Jid 2017 38 issue 1 by Hogrefe

Volume 38 / Number 1 / 2017

Journal of

Individual Differences Journal of Individual Differences

Editor-in-Chief André Beauducel Associate Editors Philip J. Corr Sam Gosling Jürgen Hennig Philipp Y. Herzberg Aljoscha Neubauer Thomas Rammsayer Karl-Heinz Renner Willibald Ruch Astrid Schütz Andrzej Sekowski Jutta Stahl Martin Voracek

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Journal of

Individual Differences Volume 38, No. 1, 2017

Editor-in-Chief

Prof. Dr. Andre´ Beauducel, Institut fu¨r Psychologie, Rheinische Friedrich-Wilhelms-Universita¨t, Kaiser-Karl-Ring 9, D-53111 Bonn, Germany, Tel. +49 228 734-151, E-mail beauducel@uni-bonn.de

Associate Editors

Philip J. Corr, UK Sam Gosling, USA Ju¨rgen Hennig, Germany Philipp Y. Herzberg, Germany Aljoscha Neubauer, Austria Thomas Rammsayer, Switzerland

Karl-Heinz Renner, Germany Willibald Ruch, Switzerland Astrid Schu¨tz, Germany Andrzej Sekowski, Poland Jutta Stahl, Germany Martin Voracek, Austria

Editorial Board

Philipp L. Ackerman, USA Jose´ Bermudez, Spain Peter Borkenau, Germany John Brebner, Australia Burkhard Brocke, Germany Ian Deary, UK Richard Depue, USA Richard Ebstein, Israel Aiden P. Gregg, UK Hartmut Ha¨cker, Germany Willem B. Hofstee, The Netherlands Klaus Kubinger, Austria

Bernd Marcus, Germany Robert R. McCrae, USA Carolyn C. Morf, Switzerland Pierre Mormede, France Jaak Panksepp, USA Kurt Pawlik, Germany Robert Plomin, UK Rainer Riemann, Germany Kurt Stapf, Germany Bob Stelmack, Canada Gerhard Stemmler, Germany Jan Strelau, Poland

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Journal of Individual Differences (2017), 38(1)

Ó 2017 Hogrefe Publishing

Contents Original Articles

Ă&#x201C; 2017 Hogrefe Publishing

The Resilient Personality Prototype: Resilience as a Self-Deception Artifact? Marcus Roth and Philipp Yorck Herzberg

Personality and Memory Conformity Nicole Doughty, Helen M. Paterson, Carolyn MacCann, and Lauren A. Monds

The Effects of Age on the Interplay Between News Exposure, Political Discussion, and Political Knowledge Sabine Trepte and Josephine B. Schmitt

Grit, Basic Needs Satisfaction, and Subjective Well-Being Borae Jin and Joohan Kim

Why Does Digit Ratio Research Fail to Give Any Implication Regarding the Organizational Effect of Prenatal Androgen? Larry Au Yeung and Wai S. Tse

The General Factor of Personality Is Stronger and More Strongly Correlated With Cognitive Ability Under Instructed Faking Carolyn MacCann, Nicola Pearce, and Yixin Jiang

The Role of Distress Disclosure Tendencies in the Experience and Expression of Laboratory-Induced Sadness Jeffrey H. Kahn, Daniel W. Cox, A. Myfanwy Bakker, Julia I. Oâ&#x20AC;&#x2122;Loughlin, and Agnieszka M. Kotlarczyk

Journal of Individual Differences (2017), 38(1)

Original Article

The Resilient Personality Prototype Resilience as a Self-Deception Artifact? Marcus Roth1 and Philipp Yorck Herzberg2 1

Department of Psychology, University Duisburg-Essen, Germany

Personality Psychology and Psychological Assessment Unit, Helmut Schmidt University of the Federal Armed Forces Hamburg, Germany

Abstract: Typologies based on Big Five questionnaire data always include the resilient prototype, which is defined by low scores on neuroticism and above-average scores on extraversion, agreeableness, and conscientiousness. When measurement of the criterion domains is based on self-reports, this type evidences superior psychological adjustment and well-being in nearly all domains. In the present study, we tested whether the personality profile constituting the resilient prototype is an artifact of self-deceptive enhancement in answering questionnaires. Therefore, we contrasted self-reports of resilients with objective data that we collected during an actual stressful event. A total of 112 pupils (15–19 years) were examined via questionnaires and asked to complete a speech task in front of a video camera. Stress reactions were measured by self-reports as well as by nonverbal behavior, achievement, and physiological responding. Results showed that resilients differed from the other personality prototypes only when self-reports (coping, affectivity) were used. By contrast, no differences between personality prototypes emerged when the three objective stress indicators (speech performance, behavior, and physiological arousal) were used. These findings call into question the superior psychological adjustment attributed to the resilient prototype and stress the necessity of multimethod assessment in personality prototype research. Keywords: personality types, Big Five, resilience, self-deception, social desirability

Researchers have repeatedly argued that personality science’s predominant focus on variable-centered approaches, such as the Five-Factor model or Big Five (McCrae & Costa, 2008), should be complemented by a person-centered approach (Allport, 1937; Asendorpf, Caspi, & Hofstee, 2002). The latter approach, also referred to as the personality prototype approach, is concerned with the particular configuration of attributes within individuals. Clustering procedures are applied to sets of quantitative trait dimensions with the purpose of identifying discrete personality prototypes that reflect unique configurations of traits. This prototype strategy moves from quantitative dimensions to categorical classifications. Although a number of contemporary typologies exist, the current study focused on the one that has received the most attention in scientific personality psychology: the personality prototypes that are based on the Big Five or Five-Factor model. Three major personality prototypes could consistently be identified in recent studies. The first, Resilients, show a generally well-adjusted profile with below-average neuroticism and above-average scores on extraversion, agreeableness, and conscientiousness. Overcontrollers score high on neuroticism and low on extraversion, whereas Undercontrollers yield high neuroticism scores and low scores on conscientiousness and agreeableness (Chapman & Goldberg, 2011; Herzberg & Ó 2017 Hogrefe Publishing

Roth, 2006). As recently shown by Specht, Luhmann, and Geiser (2014), these prototypes are highly consistent across gender, age, and time. Research on personality prototypes has provided a nomological network for each of the three personality types (for an overview, see Herzberg & Roth, 2006): Resilient type individuals are characterized by selfconfidence, academic achievement, success in relationships, and better self-rated health; those assigned to the Overcontrolled type evidence shyness and social withdrawal as well as high prejudice; and individuals assigned to the undercontrolled type are characterized by delinquency, aggression, and poor school and academic achievement. In sum, various studies have demonstrated that FFM-based personality types are reliably associated with different outcomes such as school conduct and school performance, externalizing and internalizing disorders, social attitudes, health, and even accident proneness (Hart, Atkins, & Fegley, 2003; Herzberg, 2009; Herzberg & Hoyer, 2009; Kinnunen et al., 2012; Robins, John, & Caspi, 1998; Roth & Liebe, 2011; Roth & von Collani, 2007). In the vast majority of studies, the resilient profile has been associated with positive outcomes. Across these studies, the resilient prototype appears generally well-adjusted and has an intermediate position on the continuum of Journal of Individual Differences (2017), 38(1), 1–11 DOI: 10.1027/1614-0001/a000216

psychological adjustment, whereas the over- and undercontrolled prototype show poor psychological adjustment. These unparalleled positive evaluations of the resilient prototype give rise to the suspicion that this personality profile is highly influenced by social desirability. Socially desirable responding (SDR) is typically defined as the tendency to give overly positive self-descriptions (Paulhus, 2002). There has been controversy regarding whether social desirability scales assess a response style (i.e., impression management), that is, a bias that may distort selfreports (self-deceptive enhancement), or whether they assess a substantively meaningful trait that is closely related to certain personality traits (e.g., McCrae & Costa, 1983; Smith & Ellingson, 2002). The influence of SDR on personality questionnaires has been studied extensively since the 1960s, and researchers have concluded that response styles have a negligible effect on personality assessments, at least in research contexts (Caldwell-Andrews, Baer, & Berry, 2000; Helmes, 2000). As a result, most personality researchers no longer worry about whether response styles pose a serious threat to the validity of self-report ratings (Konstabel, Aavik, & Allik, 2006; Kurtz, Tarquini, & Iobst, 2008; Schimmack, Böckenholt, & Reisenzein, 2002). However, neither the response style nor the stable disposition interpretation of social desirability was the focus of the current study. Instead, we were interested in examining the influence of social desirability on the personality prototype approach. Specifically, we were interested in the question of whether or not the overwhelmingly positive psychological adjustment of the resilient type found in almost all life domains is an artifact of self-deceptive enhancement. We hypothesized that a certain number of people are prone to a self-favoring bias when responding to self-report measures. A self-favoring bias means that people view themselves and their abilities in an overly positive light. Individuals with such self-deceptive enhancement tendencies also score high on measures of self-esteem and adjustment measures (Paulhus & Reid, 1991). We began by noticing that most of the studies summarized above relied on self-report measures (most frequently, the NEO Five-Factor Inventory [NEO-FFI]; Costa & McCrae, 1992) to measure personality and that the derivation of the prototypes was based on these self-report measures. Roth and Herzberg (2007) examined the associations between the two forms of SDR (as a response style and as self-deception) and the personality prototypes with the Balanced Inventory of Desirable Responding (BIDR; Paulhus, 1994). The BIDR is widely used to measure the two components of social desirability: impression management (IM) and self-deceptive enhancement (SDE). The highest scores on the SDE scale have been reported for the resilient prototype, followed by the overcontrolled and undercontrolled prototypes. The resilient and Journal of Individual Differences (2017), 38(1), 1–11

M. Roth & P. Y. Herzberg, Resilient Type

overcontrolled prototypes have shown the same level of impression management on the IM scale, with only slight differences from the undercontrolled prototype. The effect sizes indicate that self-deceptive enhancement distinguishes between the prototypes to a much larger extent than impression management (η2 = .26 vs. .05). This provides evidence that the resilient prototype is prone to selfdeceptive enhancement when answering self-report measures. This may also explain the favorable profile of the resilient prototype described above. Hence, we should ask whether the good adjustment of the resilients can be attributed to self-deceptive enhancement when self-reports are used as criterion measures. Thus, the next step in investigating the hypothesis that self-deceptive enhancement partly explains the positive outcomes and the impressive adjustment of the resilient prototype would be to use criterion measures that are not distorted by self-deceptive enhancement. Indeed, most of the measures used in prototype research as outcomes have been self-report measures (for exceptions, see Hart, Burock, London, Atkins, & Bonilla-Santiago, 2005; Herzberg, 2009). This line of reasoning was supported by a study that showed that resilients are not the best adjusted group when either objective criteria or criteria focusing on specific behavior (where the self-favoring bias is minimized) were used. Herzberg (2009) analyzed the relation between prototypes that were based on the Big Five and problematic driving behavior. Different kinds of aberrant driving behavior were assessed by employing official driving records and self-reports of the number of accidents, number of demerit points, and traffic fines received. Although these objective criteria are based on self-reports, many studies have confirmed that there is a fairly good correspondence between self-reported accidents and official records or accident statistics (Klen & Ojanen, 1998; McGwin, Owsley, & Ball, 1998). No matter whether the criteria were official driving records or self-reports of specific traffic behavior, this study showed for the first time that resilients are not the best adjusted group in this regard but rather constitute a medium risk group. One conclusion from this study is that there is a need to evaluate the resilient prototype by employing more “objective” criteria that are not affected by self-deceptive enhancement. Because resilients are portrayed as having high academic performance, low anxiety, and high selfconfidence (see above), they can be expected to have the ability to perform an academic task under stressful conditions. Therefore, resilients should show better performance and should experience lower stress reactions. However, to determine whether the positive view of the resilients is actually justified – regardless of any self-deceptions associated with self-reports – self-reports of the Big Five types should be contrasted with objective data. Ó 2017 Hogrefe Publishing

M. Roth & P. Y. Herzberg, Resilient Type

Therefore, in the present study, we tested whether the resilient type would actually demonstrate a resilience to stress. Thereby, we contrasted self-reports on questionnaires with actual behavior during a stressful event. Besides self-reports, stress reactions were measured with the objective indicators, nonverbal behavior, achievement, and physiological responding. We hypothesized that resilients would be the best adjusted group only when self-reports were used. However, when using objective outcomes that are not affected by self-deception, we expected that the resilients would not differ from the other types. Of course, psychophysiological indicators are widely known to show low correlation with self-reported measures. However, in the present study psychophysiological measures were only one data source with which selfreports were compared. Additional to these measures we included actual behavior observations as well as achievement data. The significance level was predefined as p = .05.

Method Participants The sample was recruited from high schools in Leipzig (Germany). Pupils were invited to take part in a “study dealing with stress and coping.” The participants were promised a reward (€24) for their participation, and they were assured of the confidentiality and anonymity of the data. A total of 112 pupils (56.3% female, 43.8% male) between the ages of 15 and 19 years (M = 16.8, SD = 0.8) took part in the study.

Procedure Participants were investigated twice at intervals of about 1 month. During the first session, participants answered some questionnaires including the NEO-FFI and the COPE (Coping Orientations to Problems Experienced, see below) in groups. The second session was arranged individually: On arrival, sensors and electrodes for measuring the physiological variables were attached. The participants then watched calming images of nature that were presented on the screen for 10 min. During this period, the baseline measures of the physiological variables were taken (note that all physiological measures were taken with the participants standing up). After this period, the participants indicated the extent of their negative affect with the Positive and Negative Affect Schedule (PANAS-NA, baseline measurement of negative affect). Afterwards, participants were given the following instructions for their speech: “This experiment analyzes how well Ó 2017 Hogrefe Publishing

you are able to comprehend and present a specialized text under time pressure. This ability is an important prerequisite for successful academic studies at a university. The experiment will proceed as follows: You will first read and prepare the text for 10 min. Then you will orally present the contents of this text for 3 min. Your speech will be videotaped and later analyzed by experts. Please try to deliver a comprehensive and well-structured speech, speaking for the full 3 min. Note that during the speech, you are not allowed to use the text or the notes you made.” Then, participants were allowed to prepare for 10 min so that they could read the text and think about the presentation. The text was concerned with the history of health effects caused by coal mining. The task was very difficult because the text to be presented included many details (total length: 1,570 words). The 3-min presentation phase immediately followed the preparation phase. The participants were instructed to remain in a standing position during both the preparation and presentation phases. To maximize the evaluative nature of the task, a video camera was positioned in front of the participants. After delivering their speech, participants again indicated their emotions (PANAS-NA). Afterwards, participants were informed about the purpose of the study, especially about the fact that the study was not concerned with analyzing their ability to study at a university. The experimenter then asked the participants not to discuss the study with classmates.

