. L., & Barbarin, O. (2008). Socioeconomic

differences in reading trajectories: The

contribution of family, neighborhood, and

school contexts. Journal of Educational

Psychology, 100, 235-251.

Annie E. Casey Foundation (2010). Early warning!

Why reading by the end of third grade matters.

Retrieved from http://www.aecf.

org/~/media/Pubs/Initiatives/KIDS%20 COUNT/123/2010KCSpecReport/AEC_ report_color_highres.pdf Bandura, A. (1982). Self-efficacy mechanism in human agency. American Psychologist, 37(2), 122-147.

Bradley, C.L., & Renzulli, L.A. (2011). The Complexity

of Non-Completion: Being Pushed or Pulled

to Drop Out of High School. Social Forces,

90(2), 521-545.

Bridgeland, J. M., Dilulio, J. J., & Morison, K. B.

(2006). The silent epidemic perspectives of

high school dropouts. A report by Civic

Enterprises in association with Peter D.

Hart Research Associates for the Bill & Melinda

Gates Foundation, Retrieved from https://docs.

gatesfoundation.org/

DocumentsTheSilentEpidemic3-06FINAL.pdf Christenson, S. & Thurlow, M. (2007). School

Dropouts: Prevention Considerations,

Interventions, and Challenges. Current

Directions in Psychological Science,

13(1), 36-39.

Coley, R. J. (2002). An uneven start: Indicators of

inequality in school readiness. Princeton, NJ:

Educational Testing Service.

Fernald, A., Marchman, V. A. and Weisleder, A. (2013),

SES differences in language processing skill and

vocabulary are evident at 18 months.

Developmental Science, 16: 234–248. doi: 10.1111/desc.12019 Gimbert, B., Bol, L., & Wallace, D. (2007). The influence

of teacher preparation on student achievement

and the application of national standards by

teachers of mathematics in urban secondary schools. Education and Urban Society, 40, 91-117.

83

Child Development

PSI ISSUE V Hammond, C., Linton, D., Smink, J., & Drew, S.

(2007). Dropout risk factors and exemplary

programs. Retrieved from National Dropout

Prevention Center, Communities In Schools,

Inc. Retrieved from http://www. dropoutprevention.org/resource/major_ reports/communities_in_schools/Dropout%20 Risk%20Factors%20and%20Exemplary%20

Programs%20FINAL%205-16- 07.pdf Hart, B., & Risley, T. (2003). The early catastrophe: The

30 million word gap by age 3. American Educator,

27(1), 4-9.

Hopkins, D. & Reynolds, D (2001). The Past, Present

and Future of School Improvement: Towards

the Third Age. British Educational Research Journal, Educational Effectiveness and

Improvement: Developing New Theories and

Methods, 27(4), 459-475.

Jensen, E. (1998). Teaching with the brain in mind.

Alexandria, VA: Association for Supervision

and Curriculum Development.

Jordan W. J., Lara J., McPartland J. M. (1994). Exploring

the complexity of early dropout causal structures.

Baltimore, MD: Center for Research on Effective

Schooling for Disadvantaged Students, The John

Hopkins University.

Kennelly, L. & Monrad, M. (2007). Approaches to

dropout prevention: Heeding early warning

signs with appropriate interventions.

Washington, DC: National High School Center

at the American Institutes for Research.

Retrieved from http://www.betterhighschools.

com/docs/NHSC_

ApproachestoDropoutPrevention.pdf National Dropout Prevention Center/Network (2009).

Effective strategies â&#x20AC;&#x201C; Early childhood education.

Retrieved from http://www.dropoutprevention. org/effstrat/early_childhood_ed/overview.htm Sefa Dei, G. J. (2008). Schooling as community: Race,

schooling and the education of African youth.

Journal of Black Studies, 38(3), 346-366.

Stegelin, D. (2004). Early childhood education. In F. P.

Schargel & J. Smink (Eds.) Helping students

graduate: A strategic approach to dropout

prevention, 115-123. Larchmont, NY: Eye on Education.

Stewart, E. B. (2008). School structural characteristics,

student effort, peer associations, and parental

involvement: The influence of school- and

individual-level factors on academic

achievement. Education and Urban Society,

40(2), 179-204.

Watt D., Roessingh H. (1994). Some you win, most you

lose: Tracking ESL dropout in high school (1988-1993). English Quarterly, 26, 5-7.

Wigfield, A., & Eccles, J. (2000). Expectancyâ&#x20AC;&#x201C;value

theory of achievement motivation.

Contemporary Educational Psychology, 25, 68 81. doi:10.1006/ceps.1999.1015

Child Development

84

PSI ISSUE V

2015

The Relationship between Perinatal Maternal Mental Illness and Theory of Mind Development in their Children Ages 2-3 Vivian Gu* Supervisors: Dr. Phyllis Zelkowitz and Anna Mackinnon *email: vivian.gu@mail.mcgill.ca Abstract Theory of mind (ToM) is the ability to attribute mental states to oneself and to others, and it plays a role in the development of empathy (Nader-Grosbois & Day, 2011). It is an important milestone in early child development, and it is thus of interest to understand if maternal mental health may influence its development.

The current investigation studied two groups of mothers — a clinical group with a history of mental illness, and a community group with no mental health concerns — from a longitudinal study. ToM in 2-3 year old children was assessed, and we hypothesized that children of mothers in the clinical group will show poorer ToM scores, and that severity (number of comorbid diagnoses) will be associated with greater ToM impairment. Further, within the clinical group, we hypothesized that greater symptomatology will be associated with poorer ToM. No significant differences were found in children’s ToM between the clinical and community groups when controlling for household income, children’s verbal ability, and number of siblings. Partial correlation analysis showed no significant associations between children’s ToM and number of comorbid diagnoses. However, within the clinical group, there was a significant positive correlation between depressive symptomatology 2-3 years postpartum and children’s ToM. Keywords: Theory of Mind; maternal psychopathology; ToM; development Acknowledgements: I would like to thank my supervisor, Phyllis Zelkowitz, as well as Anna Mackinnon, Stephanie Robins, and Simcha Samuel for their continued support and guidance.

85

Child Development

PSI ISSUE V Introduction An individual’s social cognitive abilities involve “thinking about and making sense of people in our social world” (Moskowitz, 2005, p. 614), and an essential component of these abilities is theory of mind. Theory of mind is defined as the unique ability to attribute mental states to oneself and to others; these can include perceptive states such as visual attention, volitional states including desire and intention, and epistemic states like beliefs and false beliefs (Nader-Grosbois & Day, 2011).

ToM has far reaching implications in terms of the role it plays in facilitating harmonious social interactions, developing empathetic skills, and promoting pro-social behaviours (Nader-Grosbois & Day, 2011). Research has shown that children who are better at understanding another’s emotions and beliefs display fewer aggressive interactions and behaviour problems, and are engaged in more positive friendships (Schacht, Hammond, Marks, Wood, & Conroy, 2013). Because of the importance that a well-developed ToM has in these important social outcomes, it is relevant to understand if factors such as maternal mental health may have adverse influences on the theory of mind developmental trajectory. This may inform attempts to minimize the negative consequences maternal psychiatric illness may have on children’s early ToM development.

Research on the development of theory of mind suggests that children aged 2 to 3 years old begin to develop an implicit understanding of false beliefs by participating in deception and trickery, blaming others for their own transgressions (Newton, Reddy, & Bull, 2000). Children at this age also display pro-social behaviours — like sharing with or helping others — (Ensor, Spencer, & Hughes, 2011), and can understand how others would feel in situations where they themselves would feel differently (Denham, 1986; Wellman & Banerjee 1991). By age 3, children begin to make connections between emotions and external causes, and are able to understand that they may feel two different emotions simultaneously (Nader-Grosbois & Day, 2011).

While much research exists on the developmental trajectory of early theory of mind, which identifies factors such as parenting (Hughes, Deater-Deckard, & Cutting, 1999), family socioeconomic status (Cutting & Dunn, 1999), and number of siblings (Ruffman, Perner, & Parkin, 1999) in the acquisition of ToM, little is known about the harmful effects that maternal mental illness in the perinatal period may have on normative ToM development in toddlerhood. One study conducted by Schacht et al. (2013) found that maternal borderline personality disorder was associated with worse mental

state understanding, or ToM, in children aged 3 to 5, as evidenced by lower composite ToM scores and poorer identification and description of causes of emotion. It was also found that children’s ToM, which was measured by a false beliefs task at age 3 to 5, was negatively correlated with their mothers’ depression, as determined by a structured clinical interview. While a gap in the literature concerning the relationship between maternal mental illness and children’s theory of mind does exist and certainly requires further study, there is much evidence to substantiate the claim that maternal mental health does in fact impact general child development.

Many deficits in child cognitive and socioemotional development have been associated with maternal mental illness symptomatology during the perinatal period, and it has been proposed that these negative effects may be due to the mother’s diminished attention, responsiveness, and availability as a source of comfort for her child (Brennan et al., 2000). Previous research has implicated postnatal maternal depression in poorer cognitive development in children between the ages of 2 months to 4 years old (Azak, 2012; Cogill, Caplan, Alexandra, Robson, & Kumar, 1986; Deave, Heron, Evans, & Emond, 2008; Koutra et al., 2013; Petterson & Burke, 2001; Sutter-Dally et al., 2011), with noteworthy negative impacts on language development (Mensah & Kiernan, 2011; Kahn, 2002; NICHD, 1999).

This is extremely relevant to our investigation, as a link between verbal ability and theory of mind has been well established (Astington & Jenkins, 1999; Milligan, Astington, & Dack, 2007; Astington & Baird, 2005).

Linguistic ability has been implicated as a predictor and precursor to theory of mind (Pyers & Senghas, 2009), with training-related changes in language development resulting in improved theory of mind performance in young children (Hale & Tager-Flusberg, 2003). Verbal ability— especially conversation about feelings, thoughts, and desires (otherwise referred to as mentalistic conversation)—is a significant correlate of children’s socio-cognitive abilities (Slaughter, 2011).

Maternal mental illness can affect how frequently children are presented with opportunities to engage in this mentalistic conversation, subsequently affecting children’s theory of mind abilities. Thus, because maternal mental health has effects on cognitive and linguistic development, there is reason to believe that theory of mind performance will be similarly impaired.

There is also evidence that maternal mental illness is associated with deficits in socio-emotional development in children. Conroy et al. (2012) found that comorbid maternal personality disorder and depression had adverse effects on socio-emotional development, as measured by the Infant-Toddler Social and Emotional

Child Development

86

PSI ISSUE V Assessment. Koutra et al. (2013) and Feldman et al.

(2009) independently showed links between maternal generalized anxiety disorder and poor socio-emotional skills in 18 months old children; Koutra et al. assessed socio-emotional skills with the Bayley Scales of Infant and Toddler Development (Third Edition), while Feldman et al. measured the infant’s social engagement through observational analyses, emotion regulation with a fear paradigm, and sampled infant’s cortisol production. Post-partum mood disorder has also been implicated in delayed social development of both infants and preschool children (Matthey, Guedeney, Starakis, & Barnett 2005; Murray et al., 1999). Moreover, there is evidence that maternal social phobia (Feldman et al., 2009; Murray, Cooper, Creswell, Schofield, & Sack, 2007) and maternal psychological distress (as measured by self-report) (Mensah & Kiernan, 2010) negatively affect socio-emotional development in their children. These negative influences on socio-emotional development have implications for the development of theory of mind, an ability that is deeply intertwined with emotion regulation, expression, and social interaction.

Given the effects that maternal mental health has on cognitive, linguistic, and socio-emotional development, it is logical to suspect that there may be similar effects on socio-cognitive development – specifically the development of theory of mind. These potential effects on ToM are important to study as theory of mind has important implications for a wide range of abilities and behaviours. Not only does ToM have a role in the development of empathy and other prosocial behaviours (Nader-Grosbois & Day, 2011), but it appears that there are significant adverse consequences associated with delayed development of theory of mind in young children. ToM has important implications for getting along with peers (Lalonde & Chandler, 1995), and is positively related to social popularity among 3 to 5 year olds (Slaughter, 2002). Poor theory of mind has also been related to higher levels of aggression (Renouf et al., 2010) and internalizing problems in young children (LaBounty, 2008), and to more attention problems and increased impulsivity (Fahie & Symons, 2003). It is clear that delayed development of theory of mind has harmful effects for young children’s social lives and interactions with peers (Slaughter, 2011).

While our investigation is primarily concerned with exploring the effects of maternal mental illness on ToM development in children, we postulate that the mechanism by which these effects occur is largely environmental. According to Vygotsky’s sociocultural theory, social interaction and modeling of parental behaviour provides a means through which a child may acquire higher cognitive functions (Gauvain, 2008).

Thus, one could theorize that maternal psychiatric

symptomatology – especially severe or comorbid symptom presentation – may inhibit this process from occurring normally, by delaying or even preventing normal socio-cognitive development in the child.

For example, maternal depressive symptoms such as flat affect and decreased responsiveness may hinder socio-cognitive development. Prior research has indeed found links between parental responsiveness and the development of pro-social behaviours (Ensor, Spencer, & Hughes, 2011), and between positive affect and socio-emotional development (Laible & Song, 2006). Moreover, maternal behaviours associated with child care and interaction, such as face-to-face contact, sensitivity to the child, and positive affect, are often of poorer quality in mothers suffering from psychiatric illnesses such as anxiety (Kaitz & Maytal, 2005) or depression (Cohn, Campbell, Matias, & Hopkins, 1990; Campbell, Matestic, von Stauffenberg, Mohan, & Kirchner, 2007). This is relevant because reduced warmth and positivity have been related to poorer socio-cognitive development (Brown & Dunn, 1996; Laible & Thompson, 2000) as well as poorer emotion understanding, which is a close construct of ToM (Laible & Song, 2006). It is thus likely that the adverse effects of poorer child care and interactions associated with worse psychiatric symptomatology, as evidenced by multiple comorbid diagnoses, would be proportionally related to poorer ToM development in children. Indeed, Conroy et al. (2012) found that the negative effects of mental illness on child development were stronger in mothers with comorbid depression and personality disorder than in mothers with either disorder alone. Though further research is required, preliminary research seems to concur with the idea of nurture as the largest determining factor in sociocognitive development; evidence from a genetic study indicating that environmental factors explained the majority of variance in ToM performance (Hughes & Ensor, 2005).

Our current investigation aims to advance knowledge concerning the effects of maternal mental illness on early theory of mind development in 2 to 3 year old children. Because the traditional theory of mind tasks for children are too difficult for this age range and the gaze-tracking paradigms for infants do not adequately measure theory of mind in toddlers, research has focused on studying ToM in preschool-aged children and infants. This resulting gap in the literature on theory of mind in children aged 2-3 is important to examine, and our study provides a novel look into this developmental period. Moreover, little research has looked at the effects of maternal mental illness on the development of theory of mind. We aimed to address this gap by comparing a clinical sample, consisting of

87

Child Development

PSI ISSUE V women with a history of perinatal mental illness, with a community sample, consisting of women with no such history, on their children’s ToM development.

We also planned to account for verbal ability, the child’s gender, socioeconomic status (SES), and the number of siblings each child has, as these variables have been implicated in the development of theory of mind.

Children with better verbal ability have displayed better theory of mind capabilities (Pyers & Senghas, 2009; Slaughter, 2011), and gender and SES have also been linked to general cognitive as well as ToM development.

Studies have shown more marked effects of maternal mental illness on cognitive development in boys (Sutter-Dally et al., 2011; Murray 1992; Murray, FioriCowley, Hooper, & Cooper, 1996; Kurstjens & Wolke, 2001; Mensah & Kiernan, 2010), and there is mixed evidence for a gender difference in theory of mind; studies have shown both a male advantage (Russell et al., 2007) and a female advantage (Charman, Ruffman, & Clements, 2002) in theory of mind development.

Previous research has shown adverse effects of poverty on early child development (Petterson & Burke, 2001), and negative effects of SES on cognitive development in children aged 20 months to 6 years old have also been found (Grace, Evindar, & Stewart, 2003; Kurstjens & Wolke, 2001; Mensah & Kiernan, 2010). Having more siblings was also found to predict higher ToM scores, and children with two or more siblings had significantly better ToM development than those with no siblings (McAlister & Peterson, 2007).

With this knowledge in mind, we expected to find a significant adverse effect of maternal perinatal mental illness on the early development of theory of mind. We hypothesized that the children of mothers in the clinical group would show significantly poorer ToM development as evidenced by lower ToM scores, with children of mothers with comorbid mental illnesses demonstrating the most significant impairments.

We hypothesized that there would be a differential effect of type of mental disorder on ToM, but this was exploratory given the limitations of our relatively small clinical sample who presented largely with depression and anxiety. Further, because we speculated that any effects of mental illness on ToM emerge as a proximal result of the environment created by the mother and her interactions with her child, we anticipated that within the clinical group, greater current depressive symptomatology will be correlated with poorer ToM scores.

compared a clinical sample and a community sample of women who participated in two larger studies: a longitudinal study that explored the relationships between oxytocin, perinatal mood and anxiety, and psychosocial stress, and a follow-up study which explored the links between oxytocin, mother-child attachment, and social cognition.

Participants The community sample was recruited during pregnancy from obstetric clinics at the Jewish General Hospital (JGH) in Montreal, Quebec, and from the Maison de naissance Côte-des-Neiges, a birthing centre where patients are assisted by midwives. A total of 341 women over the age of 18 were recruited. Twenty nine women were excluded from the original study due to miscarriage or preterm birth. The mean age of the community sample was 31.48 years (SD = 4.56), and 94.1% were married or living with a partner.

The clinical sample was recruited through the Perinatal Mental Health Service (PMHS) at the JGH Department of Psychiatry, a service that treats mental health problems in women during pregnancy and postpartum. Seventy five women were recruited, and 60 completed all assessments. Thirty women were recruited during pregnancy, while 30 were only seen postpartum; the mean ages were 32.37 (SD = 4.76) and 31.40 (SD = 5.40), and 87.0% and 91.67% were married or living with a partner, respectively. Though the main mental illness of focus for this investigation was depression (n = 15), as this was most prominent in our sample, the clinical group expressed a range of disorders including anxiety (n = 6), personality disorder (n = 4), attention deficit/ hyperactivity disorder (n = 2), obsessive compulsive disorder (n = 2), and panic disorder (n = 2). Seven women had comorbid diagnoses, while 17 had singular diagnoses.

The ongoing follow-up study has been recruiting participants from these two samples, and 137 women have been included in the present investigation (community group n = 111, clinical group n = 26). At the time of assessment in the follow-up study, there were no significant differences in maternal age, years of education, relationship status, income, gender of child, and child’s number of siblings between the clinical and the community groups (see Table 1). Although the clinical group had slightly older children at the time of assessment, (t(135) = -5.07, p < .001) the ToM tasks used were designed for 2-3 year olds by minimizing demands on verbal ability. Because verbal ability is controlled for, Method this difference in age is thus rendered largely innocuous.

Further, previous research has shown that individual To examine these pertinent research questions, we differences in ToM are “relatively stable across ages 2, 3, and 4” when the ToM scores are aggregated into a single Child Development 88

PSI ISSUE V score (Hughes & Ensor, 2007, p. 1457).

Procedure We used data that from the original longitudinal study that were collected at postpartum, approximately 7-9 weeks after giving birth. Participants were visited in their home, and completed demographic questionnaires and a set of self-report questionnaires assessing symptoms of anxiety and depression.

For the follow-up study, the participant and her child visited the Department of Psychiatry at the JGH for a two-hour testing session. Participants completed various self-report questionnaires, including measures of depressive symptomatology and their child’s language abilities. Three tasks assessing theory of mind were administered to children. At the end of the testing, mothers received $25 and the child was given a small gift.

Measures from the Longitudinal Study Demographic information. Mothers were asked to fill out a questionnaire to provide basic demographic information. This included questions about: age, marital status, who lives in the household, level of education, citizenship and ethnicity, religion, years of living with partner, employment status, and languages spoken.

Participants were also asked about pregnancy, including history of abortion, use of in vitro fertilization and post birth questions about the baby.

Edinburgh Postnatal Depression Scale (EPDS).

The EPDS is a measure of perinatal depressive symptomatology that contains 10 self-report items on a scale of 0-3 about feelings that the individual has experienced in the past seven days. A score of 12 or higher out of 30 indicates risk for depression.

When compared to diagnosis of major depression via psychiatric interview, it was determined that the EPDS had good sensitivity (68-95%) and specificity (7896%) (Cox, Chapman, Murray, & Jones, 2003). The instrument has shown good split-half reliability (0.88), and has been validated for use with pregnant mothers.

Generalized Anxiety Disorder scale (GAD-7).

The GAD-7 measures levels of maternal anxiety. It is a 7 item questionnaire that assesses anxiety symptoms on a scale of 0 to 3, with increasing scores indicating greater level of anxiety. The questionnaire has shown considerable internal consistency (Cronbach alpha coefficient = 0.92) and excellent test-retest reliability (r = 0.83), as well as convergent validity with the Beck Anxiety Inventory (Kroenke, Spitzer, Williams, Monahan, & Lowe, 2007). It has also been validated in relation to generalized anxiety disorder diagnosis via clinical interview (Kroenke et al., 2007).

Measures from the Follow-Up Study Background questionnaire. Participants were asked to fill out a questionnaire on basic demographic information, including: marital status, household income, employment status, pregnancy within the last two years, citizenship status, and who lives in the household. Information pertaining to the child was also obtained, including: the child’s primary caregiver, age at which the child started daycare, health problems, hours per day where the child is cared for by someone other than their parents, if the child is being breastfed, and periods of more than one week of mother-child separation.

Edinburgh Postnatal Depression Scale (EPDS).

The EPDS is described above.

MacArthur-Bates Communicative Development Inventory (MCDI). The MCDI was administered as a measure of verbal ability in the follow-up study. Mothers are asked to report which words, on a list of 100 words, are part of their children’s spoken vocabulary. Mothers must also specify if their child combines words, an evaluation of the child’s grammatical complexity. Scores range from 0 to 100, with higher scores indicating more advanced vocabulary and communicative development.

The inventory has demonstrated high reliability (Cronbach alpha coefficient = 0.99), as well as good content and concurrent validity.

Beck Depression Inventory- II (BDI-II). The Beck Depression Inventory was used in the follow-up study as a measure of depressive symptomatology. It consists of 21 items and produces a score from 0-63; scores above 20 are considered as moderate depressive symptomatology, with scores above 29 indicating severe depressive symptomatology. Each of the items is rated on a Likert scale from 0 to 3 (lowest to highest severity). The BDI-II is a widely used measure with excellent test-retest reliability, high internal consistency and convergent validity, and good discriminant validity between depressed and non-depressed individuals (Arnau, Meagher, Norris, & Bramson, 2001).

ToM tasks The ToM battery used in the follow-up study consists of three ToM tasks designed to assess theory of mind in children aged 2 to 3 years old. If the child refused to participate, their data was not scored.

Visual Perspective. This task assesses the child’s understanding that others cannot share in a visual experience if their vision is obstructed. The child is asked to show a toy to his or her mother, who has been instructed to block her vision in a certain way, for example by covering her eyes with her hands or a

89

Child Development

PSI ISSUE V magazine. The child then receives a score from 1 to 5; 1 = no show or dropped toy in mother’s lap; 2 = held toy near parent but no attempt at correction; 3 = partial correction; 4 = full correction but did not show toy; 5 = full correction and showed toy. There are 4 trials, each with a specific toy and vision blockage method, resulting in a maximum score of 20 points. The task has shown predictive validity in predicting performance at age 3 when completed at age 2, and has also demonstrated convergent validity with ToM comprehension of pretense (Carlson, Mandell, & Williams, 2004).

False Belief Understanding. False belief understanding is assessed with a peep-through picture story book that contains what the child believes is a picture of an eye, visible through a hole. On the last page, it is revealed that what was believed to be an eye was actually a spot on a snake. The child is asked two questions to gauge understanding of false belief and of reality, and the child must get both of these questions correct in order to receive a point for this portion of the task. Next, the researcher presents a puppet named Charlie to the child, who is told that Charlie has never seen the storybook. The child is again asked two questions, this time to assess understanding of another’s false belief and reality, and must answer both questions correctly to obtain a point. Scores on this task range from 0 to 2 points, and the order of alternatives (eye or spot) is counterbalanced across children. The task has established modest convergent validity with the ToM pretend play task (Hughes & Ensor, 2005), and has demonstrated reliability amongst children aged 2, 3, and 4 years old (Hughes & Ensor, 2007).

Pretend Play. The pretend play task is administered to tap into the child’s comprehension of pretense, an aspect of early developing theory of mind.

The child’s ability to engage in pretend play is gauged with four toys, two of which are realistic (toy horse and trough) and two are less realistic (horse and trough made from Lego blocks). There are three conditions: in the baseline, the examiner shows the child the two realistic toys, in the single-substitution condition, the child is shown the realistic horse and unrealistic trough, and in the double-substitution, the child is shown the two unrealistic toys. Within each condition, there are three trials – in the display trial the child is simply asked to demonstrate how they can play with the toys, in the modeling trial, the experimenter models a pretend play action and allows the child to respond, and in the suggestion trial, the experimenter prompts the child to perform a pretend play action. One point is awarded for any pretend play action in each trial, resulting in a maximum score of nine points. The pretend play task has shown convergent validity with the ToM false belief understanding picture book task (Hughes & Ensor,

2005), and has demonstrated predictive validity with a ToM deception task completed at ages 3 and 4 (Hughes & Ensor, 2007).

Data Analysis To analyze the ToM data, a single aggregate ToM score was computed by taking the average of the standardized z scores from each of the three tasks. This follows the method put forth by Hughes & Ensor (2007), and produces a single score for each child, where higher scores are indicative of greater development of theory of mind abilities. To answer our main research questions, analysis of covariance (ANCOVA), analysis of variance (ANOVA), partial correlations, and bivariate correlations (Pearson’s correlation) were used.

Results Descriptive Statistics The descriptive statistics for the main study variables, which include measures taken at 7-9 weeks postpartum and at follow-up two and a half years later, are reported in Table 2. Note the reduced sample sizes in some of the ToM tasks; some children may not have completed all the tasks and subsequently could not be included in all analyses. At 7-9 weeks postpartum, both the EPDS and the GAD-7 were significantly higher in the clinical group as compared to the community group (EPDS, t(135) = -7.89, p < .001; GAD-7, t(135) = -6.81, p < .001).