Measures Personality Dimensions The Big Five dimensions (Neuroticism, Extraversion, Openness to Experience, Agreeableness, and Conscientiousness) were assessed using the NEO Five Factor Inventory (NEO-FFI) by Costa and McCrae (1992). The NEO-FFI consists of 60 items. Each scale comprises 12 items. We used the German version of the NEO-FFI by Borkenau and Ostendorf (2008). The reliability in the present study ranged from α = .71 for Openness to α = .85 for Neuroticism. Coping Strategies The Coping Orientations to Problems Experienced (COPE) by Carver, Scheier, and Weintraub (1989; German version by Kälin, 1994) is a 60-item self-report questionnaire that examines 15 ways of coping, each containing 4 items. Subjects indicate what they usually do and feel when they experience stressful events. For the present study, we chose only the coping strategies that bore at least a theoretical relation to the speech task. The scales that measured coping strategies that were not used in the present task (e.g., substance use, religious coping, use of instrumental Journal of Individual Differences (2017), 38(1), 1–11

social support) were not implemented. The scales that were analyzed in this study were (Cronbach’s α values in the present sample are presented in parentheses): Acceptance (α = .82), Behavioral Disengagement (α = .80), Focus on Venting and Emotions (α = .78), Planning (α = .75), Active Coping (α = .64), Positive Reinterpretation and Growth (α = .70), Restraint (α = .53), and Suppression of Competing Activities (α = .73). Negative Affect To assess negative mood at baseline and after the speech, we used the Negative Affect (NA) subscale from the 20-item Positive and Negative Affect Schedule (PANAS) by Watson, Clark, and Tellegen (1988; German version by Krohne, Egloff, Kohlmann, & Tausch, 1996). The NA subscale measures affective experience on the basis of presented adjectives (e.g., “angry”). Each item is rated on a 5-point scale ranging from 1 = very slightly or not at all to 5 = extremely. In the present sample, the internal reliabilities (Cronbach’s α) of the PANAS-NA were α = .84 (baseline) and α = .90 (posttest). Physiological Responding We selected three measures for assessing physiological activity relevant to emotional responding. All data was recorded with the Portable Biosignal-Recorder VARIOPORT-B (with a sampling rate of 512 Hz) from Becker Meditec (Karlsruhe, Germany). (1) Heart rate (HR). The heart rate measure was derived from an ECG signal that was recorded by three pregelled Ag/AgCl electrodes that were placed on the subjects’ torsos. Heart rate is defined by the number of heart beats per minute and was calculated by a computer algorithm using the distance between the peaks of the R waves in the ECG curve. The change in heart rate depends on the activity of the autonomous nervous system, whereas an increase typically indicates an increase in physiological activation and therefore a stronger stress response. (2) Skin conductance level (SCL). The exosomatic measure of electrodermal activity was realized via two Ag/AgCl electrodes (1.0 cm2, filled with EDA paste of 0.5% NaCl) that were attached to the thenar and hypothenar muscles of the nondominant hand. The conductance level was recorded while a weak constant voltage was administered. The conductance level depends on the sympathetic nervous system with increases indicating an increase in physiological arousal. (3) Finger temperature (FT). A temperature sensor attached to the distal phalange of the ring finger recorded temperature in degrees Celsius. Finger temperature depends on the sympathetic nervous system with decreases indicating increases in physiological arousal. Journal of Individual Differences (2017), 38(1), 1–11

M. Roth & P. Y. Herzberg, Resilient Type

These measures were selected because they are able to provide a broad index of physiological activity and have been used frequently in previous studies (e.g., Egloff, Schmukle, Burns, & Schwerdtfeger, 2006; Gross, 1998). The measures SCL and FT detect activation of the sympathetic nervous system, whereas HR is influenced by the sympathetic as well as the parasympathetic nervous system. All three variables were continuously recorded during the baseline, preparation, and presentation phases of the experiment. The Varioport output file contained per-minute aggregated data consisting of means, standard deviations, minima, maxima, and numbers of measures. The data were checked for extremes, and a few isolated critical measures (± 3 standard deviations) excluded. Deletions and missing values were replaced with means that came from the other intervals of the respective phase. To estimate the reliability of the physiological measures, we calculated correlations between the physiological data exemplary of the fourth minute and the eighth minute for HR, SCL, and FT during the baseline period. The resulting correlation coefficients were as follows (r = product moment correlation; τ = Kendall’s tau): HR: r = .95, τ = .80; SCL: r = .88, τ = .74; FT: r = .93, τ = .81. The baseline data were used to compute individual change scores for each physiological variable by subtracting the baseline score from the scores of the preparation and speech phases, respectively. Stress Reactions A measure of the observable stress reaction was obtained by developing a category coding system for analyzing the video tapes of the speeches. On the basis of behavior coding systems for people with social phobia by Fydrich, Chambless, Perry, Buergener, and Beazley (1998), Monti et al. (1984), Rapee and Hayman (1996), and Trower (1980), we differentiated 17 (verbal and nonverbal) behavioral stress reactions. These reactions belong to four umbrella categories: gaze (e.g., blinking often, changes in viewing direction), speech (e.g., harrumphing, use of filler words), posture/orienting (e.g., changing posture often, holding the shoulders up), and self-manipulation (e.g., fiddling around with clothes, scratching oneself). The 3-min speech was divided into 6 periods (of 30 s each) for which the videotapes should be rated. Two trained student judges who were unaware of the scores on the other measures coded the behavior of the participants using the videotapes by signing the occurrence of the 17 behavior patterns within each 30-s time period. Hence, the maximal score that could theoretically be reached by a participant was (17 6) 102 stress reactions. In the present sample, the total number of stress reactions observed during the speech ranged from 12 to 48 (M = 28.6, SD = 7.0). Interrater reliability (based on 12 videotapes coded by both judges for Ó 2017 Hogrefe Publishing

M. Roth & P. Y. Herzberg, Resilient Type

all subjects; two-way-model; interclass correlation [ICC] with absolute type agreement) was r = .85. Speech Performance As a measure of speech performance, we quantified the narration of the text during the speech task. To do so, we subdivided the text into 13 units of meaning, which represented the main ideas of the text. For the reproduction of a main idea, two points were assigned (e.g., onset of search for coal in the 16th century due to scarcity of wood supply). In addition, we extracted 58 pieces of side information representing details that belonged to the main units of meaning (e.g., miners digging tunnels and going underground). Reproduction of a piece of side information was given 1 point. Hence, the maximal score that could theoretically be reached by a participant was 84 reproduction points. Three trained student judges who were unaware of the scores on the other measures rated the videotapes. In the present sample, the total number of reproduction points ranged from 8 to 30 (M = 19.7, SD = 5.1). Interrater reliability (based on 10 videotapes that were coded by all three judgers) was r = .72 (averaged above the three correlations).

Assignment of Individuals to the Big-Five-Based Prototypes Because the conventional sample-based cluster approach that is usually utilized in personality prototype research (Ward’s method followed by k-means clustering) is very sensitive to sample size and composition, sample-specific profiles were compiled for each data set and varied to a large extent across the different samples. Herzberg and Roth (2006) proposed an alternative approach for assigning individuals to prototypes using discriminant function algorithms, which are inferred from cluster results from a large representative sample. An advantage of this algorithm-based approach lies in its ability to mitigate unrepresentative sample compositions. For instance, the common practice of using undergraduate student samples in personality prototype research raises the probability of overrepresenting the resilient and underrepresenting the undercontrolled prototypes. In addition, the algorithm-based approach reduces the heterogeneity of personality prototypes in different samples, making them more comparable. Therefore, in the present study, individuals were thus assigned prototype 1

Figure 1. Personality prototypes (algorithm-based assignment) characterized by their Big Five z-score pattern.

membership by applying discriminant functions inferred from the three-cluster results of a large and representative adolescent sample (N = 888) to their Big Five values.1 Individual profiles were assigned to the best-fitting cluster center of the representative adolescent sample according to their Euclidean distance using the three clusters of the adolescent sample as the initial cluster centers for the nonhierarchical k-means clustering procedure (in which no iterative procedure was conducted, of course). In so doing, 44% (n = 49) were assigned to the resilient type, 30% (n = 34) to the overcontrolled type, and 26% (n = 29) to the undercontrolled type. Type frequencies in the present sample did not differ from those in the representative adolescent sample, w2(2) = 0.94, p = .625.

Results Description of Prototypes Figure 1 presents the pattern of mean z-scores on the five factors for the three-cluster solution. The first cluster clearly corresponds to the solutions found by other researchers. This cluster, which is characterized by low scores on Neuroticism and above-average scores on Extraversion, Agreeableness, and Conscientiousness, clearly resembles the resilient type that was found in various other studies. The second cluster was identified as the overcontrolled type as it had the lowest scores on extraversion and openness. The third cluster is characterized primarily by high scores on neuroticism and openness and low scores on

Because the representative sample used by Herzberg and Roth (2006) consisted of adults (18–96 years), classification criteria for the present study were created on a representative sample of 888 adolescents between the ages of 15 and 19 years (M = 15.8, SD = 0.6) who completed the NEO-FFI. This sample was 47% male (n = 421) and 53% female (n = 467). The sample was recruited from randomly selected schools in Leipzig and Dresden (Germany). The prototypes were derived by applying a two-step clustering procedure, which combines the hierarchical analysis method by Ward (1963) with the nonhierarchical k-means clustering procedure (MacQueen, 1967) in order to optimize the cluster solutions. This procedure was described by Blashfield and Aldenderfer (1988) and has been used in several subsequent studies that have applied the prototype approach (cf. Asendorpf, Borkenau, Ostendorf, & van Aken, 2001). On the basis of previous studies, we chose the three-cluster solution, using the IBM SPSS software.

Ó 2017 Hogrefe Publishing

Journal of Individual Differences (2017), 38(1), 1–11

M. Roth & P. Y. Herzberg, Resilient Type

Table 1. Comparisons of self-reported coping strategies for the three personality types: Descriptive statistics and MANOVA results Resilients Coping strategies

Overcontrollers

Undercontrollers

MANOVA p

η2

0.45

.638

.01

–

10.75

< .000

.17

U, O < R

.371

.02

–

6.16

.003

.11

R > U, O

11.07

< .000

.17

R>O>U

5.45

.006

.09

R>O

0.67

0.61

.546

.01

–

0.88

5.18

.007

.09

R > O, U

Acceptance

3.34

0.74

3.17

0.85

3.21

0.92

Behavioral disengagement Focus on and venting of emotions Planning

1.86

0.54

2.30

0.66

2.63

0.98

2.90

0.67

3.07

0.90

3.18

0.98

1.00

3.72

0.63

3.20

0.65

3.54

0.68

Active coping

3.64

0.50

3.33

0.56

3.00

0.70

Positive reinterpretation and growth Restraint

3.74

0.57

3.27

0.55

3.50

0.77

3.26

0.57

3.11

0.54

3.18

3.33

0.57

3.02

0.62

2.82

Suppression of competing activities

Post hoca

Note. aLSD (p .05; two-tailed).

agreeableness and conscientiousness. These profiles correspond quite accurately to the undercontrolled type found by other researchers.

Differences in Coping Strategies Between the Personality Types Differences in self-reported coping strategies were tested with a MANOVA (we used IBM SPSS software) with the cluster group as the independent variable, followed by univariate comparisons with post hoc tests. A strong overall group effect was found, F(16, 196) = 3.74, p < .001, η2p = .20. As shown by the results of the univariate comparisons given in Table 1, the resilients were distinguishable from the other two personality types because the resilients had the highest scores on Planning, Active Coping, and Suppression of competing activities, as well as the lowest scores on behavioral disengagement. According to Cohen’s (1988) specifications, these differences can be considered medium to large.

Differences Between the Types in Variables Measured During the Speech Task Negative Affect Negative affect was measured via self-report (PANAS-NA) before (directly after the period of rest) and after participants completed the speech task. Means and standard deviations for the two times of measurement are displayed separately for each type in Table 2. To test for differences 2

between types and time of measurement, we computed a repeated-measures ANOVA, which revealed a significant main effect of type, F(2, 109) = 6.35, p = .002, η2p = .10, and time, F(1, 109) = 19.54, p < .001, η2p = .15, as well as a significant interaction effect, F(2, 109) = 5.83, p = .004, η2p = .10. As shown in Figure 2, negative affect showed a large increase in overcontrollers, F(1, 33) = 6.22, p = .018, η2p = .16, and undercontrollers, F(1, 28) = 14.21, p = .001, η2p = .34, whereas the negative affectivity of the resilient type remained stable over time and was not negatively affected by the speech task, F(1, 48) = .038, p = .847, η2p = .00. Physiological Responding The physiological variables were also analyzed with repeated-measures ANOVAs with time (preparation period vs. speech period) as a within-subjects factor and personality type as a between-subjects factor. To do so, we calculated difference scores (Δ) by subtracting the baseline scores from the preparation-period scores or speech-period scores, respectively. The descriptive statistics are presented in Table 2 and illustrated in Figure 3.2 As expected, the main effect of the time factor on heart rate (HR) showed an increase from the preparation period to the speech period in general, F(1, 95) = 317.78, p < .001, η2p = .77, and the main effect of time on finger temperature (FT) showed a decrease, F(1, 109) = 117.04, p < .001, η2p = .52, both indicating a clear increase in physiological arousal in the speech period. Skin conductance level (SCL) showed no main effect of time, F(1, 99) = 3.68, p = .058, η2p = .04. Main effects of the personality type factor were not detected for HR, F(2, 95) = 1.69, p = .190, η2p = .03; FT, F(2, 109) = 0.22, p = .804, η2p = .00; or SCL, F(2, 99) = 0.44, p = .644, η2p = .01. There were no

As tested initially by ANOVAs, no differences between types were found in the baseline scores of the physiological measures; HR: F(2, 109) = 1.07, p = .345; SCL: F(2, 109) = 0.23, p = .795; FT: F(2, 109) = 1.29, p = .279.

Journal of Individual Differences (2017), 38(1), 1–11

Ó 2017 Hogrefe Publishing

M. Roth & P. Y. Herzberg, Resilient Type

Table 2. Descriptive statistics for the variables measured in the speech task, presented by personality type and time of measurement Resilients

Overcontrollers

Undercontrollers

Before speech task

1.38

0.43

1.47

0.53

1.60

0.50

After speech task

1.40

0.48

1.71

0.65

2.01

0.83

78.76

10.74

81.86

11.50

78.24

10.75

Negative affect (PANAS-NA)

Heart rate (in bpm) Baseline Preparation period Speech period Δ Preparation perioda Δ Speech perioda

85.82

9.94

87.60

11.88

83.88

12.14

102.07

14.70

100.91

12.60

102.94

18.25

6.86

5.25

5.27

5.11

5.27

6.35

23.51

11.08

18.98

8.04

24.40

10.64

Skin conductance level (in μS) Baseline

2.46

0.75

2.54

0.67

2.42

0.69

Preparation period

2.53

0.66

2.67

0.58

2.37

0.63

2.48

0.62

2.64

0.53

2.37

0.60

0.08

0.38

0.13

0.51

0.03

0.55

0.01

0.45

0.07

0.62

0.02

0.58

Speech period Δ Preparation period

Δ Speech perioda Finger temperature (in °C) Baseline

32.35

4.32

31.10

5.49

30.52

5.97

Preparation period

29.84

4.77

28.58

6.95

28.19

6.20

Speech period

26.46

5.54

25.70

6.73

25.73

7.12

Δ Preparation perioda

2.51

3.45

2.52

4.08

2.33

3.17

Δ Speech perioda

5.89

5.29

5.40

5.27

4.80

5.24

27.68

6.95

29.48

6.36

28.97

7.76

19.69

4.23

19.53

5.80

19.72

5.09

Stress reactions Total number (during speech) Speech performance Number of reproductions (during speech)

Note. aΔ = Difference scores were computed as the difference from the baseline condition (period of rest).

Stress Reactions We computed an ANOVA to compare the number of observable behavioral stress reactions obtained during the 3-min speech between the personality types. No significant differences were found between the clusters, F(2, 109) = 0.98, p = .377, η2p = .02 (see Table 2 for descriptive statistics).

Figure 2. Negative Affect (PANAS-NA) before and after the speech task by prototypes.

interaction effects between time and type; HR: F(2, 95) = 2.63, p = .077, η2p = .05; FT: F(2, 109) = 1.05, p = .355, η2p = .02; SCL: F(2, 99) = 0.98, p = .377, η2p = .02. The lack of interactions indicated that we can conclude only that the speech task caused an increase in arousal and it did not differ between the three types. Ó 2017 Hogrefe Publishing

Speech Performance Comparisons of the number of reproductions of meaningful pieces of information in the text as an index of speech performance were analyzed using an ANOVA. Again, no significant differences between the personality types were detected, F(2, 109) = 0.64, p = .527, η2p = .01 (see Table 2 for descriptive statistics).