At follow-up, the clinical group scored significantly higher on the BDI than the community group (t(134) = -2.81, p < .01). The EPDS was not significantly different at follow-up (t(134) = -1.84, p = .07).

Control Variables There were no significant differences by gender on any of the theory of mind tasks in both the clinical group (visual perspective, t(24) = -.93, p = .36; pretend play, t(18) = -.75, p = .46; false beliefs, t(14) = 1.64, p = .12) and the community group (visual perspective, t(107) = 1.3, p = .195; pretend play, t(93) = -.66, p = .51; false beliefs, t(91) = -1.36, p = .18).Consequently, gender was not included as a control variable in subsequent analyses.

Household income, which was used as a proxy measure of SES, was a marginally significant correlate of ToM on visual perspectives task scores (r(24) = .39, p = .052) within the clinical group, but not the community group. Although it was only marginally significant, income was included as a covariate in further analyses.

Performance on the visual perspective task was significantly correlated with scores on the MCDI

Child Development

90

PSI ISSUE V measure of child’s language ability (r(107) = .26, p = .007) and with number of siblings (r(107) = .22, p = .024) within the community group but not within the clinical group (MCDI r(24) = .35, p = .083; number of siblings r(24) = - .23, p = .25). Thus, child’s vocabulary and number of siblings were included as control variables in subsequent analyses.

Analyses of Variance An analysis of covariance (ANCOVA) indicated that there were no significant differences in children’s aggregate ToM scores between the clinical and community groups when controlling for verbal ability, number of siblings, and household income (F(1, 81) = .83, p = .51). We further examined ToM by individual task, which revealed no significant differences between the clinical and community groups, when verbal ability, number of siblings, and household income were controlled for (visual perspective, F(1, 133) = .01, p = .92).

An analysis of variance (ANOVA) was conducted for the remaining two ToM tasks, as these were not significantly related to verbal ability, number of siblings, or household income. No significant differences were found between the two groups (pretend play, F(1, 113) = .67, p = .42; false beliefs, F(1, 107) = .20, p = .66). Given these non-significant analyses, further exploratory analyses to compare between disorders were not conducted.

Correlations Correlations for the main study variables can be found in Table 3. Partial correlation analyses revealed that among mothers in the clinical group, the number of comorbid diagnoses was not significantly associated with ToM in the child when controlling for child’s verbal ability, number of siblings, and household income (ToM Aggregate, pr(9) = -.36, p = .31; visual perspective, pr(9) = .13, p = .7). There were no significant correlations between number of comorbid diagnoses and ToM in the child (pretend play, r(18) = -.17, p = -.47; false beliefs, r(14) = -.37, p = .15).

A positive relationship between children’s scores on the visual perspective task and mothers’ self-reported depressive symptomatology at follow-up was seen via partial correlation analysis in the clinical sample (pr(9) = .66, p = .039 for the EPDS, and pr(9) = .71, p = .022 for the BDI-II) when controlling for child’s verbal ability, number of siblings, and household income. There were no significant correlations between symptomatology at follow-up and pretend play (r(18) = -.19, p = -.41 for the EPDS, and r(18) = -.19, p = -.42 for the BDI-II) or false beliefs (r(14) = -.32, p = .23) for the EPDS, and r(14)

= .07, p = .79 for the BDI-II). Further, no significant relationships were found between symptomatology 7-9 weeks postpartum and aggregate ToM scores, nor with individual ToM tasks.

Discussion The current investigation was conducted to examine the relationship between maternal mental health and children’s theory of mind. We hypothesized that there would be a negative effect of maternal mental illness on the development of theory of mind in children ages 2-3, with the clinical sample showing significantly lower ToM scores than the community sample. This was not supported by the results. Further, no significant relationship was found between ToM ability and severity of maternal mental illness, as measured by number of comorbid diagnoses. We hypothesized that within the clinical group, self-reported depressive symptomatology at follow-up would be significantly correlated with poorer ToM scores. However, a significant positive relationship was seen between maternal self-reported depressive symptomatology at follow-up and scores on the visual perspectives task, with more depressive symptomatology correlated with higher visual perspectives scores. No significant associations were found with the other two ToM tasks.

The lack of significant differences between the community and clinical groups in ToM ability could be related to the tasks used to assess ToM. It is possible that there are several facets of ToM which are differentially affected by maternal mental illness, and that tasks used did not tap into those. Sub-skills which are especially influenced by maternal mental illness may be better captured by additional ToM tasks.

Further, the lack of significant differences between the two groups could be attributed to the small clinical sample size, which was further reduced for individual ToM tasks that the child did not complete (clinical sample n = 26; visual perspectives n = 26; false beliefs n = 16; pretend play n = 20). The lack of a significant correlation between comorbid diagnoses and ToM could also be explained by the small clinical sample, which was further split into women with singular diagnoses (n = 17) and women with comorbid diagnoses (n = 7).

While these are all plausible explanations, it is important to point out the differences in scores of maternal mental illness between the two groups at postpartum and at follow-up. Postnatally, scores on the EPDS and the GAD-7 were significantly different between the clinical group and the community group (see Table 2). However, this difference is attenuated at

91

Child Development

PSI ISSUE V follow-up, with no significant difference in scores on the EPDS, and a smaller significant difference on the BDI-II (see Table 3). Based on these data, it appears that many of the mothers in the clinical group were in remission, which renders their profiles more similar to those of mothers in the community group. At followup, the clinical group does not aptly resemble a clinical population in that their symptom presentation could have been more severe. This relative lack of psychiatric symptom presentation at follow-up could explain the lack of significant differences between the two groups, as mothers who are remitted are perhaps better able to promote their children’s ToM development than mothers who are still presenting with severe mental illness symptoms, thus making up for any adverse effects of perinatal mental illness.

The unexpected significant positive association between depressive symptomatology and ToM score on a single task could be due to the associated characteristics of mental illness. It may be that mothers with psychiatric symptomatology—especially ruminative and depressive tendencies— engage in more mentalistic conversation, which is conversation about feelings, thoughts, and desires. Mentalistic conversation is significantly correlated with children’s socio-cognitive abilities (Slaughter, 2011), and thus could account for the unexpected positive association in the clinical sample between current maternal psychiatric symptomatology and children’s theory of mind, as measured by the visual perspective task. However, it is more likely that the positive relationship observed is spurious and largely an artifact of small sample size.

Some limitations of the current study that should be addressed by future research include the correlational design, whereby we cannot attribute causation to the observed results. Future studies could look at mothers with psychiatric symptomatology with and without treatment to assess the impacts of symptomatology on children’s ToM development.

We were also not able to look at effects of maternal mental illness on ToM development based on time of mental illness onset; onset before and after birth were treated as a single variable, thus masking potentially significant differences. Future studies should address these limitations with detailed records of mental health history obtained through clinical interview in order to capture a clearer understanding of early socio-emotional development and the effects that mothers may have on her children. It may also be important to assess ToM with different tasks and with older children to clarify the associations between maternal mental illness and different ToM subsets. Larger clinical samples with worse psychiatric symptomatology presentation when the children are 2-3 years old should also be explored.

It is important to understand the links between maternal mental illness and children’s theory of mind, as clinicians and researchers will benefit from understanding the influence that a mother’s mental health may exert on her child’s socio-emotional development. The clinical applicability is far-reaching, extending to pregnant women, women who have just given birth, and mentally ill mothers. Pregnant mothers who are at risk for psychiatric illness can be assessed and monitored, in order to ensure that their psychiatric symptomatology does not worsen and lead to adverse effects for her child. The same can be said for women who have just given birth, as they are another risk group that can benefit from careful monitoring. Mentally ill mothers can also procure benefits from assessment and treatment. In some sense, our results are optimistic— despite having a mother with a history of perinatal mental illness, children had ToM skills that were comparable to those of their peers without such exposure to maternal mental illness. Yet our findings further emphasize the importance of treatment for mental illness, as it is unclear how children’s ToM would have developed had their mothers not been in remission. If there are indeed negative effects associated with psychiatric symptom presentation, treatment to reduce these symptoms in mothers may prove beneficial for children’s socioemotional development. Services and programs to enrich social environments and interactions could also be established for children who are at risk, to minimize the negative effects of nurture-deprived environments that are associated with maternal psychiatric illness.

More opportunities to develop theory of mind abilities could be created, such as periods of pretend play with peers and siblings or chances to integrate more mentalistic talk into the child’s conversation. Both have been associated with better theory of mind development, and could thus negate or at least reduce the potentially adverse impacts that maternal mental illness may have on ToM development.

It is also relevant for the field to better understand ToM deficits, as it could potentially inform research on disorders that involve impaired social functioning, such as autism, schizophrenia, and schizotypy (BaronCohen, Leslie, & Frith, 1985; Marjoram et al., 2006; Langdon & Coltheart, 2004).

Conclusion

The current investigation examined the effect of perinatal maternal mental illness on children’s theory of mind development. No significant differences were found between the community and clinical groups on ToM scores, and no significant correlations between number of comorbid diagnoses and ToM scores were Child Development 92

PSI ISSUE V found. A significant positive correlation was seen between the visual perspectives task and mother’s selfreported depressive symptomatology. Findings should be interpreted with the study’s limitations in mind, which most notably are the small clinical sample size and the relatively similar profiles at follow-up between mothers in the clinical group and the community group.

As such, further studies to address these limitations are necessary to elucidate the role that perinatal mental illness in mothers plays in socio-cognitive development in their children.

References Arnau, R. C., Meagher, M. W., Norris, M. P., & Bramson, R. (2001). Psychometric evaluation of the Beck Depression Inventory-II with primary care medical patients. Health Psychology, 20(2), 112-119.

Astington, J., & Baird, J. A (2005). Why language matters

for a theory of mind. New York, NY: Oxford

University Press.

Astington, J. W., & Jenkins, J. M. (1999). A longitudinal study of the relation between language and theoryof-mind development. Developmental Psychology, 35(5), 1311-1320.

Azak, S. (2012). Maternal depression and sex differences shape the infants’ trajectories of cognitive development.

Infant Behavior and Development, 35(4), 803-814. doi: http://dx.doi.org/10.1016/j.infbeh.2012.07.017 Baron-Cohen, S., Leslie, A. M., & Frith, U. (1985). Does the autistic child have a “theory of mind”? Cognition, 21(1), 37-46.

Brennan, P. A., Hammen, C., Andersen, M. J., Bor, W., Najman, J. M., & Williams, G. M. (2000). Chronicity, severity, and timing of maternal depressive symptoms: Relationships with child outcomes at age 5. 36, 759-766. doi: 10.1037/0012-1649.36.6.759 Brown, J. R., & Dunn, J. (1996). Continuities in emotion understanding from 3 to 6 years. Child Development, 67(3), 789-802.

Callahan, J. L., Borja, S. E., & Hynan, M. T. (2006).

Modification of the Perinatal PTSD Questionnaire to enhance clinical utility. Journal of Perinatology, 26(9), 533-539. doi: 10.1038/sj.jp.7211562 Campbell, S. B., Matestic, P., von Stauffenberg, C., Mohan, R., & Kirchner, T. (2007). Trajectories of maternal depressive symptoms, maternal sensitivity, and children’s functioning at school entry. Developmental Psychology, 43(5), 1202-1215. doi: 10.1037/00121649.43.5.1202 Carlson, S. M., Mandell, D. J., & Williams, L. (2004). Executive function and theory of mind: stability and prediction from ages 2 to 3. Developmental Psychology, 40(6), 1105-1122. doi: 10.1037/0012-1649.40.6.1105 Charman, T., Ruffman, T., & Clements, W. (2002). Is there a Gender Difference in False Belief Development?

Social Development, 11(1), 1-10. doi: 10.1111/14679507.00183 Cogill, S. R., Caplan, H. L., Alexandra, H., Robson, K. M., & Kumar, R. (1986). Impact Of Maternal Postnatal Depression On Cognitive Development Of Young Children. British Medical Journal (Clinical Research Edition), 292(6529), 1165-1167. doi: 10.2307/29523072 Cohn JF, Campbell SB, Matias R, Hopkins J. (1990). Faceto-face interactions of postpartum depressed and non-depressed mother-infant pairs at two months.

Developmental Psychology. 1990;26:15-23.

Conroy, S., Pariante, C. M., Marks, M. N., Davies, H. A., Farrelly, S., Schacht, R., & Moran, P. (2012). Maternal psychopathology and infant development at 18 months: the impact of maternal personality disorder and depression. Journal of the American Academy of Child and Adolescent Psychiatry, 51(1), 51-61. doi: 10.1016/j.jaac.2011.10.007 Cox, J. L., Chapman, G., Murray, D., & Jones, P. (1996).

Validation of the Edinburgh Postnatal Depression Scale (EPDS) in non-postnatal women. Journal of Affect Disorders, 39(3), 185-189.