Discussion In the present paper, we focused on the validity of the resilient prototype. This personality type is primarily defined by Journal of Individual Differences (2017), 38(1), 1–11

M. Roth & P. Y. Herzberg, Resilient Type

Figure 3. Mean scores of physiological variables in the preparation period and during the speech task by personality type (all scores were computed as differences from the baseline condition).

low scores on neuroticism and high scores on conscientiousness and agreeableness. Because the resilient personality profile can be described as highly socially desirable and is usually based on self-reports, we suspected that selfdeception plays an important role in constituting this prototype and the corresponding outstanding adjustment of this type. Previous studies by Roth and Herzberg (2007) also provided support for this assertion as they found that resilients had heightened scores in self-deceptive enhancement measured via the BIDR (Paulhus, 1994). Resilients have also been shown to be the best adjusted and have demonstrated proper functioning in nearly all domains when these domains were also measured by self-reports. By contrast, when official records or self-reports of specific behaviors were used instead, resilients turned out to be only moderately adjusted. In sum, these findings gave rise to the question of whether the resilient type conceivably represents the mere formation of a group of individuals who tend to respond to items in a self-deceptive manner. To explore this contention, we examined the stress resilience of the resilient type using a stress paradigm in which participants had to present a text in front of a video camera. Stress reactions were measured with objective indicators and contrasted with self-reports on questionnaires. As shown by our results, resilients appeared to cope well with stressful events when they answered the COPE questionnaire during the first part of our study: As a general course of action in light of stressful events, they reported the lowest extent of behavioral disengagement and the highest degrees of active coping, planning, and the suppression of competing activities compared with the other types. Journal of Individual Differences (2017), 38(1), 1â&#x20AC;&#x201C;11

However, when confronted with an actual stressful event, this self-reported stress resilience could not be observed when measured with objective indicators. In our study, resilients experienced the same stress loading as overand undercontrollers. This could be shown in their nonverbal behavior as well as in their achievement performance under stress (based on their verbal reproductions during speech). Furthermore, psychophysiological responding under stress did not differ between the personality types. However, the last result should not be overinterpreted given the fact that psychophysiological indicators are widely known to show only low correlations with selfreported measures. In addition, physiological variables cannot be unambiguously interpreted because these reactions are unspecific and can vary in meaning between subjects. Therefore, we interpreted only the fact that no differences were found in the physiological stress measures in the context of the corresponding findings from the behavioral data and achievement performance. In all of these kinds of data, no differences in stress reactions were observed between the types. Again, the only indication of stress resilience in the resilient group was found in the self-reports: resilientsâ&#x20AC;&#x2122; self-reported negative affectivity was not affected by the stressful event, whereas a large increase in negative activity occurred in over- and undercontrollers, indicating a high burden caused by the speech task. However, as an alternative explanation, it could be also be conceivable, that the discrepancy between reporting good coping capabilities and showing elevated levels of physiological reactions in the resilients may be a repressing Ă&#x201C; 2017 Hogrefe Publishing

M. Roth & P. Y. Herzberg, Resilient Type

coping style termed affective-autonomic response discrepancy (AARD). AARD is defined as occurring when participants report relatively little negative affect during stressful laboratory tasks while simultaneously evidencing heightened physiological responses (see Coifman, Bonanno, Ray, & Gross, 2007, p. 745).3 The tendency to direct attention away from negative affective experiences in the presence of a stressor is assumed to promote resilience following aversive events (Coifman et al., 2007). This would also be in line with the slightly lower level of focusing on and venting of emotions as reported by the resilients in the present study (Table 1). Therefore, the further exploration of AARD in context with resilient type patterns could be a productive approach in future research. In the present study, we were able to show that when the data were based on self-reports, resilients proved to be stress resilient and well-adjusted, but beyond these selfreports, resilients did not differ from other types with respect to stress resilience. Therefore, the findings of our study can be interpreted as further evidence for the validity of our suspicions as the resilient type appears to be an artifact of a self-deceptive answering style – at least when its classification is based on self-reports only. Of course, it would be premature to reject the Big-Five-based typology in its entirety based only on the findings of our study. To provide further confirmation of our findings, more studies need to use objective behavioral measures to validate the resilient prototype. In addition, the typological approach to personality would greatly profit from alternative classification strategies that are not exclusively based on self-reports. In order to ensure that the NEO types actually represent personality types (and not various types of questionnaire response styles), it appears necessary for future research to look toward validating personality types by employing objective personality tests. The current study has several limitations that need to be mentioned. The first is that the sample size was small; therefore, statistical power might have been too low to observe subtler differences in physiological variables (type II error). Second, only self-reports were used to determine the personality prototypes. As a result, for example, the proportion of individuals classified as resilients might be overestimated. In studies in which other reports of the Big Five traits were used also found the typical resilient profile and found “positive” outcomes for the resilient type (e.g., Rammstedt, Riemann, Angleitner, & Borkenau, 2004). In the Rammstedt et al. (2004) study, the three

prototypes could be clearly identified in the self-reports only, whereas only the Resilient prototype could be replicated with the ratings by others. The analysis of cross-data consistency revealed only moderate agreement in assigning individual subjects to types. The findings suggest that personality types depend strongly on personality measures and informants. However, the fact that resilients were also found in other reports does not contradict our assertion that self-reported resilients are prone to self-deception. As shown by Altmann, Sierau, and Roth (2013), interrater agreement in the Big Five type assignment between self-ratings and partner ratings was very small (on average: r = .20). Hence, we have to start from the premise that self-reported resilients are not the same group as resilients classified on the basis of other ratings. Regarding this point, it is again necessary to conduct further studies in which the two resilient groups can be differentiated. Acknowledgments This research was supported by a grant from the German Research Foundation (Deutsche Forschungsgemeinschaft, DFG; RO 3059/3-1).

References Allport, G. W. (1937). Personality: A psychological interpretation. New York, NY: Holt. Altmann, T., Sierau, S., & Roth, M. (2013). I guess you’re just not my type: Personality types and similarity of types as predictors of satisfaction in intimate couples. Journal of Individual Differences, 34, 105–117. doi: 10.1027/1614-0001/a000105 Asendorpf, J. B., Borkenau, P., Ostendorf, F., & van Aken, M. A. G. (2001). Carving personality description at its joints: Confirmation of three replicable personality prototypes for both children and adults. European Journal of Personality, 15, 169–198. doi: 10.1002/per.408 Asendorpf, J. B., Caspi, A., & Hofstee, W. K. B. (2002). The puzzle of personality types. European Journal of Personality, 16, S1–S96. doi: 10.1002/per.446 Blashfield, R. K., & Aldenderfer, M. S. (1988). The methods and problems of cluster analysis. In J. R. Nesselroade & R. B. Cattell (Eds.), Handbook of multivariate experimental psychology (2nd ed., pp. 447–473). New York, NY: Plenum. Borkenau, P., & Ostendorf, F. (2008). NEO-FFI: NEO-FünfFaktoren-Inventar nach Costa und McCrae, Manual [NEOFive-Factor Personality Inventory by Costa and McCrae, Manual]. Göttingen, Germany: Hogrefe. Caldwell-Andrews, A., Baer, R. A., & Berry, D. T. R. (2000). Effects of response sets on NEO-PI-R scores and their relations to external criteria. Journal of Personality Assessment, 74, 472–488. doi: 10.1207/S15327752JPA7403_10

We thank the anonymous reviewer who raised this issue. Fortunately, we were able to test this assumption using PANAS ratings of negative affective experience from the participants. We computed AARD scores as described by Coifman et al. (2007, p. 751). Results indicated that resilients showed higher autonomic activity relative to their self-report of negative affect compared to the undercontrolled prototype for heartrate, F(2, 102) = 4.59, p = .012, and skin conductance, F(2, 102) = 4.11, p = .019, but not for finger temperature, F(2, 102) = 2.30, p = .105.

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Watson, D., Clark, L. A., & Tellegen, A. (1988). Development and validation of brief measures of positive and negative affect: The PANAS scales. Journal of Personality and Social Psychology, 54, 1063–1070. doi: 10.1037/0022-3514.54.6.1063 Received May 15, 2015 Revision received June 20, 2016 Accepted June 22, 2016 Published online February 10, 2017 Marcus Roth Department of Psychology University of Duisburg-Essen Universitätsstr. 2 45141 Essen Germany marcus.roth@uni-due.de

Journal of Individual Differences (2017), 38(1), 1–11

Original Article

Personality and Memory Conformity Nicole Doughty, Helen M. Paterson, Carolyn MacCann, and Lauren A. Monds School of Psychology, The University of Sydney, Australia

Abstract: When an individual’s memory for an event is altered by post-event information (PEI) provided by a co-witness, this is known as memory conformity (Wright, Self, & Justice, 2000). The aim of this study was to investigate whether personality characteristics are associated with memory conformity. Ninety-nine participants viewed a crime film and then completed the Ten-Item Personality Questionnaire (TIPI; Gosling, Rentfrow, & Swann, 2003), a measure of extraversion, openness, agreeableness, neuroticism, and conscientiousness. Participants then discussed the film with a co-witness who contributed 12 items of post-event information (6 correct, 6 incorrect). Finally, participants completed a film recall questionnaire individually. Significant correlations between personality and memory conformity were found, with decreased openness, extraversion, and neuroticism related to increased reporting of post-event misinformation, increased agreeableness related to increased reporting of accurate post-event information, and decreased conscientiousness and neuroticism related to increased fabrications. These findings suggest that some individuals may be more susceptible to accepting misinformation and reporting errors than others. Keywords: memory conformity, personality, Big Five, misinformation effect

Numerous studies have demonstrated that eyewitness memory is not always an accurate record of reality (see Loftus, 2005 for a review). In a series of influential experiments, Loftus and colleagues (e.g., Loftus, Miller, & Burns, 1978; Loftus & Palmer, 1974) demonstrated that eyewitness memory can be highly vulnerable to inaccurate post-event information (PEI; information that is presented after experiencing the event that may not have been part of the original recollection of the witness), a phenomenon labeled the Misinformation Effect (for an overview, see Davis & Loftus, 2006). One way that witnesses to a crime may encounter PEI is through discussion with a co-witness. Research has consistently shown that participants report misleading information presented to them through co-witness discussion (see Harris, Paterson, & Kemp, 2008 for a review). This effect has become known as “memory conformity” (Wright, Self, & Justice, 2000) or the “social contagion of memory” (Roediger, Meade, & Bergman, 2001). Co-witness discussion is thought to be particularly influential in producing the misinformation effect relative to other methods. One study has shown that PEI encountered through co-witness discussion was significantly more misleading than that encountered through a nonsocial source (Gabbert, Memon, Allan, & Wright, 2004). Furthermore, another study demonstrated that co-witness information was more likely to be recalled by participants than information presented through leading questions or a media report (Paterson & Kemp, 2006).

Journal of Individual Differences (2017), 38(1), 12–20 DOI: 10.1027/1614-0001/a000217

Some individuals seem to be more susceptible to accepting misinformation than others. For example, in one study it was demonstrated that those who score lower on measures of cognitive ability were particularly susceptible to PEI relative to higher scorers (e.g., Zhu, Chen, Loftus, Lin, He, et al., 2010). Research on individual differences and misinformation susceptibility has also implicated a role for variables such as imagination and absorption (Drivdahl & Zaragoza, 2001; Winograd, Peluso, & Glover, 1998), hypnotic suggestibility (Heaps & Nash, 1999), fantasy proneness (e.g., Patihis & Loftus, 2015), psychopathic traits (Peace & Constantin, 2015), selfdirectedness (Zhu, Chen, Loftus, Lin, Li, et al., 2010), and acquiescence (Gudjonsson, 1986; Peiffer & Trull, 2000) in influencing susceptibility. Identifying vulnerable individuals is important in a court setting, whereby eyewitness testimony may be unjustifiably responsible for influencing decisions relating to guilt or innocence. Further, identifying which individuals might be more susceptible to the potentially adverse effects of PEI prior to investigative interviewing could help to reduce harmful results. Therefore, the focus of this paper involves investigating the effects of individual difference factors on memory conformity; in particular, personality traits. One of the most well-validated and widely used models of personality is the five-factor or “Big Five” model (Costa & McCrae, 1992; McCrae & Costa, 1987). According to this model, human personality can be divided into the five broad dimensions of openness, conscientiousness,

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N. Doughty et al., Personality and Memory Conformity

extraversion, agreeableness, and neuroticism (Digman, 1990). Generally speaking, openness refers to an appreciation for new ideas and experiences; conscientiousness refers to the tendency to act with self-discipline and aim for achievement; extraversion is characterized by enjoyment and confidence in the company of others; agreeableness refers to the tendency to be cooperative and helpful; and neuroticism is characterized by high emotional reactivity and vulnerability to stress (Digman, 1990; McCrae & Costa, 1990). Given that a growing body of research supports the fivefactor model, and that meta-analyses have confirmed its predictive value for a range of behaviors (e.g., Saulsman & Page, 2004), it is well worth examining how each trait in the model might relate to memory conformity. Personality theory and empirical evidence have hinted that some of the five traits might influence the reliability of an individual’s eyewitness account. For example, Eysenck and Eysenck (1963) proposed that since introverts are more chronically aroused than extraverts, and since high arousal has been found to impede performance in information retention tasks, introverts should be poorer witnesses than extraverts. Further, Ward and Loftus (1985) suggested that as extraverts are more aggressive and assertive, they may be more capable of guarding against misleading information. More recent research has supported this relationship, revealing that introverts – particularly those who also suffer from anxiety – are more likely to give in to pressure and comply with others (Gudjonsson, Sigurdsson, Bragason, Einarsson, & Valdimarsdottir, 2004). Openness has also been found to be a predictor of misinformation susceptibility. Liebman et al. (2002) found that more open individuals were more accurate in their retention of event information, as measured using the Gudjonsson Suggestibility Scale (GSS; Gudjonsson, 1987). Furthermore, both meta-analyses and more recent evidence demonstrate that openness is associated with higher intelligence, especially higher acculturated knowledge (Ackerman & Heggestad, 1997; Ashton, Lee, Vernon, & Jang, 2000). This Openness/intelligence is thought to occur due to the preferential investment and engagement in learning activities among high-Openness people (e.g., Ziegler, Danay, Heene, Asendorpf, & Bühner, 2012). Since intelligence predicts resistance to misinformation (Zhu, Chen, Loftus, Lin, He, et al., 2010), this provides further evidence for a potential link between openness and decreased misinformation susceptibility. Openness has also been found to be a strong predictor of deception detection; this suggests that open individuals are not just indiscriminately open to new information, but rather evaluate that information for accuracy before taking it

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on; this may make them less likely to be swayed by misinformation (Enos et al., 2006). Relationships have also been observed between the remaining personality traits and compliance, as measured on self-report questionnaires. Liebman et al. (2002) examined these associations using the GSS and a standard misinformation paradigm which utilized suggestive questioning, and discovered that more conscientious individuals were more resistant to misinformation on the GSS. These researchers also found that individuals higher in agreeableness and neuroticism were more susceptible to misleading information in the standard misinformation paradigm. However, research on neuroticism has yielded inconsistent findings, with Haraldsson (1985) finding no significant correlations between suggestibility and neuroticism. To date, there has been no study that has systematically examined the association between memory conformity and these core personality traits. The findings of Liebman et al. (2002), for example, were based on self-report measures of suggestibility and misinformation introduced through suggestive questioning. Drawing general conclusions from this paradigm is not advisable, as it is possible that any of the five personality traits might affect susceptibility to misinformation differently in a more ecologically valid research setting. Therefore, personality traits must be examined in the context of a natural social situation, such as a co-witness discussion, in order to extend the conclusions that have been made from studies using interrogative questioning and/or suggestibility questionnaires. It would be unwise to generalize findings from such studies because socially encountered misinformation affects memory differently to that encountered through a nonsocial source (Gabbert et al., 2004). Additionally, while the majority of co-witness discussion research has focused on transmission of misinformation, there is also the possibility that discussion may be beneficial to memory accuracy. In a recent study participants either took part in a collaborative interview or recalled the event alone. It was found that collaboration led to significantly fewer errors relative to individual recall (Vredeveldt, Hildebrandt, & Van Koppen, 2015). Extending this finding, it may be possible that certain personality variables may be useful in facilitating successful, accurate co-witness discussion as opposed to increasing the likelihood of misinformation.

The Current Study Therefore, the aim of this study was to explore the association between personality individual differences and memory conformity (to both misinformation and accurate statements). As this was an exploratory study with no

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known past memory conformity and personality research, it is difficult to anticipate precisely the direction of the relationships. However, it was tentatively predicted that, in line with past research on the misinformation effect, openness, extraversion, and conscientiousness would be negatively correlated with memory conformity, while agreeableness and neuroticism would be positively correlated with memory conformity. There were seven recall variables of interest: (1) number of accurate responses to items for which participants received no PEI (accurate to control), (2) number of confabulated (distorted or fabricated) responses to items for which participants received no PEI (confabulate control), (3) number of accurate responses to items for which participants received correct PEI (accurate to correct PEI), (4) number of confabulated responses to items for which participants received correct PEI (confabulate correct PEI), (5) number of responses in which participants yielded to misinformation (yield to misinformation), (6) number of responses in which participants resisted misinformation (resist misinformation), and (7) number of confabulated responses to misinformation (confabulate misinformation).

N. Doughty et al., Personality and Memory Conformity

that were inconsistent with the film (misinformation). Participants then individually completed a memory questionnaire which tested recall of items for which they had been given PEI, and items for which they had not. Personality traits from the five-factor model (i.e., openness, conscientiousness, extraversion, agreeableness, and neuroticism) were correlated with the recall variables and were predictors in relative weight analyses.

Materials Stimulus Event The eyewitness stimulus was a mock crime film (2 min 45 s in duration) used in a previous study (Paterson, Kemp, & Ng, 2011). The film depicts a thief gaining access to an apartment, stealing some items, and then being chased out by the occupant. Personality The Ten-Item Personality Inventory (TIPI; Gosling, Rentfrow, & Swann, 2003) is a 10-item measure of the five personality dimensions (openness, conscientiousness, extraversion, agreeableness, and neuroticism) with two items on the scale relating to each trait; half of the items are reverse-scored. Overall, higher scores indicate greater endorsement of that personality variable. The scale and its subscales have demonstrated validity and reliability (Gosling et al., 2003).

Design1

Post-Event Information Provided by Confederate Co-Witness During Discussion During the discussion about the film, confederates mentioned six items of correct information and six items of misinformation (see Table 1). The confederates were seven female third and fourth year Psychology students (age M = 23.57 years, SD = 6.45) who were not known to the participants. Real participants were given a sheet of prompts directing them to discuss: (1) sequence of events, (2) appearance of characters, (3) dialog between characters, (4) appearance of the building, (5) stolen items, and (6) any other details. The confederates were given a similar-looking sheet which was in fact a “cheat sheet” that listed the correct PEI and misinformation they needed to mention.

Participants were shown a mock crime film and then discussed this film with a co-witness (confederate) who introduced six items of PEI that were correct and six items

Manipulation Awareness Check Participants were asked what they thought the purpose of the study was.

Method Participants Participants were 100 first-year Psychology students who participated for course credit. One participant was excluded from the study because the manipulation check revealed they correctly surmised the study aims and confederate’s role. Thus, 99 participants (70 females; age M = 20.08 years, SD = 5.24) were included in the final analysis. Students received course credit for their participation.

Originally the study included a 2 2 design, investigating the effects of co-witness likeability (likeable vs. neutral/control) and recall type (public vs. private/control) on memory for the event. However, the experimental manipulations were not successful: none of the recall measures revealed any differences in responding based on the type of co-witness the participant was paired with, or the type of recall condition they were allocated to. Furthermore, there was no interaction of likeability and recall condition, all ps > .19. Thus, for the interest of brevity, they have not been included in this manuscript. Further information regarding these aspects of the study can be provided upon request to the corresponding author.

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Table 1. Correct PEI and misleading PEI (misinformation) mentioned by the confederate in the discussion Item no.

What participants viewed

What confederates said

Correct post-event information 1

Thief used the intercom to gain access

Female wore leather coat, purple top, jeans

Thief is looking for a friend named Paul

Thief wears white sneakers

Thief wears striped top, blue jacket, jeans

Thief steals jewellery from bedroom last

Misleading post-event information (misinformation) 1

Main entrance had glass doors

Main entrance had wooden doors

Thief said his name was James

Thief said his name was Jason

Thief entered unit number 2

Thief entered unit number 3

Thief stole a wallet first

Thief stole a laptop first

Man yelled out “Kate, have you seen the salt?”

Man yelled out “Who’s out there!”

Thief escaped alone

Thief escaped with an accomplice

Note. Misinformation and its corresponding correct information are indicated in bold.

Recall Questionnaire The recall questionnaire consisted of 18 open-ended items on the contents of the film, including descriptions of the thief and victims, the event, and the setting. Of these questions, six of the questions directly corresponded to items of correct information mentioned by the confederate, six directly corresponded to items of misinformation mentioned by the confederate, and the remaining six questions related to items in the film that were not mentioned by the confederate.

Procedure One participant and one confederate participated in each experimental session, with the participant believing that the confederate was another first-year psychology student. Participants completed a consent form and were then asked to complete the TIPI. Prior to watching the film, participants were warned that they would be viewing a video of a crime scene and that they should pay close attention because they would be asked questions about it later. Lights were switched off and the participants viewed the film with the confederate on one computer. Afterwards, participants completed filler questionnaires to allow for sufficient memory decay between exposure to the event and recall. Following this, participants were instructed to discuss the film with one another and that they should use the prompt 2

sheets to guide their discussion. At the beginning of the discussion, confederates were instructed to say “why don’t you start first and I’ll add anything I can remember.” As the participant began describing the film, the confederate contributed the correct information and misinformation. All other details mentioned by participants were considered to be control items (no-PEI) and were not commented on by confederates. If challenged by the participant on any of their answers, confederates responded once with: “That’s what I remember from the video.” In the final phase of the study participants were given 10 min to complete the 18-item recall questionnaire. Upon completion, the experimenter gave participants the manipulation check. Participants were given demographic questions to fill out and were then fully debriefed. They were asked not to discuss the experiment with potential participants and thanked for their participation. The session usually lasted 1 hr.

Data Coding A coding system was developed and is summarized in Table 2.2 Written responses to each of the 18 questions were coded by the experimenter, who was blind to the participant personality measure scores. In order to assess inter-rater reliability, responses from 10 participants were separately coded by another person familiar with the coding

As demonstrated in Table 2, there are four potential responses to misinformation: yield, resist, confabulate, and omission. While yield and resist are related in that if a participant yielded to misinformation it means they did not resist it. However, it does not follow that if they did not yield that means they resisted the misinformation. A participant may instead have confabulated by reporting a different response altogether or simply did not report anything related to that item. Therefore all four measures are useful and necessary for misinformation analyses.

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Table 2. Classification of recall questionnaire responses based on post-event information delivered Type of PEI delivered Correct PEI

Misinformation

Control (No PEI)

Example of PEI The name of the thief’s “friend” was Paul

The thief said his name was Jason

N/A

Recall question

Example of participant response

What was the name of the friend the thief said he was looking for?

What did the thief say his name was?

What day was garbage day?

template and the crime film, also blind to personality questionnaire scores. Correlations were computed to examine inter-rater reliability, with the number of correct PEI, misinformation, and no PEI items as the dependent variables. Acceptable inter-rater reliability was achieved for the classification of Correct PEI, Misinformation, and no PEI items, with intra-class correlations of .88, .92, and .79 respectively.

Results Pearson correlations (two-tailed) and linear regressions with relative weight analysis were computed to determine whether scores on the five personality traits were associated with performance on the recall questionnaire. Regressions were run in SPSS and the relative weight analysis was conducted using R (R Core Team). Relative weights partition R2 variance among the predictors after accounting for the predictor covariation using principal component analysis. Relative weights thus address issues of collinearity when determining the relative importance of correlated predictors, and can be superior to β weights for this purpose when predictors are correlated (Johnson, 2000; Tonidandel & LeBreton, 2011). Although the Kolmogorov-Smirnov test for normal distribution indicated departure from normality for the dependent variables (all ps < .001), as this test is oversensitive to larger sample sizes (N > 50; Howell, 2013) we looked at skew and kurtosis to check how serious the violations from normality were, and concluded that these were not serious (skewness < |1.4|; kurtosis < 2.1; West, Finch, & Curran, 1995). As such, parametric statistics were still used.

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The name of the thief’s “friend” was Paul The name of the thief’s “friend” was Peter Don’t know/not sure/can’t remember The thief said his name was James The thief said his name was Jason The thief said his name was Jake

Dependent variables Accurate to correct PEI Confabulate correct PEI Omission Resist misinformation Yield to misinformation Confabulate misinformation

Don’t know/not sure/can’t remember Tuesday

Omission Accurate to control

Wednesday

Confabulate control

Don’t know/not sure/can’t remember

Omission

The Five-Factor Model Personality Traits In line with hypotheses, Openness was significantly correlated with yielding to and resisting misinformation, such that higher reported levels of openness were associated with lower yielding and greater resistance to misinformation. Also in line with hypotheses, Extraversion was significantly correlated with yielding to and resisting misinformation, with increased levels of extraversion related to less yielding and more resistance to misinformation. Conscientiousness was significantly correlated with confabulations of misinformation, in that higher levels of conscientiousness were linked to fewer confabulations of misinformation; however, conscientiousness was not significantly correlated with misinformation, which is not consistent with hypotheses. Neuroticism was significantly correlated with yielding to misinformation and confabulations of control items, such that higher levels of reported neuroticism were linked to a decreased likelihood of yielding to misinformation or confabulating control items; this is the opposite of what was predicted. Finally, agreeableness was positively correlated with accurate reporting of correct PEI and negatively correlated with confabulated responses to correct PEI; again this was inconsistent with predictions (see Table 3 for descriptives and correlations). Effect sizes were moderate for agreeableness and small to moderate for the other significant correlations. That is, the largest effect was that agreeable people were more sensitive to receiving correct information. Regressions with relative weight analyses (Johnson, 2000; Tonidandel & LeBreton, 2011) were conducted to determine which personality variables were independent predictors of the recall variables. “The goal of such analyses is to partition explained variance among multiple predictors

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Table 3. Descriptives of personality measures and Pearson correlations between personality measures and performance on the recall questionnaire Memory conformity correlations Big Five trait

Descriptives M (SD)

Openness

Accurate to correct PEI

Confabulate correct PEI

Resist misinformation

Yield to misinformation

Confabulate misinformation

Accurate to control

Confabulate control

10.40 (1.98)

.107

.102

.224*

.273**

.064

.008

.073

Extraversion

9.29 (2.92)

.014

.008

.219*

.254*

.137

.002

.151

Conscientiousness

9.21 (2.56)

.159

.085

.150

.062

.221*

.091

.115

Agreeableness

9.60 (2.28)

.320**

.353**

.023

.013

.055

.010

.057

Neuroticism

9.29 (2.69)

.037

.066

.175

.221*

.026

.183

.222*

Note. *p < .05; **p < .01 (two-tailed).

to better understand the role played by each predictor in a regression equation. . .when predictors are correlated, typically relied upon metrics are flawed indicators of variable importance” (Tonidandel & LeBreton, 2011, p. 1). It was found that conscientiousness was a significant negative predictor of accurate to correct PEI, β = .22, p < .05, and agreeableness was a significant positive predictor of accuracy for correct PEI, β = .39, p < .01. Agreeableness was also a significant negative predictor of confabulations to correct PEI, β = .42, p < .01. No other predictors were significant for any of the other recall variables (see Table 4).

Discussion In the current study the Big Five personality traits of openness, conscientiousness, extraversion, agreeableness, and neuroticism were examined as to how they influence memory conformity. Although this study was exploratory in nature, based on related findings in previous research it was anticipated that openness, extraversion, and conscientiousness may be negatively correlated with memory conformity, while agreeableness and neuroticism could be positively correlated with memory conformity.

Openness Based on theory and empirical findings (e.g., Ashton et al., 2000; Garcia, Aluja, Garcia, & Cuevas, 2005; Liebman et al., 2002; McCrae, 2000; Zhu, Chen, Loftus, Lin, He, et al., 2010) a link between openness and decreased susceptibility to misinformation was anticipated. As predicted, individuals who scored higher on openness were significantly more likely to resist misinformation, and significantly less likely to yield to misinformation.

Extraversion Theory and evidence from some of the research on extraversion suggests that extraverts may be able to resist Ó 2017 Hogrefe Publishing

misinformation due to their confident nature (Gudjonsson et al., 2004). Thus, extraversion was expected to be linked to reduced memory conformity, that is, fewer yields and increased resistance to misinformation. These predictions were supported, contributing toward the theory that extraverts are more accurate witnesses than introverts (e.g., Eysenck & Eysenck, 1963).

Conscientiousness Conscientiousness was predicted to be linked to decreased misinformation susceptibility, however, no such findings were observed in the current study. However, correlation analyses indicated participants who were more conscientious were less likely to distort or fabricate items for which they had received misleading information. This relationship did not hold in the relative weight analysis; however, conscientiousness was a significant negative predictor of accuracy for correct PEI items. This was an unexpected finding and may be a statistical artifact.

Agreeableness It was anticipated that highly agreeable individuals would be likely to take on misinformation in an atmosphere of social pressure (Eisen, Winograd, & Qin, 2002; Graziano & Eisenberg, 1997); however, agreeableness was positively correlated with accurate reporting of correct PEI and negatively correlated with confabulated responses to correct PEI. Both of these relationships remain in the relative weight analyses as well, suggesting these are robust findings.

Neuroticism Contrary to predictions, participants who reported higher levels of neuroticism were significantly less likely to yield to misinformation delivered by their co-witness. In addition, participants who reported higher levels of neuroticism were Journal of Individual Differences (2017), 38(1), 12–20

.070 .042 .180** .177** .074 .104 .133*

Notes. RW = relaxive weight. *p < .05, **p < .01 (two-tailed).

0.148 R2

2.10

60.60 0.208 0.043 79.00 0.192 0.033 2.30 0.004 0.048 0.80 0.001 0.004 1.10 0.019 0.001 18.10 0.104 0.019 24.60

24.60

0.033

0.024 0.001

0.123 0.017 0.90

0.40 0

0 0.026

0.015 79.60

0.80 0.001

0.143 0.416**

0.065 0.50

69.30 0.123

0.001 0.054

0.392** 3.20

22.50 0.125 0.017

0.038 0.002 4.00

31.50 0.151 0.033

0.093 0.004 0.80

36.10

0.05

0.048 0.195 E

0.001

2.20

10.50 0.059 0.007

0.036 0.002 3.10

16.60 0.078 0.007

0.053 0.001 9.90

7.30 0.013

0.018 0.169

0.142 19.20

10.20 0.018

0.034 0.216*

0.169 13.80

59.30 0.205 0.044

0.139 0.01 32.50

13.90 0.097 0.014

0.159 0.034 37.70

0.80 0.001

0.050 0.191

0.02

% of R2 RW % of R2 RW % of R2 RW

Correct PEI accurate

β % of R2 RW

Confab Mis

β % of R2 RW

Resist Mis

β % of R2 Yield Mis

RW β

Table 4. Relaxive weight analysis results investigating predictors of performance on the recall questionnaire

Correct PEI Confab

Acc Cont

% of R2

N. Doughty et al., Personality and Memory Conformity

Confab Cont

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less likely to confabulate control items on the recall questionnaire. These results do partially cohere with those of Liebman et al. (2002), who found that participants high in neuroticism were unlikely to provide blends of misinformation and other information (i.e., confabulations). Perhaps individuals in the current study were more neurotic or self-conscious about the possibility of being seen as unreliable or inaccurate by the experimenter, than they were about being negatively evaluated by the co-witness. Overall, the most prominent findings are those relating to agreeableness and accuracy. While it was thought that more agreeable participants would be more likely to conform to misinformation introduced by the confederate this was not found to be the case. However, some conformity did occur, in that there was enhanced reporting of correct PEI. This finding may mean that agreeable participants were focused on being cooperative and helpful to the overall goal of the study – accuracy for eyewitness testimony, rather than to cooperation with their co-witness. As mentioned earlier, predictors of both accuracy and susceptibility to error are important for the field of eyewitness memory research (e.g., Vredeveldt et al., 2015) and thus this finding is relevant and worthy of further study to replicate and expand on these findings. Despite these promising correlations between personality traits and memory conformity, the current study is limited in that only the broad personality domains were investigated (using the TIPI which is small scale with few items). We did not consider the specific elements underlying each domain, such as aspects or facets of personality (DeYoung, Quilty, & Peterson, 2007). It has been demonstrated that individual facets (e.g., “sociability” on the Extraversion dimension; not to be confused with the term facet in Guttman’s Facet theory; Guttman & Greenbaum, 1998) are better at predicting and explaining behavior than the five broad traits (Paunonen & Ashton, 2001). While the TIPI may be useful as a screener, in future studies, focusing on the individual facets of each personality trait with a more comprehensive measure (e.g., HEXACO Personality Inventory Revised [HEXACO-PI-R] or NEO Psychological Inventory Revised [NEO-PI-R]) may allow for better predictive power, with a more in-depth understanding of the ways in which personality traits relate to memory conformity. Further, recently a sixth personality trait has been identified in addition to the Big Five; Honesty/ Humility (the HEXACO model; Ashton & Lee, 2007). Honesty is potentially another important variable relevant for truthful depictions of events, thus necessitating further research including this personality variable. A further limitation of the study was the lack of counterbalancing. As far as possible, the different types of PEI were matched on their sequence in the film and judged level of difficulty. With this study’s materials, it was not Ó 2017 Hogrefe Publishing

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feasible to effectively counterbalance as some of the items lent themselves more naturally to being correct PEI. There may have been systematic differences between responding to the correct PEI and misinformation itemrelated questions. It is worth exploring the current findings in future research using counterbalanced PEI items to rule out this possibility. Lastly, due to the small sample size, some nonsignificant findings may have been due to limited power. Regardless, the relationships observed still highlight a need for further investigation of these variables; however, a replication of the current study may be required first.

Conclusions The current study is the first to demonstrate how the Big Five personality traits are linked to memory conformity. This contributes toward the body of research investigating eyewitness testimony. In particular, decreased openness, extraversion, and neuroticism were related to greater conformity to post-event misinformation, increased agreeableness was related to greater conformity (but only in relation to correct information), and decreased conscientiousness and neuroticism were related to more fabrications. These findings suggest that some individuals may be more susceptible to accepting co-witness misinformation and reporting errors than others. This has important legal implications in terms of identifying individuals who are at risk of co-witness contamination and protecting these vulnerable witnesses from the potentially adverse effects of co-witness discussion.