Cutting, A. L., & Dunn, J. (1999). Theory of Mind, Emotion Understanding, Language, and Family Background: Individual Differences and Interrelations. Child Development, 70(4), 853-865. doi: 10.1111/14678624.00061 Deave, T., Heron, J., Evans, J., & Emond, A. (2008). The

impact of maternal depression in pregnancy on

early child development. BJOG: An International

Journal of Obstetrics & Gynaecology, 115(8), 1043 1051. doi: 10.1111/j.1471-0528.2008.01752.x Denham, S. A. (1986). Social Cognition, Prosocial Behavior, and Emotion in Preschoolers: Contextual Validation. Child Development, 57(1), 194-201. doi: 10.2307/1130651 Ensor, R., Spencer, D., & Hughes, C. (2011). ‘You Feel Sad?’ Emotion Understanding Mediates Effects of Verbal Ability and Mother–Child Mutuality on Prosocial Behaviors: Findings from 2 Years to 4 Years. Social Development, 20(1), 93-110. doi: 10.1111/j.14679507.2009.00572.x Fahie, C. M., & Symons, D. K. (2003). Executive functioning and theory of mind in children clinically referred for attention and behavior problems. Journal of Applied Developmental Psychology, 24(1), 51-73. doi: http:// dx.doi.org/10.1016/S0193-3973(03)00024-8 Feldman, R., Granat, A., Pariente, C., Kanety, H., Kuint, J., & Gilboa-Schechtman, E. (2009). Maternal depression and anxiety across the postpartum year and infant social engagement, fear regulation, and stress reactivity. Journal of the American Academy of Child and Adolescent Psychiatry, 48(9), 919-927. doi: 10.1097/CHI.0b013e3181b21651 Fenson, L., Pethick, S., Renda, C., Cox, J. L., Dale, P. S., & Reznick, J. S. (2000). Short-form versions of the MacArthur Communicative Development

93

Child Development

PSI ISSUE V Inventories. Applied Psycholinguistics, 21(01), 95116. doi: doi:null Gauvain, M. (2008). Vygotsky’s Sociocultural Theory. In M. M. Haith & J. B. Benson (Eds.), Encyclopedia of Infant and Early Childhood Development (pp. 404413). San Diego: Academic Press.

Grace, S. L., Evindar, A., & Stewart, D. E. (2003). The effect of postpartum depression on child cognitive development and behavior: A review and critical analysis of the literature. Archives of Women’s Mental Health, 6(4), 263-274. doi: 10.1007/s00737-0030024-6 Green, J. M., Kafetsios, K., Statham, H. E., & Snowdon, C. M. (2003). Factor structure, validity and reliability of the Cambridge Worry Scale in a pregnant population.

Journal of Health Psychology, 8(6), 753-764. doi: 10.1177/1359105303008600 Hale, C. M., & Tager-Flusberg, H. (2003). The influence of language on theory of mind: a training study.

Developmental Science, 6(3), 346-359. doi: 10.1111/1467-7687.00289 Hughes, C., Deater-Deckard, K., & Cutting, A. L. (1999).

‘Speak roughly to your little boy’? Sex Differences in the Relations Between Parenting and Preschoolers’ Understanding of Mind. Social Development, 8(2), 143-160. doi: 10.1111/14679507.00088 Hughes, C., & Ensor, R. (2005). Executive Function and Theory of Mind in 2 Year Olds: A Family Affair?

Developmental Neuropsychology, 28(2), 645-668. doi: 10.1207/s15326942dn2802_5 Hughes, C., & Ensor, R. (2007). Executive function and theory of mind: Predictive relations from ages 2 to 4. Developmental Psychology, 43(6), 1447-1459. doi: 10.1037/0012-1649.43.6.1447 Hughes, C., Jaffee, S. R., Happe, F., Taylor, A., Caspi, A., & Moffitt, T. E. (2005). Origins of individual differences in theory of mind: from nature to nurture? Child Development, 76(2), 356-370. doi: 10.1111/j.14678624.2005.00850.x Kahn, R. S., Zuckerman, B., Bauchner, H., Homer, C. J., & Wise, P. H. (2002). Women’s Health After Pregnancy and Child Outcomes at Age 3 Years: A Prospective Cohort Study. American Journal of Public Health, 92(8), 1312-1318.

Kaitz, M., & Maytal, H. (2005). Interactions between anxious

mothers and their infants: An integration of theory

and research findings. Infant Mental Health Journal, 26(6), 570-597. doi: 10.1002/imhj.20069 Koutra, K., Chatzi, L., Bagkeris, M., Vassilaki, M., Bitsios, P.,

& Kogevinas, M. (2013). Antenatal and postnatal

maternal mental health as determinants of infant

neurodevelopment at 18 months of age in a mother child cohort (Rhea Study) in Crete, Greece. Social

Psychiatry and Psychiatry Epidemiology, 48(8), 1335 1345. doi: 10.1007/s00127-012-0636-0 Kroenke, K., Spitzer, R. L., Williams, J. B., Monahan, P. O., &

Lowe, B. (2007). Anxiety disorders in primary care: prevalence, impairment, comorbidity, and detection.

Ann Intern Med, 146(5), 317-325.

Kurstjens, S., & Wolke, D. (2001). Effects of Maternal Depression on Cognitive Development of Children Over the First 7 Years of Life. Journal of Child Psychology and Psychiatry, 42(5), 623-636. doi: 10.1111/1469-7610.00758 LaBounty, J. C. (2008). Social cognition and its effects on young children’s social and mental health outcomes.

(3343125 Ph.D.), University of Michigan, Ann Arbor.

Retrieved from http://search.proquest.com/docview /304578347?accountid=12339. (304578347).

Laible, D., & Song, J. (2006). Constructing Emotional and Relational Understanding: The Role of Affect and Mother-Child Discourse. Merrill-Palmer Quarterly (1982-), 52(1), 44-69. doi: 10.2307/23096067 Laible, D. J., & Thompson, R. A. (2000). Mother-child discourse, attachment security, shared positive affect, and early conscience development. Child Development, 71(5), 1424-1440.

Lalonde, C. E., & Chandler, M. J. (1995). False belief understanding goes to school: On the socialemotional consequences of coming early or late to a first theory of mind. Cognition & Emotion, 9(2-3), 167-185. doi: 10.1080/02699939508409007 Langdon, R., & Coltheart, M. (2004). Recognition of metaphor and irony in young adults: The impact of schizotypal personality traits. Psychiatry Research, 125(1), 9-20.

Marjoram, D., Miller, P., McIntosh, A. M., Cunningham Owens, D. G., Johnstone, E. C., & Lawrie, S. (2006).

A neuropsychological investigation into ‘Theory of Mind’ and enhanced risk of schizophrenia.

Psychiatry Research, 144(1), 29-37. doi: http://dx.doi. org/10.1016/j.psychres.2006.01.008 Matthey, S., Guedeney, A., Starakis, N., & Barnett, B. (2005).

Assessing the social behavior of infants: Use of the ADBB Scale and relationship to mother’s mood.

Infant Mental Health Journal, 26(5), 442-458. doi: 10.1002/imhj.20061 McAlister, A., & Peterson, C. (2007). A longitudinal study of

child siblings and theory of mind development.

Cognitive Development, 22(2), 258-270. doi: 10.1016/j.cogdev.2006.10.009 Mensah, F. K., & Kiernan, K. E. (2011). Maternal general health and children’s cognitive development and behaviour in the early years: findings from the Millennium Cohort Study. Child: Care, Health & Development, 37(1), 44-54. doi: 10.1111/j.13652214.2010.01150.x Mensah, F. K., & Kiernan, K. E. (2010). Parents’ mental health and children’s cognitive and social development.

Social Psychiatry and Psychiatry Epidemiology, 45(11), 1023-1035. doi: http://dx.doi.org/10.1007/ s00127-009-0137-y Milligan, K., Astington, J. W., & Dack, L. A. (2007).

Language and Theory of Mind: Meta-Analysis of the

Child Development

94

PSI ISSUE V Relation Between Language Ability and False-belief Understanding. Child Development, 78(2), 622-646. doi: 10.1111/j.1467-8624.2007.01018.x Moskowitz, G. B. (2005). Social cognition: understanding self and others. New York: Guilford Press.

Muller, U., Liebermann-Finestone, D. P., Carpendale, J. I., Hammond, S. I., & Bibok, M. B. (2012). Knowing minds, controlling actions: the developmental relations between theory of mind and executive function from 2 to 4 years of age. Journal of Experimental Child Psychology, 111(2), 331-348. doi: 10.1016/j.jecp.2011.08.014 Murray, L. (1992). The Impact of Postnatal Depression on Infant Development. Journal of Child Psychology and Psychiatry, 33(3), 543-561. doi: 10.1111/j.14697610.1992.tb00890.x Murray, L., Cooper, P., Creswell, C., Schofield, E., & Sack, C. (2007). The effects of maternal social phobia on mother-infant interactions and infant social responsiveness. Journal of Child Psychology and Psychiatry, 48(1), 45-52. doi: 10.1111/j.14697610.2006.01657.x Murray, L., Fiori-Cowley, A., Hooper, R., & Cooper, P. (1996).

The impact of postnatal depression and associated adversity on early mother-infant interactions and later infant outcome. Child Development, 67(5), 2512-2526.

Murray, L., Sinclair, D., Cooper, P., Ducournau, P., Turner, P., & Stein, A. (1999). The Socioemotional Development of 5-year-old Children of Postnatally Depressed Mothers. Journal of Child Psychology and Psychiatry, 40(8), 1259-1271. doi: 10.1111/1469-7610.00542 Nader-Grosbois, N., & Day, J. (2011). Emotional Cognition: Theory of Mind and Face Recognition. In J. L. Matson & P. Sturmey (Eds.), International Handbook of Autism and Pervasive Developmental Disorders (pp. 127-157): Springer New York.

Newton, P., Reddy, V., & Bull, R. (2000). Children’s everyday deception and performance on false-belief tasks.

British Journal of Developmental Psychology, 18(2), 297-317. doi: 10.1348/026151000165706 NICHD Early Child Care Research Network. (1999).

Chronicity of maternal depressive symptoms, maternal sensitivity, and child functioning at 36 months. 35, 1297-1310. doi: 10.1037/00121649.35.5.1297 Peters, E., Joseph, S., Day, S., & Garety, P. (2004). Measuring delusional ideation: the 21-item Peters et al.

Delusions Inventory (PDI). Schizophrenia Bull, 30(4), 1005-1022.

Petterson, S. M., & Alison Burke, A. (2001). Effects of Poverty and Maternal Depression on Early Child Development. Child Development, 72(6), 1794-1813. doi: 10.2307/3654379 Priest, S. R., Austin, M. P., Barnett, B. B., & Buist, A. (2008). A psychosocial risk assessment model (PRAM) for use with pregnant and postpartum women in primary care settings. Archives of Women’s Mental Health,

11(5-6), 307-317. doi: 10.1007/s00737-008-0028-3 Pyers, J. E., & Senghas, A. (2009). Language Promotes FalseBelief Understanding: Evidence From Learners of a New Sign Language. Psychological Science, 20(7), 805-812. doi: 10.1111/j.1467-9280.2009.02377.x Renouf, A., Brendgen, M., Séguin, J., Vitaro, F., Boivin, M., Dionne, G., . . . Pérusse, D. (2010).

Interactive Links Between Theory of Mind, Peer Victimization, and Reactive and Proactive Aggression. Journal of Abnormal Child Psychology, 38(8), 1109-1123. doi: 10.1007/s10802-010-9432-z Ruffman, T., Perner, J., & Parkin, L. (1999). How

Parenting Style Affects False Belief Understanding. Social Development, 8(3), 395411. doi: 10.1111/1467-9507.00103 Russell, T. A., Tchanturia, K., Rahman, Q., Schmidt, U., Tchanturia, K., Schmidt, U. (2007). Sex differences in theory of mind: A male advantage on Happe’s “cartoon’’ task. Cognition and Emotion, 21(7), 15541564. doi: 10.1080/02699930601117096 Schacht, R., Hammond, L., Marks, M., Wood, B., & Conroy, S. (2013). The Relation between Mind-mindedness in Mothers with Borderline Personality Disorder and Mental State Understanding in their Children.

Infant and Child Development, 22(1), 68-84. doi: 10.1002/icd.1766 Slaughter, V. (2011). Development of Social Cognition Child Psychology and Psychiatry (pp. 51-55): John Wiley & Sons, Ltd. Slaughter, V., Dennis, M. J., & Pritchard, M. (2002). Theory

of mind and peer acceptance in preschool children.

British Journal of Developmental Psychology, 20(4),

545-564. doi: 10.1348/026151002760390945 Sutter-Dallay, A. L., Murray, L., Dequae-Merchadou, L.,

Glatigny-Dallay, E., Bourgeois, M. L., & Verdoux,

H. (2011). A prospective longitudinal study of the

impact of early postnatal vs. chronic maternal

depressive symptoms on child development.