Acknowledgments This research was supported by Australian Research Council Grants LP0989719 and LP110100220.

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Roediger, H. L. III, Meade, M. L., & Bergman, E. T. (2001). Social contagion of memory. Psychonomic Bulletin & Review, 8, 365–371. doi: 10.3758/BF03196174 Saulsman, L. M., & Page, A. C. (2004). The five-factor model and personality disorder empirical literature: A metaanalytic review. Clinical Psychology Review, 23, 1055–1085. doi: 10.1016/j.cpr.2002.09.001 Tonidandel, S., & LeBreton, J. M. (2011). Relative importance analysis: A useful supplement to regression analysis. Journal of Business and Psychology, 26, 1–9. doi: 10.1007/s10869-0109204-3 Vredeveldt, A., Hildebrandt, A., & Van Koppen, P. J. (2015). Acknowledge, repeat, rephrase, elaborate: Witnesses can help each other remember more. Memory, 24(5). doi: 10.1080/ 09658211.2015.1042884 Ward, R. A., & Loftus, E. F. (1985). Eyewitness performance in different psychological types. The Journal of General Psychology, 112, 191–200. doi: 10.1080/00221309.1985. 9711003 West, S. G., Finch, J. F., & Curran, P. J. (1995). Structural equation models with nonnormal variables: Problems and remedies. In S. G. West, J. F. Finch, P. J. Curran, & R. H. Hoyle (Eds.), Structural equation modeling: Concepts, issues, and applications (pp. 56–75). Thousand Oaks, CA: Sage. Winograd, E., Peluso, J. P., & Glover, T. A. (1998). Individual differences in susceptibility to memory illusions. Applied Cognitive Psychology, 12, S5–S27. doi: 10.1002/(SICI)10990720(199812)12:7<S5::AID-ACP553>3.0.CO;2-D Wright, D. B., Self, G., & Justice, C. (2000). Memory conformity: Exploring misinformation effects when presented by another person. British Journal of Psychology, 91, 189–202. doi: 10.1348/000712600161781 Zhu, B., Chen, C., Loftus, E. F., Lin, C., He, Q., Chen, C., . . . Dong, Q. (2010). Individual Differences in false memory from misinformation: Cognitive factors. Memory, 18, 543–555. doi: 10.1080/09658211.2010.487051 Zhu, B., Chen, C., Loftus, E. F., Lin, C., Li, H., Chen, C., . . . Dong, Q. (2010). Individual differences in false memory from misinformation: Personality characteristics. Personality and Individual Differences, 48, 889–894. doi: 10.1016/j.paid.2010.02.016 Ziegler, M., Danay, E., Heene, M., Asendorpf, J., & Bühner, M. (2012). Openness, fluid intelligence, and crystallized intelligence: Toward an integrative model. Journal of Research in Personality, 46, 173–183. doi: 10.1016/j.jrp.2012.01.002 Received November 2, 2015 Revision received June 20, 2016 Accepted June 22, 2016 Published online February 10, 2017 Helen M. Paterson School of Psychology The University of Sydney Sydney, 2006 Australia helen.paterson@sydney.edu.au

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Original Article

The Effects of Age on the Interplay Between News Exposure, Political Discussion, and Political Knowledge Sabine Trepte1 and Josephine B. Schmitt2 1

Department of Media Psychology, School of Communication, University of Hohenheim, Germany

Media and Communication Psychology, University of Cologne, Germany

Abstract: Using the theory of fluid-crystallized intelligence, we argue that with growing age, political discussion becomes less important as a complement to news exposure in political knowledge building. We applied moderated mediation analyses to the survey data of N = 69,125 German respondents. The data supported the hypothesis that news exposure influences political discussion, which in turn leverages political knowledge. As expected, we showed that news exposure is more strongly associated with political discussion for younger age groups. The results are discussed with regard to how to integrate a psychological lifespan perspective into further research on knowledge acquisition. Keywords: age, lifespan, political discussion, political knowledge, news exposure

The acquisition of knowledge varies tremendously across the lifespan (Baltes, 1987; Beier & Ackerman, 2005; Salthouse, 2003). The ways in which differential forms of knowledge are acquired also vary with age (Ackerman, 2008). The theory of fluid-crystallized intelligence refers to age-related differences in knowledge: It implies that knowledge is generated and stored differently across the lifespan (Ackerman, 2008; Horn, 1982; Horn & Cattell, 1967). Crystallized intelligence is one of two main factors of the theory of fluid-crystallized intelligence. It refers to intelligence as cultural knowledge and represents a person’s experiences (Baltes, 1987). Crystallized abilities also imply a type of knowledge that is referred to as declarative knowledge, namely, the knowledge that is usually learned in school (e.g., European history as a part of political knowledge), the knowledge that we need to survive (e.g., how to behave during a thunderstorm), or the knowledge that is necessary to sustain well-being and physical health (Ackerman, 2008). Crystallized abilities have been shown to increase linearly with age, and in previous research, a peak in crystallized intelligence was observed at age 60–70 (Rönnlund, Nyberg, & Bäckman, 2005; Schaie, 1996). However, positive effects of age on crystallized intelligence can also be found in younger age groups and in samples with smaller age ranges (Beauducel & Kersting, 2002; Beauducel, Liepmann, Felfe, & Nettelnstroth, 2007). Political knowledge can be considered one domain of declarative knowledge and is significantly related to Ó 2017 Hogrefe Publishing

crystallized intelligence (Beauducel & Kersting, 2002). Political knowledge has been shown to be an important outcome variable because it is bound to participation and deliberation (Delli Carpini, 2004). The most important factor that influences political knowledge acquisition is exposure to news media in general and to print news in particular: Countless studies have shown that people who more frequently read the news score higher on tests of political knowledge (e.g., Yang & Grabe, 2011). Another factor that influences knowledge acquisition is political discussion: Particularly when the news is repeated and collaboratively elaborated, individuals become able to learn from it (Eveland, 2004). For example, in a longitudinal panel survey, Eveland and Thomson (2006) found that the frequency of political discussion caused significant changes in political knowledge over the course of 1 year. Eveland and Hively (2009) conducted a telephone survey of 600 adults and revealed that frequency of discussion was positively related to knowledge about candidates’ stances on issues. Previous studies have investigated the question of how political news reading and political discussion work their way into political knowledge. The relations between news exposure, discussion, and knowledge were suggested to be sequential such that people who are exposed to political news discuss the information they have read online or in the printed press, and by engaging in these two activities, they acquire knowledge (Eveland, 2004). For example, Nisbet and Scheufele (2004) showed that political Journal of Individual Differences (2017), 38(1), 21–28 DOI: 10.1027/1614-0001/a000218

S. Trepte & J. B. Schmitt, Effects of Age on Discussion and Knowledge

discussion strengthens the effects of campaign exposure. In the 2000 American Election Study, they demonstrated that only those who were exposed to both online campaigns and political discussions benefitted in terms of political knowledge. These results suggest that political discussion is related to news exposure and provides a powerful means for generating political knowledge. In other words, individuals who tend to read the news more frequently also discuss politics more frequently and, in turn, have a higher chance to generate political knowledge. Therefore, we predicted the following:

political issues in order to make sense of the news. Then, at an older age with advancing cognitive development, the two activities – news exposure and political discussion – become increasingly detached. Knowledge structures become much more established (Ackerman, 2008). Moreover, with growing age, political schemas become developed further, and the need for communication decreases (Fiske & Kinder, 1986). A meta-analysis provided support for this notion by showing that age was negatively related to elaborative processing by discussing the news (Eveland, 2005). Therefore, we predicted the following:

Hypothesis 1 (H1): Exposure to (a) print as well as (b) online news will positively influence political discussion, which, in turn, will positively influence political knowledge.

Hypothesis 2 (H2): Age will negatively moderate the effect of (a) print and (b) online news exposure on political discussion.

Different habits, capacities, and needs across the lifespan might influence whether and how news exposure and discussions leverage political knowledge. As stated above, knowledge acquisition and knowledge testing cannot be considered without referring to the differential effects of age. Knowledge acquisition varies tremendously across the lifespan and with age (Ackerman, 2008; Horn, 1982; Horn & Cattell, 1967). Here, we suggest that people from different age groups benefit differently from political discussions. In other words, we expected to find a moderated mediation with age moderating the relations between both (a) news exposure and political discussion and (b) political discussion and knowledge. Thus, the interplay between news exposure, political discussion, and knowledge may be subdivided into two relations, both mediated by age: one referring to the relation between news exposure and political discussion and the other addressing the relation between political discussion and political knowledge. With regard to the first relation between news exposure and political discussion, it seems likely that younger individuals – more than older persons – tend to combine news exposure with political discussions. According to Ackerman’s (2008) interpretation of the theory of fluidcrystallized intelligence, younger individuals actively seek interpersonal experiences (e.g., political discussion) to develop domain knowledge. Fluid abilities such as concentration, attention, and active elaboration are invested with the aim of converting these experiences into crystallized abilities (Salthouse, 2003). As many gaps in their cognitive skeletons need to be filled with relevant experiences and knowledge, young people in particular converse about 1

With regard to the second relation describing the interplay between political discussion and political knowledge, one might assume that political discussion positively influences political knowledge because it delivers additional factual information. However, referring to the fluid-crystallized theory of intelligence and previous research on declarative, domain knowledge (Ackerman, 2008), it seems plausible to argue that growth and decline may make this extra information less effective for knowledge building in older age groups (Baltes, 1987). With regard to growth, more experience produces less incremental knowledge (Smith & Baltes, 1990). With regard to decline, it has been shown that large amounts of novel learning that must occur quickly and that might not be controlled by the learner, such as in political discussions, work better for younger than for older individuals (Schaie, 1996). As age increases, political discussions may be important for exchanging attitudes and evaluations, but they are no longer important for crystallizing knowledge and schemas (Lau & Redlawsk, 2008). On the basis of this rationale, we predicted: Hypothesis 3 (H3): Age will negatively moderate the positive effect of political discussion on political knowledge.

Method Procedure The data used in this analysis originated from a broadly conceived online survey conducted in 2009 in Germany to investigate general knowledge.1 A total of 36.8% of the

Respondents were offered a personalized knowledge test score sheet as an incentive. Comparisons of how incentives work in online studies have shown that personal feedback that is based on study results significantly increases response quantity (Marcus, Bosnjak, Lindner, Pilischenko, & Schütz, 2007; Singer & Ye, 2013). Response quality was checked with a number of tests that were published in Trepte and Verbeet (2010).

Journal of Individual Differences (2017), 38(1), 21–28

Ó 2017 Hogrefe Publishing

S. Trepte & J. B. Schmitt, Effects of Age on Discussion and Knowledge

participants were recruited via links on a German social network site, which was the most prominent social network site at the time of the study. The other 63.2% of the participants were recruited via links on the German online news magazine spiegel.de, which was one of the top-ranked news magazines in Germany at the time of the study. The online questionnaire comprised five different categories of knowledge, namely, political knowledge, history, economics, culture, and the natural sciences. After analyzing the items and scales with a pretest administered to N = 6,224 respondents, a total of 180 items were chosen for the main study. Four parallelized item sets were assessed for each of the five knowledge categories. Each respondent was randomly assigned to one of the parallel item sets that comprised questions from all of the knowledge categories. In sum, each participant answered nine questions on each of the five topics, adding up to a total of 45 questions per participant. In addition to being tested on their knowledge, participants were randomly assigned to fill out questionnaires that referred to their discussion habits with regard to one of the five categories: politics, history, economics, culture, or the natural sciences. In addition, demographics and exposure to print and online news were assessed. In the study presented here, we will refer to political knowledge, political discussion, online and print news exposure, as well as sociodemographics (age, gender, educational level). The other knowledge categories described above were regarded elsewhere (Trepte & Verbeet, 2010).

Sample For the present analysis, a subsample of n = 69,125 persons ranging from 18 to 70 years of age was chosen from the overall sample of N = 692,215. Participants were considered if they provided valid data on the following variables: print and online news exposure, political discussion, political knowledge, age, gender, and educational level. As explained above, only one fifth of the sample was asked to fill out questions on political discussion habits. Thus, the overall sample was reduced in this respect. Previous literature was consulted to define valid age thresholds, which were supposed to include the span of adulthood from young adulthood to older adulthood. In line with studies on cognitive aging, the sample was restricted to the ages between 18 and 70 because at age 60, the peak of declarative knowledge is reached with slow attenuation in the 70s and 80s (Ackerman, 2008; Baltes, 1987). The mean age was 26.4 years (SD = 8.28), and 61.3% of respondents were male; 43% of the respondents had achieved at least a high school diploma. In terms of occupational status, the sample consisted of 41.0% college or university students, 32.2% full or part-time employees, 8.8% pupils, 7.2% participants in vocational training, and 10.4% retired, Ó 2017 Hogrefe Publishing

unemployed, or other; 0.4% of the data on occupational background was missing. As participants were self-selected to participate in the survey online (social network site and online magazine), the sample was not representative of the overall German population. In terms of age and educational background, the sample was biased as we had a large proportion of younger participants due to the recruiting strategy. However, concerning educational level, the sample was very similar to the German online population (37% of German “onliners” have at least a high school diploma; AGOF, 2015).

Measures Political Knowledge The political knowledge items were generated with a Delphi method by 12 German journalists working in different fields of interest at the German news magazine Der Spiegel. The items covered political events, the political system, countries, capital cities, and political candidates. The procedure of generating the knowledge items and selecting them according to item and scale analyses is described in detail in Trepte and Verbeet (2010). Multiple-choice items (e.g., “What is the name of the current UN Secretary General?”; answer options: Ban Ki Moon, Kofi Annan, José Manuel Barroso, and Joseph Blatter) as well as free-choice items (e.g., provide a candidate’s name to go with a photo; no answer options were available) were used. A time limit of 30 s per question reduced the possibility that participants would use additional help in answering the questions. All answers were coded as 0 (= false or not answered) or 1 (= correctly answered). The political knowledge score ranged from zero to nine correct answers (M = 4.70, SD = 2.23). Print News Exposure Participants were asked how many of the 12 recently published issues of the three most read German news magazines (Der Spiegel, Focus, Stern) they had read in the last 3 months. Answer options ranged from 0 (= no issues) to 12 (= 12 issues). The score for print exposure represents the arithmetic mean of the exposure to all three magazines (M = 1.63, SD = 1.93, min = 0, max = 12). Online News Exposure Participants were asked how often they read news online from the same three German news magazines. Answer options for every magazine ranged from 0 (= never/ almost never) to 6 (= daily/almost daily). The score for online news exposure was computed by using the arithmetic mean of these three items (M = 1.30, SD = 1.33, min = 0, max = 6). Journal of Individual Differences (2017), 38(1), 21–28

S. Trepte & J. B. Schmitt, Effects of Age on Discussion and Knowledge

Political Discussion Political discussion was measured with an additive index of four items that addressed discussion frequency (e.g., “How often do you talk with your friends about politics in general?”) as well as discussion intensity (e.g., “How much information do you share in discussions about politics with your friends?”). Each of the items had to be rated on a 5-point scale with smaller values indicating fewer political discussions (less intensity) and higher scores indicating more political discussions (greater intensity; M = 3.10, SD = 0.93, min = 1, max = 5; α = .85). Control Variables As control variables, we included gender (0 = male, 1 = female) as well as education (0 = no high school diploma, 1 = high school diploma).

Results In order to test the proposed hypotheses, we computed multivariate path analyses in the statistical environment R (R Core Team, 2015). The model was estimated with the package lavaan. As recommended by Hayes (2012), we mean-centered the predictor variables prior to the analyses and tested for the significance of indirect effects with bootstrapped confidence intervals with 1,000 samples (Hayes & Scharkow, 2013). We controlled for gender and education. To illustrate the conditional effects, we used the package ggplot2. The estimated model fit the data well, w2(4) = 216.16, p < .001 (CFI = .99; TLI = .98; RMSEA = .03, 90% CI [.025, .032], SRMR = .006, see also Figure 1 and Table 1). The predictors included in the model were able to explain 21% of the variance in political discussion and 31% of the variance in political knowledge. Hypothesis 1 indicated a positive indirect effect of (a) print and (b) online news exposure on political knowledge through political discussion. The path analysis revealed that print news exposure (b = .09, 95% CI [.088, .095], β = .19) as well as online news exposure (b = .16, 95% CI [.153, .164], β = .23) positively influenced political discussion. Political discussion, in turn, was positively related to political knowledge (b = .62, 95% CI [.605, .638], β = .26). We found significant indirect effects of print news exposure (b = .06, 95% CI [.054, .059], β = .05) and online news exposure (b = .10, 95% CI [.094, .103], β = .06) on political knowledge through political discussion. Hypotheses 1a and 1b were supported by the data. Individuals who read online or print news more intensely tended to discuss politics more and, in turn, possessed higher political knowledge. With this result, we replicated previous research that had shown that news exposure and political discussion sequentially influence political knowledge. Journal of Individual Differences (2017), 38(1), 21–28

Figure 1. Results for Hypotheses 1–3 are shown. Standardized path coefficients of direct and conditional effects are shown. All coefficients were significant at the p < .001 level; gender and education were controlled for; dark gray lines indicate conditional indirect effects; light gray lines indicate direct effects.