European Psychiatry, 26(8), 484-489. doi: http:// dx.doi.org/10.1016/j.eurpsy.2010.05.004 Wellman, H. M., & Banerjee, M. (1991). Mind and emotion: Children’s understanding of the emotional consequences of beliefs and desires. British Journal of Developmental Psychology, 9(2), 191-214. doi: 10.1111/j.2044-835X.1991.tb00871.x

95

Child Development

PSI ISSUE V Appendix Table 1: Demographic Information Clinical Motherâ&#x20AC;&#x2122;s Age, M (SD) 34.66 (3.64) Relationship Status (%) Married/Long term relationship 84.6 Divorced 7.7 Single/widowed 7.7 Income (%) < 25,000 15.4 25,000- 64,999 23.1 65,000- 104,999 26.9 105,000-144,999 11.5 145,000- 184,999 11.5 185,000- 224,999 3.8 >225,000 7.7 Years of Education, M (SD) 17.85 (3.64) Child Characteristics Child Gender (Male/Female; %) 42.3/49.5 Childâ&#x20AC;&#x2122;s Age, M (SD) 3.07 (.73)* Number of siblings, M (SD) 1.27 (1.08) Note. * p < .001 Table 2: Descriptive Statistics Clinical Community M SD N M

Variable 7-9 weeks postpartum EPDS GAD-7 Follow-up EPDS BDI-II MCDI ToM Aggregate Visual Perspective Pretend Play False Beliefs

Variable 7-9 weeks postpartum

Community 35.26 (4.41) 91.0 4.5 4.5 8.3 26.9 33.3 14.8 7.4 2.8 6.5 16.77 (2.89) 49.5/50.5 2.66 (.22)* 1.11 (.74)

SD

N

12.23** 8.23**

6.33 6.32

26 26

4.77** 2.90**

3.74 2.60

111 111

7.08 10.15* 60.46

4.63 8.57 27.76

26 26 26

5.40 6.25* 67.90

4.08 5.76 25.21

110 110 111

.23 .62 13 14.81 4.22 26 4.75 1.99 20 .44 .63 16 Note. * p < .01, ** p < .001

.06 14.90 4.27 .37

.68 3.89 2.44 .59

82 109 95 93

Table 3: Correlations among Main Study Variables 1.

2.

3.

4.

5.

6.

7.

8.

.83 .05 .12 -.06 .27 -.25 -.22 1. EPDS -.24 2. GAD-7 .76** .07 .07 -.15 .33 -.08 Follow-up .10 3. EPDS .60** .49** .68 .66* -.19 -.32 .23 4. BDI-II .46** .52** .67** .71* -.19 .07 .13 .03 .05 .05 5. Visual Perspective .007 .00 .55 6. Pretend Play -.01 -.09 -.08 -.12 .21* .34 .61* 7. False Beliefs -.06 -.17 -.17 -.18 .15 .23 .82** .05 -.07 -.07 -.07 .66** .71** .69** 8. ToM Aggregate Note. Above diagonal = clinical sample; Below diagonal = community sample. Bold = partial correlations. All other correlations are bivariate. EPDS = Edinburgh Postnatal Depression Scale; GAD-7 = Generalized Anxiety Disorder scale; BDI-II = Beck Depression Inventory- II. * p < .05, ** p < .01.

Child Development

96

PSI ISSUE V

The Cross-Cultural Construct of PTSD Diagnoses: Implications for Refugee Populations

Beth Mansell* *email: beth.mansell@gmail.com

Keywords: Posttraumatic stress disorder; refugees; cross-cultural; interventions

97

Cultural and Social

PSI ISSUE V Introduction

The nature of the refugee course warrants the assumption that individuals experience and witness a variety of traumatic events. There has recently been concern that the refugee experience has been pathologized; however, psychopathology should not be an inevitable consequence of refugee exposure to traumatic events.

Varying prevalence rates of post-traumatic stress disorder (PTSD) lead to the questionability of the cross-cultural validity of the conceptualized diagnosis for defined symptoms, as PTSD diagnoses in refugee populations are excessively common and exceed expected bounds. Contextual factors highlighted in pre- and post-migration, while often ignored by governments and agencies, are important mitigating factors influencing the development and perpetuation of PTSD symptoms. The importance of these factors is reflected in effective treatment options, which give agency to the refugee and allow for the traumatic experience to be put in a socio-political context.

History and Definition As of 2011, the United Nations High Commissioner for Refugees (UNHCR) had concern for 10.5 million refugees, mainly from conflicts, as well as an additional 14.7 million internally displaced persons (IDPs) in 27 countries under UNHCR protection (UNHCR, 2012).

Today’s wars may seem to kill fewer people than past conflicts, but greater numbers of civilians appear to be exposed and vulnerable to violence, torture and persecution, especially in situations where the state offers little protection for its citizens (UNHCR, 2012; Rousseau, 2011).

PTSD was first coined in the 1970s after an understanding of the experience of Vietnam War veterans as a mental disorder (Scott, 1990). The disorder was first included in the 1980 publication of the The Diagnostic and Statistical Manual of Mental Disorders (DSM), the DSM-III (Scott, 1990). PTSD is currently considered to be a trauma- and stressor-related disorder (American Psychiatric Association, 2013a), whereas previously it was listed as an anxiety disorder (American Psychiatric Association, 2000). The DSM-5 outlines the current criteria for diagnosis of PTSD. The trigger is identified as exposure to actual or threatened death, serious injury or sexual violation resulting from one or more of the following: • “Direct experience of the traumatic event • Witness of the traumatic event in person • Learns that the traumatic event occurred to a close family member or close friend

• Experiences first-hand repeated or extreme exposure to aversive details of the traumatic event” (American Psychiatric Association, 2013b, p. 1).

A myriad of factors are included within the diagnosis, such as re-experiencing the traumatic event, avoidance, negative cognitions and mood, and increased arousal. These disturbances must cause distress or impairment of functioning for longer than a month (American Psychiatric Association, 2013b).

PTSD as a diagnostic category has been established as cross-culturally valid, as it has been found to constitute a similar and consistent group of symptoms occurring in diverse cultural settings in response to trauma (Hinton and Lewis-Fernandez, 2011, p. 796). However, these reviewers found that the expression of PTSD is by no means identical, and their analysis suggests that cultural syndromes may shape symptom comorbidities and symptom profiles.

For example, mental health professionals working with Cambodian refugees in the 1980s observed different manifestations of post-traumatic distress with patients describing themselves as ‘thinking too much’, which became known as the ‘Cambodian sickness’, resembling the symptoms of PTSD (Van de Put & Eisenbruch, 2004).

Cambodians described the next stage of the illness as ‘small heart’, recounting the state of demoralization, followed by ‘broken down heart-mind’, describing the fragmented thoughts that they were experiencing (Van de Put & Eisenbruch, 2004). Examples such as these have led others to argue that the concept of PTSD is a Western-defined diagnostic category, and thus may be less applicable to those refugees from non-Western nations (Bracken, 2001; Wilson, 2007). However, the reviews of Bracken and Wilson did not address whether PTSD is cross culturally valid, only whether it can be readily applied outside Western cultures. In a UNHCR report by Gojer and Ellis (2014), it is argued that PTSD is not a biological disease that can be assessed universally.

They further claim that this socially constructed psychiatric category fails to capture a holistic view of people’s trauma, and is used to evaluate the reliability and consistency of people’s trauma narrative (Gojer & Ellis, 2014). Bracken (2001) proposes that not only has PTSD been constructed as a Western disorder, but also that it has become a “disorder of our times” (p. 742) as Western society has developed an increased awareness of psychological distress as a reaction to trauma. This highlights a critical issue with DSM diagnoses: they remain constrained to specific criteria, and once an individual is diagnosed individual differences are not considered. However, this view ignores that meeting the specific criterion is the intended purpose of DSM diagnoses. The categories are intended to establish

Cultural and Social

98

PSI ISSUE V consistent and reliable diagnoses between clinicians to advise specific treatment plans (American Psychiatric Association DSM-5 Development, 2014). The criteria developed for disorders were created with the intention that ultimately only a minority of people could be diagnosed with a specific disorder. Yet, once prevalence rates reach over 50% it becomes dubious whether the behavior is truly a “disorder,” or if it is capturing a “normal” part of human life.

In a meta-analysis yielding diagnostic information from 81, 866 refugees from 40 countries, the reported prevalence for PTSD varied from 0% to 99% (Steel et al., 2009). Evidently, the prevalence of the disorder ranges between contexts, with higher prevalence likely in higher conflict zones. A weighted prevalence estimate derived from this meta-analysis ranges from 13% to 25% PTSD prevalence in refugee populations (Steel et al., 2009). Populations displaced within or external to the source country, or living in a refugee camp had higher rates of PTSD than those permanently resettled in another country (Steel et al., 2009; Porter & Haslam, 2005). In a review of data for 5,499 adult refugees resettled in high-income Western countries 9% were clinically diagnosed with PTSD, whereas the data for 260 children refugees yielded an 11% prevalence rate (Fazel, Wheeler, & Danesh, 2005).

Fazel et al. (2005) highlight that in comparison to the American population, refugees are 10 times more likely to have PTSD. Nonetheless, it has not been explained whether this difference is simply due to the increased exposure to traumatic experiences in comparison with the American population.

Diagnosing PTSD

different meanings across cultures (Kleijn et al., 2001).

In this study, it was noted that these high correlation scores may just reflect the psychometric properties for extreme cases, as all subjects were referred to an expert center for PTSD in refugees (Kleijn, et al., 2001). It is highly possible that in less severe cases of traumatic experiences, or for individuals that do not need such professional treatment, that cultural phenomena could have more subtle influences. In addition to this study, Jakobsen, Thoresen, and Johansen (2011) examined the validity of screening for PTSD among asylum seekers from different countries currently in Norway. Validating the HTQ against the World Health Organization Composite International Diagnostic Interview (CIDI), exposure to traumatic events was reported by 95% of participants, and the prevalence of PTSD was 45% (Jakobsen et al., 2011). The CIDI is a structured interview for psychiatric disorders designed to allow for administration by those who are not clinically trained in a short period of time (Robins et al., 1988). It was found to be an epidemiological instrument suitable for use in conjunction with different diagnostic systems and for use in different cultures (Robins et al., 1988).

Although there was agreement between the instruments and interview, there were major differences between the subgroups of asylum seekers, with overestimation for the MENA group, and underestimation for the Somali group (Jakobsen et al., 2011). These results inevitably lead to the conclusion that screening instruments should not be interpreted in the same manner across groups. These screening tools may not provide perfect diagnostic information for highly symptomatic samples and the burden of PTSD symptoms may not be accurately represented. Jakobsen et al. (2011) state that this overlap between the screening instruments is likely because they all tap into the total burden of mental health problems. Ideally, screening measures should be applicable to populations that have a varying prevalence of PTSD, have experienced a variety of traumas, as well as serving individuals from different cultural backgrounds.

Without extensive local validation in each context, even measures such as the HTQ may be unable to distinguish disorder from severe non-disordered stress. In order to assess the validity of such cross cultural measures, they should first be translated into the local language, and then translated back into the original language to check that all concepts have been properly understood. As well, it should be understood that the Harvard Trauma Questionnaire was developed to measure mental disorders and should not be used as a means of assessing broader psychosocial needs.

In this respect, subclinical symptoms should not be used to assume that an individual needs immediate

Measures such as the Harvard Trauma Questionnaire (HTQ) have been adapted in specific cases, such as that for Indochinese Refugees (Mollica et al., 1992) and Iraqi refugees (Shoeb, Weinstein, & Mollica, 2007), with both showing cross-cultural validity as a measure of PTSD in their respective cases. The HTQ consists of several kinds of questions relating to traumatic events, DSM related posttraumatic symptoms, and culture-related posttraumatic symptoms, which are rated on a 4-point rating scale with anchors of 1 (not at all distressed by the symptoms) and 4 (extremely distressed) (Kleijn, Hovens, & Rodenburg, 2001). Kleijn et al. (2001) examined the psychometric properties of the HTQ in Arabic, Farsi, Serbo-Croatian, Russian, and English bilingual adaptations for refugees referred for psychiatric concerns to a Dutch treatment center. It was concluded that the internal consistencies of PTSD were acceptable in all five languages; however, some items showed low correlations, indicating that these items may have

99

Cultural and Social

PSI ISSUE V intervention. This relates to UNICEF’s recent shift from trauma-based models of delivery to a resiliencybuilding approach, in which resilience is recognized and strengthened autonomously in the face of adversity (UNICEF, 2011).

Risk Factors

functioning, which leads to in an inability to remember key aspects of the event (American Psychiatric Association, 2013b). Therefore, refugees suffering from PTSD may be unable to narrate a consistent, credible testimony for a review board. Evidently, review board officials need a better understanding of PTSD so that asylum claims by individuals suffering from PTSD are not minimized in the system.