Hypothesis 2 proposed that age would moderate the relations between (a) print and (b) online news exposure and political discussion. For H2a, evidence of moderation by age was found in a significant negative interaction between print news exposure and age on political discussion (b = .001, 95% CI [ .002, .001], β = .03). Figure 2 shows that with decreasing age, the magnitude of the coefficient of print news exposure on political discussion also decreased considerably. Hypothesis 2a was supported by the data. For H2b, a significant negative interaction between online news exposure and age on political discussion was found (b = .002, 95% CI [ .003, .002], β = .03). Figure 3 shows that with decreasing age, the magnitude of the coefficient of print news exposure on political discussion also decreased considerably. Hypothesis 2b was supported by the data. With these results on how age was found to moderate the relation between news use and political discussion, we complement current research. Younger people tended to combine online or print news exposure with political discussions. By contrast, older news readers did not relate their reading of the news to political discussions as often. Hypothesis 3 predicted that age would moderate the relation between the mediator variable political discussion and the outcome variable political knowledge. We found a significant negative conditional effect (b = .001, 95% CI [ .002, .001], β = .001). Figure 4 shows that with decreasing age, the magnitude of the effect of political discussion on political knowledge decreased considerably. Hypothesis 3 was supported by the data. The older people grow, the less their political discussions affect their political knowledge. Ó 2017 Hogrefe Publishing

S. Trepte & J. B. Schmitt, Effects of Age on Discussion and Knowledge

Table 1. Coefficients and conditional indirect effects for the moderated mediation model 95% CI β

Online news exposure (X1)

.23

.16

.002

.153

.164

Print news exposure (X2)

.19

.09

.002

.088

.095

Online news exposure age (I1)

–.03

–.002

.000

–.003

–.002

Print news exposure age (I2)

–.03

–.001

.000

–.002

–.001

.08

.01

.000

.008

.010

–.21

–.41

.006

–.419

–.393

.08

.15

.006

.141

.168

.15

.26

.006

.243

.267

Regressions

Lower bound

Upper bound

Political discussion (M)

Age Gender Education Political knowledge (Y) Online news exposure (X1) Print new exposure (X2)

.02

.01

.004

.009

.024

Political discussion (M)

.26

.62

.008

.605

.638

–.001

.000

–.002

–.001

.22

.06

.001

.056

.060

–.19

–.85

.015

–.876

–.816

Education

.16

.73

.015

.704

.763

Indirect Effect 1: X1 ? M ? Y

.06

.10

.002

.094

.103

Indirect Effect 2: X2 ? M ? Y

.05

.06

.001

.054

.059

Total effect

.27

.43

.006

.414

.439

Political discussion age (I3) Age Gender

Conditional indirect effect of online news exposure on political knowledge at specific values of the moderator age 95% CI β

Lower bound

.067

.112

.003

.107

.118

26.40 (mean)

.059

.099

.002

.094

.103

38.68 (M + 1 SD)

.051

.085

.002

.081

.090

.067

.113

.003

.107

.118

.060

.101

.002

.097

.105

.051

.085

.001

.080

.090

.041

.069

.004

.062

.076

.033

.055

.005

.045

.064

.024

.041

.006

.028

.053

.020

.034

.007

.020

.047

Values of the moderator age 18.12 (M

1 SD)

Upper bound

Conditional indirect effect of print news exposure on political knowledge at specific values of the moderator age 95% CI β

Lower bound

.057

.066

.002

.062

.069

26.40 (mean)

.049

.057

.001

.054

.059

38.68 (M + 1 SD)

.042

.048

.001

.045

.051

.057

.066

.002

.062

.069

.050

.058

.001

.055

.061

.041

.048

.001

.045

.051

.033

.038

.002

.034

.042

.025

.028

.003

.023

.033

.017

.019

.003

.013

.025

.013

.015

.003

.009

.021

Values of the moderator age 18.12 (M

1 SD)

Upper bound

Note. Confidence intervals for conditional indirect effects are bias-corrected; Number of bootstrap samples: 1,000; All coefficients were significant at the p < .001 level.

Ó 2017 Hogrefe Publishing

Journal of Individual Differences (2017), 38(1), 21–28

S. Trepte & J. B. Schmitt, Effects of Age on Discussion and Knowledge

Figure 2. Plot of changes in the estimated coefficients for the regression of the dependent variable (political discussion) on the independent variable (print news exposure) at different levels of the moderator (age); unstandardized coefficients; gray area indicates the 95% CI.

Figure 3. Plot of changes in the estimated coefficients for the regression of the dependent variable (political discussion) on the independent variable (online news exposure) at different levels of the moderator (age); unstandardized coefficients; gray area indicates the 95% CI.

To examine the influence of different levels of the moderator on the mediation, we calculated the conditional effects for one standard deviation above and below Journal of Individual Differences (2017), 38(1), 21–28

Figure 4. Plot of changes in the estimated coefficients for the regression of the dependent variable (political knowledge) on the independent variable (political discussion) at different levels of the moderator (age); unstandardized coefficients; gray area indicates the 95% CI.

the arithmetic mean. To further depict how the interplay between news exposure, political discussion, and political knowledge develops with age, we estimated the indirect effects of different values of the moderator variable age (18, 25, 35, 45, 55, 65, 70). As can be seen in Table 1, the indirect effects were consistently positive but decreased with increasing age. The indirect effect of print news exposure through political discussion to political knowledge was nearly two times larger for 18-yearolds (β = .057) than for 45-year-olds (β = .033) and four times larger for 18-year-olds than for 70-year-olds (β = .013). Thus, the probability that an 18-year-old person will link print news exposure with political discussions to finally generate political knowledge is considerably higher than for a 45-year-old or a 70-year-old. The same applies for online news use. The indirect effect was nearly two times larger for 18-year-olds (β = .067) when compared with 55-year-olds (β = .033) and three times larger when compared with 70-year-olds (β = .020). The older people grow, the more they learn directly from news exposure and the less through engaging in political discussion. In line with previous research, we found gender as well as educational level to be relevant covariates. People who are male or highly educated are more likely to have more intense and frequent discussions about politics (Table 1). In addition, they are more likely to know more about politics than less educated or female respondents.

Ó 2017 Hogrefe Publishing

S. Trepte & J. B. Schmitt, Effects of Age on Discussion and Knowledge

Discussion Supporting previous research, we found that news exposure influences political discussion, which, in turn, influences political knowledge. Further, our results demonstrate that this mediation is moderated by age. In particular, younger news users combine print and online news with political discussions to generate political knowledge. We suspect that younger news readers acquire knowledge from news more easily when they get the chance to discuss it with others because in a political discussion, they are more intensely exposed to political content and get the chance to complement their lack of experience in the field of politics (Eveland, 2004). As predicted by the theory of fluid-crystallized intelligence and its current applications, not only knowledge and crystallized abilities but also learning experiences differ significantly across the lifespan (Salthouse, 2003; Schaie, 1996). For example, in our sample, 18-year-olds gave considerably more correct answers to knowledge questions when they reported reading and discussing political topics. The picture was very different for news readers in their 60s for whom previous news reading significantly affected their political knowledge, but for whom the sequence of news reading and political discussion was only marginally important when political knowledge was required.

Limitations Of course the data impose some limitations on our findings. Large sample sizes such as the one applied here are known to inflate the Type I error rate and to increase the chances of achieving statistical significance (Mallinckrodt, Abraham, Wei, & Russell, 2006). However, a large sample can also be seen as a strength as it allows researchers to detect small effects that could not have been found with a smaller sample (Button et al., 2013; Cohen, 1992). On the one hand, some of the effects in our sample were small and should therefore be interpreted with caution. On the other hand, small effect sizes do not necessarily indicate that an effect does not exist or is not important. Due to the cross-sectional nature of the survey, causality could not be measured, and our results could also represent differences between cohorts. Longitudinal studies will be needed to investigate causal effects and the differential evaluation of age versus cohort effects. Another limitation of our study is that we did not measure important covariates such as motivation, political interest, or attention to the news. In previous research, these have been shown to be significantly related to political knowledge (Eveland, 2005).

Ó 2017 Hogrefe Publishing

Conclusion Our research underscores the idea that it is important to apply a lifespan perspective to questions of learning and knowledge acquisition. In particular, we demonstrated for the first time that the previously assumed sequence of news use, political discussion, and political learning considerably applies to younger but not older members of the population. Our research complements the current understanding of news learning. The development of political knowledge is a core task of governments and educational policy. To inspire political learning and to guarantee the sustainability of political knowledge, a psychological lifespan perspective seems crucial. Young adolescents with only marginal experience in political and media landscapes need political discussion as a means to learn the news.

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Eveland, W. P. Jr. (2005). Information processing strategies in mass communication research. In S. Dunwoody, L. B. Becker, G. Kosicki, & D. McLeod (Eds.), The evolution of key mass communication concepts: Honoring Jack McLeod (1st ed., pp. 217–248). New York, NY: Hampton Press. Eveland, W. P. Jr., & Hively, H. M. (2009). Political discussion frequency, network size, and “heterogeneity” of discussion as predictors of political knowledge and participation. Journal of Communication, 59, 205–224. doi: 10.1111/j.1460-2466.2009. 01412.x Eveland, W. P. Jr., & Thomson, T. (2006). Is it talking, thinking or both? A lagged dependent variable model of discussion effects on political knowledge. Journal of Communication, 56, 523–542. doi: 10.1111/j.1460-2466.2006.00299.x Fiske, S. T., & Kinder, D. R. (1986). Involvement, expertise, and schema use: Evidence from political cognition. In N. Cantor & J. F. Kihlstrom (Eds.), Personality, cognition and social interaction (pp. 171–190). Hillsdale, NJ: Erlbaum. Hayes, A. F. (2012). PROCESS: A versatile computational tool for observed variable mediation, moderation, and conditional process modeling. [White paper]. Retrieved from http://www. afhayes.com/public/process2012.pdf Hayes, A. F., & Scharkow, M. (2013). The relative trustworthiness of inferential tests of the indirect effect in statistical mediation analysis: Does method really matter? Psychological Science, 24, 1918–1927. doi: 10.1177/ 0956797613480187 Horn, J. L. (1982)The theory of fluid and crystallized intelligence in relation to concepts of cognitive psychology and aging in adulthood. In F. I. M. Craik & S. Trehub (Eds.), Aging and cognitive processes (pp. 847–870). New York, NY: Plenum Press. Horn, J. L., & Cattell, R. B. (1967). Age differences in fluid and crystallized intelligence. Acta Psychologica, 26, 107–129. doi: 10.1016/0001-6918(67)90011-X Lau, R. R., & Redlawsk, D. P. (2008). Older but wiser? Effects of age on political cognition. Journal of Politics, 70, 168–185. doi: 10.1017/S0022381607080127 Mallinckrodt, B., Abraham, W. T., Wei, M., & Russell, D. W. (2006). Advances in testing the statistical significance of mediation effects. Journal of Counseling Psychology, 53, 372–378. doi: 10.1037/0022-0167.53.3.372 Marcus, B., Bosnjak, M., Lindner, S., Pilischenko, S., & Schütz, A. (2007). Compensating for low topic interest and long surveys: A field experiment of nonresponse in surveys. Social Science Computer Review, 25, 372–383. doi: 10.1177/ 0894439307297606 Nisbet, M. C., & Scheufele, D. A. (2004). Political talk as a catalyst for online citizenship. Journalism & Mass Communication Quarterly, 81, 877–896. doi: 10.1177/ 107769900408100410

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R Core Team. (2015). R: A Language and Environment for Statistical Computing [Computer Software]. Vienna, Austria: R Foundation for Statistical. Retrieved from https://www. R-project.org Rönnlund, M., Nyberg, L., & Bäckman, L. (2005). Stability, growth, and decline in adult life span development of declarative memory: Cross-sectional and longitudinal data from a population-based study. Psychology and Aging, 20, 3–18. doi: 10.1037/0882-7974.20.1.3 Salthouse, T. A. (2003). Interrelations of aging, knowledge and cognitive performance. In U. M. Staudinger & U. Lindenberger (Eds.), Understanding human development. Dialogues with lifespan psychology (pp. 267–287). Norwell, MA: Kluwer Academic. Schaie, K. W. (1996). Intellectual development in adulthood: The Seattle longitudinal study. New York, NY: Cambridge University Press. Singer, E., & Ye, C. (2013). The use and effects of incentives in surveys. The ANNALS of the American Academy of Political and Social Science, 645, 112–141. doi: 10.1177/ 0002716212458082 Smith, J., & Baltes, P. B. (1990). A life-span perspective on thinking and problem-solving. In M. Schwebel, C. A. Maher, & N. S. Fagley (Eds.), Promoting cognitive growth over the life span (pp. 47–69). Hillsdale, NJ: Erlbaum. Trepte, S., & Verbeet, M. (2010). Der Studentenpisa-Test 2009: Idee, Entwicklung, Validierung [The Students-Pisa-Test: Idea, development, validation]. In S. Trepte & M. Verbeet (Eds.), Allgemeinbildung in Deutschland. Erkenntnisse aus dem SPIEGEL-Studentenpisa-Test (pp. 55–71). Wiesbaden: VS Verlag. Yang, J., & Grabe, M. E. (2011). Knowledge acquisition gaps: A comparison of print versus online news sources. New Media & Society, 13, 1211–1227. doi: 10.1177/1461444811401708

Received June 2, 2015 Revision received July 1, 2016 Accepted July 12, 2016 Published online February 10, 2017 Sabine Trepte Department of Media Psychology School of Communication University of Hohenheim Wollgrasweg 23 70599 Hohenheim Germany sabine.trepte@uni-hohenheim.de

Ó 2017 Hogrefe Publishing

Original Article

Grit, Basic Needs Satisfaction, and Subjective Well-Being Borae Jin1 and Joohan Kim2 1

Department of Media Communications, Joongbu University, Gyeonggi, South Korea

Department of Communication, Yonsei University, Seoul, South Korea

Abstract: In this study, we investigated how grit is related to the satisfaction of the basic needs and subjective well-being. Grit means dedication to long-term goals with enthusiasm, which is closely related to success in objective terms. Thus, we expected that grit would be positively related to satisfying the autonomy and competence needs, which would lead to greater subjective well-being (i.e., higher life satisfaction and lower depression). A survey of young adults (N = 455) revealed that grit is strongly related to both the autonomy and competence needs, and these needs mediated the effect of grit on subjective well-being. Grit did not directly increase life satisfaction but weakly decreased depression. Further, the two basic needs played different roles in enhancing subjective well-being. Autonomy reduced depression, and competence increased life satisfaction. Keywords: grit, self-determination theory, autonomy, competence, life satisfaction, depression, subjective well-being

Interviewing with professionals in various fields, Duckworth, Peterson, Matthews, and Kelly (2007) found that highachieving individuals do rarely change or give up their goals, despite difficulties, failures, and boredom. Thus, they claimed grit is the characteristic that those achieving people commonly have, conceptualizing it as “perseverance and passion for long-term goals” (Duckworth et al., 2007, p. 1087). Duckworth et al. (2007) showed that grit was a significant predictor for various types of achievements including adults’ education level, undergraduate grade point average (GPA), cadet’s first summer retention at West Point, and spelling bees’ performance at the national competition. As such, Duckworth and colleagues have demonstrated grit’s predictability for personal success in many professional areas (e.g., Duckworth et al., 2007; Eskreis-Winkler, Shulman, Beal, & Duckworth, 2014). Given its importance in individuals’ achievements in objective terms, then, how about in their subjective wellbeing? The purpose of this study is to answer this question. Also, we view satisfying the needs of autonomy and competence as a mediator for gritty people to be well.