It is important to consider the risk factors that contribute to the development of PTSD in refugees. For example, it Symptoms was found that pre-displacement factors associated with future PTSD development included higher age, coming In a symptomatic sense, PTSD can influence a variety from a rural area, being more educated, and having a of actions, as the increased arousal symptom results higher socioeconomic status (SES) (Porter & Haslam, in aggressive, reckless or self-destructive behaviour 2005). Post-displacement accommodation was also (American Psychiatric Association, 2013b). For a found to act as a moderator variable, with those resettled refugee settling in a new environment this behaviour in institutional and temporary accommodation faring will not fare well for integration. Additionally, people worse on mental health outcomes (Porter & Haslam, with PTSD instantaneously see the world differently 2005). Those with poor economic opportunities in because the disorder distorts the normal appraisal the host country, repatriated refugees, and those from process (Friedman, 1997). The appraisal process refers conflicts that remained ongoing also experienced to the theory of emotion in which a person’s personal greater levels of PTSD symptoms (Porter & Haslam, interpretation of an event determines their emotional 2005). It is understandable that factors such as age reaction (Lazarus, 1991). If this process is disturbed in and the instability of accommodation should affect a refugee, a variety of negative outcomes are possible. mental health outcomes; yet, the increased risk for For example, a refugee with PTSD settled in a Western PTSD development in more educated and higher SES country who perceives a regular interaction with a bus individuals is unexpected as it is generally considered driver politely asking for the correct change as being that those individuals will have more resources to negative may feel dejected, upset, or fearful. Clearly combat the debilitating effects of the refugee experience. this is a maladaptive aspect to refugee integration, as This is evidently not the case, and it appears that these refugees will start to attribute their negative emotions classes are suffering more due to the unexpectedness to the outcomes of interactions with citizens of the of the situation and having more to lose. Thus, these host country. Biologically, PTSD disrupts the balance results demonstrate that PTSD can affect all sectors of between the hypothalamic-pituitary-adrenal (HPA) the refugee population. These factors are important for axis and adrenergic systems, resulting in allostasis: practice, as they provide information for at-risk sectors an abnormal steady state (Friedman, 1997). As the of the refugee population. allostatic load increases over time it results in greater Understanding pre- and post-migration risk wear and tear on several organs and tissues, especially factors leads into a discussion of short- and long- the cardiovascular system (McEwen and Stellar, term outcomes for a PTSD diagnosis and the ensuing 1993). This system usually controls reactions to stress; symptoms. Separate from the potential effect of therefore, it is apparent that refugees living with PTSD symptoms on the refugee and their surrounding social are putting their bodies under a substantial amount of structure is the ability for a PTSD diagnosis to affect a stress that would usually be restored as situations are refugee’s credibility. Limited understanding of mental resolved. health variables and over reliance on categorical PTSD diagnoses can have serious consequences in the process Cross-cultural Validity of ascertaining claimant credibility (Gojer & Ellis, 2014). Gojer and Ellis (2014) explain that refugees who Research is usually either conducted while refugees experience pre-migratory traumatic events may be at are accommodated in refugee camps or within a short increased risk of receiving a negative refugee decision time after resettlement in a host country, which does due to lack of knowledge, training and experience among not give any indication for the potential long-term board members, lawyers and immigration officials. effects of PTSD on refugees. It is thus understandably Refugee stories are evaluated through testimony, which difficult to determine whether the symptoms reported faces the legal test of credibility (Gojer & Ellis, 2014). in these studies represent an acute condition, which One of the core symptoms of PTSD is impaired cognitive Cultural and Social 100

PSI ISSUE V could resolve spontaneously, or whether it reflects a persisting chronic condition (Marshall, Schell, Elliott, Berthold, & Chun, 2005). Nevertheless, PTSD appears to change refugeesâ&#x20AC;&#x2122; long-term perception of certain initiatives. Eight years after the Rwandan genocide, researchers sought to examine how the level of trauma exposure and prevalence of PTSD among Rwandans was associated with long-term attitudes towards justice and reconciliation (Pham, Weinstein & Longman, 2004).

Out of the 2,074 respondents who reported exposure to trauma, 72.8% were displaced and lived as refugees during the 1994 conflict (Pham et al., 2004). Surprisingly, eight years later, 24.8% still met symptom criteria for PTSD (Pham et al., 2004). Those with PTSD symptoms were less likely to hold positive attitudes toward the Rwandan national and the local Gacaca trials when compared to individuals who did not suffer from PTSD, who showed high levels of support for these governmental responses.

Additionally, individuals with PTSD symptoms showed less belief in their community and interdependence with other ethnic groups. The authors hypothesize that the high support among individuals who did not suffer from PTSD symptoms could be attributed to the fact that individuals felt more informed, as Gacaca trials were built on a traditional local dispute structure in which popularly elected committees of lay judges were organized to try those accused of less serious crimes in open community trials (Pham et al., 2004). This finding implies that those with PTSD feel less self-efficacy and control over the process compared to those Rwandans not suffering from PTSD. This is something that social learning theories propose as being a critical dimension of well-being and behaviour change (Bandura, 1977).

It was also found that a higher level of education was associated with less support for the trials and less openness to reconciliation (Pham et al., 2004). This relates to Porter and Haslamâ&#x20AC;&#x2122;s finding that a higher level of education was associated with a higher level of PTSD symptoms. While it can be argued that these specific judicial responses did not work in the Rwandan case, it should be understood that reconciliation is a very complex undertaking that requires participation from all parties involved. The reluctant attitudes from those suffering from PTSD ultimately hinder the efforts for reconciliation. This study suggested that in seeking to rebuild societies such as Rwanda, where displacement during the conflict was widespread, it is important to understand how traumatic experience may affect the ability of individuals to respond to reconciliation and development initiatives.

Cambodian refugees are another example of a refugee population that experienced mass exposure to traumatic events during the Cambodian Civil war, with a large population permanently resettled in the United

States. A study conducted 20 years after resettlement in the US found that psychiatric morbidity was still high, with 62% still meeting diagnostic criteria for PTSD (Marshall et al., 2005). Poor English-speaking skills, unemployment, retirement, disability, and living in poverty were associated with higher rates of PTSD (Marshall et al., 2005), raising concerns about access to services and treatment contained in policies regarding refugee resettlement. Asylum policies need to examine their capacity to promote long-term health and well-being of the refugees that they are taking in.

High levels of PTSD can be related to this insufficient capacity. The study reported that since arriving in the US, 34% of the sample reported seeing a dead body in their neighbourhood, 28% reported being robbed, and 17% reported having been threatened with a weapon (Marshall et al., 2005). Interestingly, the study found that alcohol abuse and dependence rates were much lower in Cambodian refugees compared to that of the general US population, where numerous studies show a high comorbidity between PTSD and alcohol abuse (Marshall et al., 2005). This provides possible evidence that the cultural context in which drinking occurs may moderate this relationship.

A follow-up study of psychosocial functioning in refugees settled in Norway actually found an increase in PTSD symptoms in a significant amount of the refugees who had been diagnosed with PTSD 3 years previously (Lie, 2002). The study found that the level of affective social support was an important determinant of the PTSD symptom severity (Lie, 2002). It was also indicated that concerns with the situation in the home country due to continued war and persecutions after arriving in the host country had a perpetuating influence on the symptoms of illness (Lie, 2002). This result supports the finding by Porter and Haslam that unresolved conflict can act as a moderator variable for increased PTSD symptoms.

Finally, a study of PTSD symptoms in Bosnian refugees a year after resettlement in the U.S. found that 60% of participants originally diagnosed with PTSD still met criteria 12 months later (Weine et al., 1998).

Positive outcomes were associated with increased length of time since the most severe trauma, the passing of time since the shock of displacement, acculturation, and stability in life structure in aspects such as family, work, and community. Most importantly, participation in opportunities such as informal counselling to communicate traumatic memories resulted in reduced PTSD symptoms(Weine et al., 1998). Those with ongoing PTSD were characterized to utilize more primitive defensive functions, such as avoidance, numbing, and denial to distance themselves psychologically from the traumatic experiences (Weine et al., 1998).

101

Cultural and Social

PSI ISSUE V Interventions These examples of short- and long-term outcomes for refugee populations with PTSD indicate a need for more effective treatment options. In many cultures of displaced refugees, treatments of mental and emotional concerns are assigned to traditional healers. However, these networks may be disrupted through resettlement and thus become inaccessible to refugees. Some research suggests that early intervention may be helpful and can serve to transcend cultural and other barriers to mental health treatment for refugees. Upon arrival in the US, refugees are often offered additional health screenings (to supplement the pre-departure screening for communicable and other diseases), which enable them to be referred to health care services as needed.

(Barnes, 2001). Unfortunately, mental health screenings are not often incorporated with this practice. With more attention to mental health issues earlier in the resettlement process, long-term adjustment and daily functioning of those individuals at-risk for developing PTSD may be improved (Savin, Seymour, Littleford, Bettridge, & Giese, 2005, p. 225). In a trial of psychiatric screening for refugees in Texas, a clinic found that 77% refused to be interviewed by a psychiatric resident (Barnes, 2001). Reasons cited for refusal included the stigmatization of mental health labels, as well as fear that they could be deported or discriminated against for employment or housing opportunities (Barnes, 2001). It is clear that cultural boundaries in this situation had not been transcended, especially considering the psychiatric residents could not speak the refugee’s language and an interpreter was used to communicate (Barnes, 2001).

In contrast, interventions such as mental health screenings interweaved with obligatory physical health examinations have seen positive results. In an experimental study, a multi-disciplinary team performed mental health screenings in connection with physical examinations for 1,580 refugees resettled in Colorado (Savin et al., 2005). If from the screening measures the team determined that an individual was likely to have a psychiatric disorder that would significantly impair their ability to work, attend school, or interact with other people, the result was defined as positive (Savin et al., 2005). A total of 146 (9.2%) screened positively. In contrast to measures such as the HTQ, this method had strength in that it did not use a cut-off number of symptoms on the checklist to determine a positive screen, as cultural factors and differences could influence symptom endorsement on the checklist. This appears to be reflected in the smaller number of positive screens, which seems to more realistically reflect psychiatric diagnoses in comparison with the high results previously discussed when using the

HTQ. Those individuals who screened positively were referred to a psychiatrist or psychologist with extensive experience dealing with war trauma in a cross-cultural context (Savin et al., 2005). Of these individuals, 37% followed up with the treatment referral, and notably, this group had endorsed more PTSD symptoms than the non-treatment group (Savin et al., 2005). This finding suggests that early screenings may be beneficial for refugees with more severe symptoms who may be reluctant to seek treatment options otherwise.

Despite the diverging accounts of PTSD, cross-cultural treatment options are optimistic. A review by Nicholl and Thompson (2004) on the state of psychological therapies for refugees suffering from PTSD revealed significant methodological limitations; however, some potentially effective treatments that attempt to employ innovative and diverse elements were highlighted. The authors found that approaches delivered by multidisciplinary teams – which encompassed social, medical and psychological elements – provided a holistic treatment experience and were often effective. (Nicholl & Thompson, 2004). It is likely that this treatment method worked due to greater consideration of the social and political context of the symptom presentation.

A systematic review of randomized control trials (RCTs) of treatment for PTSD among refugees evaluated ten RCTs (n = 528). The setting for the trials varied between resettlement in Europe and the US, as well as a refugee camp in Uganda (Crumlish & O’Rourke, 2010). Two common forms of treatment were identified: narrative exposure therapy (NET) and cognitive behaviour therapy (CBT) (Crumlish & O’Rourke, 2010). NET is a form of treatment for multiple and complex trauma in which the patient, with the assistance of the therapist, constructs a chronological narrative of his life specifically focusing on the traumatic experiences (Schauer, Neuner, Elbert, 2011). Reprocessing - the creation and integration of traumatic experiences – is facilitated through this therapy (Schauer et al., 2001). CBT treatment involves components of psycho-education, exposure, cognitive restructuring, and anxiety management (Harvey, Bryant, & Tarrier, 2003). It is undertaken for specific problems (“problem focused”), and the therapist assists the patient to find specific, adaptive strategies to address those problems (“action oriented”) (Harvey et al., 2003).

NET appeared to be best supported for PTSD treatment in refugee populations, with one study reporting only 29% of refugees in a NET treatment group meeting criteria for PTSD at a one year follow-up, compared with 79% in a supportive counselling treatment group, and 80% in a psycho-education group (Neuner, Schauer, Klaschik, Karunakara, & Elbert, 2004). CBT was also

Cultural and Social

102

PSI ISSUE V effective in a smaller study, with one study finding that References 60% of patients in the immediate CBT treatment group were in remission from PTSD after their course of CBT, American Psychiatric Association. (2000). Diagnostic and compared to 0% in the wait-list group (Hinton et al., statistical manual of mental disorders, (4th ed.).

2005).

Washington, DC: Author.

American Psychiatric Association. (2013a). Diagnostic and A criticism of the NET and CBT treatment statistical manual of mental disorders, (5th ed.). studies mentioned is that they have not been conducted Washington, DC: Author. in realistic settings that the refugees would encounter American Psychiatric Association. (2013b). Posttraumatic in a regular resettlement process. A more recent Stress Disorder – Fact Sheet. Retrieved from http:// study sought to examine whether refugees can be www.dsm5.org/Documents/PTSD%20Fact%20 treated successfully for PTSD with NET in the general Sheet.pdf psychiatric health care system in Western host countries American Psychiatric Association DSM-5 Development.

(Stenmark, Catani, Neuner, Elbert, & Holen, 2013). At (2014). Retrieved November 20, 2014, from http:// a six-month follow-up, only 54.5% of patients in the www.dsm5.org/about/pages/faq.aspx NET group met PTSD criteria, compared to 81% in Bandura, A. (1977). Self-efficacy: toward a unifying theory of behavioral change. Psychological review, 84(2), 191. the treatment as usual group (Stenmark et al., 2013).

Barnes, D. M. (2001). Mental health screening in a refugee This result provided evidence that more culturally population: A program report. Journal of immigrant sensitive treatments such as NET can also be used in health, 3(3), 141-149. the psychiatric health care systems to significantly Bracken, P. J. (2001). Post-modernity and post-traumatic reduce PTSD symptoms in refugees. NET appears to stress disorder. Social Science & Medicine, 53(6), be a straightforward treatment option that can be used 733-743. effectively for refugees seeking PTSD treatment in Crumlish, N., & O’Rourke, K. (2010). A systematic review of Western health care settings. treatments for post-traumatic stress disorder among Conclusion Individual differences due to contextual factors in response to trauma are inevitable. Thus, the implications of PTSD will vary across and within contexts and treatment options will not be fitting in all situations. The economic, social and cultural conditions from which refugees are displaced and in which they are placed have a lasting effect on their psychological outcomes; therefore, “psychological aftereffects of displacement cannot be understood simply as the product of an acute and discrete stressor” (Porter & Haslam, 2005, p. 611).

The validation of each screening instrument for each specific language or cultural group would be a costly and time-consuming task; however, it may be necessary in order to not pathologize natural human reactions to a traumatic experience. While it is evident that a great majority of refugees are not in need of clinical mental disorder services, it is crucial that all refugees have access to these services. Additionally, implementing preventive post-traumatic symptom interventions following the exposure to or experience of traumatic events can mitigate the effects of PTSD. Finally, it appears that focus on post-migration factors should be given consideration to ensure that PTSD symptoms are not exacerbated in the host-country, with treatment options allowing for the refugee to conceptualize their traumatic experience in a socio-political context.

refugees and asylum-seekers. The Journal of nervous and mental disease, 198(4), 237-251.

Fazel, M., Wheeler, J., & Danesh, J. (2005). Prevalence of serious mental disorder in 7000 refugees resettled in western countries: a systematic review. The Lancet, 365(9467), 1309-1314.

Friedman, M. J. (1997). Post-traumatic stress disorder: An overview. National Center for PTSD. Retrived from http://www.ptsd.va.gov/professional/PTSDoverview/ptsd-overview.asp Gojer, J., & Ellis, A. (2014). Post-Traumatic Stress Disorder and the refugee determination process in Canada: Starting the discourse. New Issues in Refugee Research, Research Paper No. 270, Geneva, UNHCR. Retrieved from http://www.unhcr.org/53356b349. html Harvey, A. G., Bryant, R. A., & Tarrier, N. (2003). Cognitive behaviour therapy for posttraumatic stress disorder. Clinical psychology review, 23(3), 501-522.

Hinton, D. E., Chhean, D., Pich, V., Safren, S. A., Hofmann, S. G., & Pollack, M. H. (2005). A randomized controlled trial of cognitive‐behavior therapy for Cambodian refugees with treatment‐resistant PTSD and panic attacks: A cross‐over design. Journal of traumatic stress, 18(6), 617-629.

Hinton, D. E., & Lewis‐Fernández, R. (2011). The cross‐ cultural validity of posttraumatic stress disorder: implications for DSM‐5. Depression and anxiety, 28(9), 783-801.

Jakobsen, M., Thoresen, S., & Johansen, L. E. E. (2011).

The validity of screening for post-traumatic stress disorder and other mental health problems among asylum seekers from different countries. Journal of refugee studies,24(1), 171-186.

103

Cultural and Social

PSI ISSUE V Kleijn, W. C., Hovens, J. E., & Rodenburg, J. J. (2001).

Posttraumatic stress symptoms in refugees: assessments with the Harvard Trauma Questionnaire and the Hopkins symptom Checklist-25 in different languages. Psychological reports, 88(2), 527-532.

Lazarus, R.S. (1991). Progress on a cognitive-motivationalrelational theory of emotion. American Psychologist, 46(8), 819-834.

Lie, B. (2002). A 3‐year follow‐up study of psychosocial functioning and general symptoms in settled refugees. Acta Psychiatrica Scandinavica, 106(6), 415-425.

Marshall, G. N., Schell, T. L., Elliott, M. N., Berthold, S. M., & Chun, C. A. (2005). Mental health of Cambodian refugees 2 decades after resettlement in the United States. Jama, 294(5), 571-579.

McEwen, B. S., & Stellar, E. (1993). Stress and the individual: mechanisms leading to disease. Archives of internal medicine, 153(18), 2093-2101.

Mollica, R. F., Caspi-Yavin, Y., Bollini, P., Truong, T., Tor, S., & Lavelle, J. (1992). The Harvard Trauma Questionnaire: validating a cross-cultural instrument for measuring torture, trauma, and posttraumatic stress disorder in Indochinese refugees. The Journal of nervous and mental disease, 180(2), 111-116.

Neuner, F., Schauer, M., Klaschik, C., Karunakara, U., & Elbert, T. (2004). A comparison of narrative exposure therapy, supportive counseling, and psychoeducation for treating posttraumatic stress disorder in an African refugee settlement. Journal of consulting and clinical psychology, 72(4), 579.

Nicholl, C., & Thompson, A. (2004). The psychological treatment of post traumatic stress disorder (PTSD) in adult refugees: A review of the current state of psychological therapies. Journal of Mental Health, 13(4), 351-362.

Pham, P. N., Weinstein, H. M., & Longman, T. (2004).

Trauma and PTSD symptoms in Rwanda: implications for attitudes toward justice and reconciliation. Jama, 292(5), 602-612.

Porter, M., & Haslam, N. (2005). Predisplacement and postdisplacement factors associated with mental health of refugees and internally displaced persons: a meta-analysis. Jama, 294(5), 602-612.

Robins, L. N., Wing, M. D., Helzer, M. D., Babor, T. F., Burke, J., Farmer, M. D., ... & Pickens, R. (1988).

The Composite International Diagnostic Interview: An epidemiological instrument suitable for use in conjunction with different diagnostic systems in different cultures. Arch Gen Psychiatry, 45, 10691077.

Rousseau, C., Pottie, K., Thombs, B., Munoz, M., and T.

Jurcik. (2011). Post Traumatic Stress Disorder:

Evidence Review for Newly Arriving Immigrants

and Refugees. Canadian Collaboration for

Immigrant and Refugee Health (CCIRH).

Savin, D., Seymour, D. J., Littleford, L. N., Bettridge, J., & Giese, A. (2005). Findings from mental health screening of newly arrived refugees in Colorado.

Public Health Reports, 120(3), 224.

Schauer, M., Neuner, F., & Elbert, T. (2005). Narrative exposure therapy: A short-term intervention for traumatic stress disorders after war, terror, or torture.

Boston, US: Hogrefe & Huber Publishers.

Scott, W. J., 1990. PTSD in DSM-III : A case in the politics of diagnoses and disease. Social Problems, 37 (3).

Shoeb, M., Weinstein, H., & Mollica, R. (2007). The Harvard Trauma Questionnaire: Adapting a cross-cultural instrument for measuring torture, trauma and posttraumatic stress disorder in Iraqi refugees. International Journal of Social Psychiatry, 53(5), 447-463.

Steel, Z., Chey, T., Silove, D., Marnane, C., Bryant, R. A., & Van Ommeren, M. (2009). Association of torture and other potentially traumatic events with mental health outcomes among populations exposed to mass conflict and displacement: a systematic review and meta-analysis. Jama, 302(5), 537-549.

Stenmark, H., Catani, C., Neuner, F., Elbert, T., & Holen, A. (2013). Treating PTSD in refugees and asylum seekers within the general health care system. A randomized controlled multicenter study. Behaviour research and therapy,51(10), 641-647.

UNICEF, (2011). Inter-Agency Guide to the Evaluation of Psychosocial Programming in Emergencies. New York: United Nations Childrens Fund.

UN High Commissioner for Refugees (UNHCR), (2012).

The state of the world’s refugees: In search of solidairy. Retrieved from http://www.refworld.org/ docid/5100fec32.html van de Put W. A. & Eisenbruch M. (2004). Internally displaced cambodians: Healing trauma in communities.

In K. E. Miller & L. M. Rasco (Eds.), The mental health of refugees: Ecological approaches to healing and adaptation. (p. 133-159). London: Lawrence Erlbaum Associates Publishers Weine, S. M., Vojvoda, D., Becker, D. F., McGlashan, T. H., Hodzic, E., Laub, D., ... & Lazrove, S. (1998).

PTSD symptoms in Bosnian refugees 1 year after resettlement in the United States. American Journal of Psychiatry, 155(4), 562-564.

Wilson. J. (2007). Cross-cultural assessment of psychological trauma and stress. In J. Wilson & C. Tang (Eds.), The lens of culture: Theoretical and conceptual perspectives in the assessment of psychological trauma and PTSD (p. 3-30). New York, US: Springer.

Cultural and Social

104

PSI ISSUE V

2015

Coming to Canada: Investigating the Effects of Cultural Saliency Among Bicultural sub-Saharan Africans Marilyn N. Ahun* Supervisors: Régine Debrosse & Donald M. Taylor *email: marilyn.ahun@mail.mcgill.ca

Abstract Our research sought to expand the literature on cultural saliency by examining how cultural saliency and values affected the motivations of bicultural individuals. We investigated how the value of meaning in life in Western and sub-Saharan African cultures and changing cultural contexts affected bicultural sub-Saharan African immigrants’ motives for attending university. We hypothesized that participants would associate meaning in life with interdependent motives when primed with sub-Saharan cultures, but not when primed with Canadian culture. Additionally, we hypothesized that meaning in life would be associated with independent motives when participants were primed with Canadian culture, but not sub-Saharan cultures. Participants did not associate meaning in life with interdependent or independent motives when primed with sub-Saharan cultures, however, they did associate meaning in life with independent and interdependent motives when primed with Canadian culture. The overall results of this study suggest that cultural context and meaning in life interact in predicting both independent and interdependent motives for attending university.

Keywords: bicultural; sub-Saharan Africa; meaning in life; motives Acknowledgements I would like to acknowledge my Ph.D. supervisor (Régine Debrosse), Professor (Dr. Donald Taylor) and the entire team of the Intergroup Relations and Aboriginal People’s Lab.

105

Cultural and Social

PSI ISSUE V Introduction A bicultural individual is someone who has internalized two cultures to such an extent that both cultures are readily available to guide them as they navigate their environment (Hong, Morris, Chiu & BenetMartinez, 2000). As more and more people migrate and are exposed to the cultures of their new countries, it is important to understand the effect of alternating between contexts associated with one culture or the other on the thoughts and behaviors of these migrant groups. Many studies have investigated the effect of alternating between cultural contexts on the thoughts and behaviors of bicultural individuals belonging to immigrant groups (Hong et al, 2000; Benet-Martinez, Leu, Lee & Morris, 2002; Markus & Kitayama, 1991). To date, however, few have examined the effect of cultural saliency on a critical aspect of bicultural individuals’ adjustment: motivation. We know that values affect our motivations; that is, the biological, social, and cognitive forces that direct our behaviour (Fulmer & Frijters, 2009), by acting as guiding principles in our lives, and that these values change across cultures (Schwartz, 1992). Investigating how cultural saliency effects bicultural individuals’ motivations can provide further insight into how cultural saliency and values affect motivation and expand our understanding of the behaviors of bicultural individuals.

Western cultures have been found to place a high value on independence; thus, they encourage individuals to assert themselves and to appreciate their individual differences from others (Markus & Kitayama, 1991). Sub-Saharan African cultures, on the other hand, tend to place a high value on interdependence; thus, they emphasize the importance of fitting in with and attending to others to ensure harmonious interdependence among individuals (Kamwangamalu, 1999). Having to alternate between Western and subSaharan African cultures, which are vastly different from each other, could have a significant impact on the thoughts, motivations and behaviors of bicultural sub-Saharan African immigrants. We were interested in the impact of values and changing cultural contexts on motivation. In the present study we examined the differences between cultural values in sub-Saharan Africa and Canada, how these differences affected their values, and how cultural saliency and values affected the motivations of bicultural sub-Saharan African immigrants.

end states or behaviours and guide an individual’s selection of behaviour and events (Schwartz, 1992).

Meaning in life is a value which can be described as the feeling that one’s life has a purpose, and it involves making a commitment to attain cherished goals (Kings, Hicks, Krull, & Del Gaiso, 2006). Finding meaning in life – or a purpose in life – is a basic human need that can be fulfilled through the pursuit of other types of values such as ambition, success, or honoring parents and elders.

Meaning in life is a value in itself. Nonetheless, in different cultures it is associated with a variety of value types, suggesting that whichever values associated with it are more important in those cultures.

Extrapolating from Schwartz’s (1992) findings, we expected that a culture which places high importance on interdependence, relative to a culture which places low importance on interdependence, will associate meaning in life with motives and behaviors which promote interdependence (e.g. giving back to the community, be a role model for people in my community). Likewise, a culture which places high importance on independence would be expected to associate meaning in life with motives and behaviors which promote independence (e.g. becoming an independent thinker, learn more about my interests), compared to a culture which places low importance on independence.

Associating one set of motives – either interdependence or independence – with meaning in life suggests that an individual values those specific motives for attending university. Previous research on motivation in academics has found that placing a high value on a domain leads to better performance and achievement in that domain (Osborne & Jones, 2011).

How do sub-Saharan African and Western cultures interact with the value of meaning in life? And what effect does this have on the motivations of bicultural sub-Saharan African immigrants?

Western Culture versus sub-Saharan African Culture Our research focused on bicultural sub-Saharan Africans (from West, East, Central and Southern Africa) who have also internalized a Western culture (although our paper focused on Canadian culture, other researchers also include US and Western European cultures in their definition of Western cultures). Studies on sub-Saharan African cultures have found that these cultures encourage interdependent behaviours (Kamwangamalu, 1999), whereas Western cultures (North American and Western European) have been Values and Meaning Associated with Motivation to found to encourage independent behaviors (Markus & Kitayama, 1991). Even though the independent Study versus interdependent dichotomy is a generalization Values are concepts or beliefs that pertain to desirable that cannot encompass all aspects of every culture, Cultural and Social 106

PSI ISSUE V it provides a concrete framework for understanding how cultures differ. Members of Western cultures generally strive to “maintain their independence from others by attending to the self and by discovering and expressing their unique inner attributes” (Markus & Kitayama, 1991) which may include qualities such as creativity and competitiveness. These inner attributes are a core part of the university environment, where students are encouraged to realize their individual potential to influence the world by developing their voices, following their passions, and finding themselves (Stephens, Fryberg, Markus, Johnson, & Covarrubias, 2012). The high importance placed on independence

by Western cultures suggests that members of these cultures are more likely to associate meaning in life with thoughts and behaviors that promote independence.