Grit There are multiple constructs, other than grit, related to achievement such as conscientiousness and self-control. Duckworth et al. (2007) tried to distinguish grit from conscientiousness and self-control, but scholars tend to view conscientiousness as a higher-order trait that Ó 2017 Hogrefe Publishing

encompasses self-control, grit, and some others (Ivcevic & Brackett, 2014; Roberts, Lejuez, Krueger, Richards, & Hill, 2014). Conscientious people are then self-controlled and hardworking as well (Roberts et al., 2014). Conscientiousness, however, according to Duckworth et al. (2007), does not necessarily mean seeking and accomplishing long-term goals. Also, while self-control implies resisting temptation and managing impulsivity in a given moment, grit represents pursuing long-term goals by overcoming various hardships (Duckworth et al., 2007). Duckworth emphasized the persistency and consistency in goal pursuit as the distinct feature of grit from other similar constructs (Duckworth & Gross, 2014; Duckworth et al., 2007). Thus, the Grit Scale consists of two dimensions: consistency of interests and perseverance of effort. From the perspective of the hierarchy of goals, every day people have to deal with lower-level goals conflicting with each other (e.g., reading a research paper or celebrity gossips), which is a matter of self-control (Duckworth & Gross, 2014). Grit concerns, in contrast, higher-level goals (e.g., being a prominent psychologist). Therefore, gritty people get over failures in lower-level goals by seeking alternatives so as to keep on pursuing the higher-level, long-term goals (Duckworth & Gross, 2014). Accordingly, it is not surprising that gritty people do not give up on their duties. For instance, grittier soldiers were more likely to complete especially intensive courses; high-school students to graduate; sales persons and teachers to keep their job; and even men to stay married Journal of Individual Differences (2017), 38(1), 29–35 DOI: 10.1027/1614-0001/a000219

B. Jin & J. Kim, Grit, Basic Needs Satisfaction, and Subjective Well-Being

(Duckworth, Quinn, & Seligman, 2009; Eskreis-Winkler et al., 2014). Gritty people also tend to have different strategies for doing their job well. Among National Spelling Bee finalists, grittier spellers spent more time on preparation and preferred to use the least pleasant, yet most effective preparatory activities (i.e., deliberate practice) over more enjoyable ones such as being quizzed and leisure verbal activities (Duckworth, Kirby, Tsukayama, Berstein, & Ericsson, 2010). These grittier competitors surely showed better performance at the competitions.

Grit and Subjective Well-Being It is evident that grit is necessary for achievements, but few studies have examined how grit contributes to subjective well-being. Studies on conscientiousness or self-control may provide clues to infer the relationship between grit and subjective well-being. Duckworth, Weir, Tsukayama, and Kwok (2012) demonstrated that conscientiousness was the only stable predictor – among the Big Five personality traits, emotional stability, and cognitive ability – for both objective and subjective indicators of success. For instance, extraversion was not related to income but rather strongly to life satisfaction; and openness was positively related to positive affect but negatively to life satisfaction. Conscientiousness, however, showed a significant effect in a consistent manner on every success indicator including income, wealth, positive affect, negative affect, and life satisfaction (Duckworth et al., 2012). Similarly, self-control is related to various positive aspects of adjustments such as fewer impulse control problems, lower depression, and higher self-esteem (Tangney, Baumeister, & Boone, 2004). In fact, Von Culin, Tsukayama, and Duckworth (2014) exceptionally examined the relationship between grit and Seligman’s (2002) three facets of happiness: pleasure, meaning, and engagement. They found positive associations of grit with meaning and engagement, but a negative one with pleasure. Von Culin et al. argued that seeking meaning and engagement relates to participating in challenging activities as well as to developing skills and virtues, which require persistent efforts. In contrast, seeking pleasure is less likely related to keeping an interest focused and pursuing long-term goals. Yeager and colleagues (2014), focusing on learning motivation, showed that adolescents high in grit tend to view academic work as not only meaningful to themselves but also worthwhile to others and the world. Also, grittier individuals tended to make attributions in more optimistic ways (Duckworth et al., 2009). These findings indicate that the personality state of grit may be associated with certain types of motivations and attitudes that can increase subjective well-being. Journal of Individual Differences (2017), 38(1), 29–35

Gritty people would have more positive attitudes and expectations about self, life, and the world. These people may also view difficulties, adversities, and misfortunes differently than those low in grit. Thus, we expect that grit would directly increase subjective well-being.

Autonomy and Competence Needs as Mediators We also think grit enhances subjective well-being indirectly and view the satisfaction of basic needs, autonomy and competence in particular, as mediator. That is, grit increases subjective well-being by boosting autonomy and competence that are critical for individuals’ well-being (Reis, Sheldon, Gable, Roscoe, & Ryan, 2000). The basic psychological needs have their origins in self-determination theory (SDT; Deci & Ryan, 1985). As an extensive framework of human motivation and behavior, SDT concerns about why people do what they do. The theory tries to explain how personal and social conditions facilitate or forestall growth and well-being (Deci & Ryan, 1985). In experiencing psychological progress and health, SDT emphasizes the satisfaction of three basic needs: autonomy, competence, and relatedness (Deci & Ryan, 1985). Autonomy refers to behaving upon one’s volition; competence concerns fulfilling one’s capacities; and relatedness involves feeling connected to social network (Deci & Ryan, 2000). Although these three are equally important (Deci & Ryan, 2000), autonomy and competence are of interest in the present study, because the personality trait of grit seems more directly related to the satisfaction of autonomy and competence than of relatedness need. In fact, scholars did not always study all of the three needs at the same time, and whether the needs are considered all together or not, each need tends to show a unique effect on wellness in various contexts (e.g., Hofer & Busch, 2011; Kasser & Ryan, 1999). Studies showed that autonomy promotes subjective wellbeing by enhancing internal energy or vitality (Nix, Ryan, Manly, & Deci, 1999). Thus, Moller, Deci, and Ryan (2006) viewed autonomy as an “antidote” to ego depletion. In the context of SDT, autonomy is often discussed in combination with competence because they both are critical for intrinsic motivation (Deci & Ryan, 1985; Gagné & Deci, 2005). In short, feeling autonomous in doing a job increases competence and thereby improves performance (Black & Deci, 2000). A three-year longitudinal study reported that the students who could more satisfy their basic needs showed better performance and well-being (Sheldon & Krieger, 2007). These results indicate that the satisfaction of the basic needs is essential for subjective well-being. Ó 2017 Hogrefe Publishing

B. Jin & J. Kim, Grit, Basic Needs Satisfaction, and Subjective Well-Being

Aut_p1 Aut_p2 Aut_p3

.62 .78 .72

Grit_p2

.76 .89

Ls_1 .76 Ls_2 .85

-.22(-.21)**

Aut

.60(.62)*** Grit_p1

.84(.84)

***

.85

Ls_3

.77 .78 Ls_4

.01

Ls_5

Grit

.44(.43)

***

Figure 1. Results of SEM analyses. Sex and age were controlled, and standardized coefficients are presented. Coefficients in parentheses are the results of the indirect model. Aut = Autonomy, Comp = Competence, LS = Life Satisfaction, Dep = Depression. *p < .05; **p < .01; ***p < .001 (two-tailed).

*** -.61(-.68)*** -.42(-.42)

.82

-.14*

Grit_p3 .60(.60)

***

Dep Comp .80

Com_p1

.09 (.05)

.77 .81

Com_p3 Com_p2

Therefore, we think that gritty people who can better satisfy their autonomy and competence needs will be more prosperous in their life. Considering the characteristics of grit – perseverance and passion, grittier people would be more vigorous and resilient as well as competent and productive. They may be better able to make their environments more conducive to their basic needs. In addition, studies showed that conscientiousness is associated with intrinsic regulation (i.e., autonomy) for health behavior (Ingledew, Markland, & Sheppard, 2004) and achievement motivation (i.e., competence) for studying (Komarraju & Karau, 2005). These results indicate that conscientious people have higher levels of autonomy and competence, and probably so do gritty people. Taken all together, grit or the mental power to sustain interest in and effort toward long-term goals (Duckworth et al., 2007) should work in ways that gratify the basic psychological needs that are closely related to subjective well-being. Thus, in this study, we posit that grit would be related to the need satisfaction of autonomy and competence, which would in turn increase subjective well-being in terms of life satisfaction and depression. As indicated earlier, we also expect a direct relationship between grit and subjective well-being. These direct and indirect relationships are presented in Figure 1.

Method Participants Participants were Korean adults in their 20s and 30s living in Seoul. Age and residential area were restricted due to the nature of the larger project concerning this survey. Ó 2017 Hogrefe Publishing

.89 .90 .88

Dep_p1

Dep_p3 Dep_p2

These participants were recruited by a research company (embrain.com) in South Korea via an online survey. The online survey system randomly sent an invitation email to 3,680 people among the research pool of about 190,000 people, who were aged from 20 to 39 years living in Seoul. Of those invited, 557 started the online survey, but 39 people were excluded because of the quota ratio of sex and age. In addition, 63 failed to finish or sincerely complete it. The final sample consisted of 455 people (217 men, 238 women) whose mean age was 29.8 years (SD = 5.56).

Measures Grit was measured by using the Grit Scale (Duckworth et al., 2007) which consisted of two 6-item subscales: consistency of interest and perseverance of effort. The former subscale included items such as “I often set a goal but later choose to pursue a different one (reversed),” and “I have difficulty maintaining my focus on projects that take more than a few months to complete (reversed).” The latter subscale included items such as “I finish whatever I begin,” and “Setbacks don’t discourage me.” Translation and back-translation process was iteratively employed by the authors and bilingual students to ensure cross-cultural compatibility. For each item, a 5-point Likert-type scale (1 = not at all like me to 5 = very much like me) was provided. Although the original scale included two subsets of grit, we computed all 12 items into one single score that represents the level of grit (i.e., the higher the score, the grittier) because Duckworth et al. (2007) suggested combining the two sub-factors, and most studies followed it (e.g., Duckworth et al., 2009; Ivcevic & Brackett, 2014; Yeager et al., 2014). Journal of Individual Differences (2017), 38(1), 29–35

B. Jin & J. Kim, Grit, Basic Needs Satisfaction, and Subjective Well-Being

Table 1. Correlations, means, standard deviations, and reliabilities 1

α –

1. Sex

–

2. Age

.07

–

29.80

5.56

–

3. Grit

.11*

.09

–

3.28

0.51

.80

4. Autonomy

.06

.11*

.46***

5. Competence

.05

.12**

.50***

.60*** – .47***

.61*** .65*** –

6. Life satisfaction

.16***

.12**

.35***

.25***

.62***

7. Depression

.06

.04

.40***

.55***

.34***

.39***

.45***

.33***

.63***

3.41

0.60

.74

.71***

.39***

3.50

0.66

.85

– .38***

.41*** –

2.97

0.89

.90

2.09

0.54

.92

Notes. The under diagonal presents correlations of measured variables; the upper diagonal presents correlations of latent constructs with sex and age controlled for. Sex was coded as 1 being male and 2 being female, N = 455. *p < .05; **p < .01; ***p < .001 (two-tailed).

To assess the need satisfaction of autonomy and competence, we used the Basic Psychological Needs Scale for Korean Adolescents (Lee & Kim, 2008) which was developed based on Deci and Ryan’s (1985) SDT. This scale consists of 18 items, of which six autonomy and six competence items were used for this study. Example items are “I feel like I am free to decide for myself how to live my life (autonomy),” and “People I know tell me I am good at what I do (competence).” Also, a 5-point response scale (1 = strongly disagree to 5 = strongly agree) was employed. We used life satisfaction and depression as indicators of subjective well-being. Life satisfaction is a representative measure of well-being, and depression was selected as the opposite aspect of well-being (see Diener, Oishi, & Lucas, 2003). Life satisfaction was measured by Kim’s (2007) Korean version of SWLS (Satisfaction With the Life Scale) that Diener, Emmons, Larsen, and Griffin (1985) originally developed. This scale consisted of five items such as “I am satisfied with my life,” and a 5-point response scale (1 = strongly disagree to 5 = strongly agree) was used. Depression was assessed by Lee and Song’s (1991) Korean version of BDI (Beck Depression Inventory; Beck, 1967). We excluded one item about sex (libido) and thus provided 20 items (e.g., “I feel sad,” “I am disappointed in myself.”) with a 4-point Likert-type scale (1 = not at all to 4 = almost always). Table 1 presents correlations, descriptive statistics, and reliabilities of the variables.

Results We tested the hypothesized research model (Figure 1) using structural equation modeling (SEM) with maximum likelihood estimation (AMOS 21). We created three parcels to avoid too many items (indicators) per latent construct except for the life satisfaction construct. Generally, scholars recommend three or four indicators for a construct (e.g., Little, Cunningham, Shahar, & Widaman, 2002). There are conditions in which parceling is acceptable such as when the analysis focuses on the relationship between Journal of Individual Differences (2017), 38(1), 29–35

constructs rather than individual items (Little et al., 2002). We employed the random parceling technique to create three indicators for the constructs of grit, autonomy, competence, and depression. As for the life satisfaction, all of the five items were included as indicators. We evaluated the normality of indicators by examining skewness and kurtosis. The former was smaller than |0.65|, and the latter was smaller than |0.88|, satisfying the normality assumption. We also provided w2 test, CFI (Comparative Fit Index), TLI (Tucker-Lewis Index), and RMSEA (Root Mean Square Error of Approximation) as model fit criteria. CFI and TLI greater than 0.9 and RMSEA smaller than 0.08 indicate adequate model fit (Kline, 2005). Because sex and age were correlated with the variables of interest (see Table 1), we generated the correlation matrix of all indicators with sex and age partialled out and used it as the input data. The research model (Figure 1) fitted the data well: w2 = 363.9, df = 109, p < .001, CFI = .947, TLI = .934, RMSEA = .072 (90% CI: .064 .080). Grit was positively, relatively strongly related to autonomy (β = .60, p < .001) and competence (β = .60, p < .001). Grit was negatively related to depression (β = .14, p = .038) yet not significantly to life satisfaction (β = .01, p = .842). Autonomy negatively predicted both life satisfaction (β = .22, p = .004) and depression (β = .61, p < .001). The satisfaction of competence need was strongly related to life satisfaction (β = .84, p < .001) but not significantly to depression (β = .09, p = .223). These results suggest the two basic needs mediated the effect of grit on life satisfaction and depression. To determine the significance of the mediating effect of autonomy and competence, we set the two direct paths from grit to life satisfaction and depression as zero. This indirect model also yielded a good fit: w2 = 368.0, df = 111, p < .001, CFI = .947, TLI = .935, RMSEA = .071 (90% CI: .063 .080). Since this indirect model was nested within the original model, we conducted a w2 difference test: Δw2 = 4.16, df = 2, p = .125. This result indicates restricting the direct paths to zero did not worsen the model fit. Thus, the indirect model can be accepted over the original model. Ó 2017 Hogrefe Publishing