It is therefore expected that the independent nature of Western cultures will result in bicultural students associating meaning in life with independent motives for attending university when these cultures are made salient.

Sub-Saharan Africa is a diverse multi-cultural region. However, despite this cultural diversity, threads of underlying similarities run through the customs and value systems of various sub-Saharan societies (Kamwangamalu, 1999). Within most subSaharan societies individuals are encouraged to be interdependent, such that an individual is as dependent on his or her family and community for social, financial, and moral support as they are on him or her. This web of interdependence places the community at the center of social relations.

The interdependent characteristics that certain sub-Saharan cultures have in common can be embodied in the way children of these communities are educated.

Lloyd and Blanc’s (1996) study investigating the role of parents and extended family members in children’s schooling in sub-Saharan Africa found that the costs and investments in education were more likely to be dealt with on a larger, communal level than on a smaller scale involving just the parents or the individual child (Lloyd & Blanc, 1996). These extended family networks provide financial and social support, subsequently enabling a greater number of children to be educated in a framework where there are limited resources and economically valued alternative roles for children (Lloyd & Blanc, 1996). The high importance placed on interdependence by sub-Saharan African cultures suggests that members of these cultures are more likely to associate meaning in life with thoughts and behaviors that promote harmonious interdependence.

It is therefore expected that the interdependent nature of sub-Saharan African cultures will result in bicultural students associating meaning in life with interdependent

motives for attending university when these cultures are made salient.

The Present Study The literature provides support for the argument that Westerners are more likely to associate meaning in life with independent motives for attending university whereas individuals from sub-Saharan African cultures are more likely to associate meaning in life with interdependent motives. Research has found that the factors an individual associates with meaning in life changes across cultures (Schwartz, 1992). We expanded on these ideas by examining how cultural saliency and values affected the motives for attending university among sub-Saharan African students who have also internalized Western cultures. The arguments presented apply to the ‘West’ but for practical purposes the study will only include participants who have been exposed to Canadian culture.

In the study, sub-Saharan African biculturals were primed with either sub-Saharan African or Canadian cultures and the effect of these cultural activations and their ratings of meaning in life on their interdependent and independent motives for attending university were recorded. Based on the relevant literature concerning cultures, meaning in life, and how they affect the motives for attending university, we expected that the motives associated with meaning in life would differ in such a way that bicultural sub-Saharan African students would associate their meaning in life with interdependent motives for attending university when sub-Saharan African cultures were made salient, but not when Canadian culture was made salient. As well, we hypothesized that bicultural sub-Saharan African students would associate their meaning in life with independent motives for attending university when Canadian culture was made salient, but not when subSaharan African cultures were made salient.

Method Participants Twenty-three bicultural students who have a subSaharan African cultural background and who now attend university in Canada participated in this study.

All participants were financially compensated for their time. Fifty-seven percent were female. The mean age of participants was 20.65 years old (SD = 2.06). According to reported demographics, 100% of participants identified as being Black, 100% of participants’ parents were born in sub-Saharan Africa and 17% of the participants were born in Canada.

107

Cultural and Social

PSI ISSUE V Procedure When they entered the lab participants were randomly assigned to one of two cultural prime groups: subSaharan Africa or Canada. They were told that they were participating in a study on the goals and motives of students and that the study consisted of two tasks.

The first was a Visual Recognition Task ran by Honors students and the second was a survey on study habits which was run by a Ph.D. student.

Materials After granting consent participants completed the Visual Recognition Task and the survey. The tasks consisted of the following items: Cultural Saliency. In the Visual Recognition Task, participants were shown pictures that represented icons from Canadian and sub-Saharan African cultures depending on the group they had been assigned to.

Participants were instructed to press one button on the keyboard (‘E’) if they did not recognize the subject in the picture, and ‘I’ if they did recognize the subject in the picture to make sure that the icons were serving as real primes.

Interdependent and Independent Motives for Attending University. The items on this measure were developed by Stephens and her colleagues (2012).

Participants were prompted with the question “What do you want to get from your studies?”, and they had to rate the items on the scale in response to the question. The items were rated on a scale from 1 (strongly disagree) to 7 (strongly agree). Half of the 12 survey items reflected the motives of independence (explore my potential in many domains, expand my understanding of the world, expand my knowledge of the world, explore new interests, become an independent thinker, and learn more about my interests), and the other half reflected motives of interdependence (help my family out after I’m done with college, be a role model for people in my community, show that people with my background can do well, give back to my community, provide a better life for my own children, and bring honor to my family).

Rating of Meaning in Life. This item was taken from Schwartz’s (1992) Value Survey Instrument which explores the importance of values in a wide variety of contexts. Participants were asked to indicate the importance of ‘meaning in life (a purpose in life)’ as a guiding principle in their lives on a scale from -1 (opposed to my values) to 7 (of supreme importance).

African students would associate meaning in life with interdependent motives for attending university when primed with sub-Saharan African cultures, but not when primed with the Canadian culture. To test this hypothesis we examined the interaction between meaning in life and culture saliency condition to predict interdependent motives. The interaction between meaning in life, a continuous variable, and culture saliency condition, a discrete variable, was tested by performing a moderation model tested with a linear regression of the two variables.

The regression model did not support the hypothesis that participants would associate meaning in life with interdependent motives when primed with sub-Saharan cultures but not when primed with the Canadian culture (r = .57, p = .06). However, the interaction between meaning in life and culture saliency condition did significantly predict interdependent motives for attending university (β = -1.73, p < .05).

Testing for simple slope effects revealed that participants did not associate meaning in life with interdependent motives for attending university when primed with subSaharan African cultures (β = -.20, p = .19), but they did associate meaning in life with interdependent motives when primed with the Canadian culture (β = 1.53, p < .05) (see Figure 1).

Independent Motives The second hypothesis posited that bicultural subSaharan African students would associate meaning in life with independent motives for attending university when primed with the Canadian culture, but not when primed with sub-Saharan African cultures. To test this hypothesis we examined the interaction between meaning in life and culture saliency condition to predict independent motives for attending university.

Again, we tested the interaction between meaning in life and culture saliency condition by performing a moderation model tested with a linear regression of the two variables.

The regression model supported our hypothesis that participants would associate meaning in life with independent motives for attending university when primed with the Canadian culture, but not when primed with sub-Saharan African cultures (r = .65, p < .05).

The interaction between meaning in life and culture saliency condition was also significant in predicting independent motives for attending university (β = -2.73, p < .01). Testing for slope effects revealed that participants primed with the Canadian culture did Results associate meaning in life with independent motives for attending university (β = 2.39, p < .05), and that those Interdependent Motives primed with sub-Saharan African cultures did not The first hypothesis posited that bicultural sub-Saharan associate meaning in life with independent motives for Cultural and Social 108

PSI ISSUE V attending university (β = -.34, p = .09) (see Figure 2).

Discussion Our research examined how cultural saliency and values affected the motivations of bicultural sub-Saharan African immigrants studying in Canada. Specifically, we were interested in how cultural saliency interacted with the value of meaning in life to influence their interdependent and independent motives for attending university. We predicted that participants would associate meaning in life with interdependent motives for attending university when primed with sub-Saharan African cultures, but not when primed with Canadian culture. We also predicted that participants would associate meaning in life with independent motives for attending university when primed with Canadian culture, but not when primed with sub-Saharan African cultures. The results did not confirm the first hypothesis, but there was a significant interaction between culture saliency condition and meaning in life to predict interdependent motives. The second hypothesis was confirmed, and the results showed a significant interaction between culture saliency condition and meaning in life to predict independent motives for attending university. The overall results of this study suggest that cultural context and meaning in life interact in predicting both independent and interdependent motives to study in university.

Given that sub-Saharan cultures place a high importance on interdependence, we expected that making these cultures salient to bicultural sub-Saharan African students would result in them associating meaning in life with interdependent, but not independent, motives for attending university. Likewise, we expected participants to associate meaning in life with independent, but not interdependent, motives for attending university when primed with Canadian culture because of the high importance the Canadian culture places on independence.

Why did bicultural individuals not associate meaning in life with interdependent motives for attending university when their interdependent culture was made salient? Why did bicultural individuals associate meaning in life with interdependent motives for attending university when their independent culture was made salient? A possible answer for these questions may be that because these bicultural individuals are attending university in a Western culture, they associate attending university solely with their Western culture and not their sub-Saharan African cultures. We propose that because these students do not associate their sub-

Saharan African cultures with attending university, they did not associate meaning in life with any motives – whether interdependent or independent – with attending university when primed with sub-Saharan African cultures.

This interpretation of our findings suggests that the culture in which bicultural individuals are attending university, or engaging in any other activity, has a more significant impact on the motives they associate with meaning in life than the cultural context they are in. In other words if a bicultural individual from culture A, which places a high value on interdependence, works in and associates her job with culture B, a culture which encourages independence we hypothesize that firstly, the individual will associate meaning in life with independent and interdependent motives for working when primed with culture B. Secondly, the individual will not associate meaning in life with any motives – not even interdependent ones – for working when primed with culture A. It does not matter that culture A places a high importance on interdependence. What appears to be important is that the individual associates work with culture B, and this association has a significant impact on the motives the individual associates with meaning in life.

This study was limited due to its small sample size and its lack of control for the length of time the participants had been in contact with their sub-Saharan African cultures. However, the findings presented were significant, suggesting a strong effect of the interaction between cultural saliency and meaning in life to predict the motives of bicultural individuals. Further research on the effect of cultural saliency on the motivations of bicultural individuals could test the hypotheses presented in this discussion on other immigrant groups and expand our understanding of how the interaction of cultural saliency and meaning in life to predict motivations affects their behavior.

References Benet-Martinez, V., Leu, J., Lee, F., & Morris, M. W. (2002).

Negotiating Biculturalism: Cultural Frame Switching

in Biculturals with Oppositional Versus Compatible

Cultural Identities. Journal of Cross-Cultural

Psychology, 33(5), 492-516. DOI:10.1177/002202

2102033005005. Retrieved from:http://jcc.sagepub.

com/content/33/5/492 Fulmer, S.M. & Frijters, J.C. (2009). A Review of Self-Report

and Alternative Approaches in the Measurement of

Student Motivation. Educational Psychological

Review , 21, 219-46.

Hong, Y., Morris, M. W., Chiu, C., & Benet-Martinez, V.

(2000). Multicultural minds: A dynamic

constructivist approach to culture and cognition.

109

Cultural and Social

PSI ISSUE V

American Psychologist, 55(7), 709-720. DOI: 10.1037//0003-066X.55.7.709.

Kamwangamalu, N. M. (1999). Ubuntu in South Africa: a

sociolinguistic perspective to a pan-African concept.

Critical Arts: South-North Cultural and Media

Studies 13(2).24-41.DOI:

10.1080/02560049985310111. Retrieved from http://

dx.doi.org/10.1080/02560049985310111 Kings, L. A., Hicks, J. A., Krull, J. L. & Del Gaiso, A. K.

(2006). Positive Affect and the Experience of

Meaning in Life. Journal of Personality and

Social Psychology 90(1). 179-196. DOI: 10.1037//0022-3514.90.1.179 Lloyd, C. B. & Blanc, A. K. (1996). Childrenâ&#x20AC;&#x2122;s Schooling

in sub-Saharan Africa: The Role of Fathers, Mothers,

and Others. Population and Development Review 22(2). 265-298.Retrieved from http://jstor.org/

stable/2137435 Markus, H. R. & Kitayama, S. (1991). Culture and the Self:

Implications for Cognition, Emotion, and Motivation. Psychological Review 98(2), 224-253.

DOI:10.1037/0033-295X.98.2.224 Osborne, J. W. & Jones, B. D. (2011). Identification with

Academics and Motivation to Achieve in School:

How the Sturcutre of the Self Influences Academic Outcomes. Educational Psychology Review 23. 131 158. DOI: 10.0007/s10648-011-9151-1 Schwartz, S. H. (1992). Universals in the Content and

Structure of Values: Theoretical Advance and

Empirical Tests in 20 Countries. Advances in

Experimental Social Psychology 25(1).

Stephens, N. M., Fryberg, S. A., Markus, H. R., Johnson, C.

S., & Covarrubias, R. (2012). Unseen Disadvantage:

How American Universitiesâ&#x20AC;&#x2122; Focus on Independence

Undermines the Academic Performance of First Generation College Students. Journal of Personality

and Social Psychology 102(6). 1178-1197. DOI:

10.1037/a0027143

Cultural and Social

110

PSI ISSUE V Appendix

Figure 1. Moderation model tested with a linear regression. Interaction between meaning in life and culture saliency condition significantly predicted interdependent motives for attending university.

Figure 2. Moderation model tested with a linear regression. Interaction between meaning in life and culture saliency condition significantly predicted independent motives for attending university.

111

Cultural and Social