B. Jin & J. Kim, Grit, Basic Needs Satisfaction, and Subjective Well-Being

Discussion The aim of this study was to examine the influence of grit on subjective well-being and the mediating role of autonomy and competence needs satisfaction. We viewed the basic psychological needs as an important mediator for grit to have positive effects on well-being. The findings from a survey of young adults indicate that the direct effect of grit on subjective well-being was none or minimal, taking the autonomy and competence into account. Rather, grit satisfied the autonomy and competence needs to a great degree. These two basic needs were then differently related to the two indicators of subjective well-being, life satisfaction and depression. Put it simply, autonomy decreased depression, while competence increased life satisfaction. We expected positive direct relationships between grit and subjective well-being, based on previous evidence (e.g., Duckworth et al., 2012; Von Culin et al., 2014). The previous studies reported that grit or similar constructs (e.g., conscientiousness) are associated with various indicators of subjective well-being such as positive emotions, life satisfaction, and happiness. The results of the present study did not support the significant direct relationship between grit and subjective well-being. Rather, this relationship was fully mediated by the satisfaction of autonomy and competence needs. We posited those mediators, because these needs are important for subjective well-being, and because gritty people may be better able to get the needs satisfied. Grit is essential for making remarkable achievements in one’s profession (Duckworth et al., 2007). Those who are grittier, then, should be more capable of making their productivity and creativity maximized in a given situation. One way of it may involve raising up their competence and autonomy that are fundamental for personal growth (Deci & Ryan, 1985). Regarding subjective well-being, grit fostered life satisfaction mainly by way of increasing competence. Also, grit supported the autonomy need strongly, which in turn decreased depression strongly as well. The competence need was not significantly related to depression, thus it would not deliver the effect of grit on depression. Instead, life satisfaction bolstered by competence may contribute to lessening depression. These findings suggest that grit alone cannot explain subjective well-being. Grit is meaningful for the quality of life in conjunction with the satisfaction of autonomy and competence needs. This is understandable in hindsight because grit could bring down the quality of life if perseverance and persistence prohibit using adoptive and flexible coping strategies in difficult times (Bailly, Joulain, Hervé, & Alaphilippe, 2012). As Duckworth and Gross (2014) emphasized, if flexibility in lower-level goal pursuit is important for grit, gritty people should be flexible in pursuing lower-level goals and be tenacious in pursuing Ó 2017 Hogrefe Publishing

higher long-term goals. Then, future studies should explore what the interplay between tenacity and flexibility is, and how it is related to subjective well-being (see Brandtstädter & Rothermund, 2002). As for the relationship between the basic needs satisfaction and subjective well-being, the effect of each need on life satisfaction and depression was distinct from each other. Autonomy was negatively related to depression and, unexpectedly, life satisfaction as well. Also, the competence need was positively related to life satisfaction but not significantly to depression. Studies generally found that increases in the basic needs satisfaction are associated with increases in well-being (e.g., Reis et al., 2000). In fact, correlations of the present study showed similar results: Autonomy and competence needs were significantly positively correlated with life satisfaction and negatively with depression (see Table 1). However, in the research model in which causal paths were hypothesized, autonomy was negatively related to depression, and competence was not significantly related to depression. These results may be due to controlling for variables. The SEM results indicate, given the same levels of grit and competence, those who are more autonomous may be slightly less satisfied with their life conditions. Also, for those who have the same levels of grit and autonomy, the competence need satisfaction hardly decreases depression. Although we could not clearly explain why we obtained these results, our findings indicate that autonomy and competence needs are intertwined and uniquely important for subjective well-being. In addition, cultural differences may matter. Some scholars argue that basic needs may not be equally important across cultures. Particularly, the autonomy need is important in Western cultures because they value it, whereas Asian cultures value interdependency and relatedness (Smith & Schwartz, 1997). However, many studies showed the importance of autonomy need and its positive association with subjective well-being in Asian cultures too (Chirkov, Ryan, Kim, & Kaplan, 2003). Just the degrees of associations may differ across cultures (Lynch, La Guardia, & Ryan, 2009). Therefore, the relative effects of competence and autonomy needs on life satisfaction and depression may reflect certain aspects of Korean culture. It would be then interesting and meaningful to examine how grit and needs satisfaction contribute to subjective well-being across cultures in future studies. There are limitations to this study. The current findings do not provide any evidence on the causal relationships. It is possible that basic needs satisfaction causes differences in grit. Also, assessing needs satisfaction and subjective well-being at the same time may yield different results than those from longitudinal studies. Therefore, it would be valuable to investigate this relationship in more controlled conditions. Although we used life satisfaction and Journal of Individual Differences (2017), 38(1), 29–35

B. Jin & J. Kim, Grit, Basic Needs Satisfaction, and Subjective Well-Being

depression as indicators of subjective well-being, these two variables may not comprehensively represent individuals’ subjective well-being. Examining other indicators such as positive and negative affect would be beneficial. In addition, the grit scale has not yet been validated for Koreans, and the sample consisted of relatively young people only. Despite these limitations, this study contributes to understanding the importance of basic needs satisfaction in the link between grit and well-being. Grittier people are more capable of satisfying their needs of autonomy and competence, which improves the quality of life.

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Reis, H. T., Sheldon, K. M., Gable, S. L., Roscoe, J., & Ryan, R. M. (2000). Daily well-being: The role of autonomy, competence, and relatedness. Personality and Social Psychology Bulletin, 26, 419–435. doi: 10.1177/0146167200266002 Roberts, B. W., Lejuez, C., Krueger, R. F., Richards, J. M., & Hill, P. L. (2014). What is conscientiousness and how can it be assessed? Developmental Psychology, 50, 1315–1330. doi: 10.1037/a0031109 Seligman, M. E. (2002). Authentic happiness. New York, NY: Free Press. Sheldon, K. M., & Krieger, L. S. (2007). Understanding the negative effects of legal education on law students: A longitudinal test of self-determination theory. Personality and Social Psychological Bulletin, 33, 883–897. doi: 10.1177/ 0146167207301014 Smith, P., & Schwartz, S. (1997). Values. In J. Berry, M. Segall, & C. Kagitcibasi (Eds.), Handbook of cross-cultural psychology (Vol. 3): Social behavior and applications (2nd ed., pp. 78–118). Needham Heights, MA: Allyn & Bacon. Tangney, J. P., Baumeister, R. F., & Boone, A. L. (2004). High selfcontrol predicts good adjustment, less pathology, better grades, and interpersonal success. Journal of Personality, 72, 271–324. doi: 10.1111/j.0022-3506.2004.00263.x

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Von Culin, L. R., Tsukayama, E., & Duckworth, A. L. (2014). Unpacking grit: Motivational correlates of perseverance and passion for long-term goals. Journal of Positive Psychology, 9, 306–312. doi: 10.1080/17439760.2014.898320 Yeager, D. S., Henderson, M. D., Paunesku, D., Walton, G. M., D’Mello, S., Spitzer, B. J., & Duckworth, A. L. (2014). Boring but important: A self-transcendent purpose for learning fosters academic self-regulation. Journal of Personality and Social Psychology, 107, 559–580. doi: 10.1037/a0037637 Received June 25, 2015 Revision received May 13, 2016 Accepted June 29, 2016 Published online February 10, 2017 Joohan Kim Department of Communication Yonsei University 50 Yonsei-ro, Seodaemun-gu Seoul 03722 South Korea jkim@yonsei.ac.kr

Journal of Individual Differences (2017), 38(1), 29–35

Original Article

Why Does Digit Ratio Research Fail to Give Any Implication Regarding the Organizational Effect of Prenatal Androgen? Larry Au Yeung1 and Wai S. Tse2 1

Department of Psychology, The Chinese University of Hong Kong, Shatin, N.T., Hong Kong

Department of Educational Psychology, The Chinese University of Hong Kong, Shatin, N.T., Hong Kong

Abstract: The digit ratio is a putative biomarker for evaluating the organizational effects of prenatal testosterone. This evaluation was performed by relating postnatal traits to digit ratio. We examined the relationship among digit ratio, depression, and positive/negative affect. A total of 335 university students who completed a set of questionnaires had both of their hands scanned, and the digit ratios were measured using a computer program. All the studied variables were insignificantly related to the right-hand digit ratio. The variables remained insignificant even when the data for males and females were analyzed separately. Furthermore, a meta-analysis, including a previous study combined with current data, showed no association between digit ratio and depression, although the current sample size of 355 could detect r = 0.2 at α = 0.05, and β = 0.2. The lack of association between digit ratio and depression was common, and the present results corroborated those of previous studies, which showed no association between digit ratio and depression. This nil result would be least likely attributable to an inadequate sample size, considering that the current sample size of 335 allowed the detection of r = 0.2 at α = 0.05 and β = 0.2, nor idiosyncratic results, given that the meta-analysis with previous relevant studies also concluded the same results. We extensively reviewed the relevant literature and evaluated the use of digit ratio as a biomarker for prenatal testosterone exposure in seven different perspectives. Nearly all the analysis showed the problems of using digit ratio as a biomarker for evaluating the organizational effect of prenatal hormones. Keywords: digit ratio, depression, androgen

Digit ratio (2D:4D) is the length of the second (index) finger divided by the length of the fourth (ring) finger. This ratio is proposed to be a lifelong signature of prenatal hormonal exposure and is a noninvasive alternative for measuring prenatal testosterone exposure (Manning, Bundred, Newton, & Flanagan, 2003). In adults, circulating hormones activate previously built neural systems and mediate specific behaviors; this effect is called “activation.” However, exposure to androgen during critical periods of fetus development organizes the development of neural systems, which exert long-term effects. This effect is referred to as “organizational” because prenatal high androgen exposure builds a masculinized brain structure, whereas low exposure results in a feminized structure (Phoenix, Goy, Gerall, & Young, 1959). Research involving rodents demonstrated the following results. (1) Sex hormone is involved in both physiological and behavioral sexual differentiation (Cohen-Bendahan, van de Beek, & Berenbaum, 2005). (2) The critical period Journal of Individual Differences (2017), 38(1), 36–45 DOI: 10.1027/1614-0001/a000220

of sexual differentiation occurs when the difference in sex hormones reaches its maximum (Collaer & Hines, 1995). The male fetal testosterone level surges between 8 and 24 weeks of gestation and peaks at around week 16 (Auyeung, Lombardo, & Baron-Cohen, 2013; Clements, Reyes, Winter, & Faiman, 1976). By contrast, the female testosterone level remains low throughout pregnancy (Hines, 2004). Therefore, the organizational effect of androgen occurs within this period of gestation. However, administering testosterone in human fetuses incurs an ethical issue. Thus, the best approach to test the organizational effects of prenatal androgen exposure on adult behavior is to conduct a prospective longitudinal study. The androgen level in amniotic fluid should be measured via amniocentesis during the second trimester of pregnancy, which overlaps with the suggested critical organizational period. Then, the androgen level is correlated with the behavior of the participants when they become adults. However, conducting a large-scale study is infeasible under Ó 2017 Hogrefe Publishing

L. Au Yeung & W. S. Tse, Why Does Digit Ratio Research Fail

a prospective longitudinal study design because of the time involved. The digit ratio is a putative retrospective alternative for measuring prenatal androgen stimulation, and adult behavior is readily accessible. Thus, examining the correlation between digit ratio and adult behavior provides a rapid and convenient method to understand the organizational effects of prenatal androgen exposure on human behavior (Breedlove, 2010). Sexually dimorphic traits organized by prenatal testosterone are suggested to be correlated with the within-sex digit ratio (Austin, Manning, McInroy, & Mathews, 2002). In general, feminized/masculinized digit ratio (i.e., larger/smaller) has been associated with traits or disorders prevalent among both sexes (Putz, Gaulin, Sporter, & McBurney, 2004). Depression has been demonstrated as a sexually dimorphic trait (Endler, Macrodimitris, & Kocovski, 2000; Piccinelli & Wilkinson, 2000). Women are more susceptible to stressors, report depression more frequently, and exhibit more depressive symptoms than men. The risk and lifetime prevalence of a major depressive disorder are twice among females compared with those of males (Nolen-Hoeksema, 2001). Testosterone is suggested to act as an antidepressant during adulthood (Zarrouf, Artz, Griffith, Sirbu, & Kommor, 2009); however, the function of testosterone during prenatal period remains unclear. Therefore, studies on digit ratio may verify whether prenatal testosterone on prenatal organizational effect on the nervous system exerts any preventive effect against depression in the later course of life. We expect that a higher (feminized) digit ratio, which reflects low prenatal testosterone exposure, is correlated with higher depression level within each gender group and the sample of the whole groups. However, previous research that related depression to digit ratio yielded inconsistent results. Martin, Manning, and Dowrick (1999) found an insignificant relationship between digit ratio and depression in men. Austin et al. (2002) also failed to show a significant relationship between the two factors. Bailey and Hurd (2005) found that males with higher (feminized) digit ratios demonstrated higher depression scores; however, no such relationship was found in women. Smedley, McKain, and McKain (2014) determined a significant association between digit ratio and depression scores in the entire sample and the female subsample but not in the male subsample. The present study examined the relationship between digit ratio and depression by using the depression subscale of the Depression Anxiety Stress Scale (DASS; Lovibond & Lovibond, 1995). The relationship of positive affect (PA) and negative affect (NA) with digit ratio was also examined, given that both PA and NA predicted depression; high levels of depression were associated with low levels of PA and high levels of NA (Crawford & Henry, 2003). Females Ó 2017 Hogrefe Publishing

were found to exhibit higher NA and lower PA than males across different studies (Crawford & Henry, 2004; Fujita, Diener, & Sandvik, 1991). In summary, the current study hypothesized that the feminized digit ratio would be associated with higher depression and NA scores but lower PA scores. Furthermore, the present study examined the validity of digit ratio in the discussion. This study is the first to reflect the validity of digit ratio from seven different perspectives by collecting current research findings and analyzing problems in the classic study by Lutchmaya, Baron-Cohen, Raggatt, Knickmeyer, and Manning (2004), which is frequently cited to provide empirical data to support the use of digit ratio as a biomarker for prenatal testosterone exposure.

Methods Participants A total of 335 university students (138 males and 197 females) from a public university in Hong Kong were recruited for the study. Among them, 200 participants (59.701%) were undergraduate students, 115 (34.328%) were postgraduate students, and 20 (5.979%) were high school students. The age of the participants ranged from 17 to 35 years, with a mean age (SD) of 21.97 (2.75). To minimize type II error caused by extreme cases, we included previous or current history of psychiatric illness and current physical illness in our exclusion criteria. None of the participants was excluded from the study because of these criteria. All the volunteers provided written consent. We found that the 335 participants could detect r 0.15 at α = .05 and β = .20 by using the power calculator provided by Kohn, Jarrett, and Senyak (2016).

Measure Questionnaires The depression subscale of the Depression Anxiety Stress Scale (DASS-D; Lovibond & Lovibond, 1995) was adopted to measure depression level. DASS-D is a seven-item selfreported scale, and each item is rated on a four-point Likert scale ranging from 0 to 3. The Cronbach’s α for DASS-D in the current study is .88. The Positive and Negative Affect Scale (PANAS; Watson, Clark, & Tellegen, 1988) is a 20-item self-report inventory on a five-point Likert scale that assesses PA and NA in the past 2 weeks based on common mood descriptors (e.g., for PA: “interested” and “alert”; for NA: “upset” and “nervous”; α = .86 and .87, respectively, for the present study). Journal of Individual Differences (2017), 38(1), 36–45

L. Au Yeung & W. S. Tse, Why Does Digit Ratio Research Fail

Table 1. Gender differences on digit ratios, depression, positive and negative affects Male (n = 138) Variable

Female (n = 197)

Right digit ratio

0.963

0.043

0.971

0.044

Left digit ratio

0.957

0.034

0.969

0.040

DASS-D

4.080

4.029

3.193

32.775

6.609

26.891

7.836

t(1, 333)

Cohen’s d value

2.840

.005**

0.323

1.582

.115

0.184

3.615

2.108

.036*

0.231

33.593

6.433

1.133

.258

0.125

26.005

6.867

1.096

.274

0.120

Note. *p < .05; **p < .01 (two-tailed).

Digit Ratio Measurement Both hands of each participant were scanned using a portable scanner (Canon LiDE 120), and the digit ratios were measured using Adobe InDesign CS5 with 500% magnification. Ten random samples of the right-hand 2D and 4D were selected and rated by another research assistant to determine inter-rater reliability. The intra-class correlations based on average measures and absolute agreement ranged from 0.792 [F(1, 9) = 4.606; p = .016] to 0.866 [F(1, 9) = 7.235; p = .003].

Procedure The study was approved by the University Ethics Committee. Students were recruited from university cafeterias and libraries by using flyers. Upon arrival at the research laboratory, volunteers provided informed consent. The volunteers were asked to fill in a set of questionnaires containing scales that concerned demographic information, depression, and affects. After the participants completed the questionnaires, both of their hands were scanned using a Canon LiDE 120 scanner to determine the lengths and digit ratios of the left- and right-hand 2D and 4D.

Statistical Analysis Student’s t-test was performed to examine gender differences on the target variables. Three different sets of Pearson’s correlation were conducted to examine the relationship between right-hand digit ratio and target variables in the whole sample, male-only sample, and female-only sample. A meta-analysis was conducted as described by Hunter and Schmidt (2004), including previously relevant studies.

Result Gender Difference On the average, the right-hand digit ratio of males was significantly lower than that of females (Table 1). Moreover, the left-hand digit ratio of males was not significantly lower Journal of Individual Differences (2017), 38(1), 36–45

Table 2. Pearson’s correlation between right-hand digit ratio and the studied variables Predictor

Outcome variables

Right-hand digit ratio of the entire sample

DASS

.02

.79

.02

.76

.04

.44

DASS

.04

.66

.00

.96

.10

.27

DASS (female)

.03

.67

PA (female)

.04

.58

NA (female)

.01

.91

Right-hand digit ratio (male)

Right-hand digit ratio (female)

than that of females. In addition, no significant difference in both PA and NA between males and females was observed (Table 1). Unexpectedly, the male participants were found to be significantly more depressed than their female counterpart (Table 1).

Relationship Among Right-Hand Digit Ratio, Depression, as Well as PA and NA Pearson’s correlation was conducted in the whole sample; through the correlation, we found that the right-hand digit ratio was neither associated with depression, PA, nor NA scores. The same results were observed when analyses were conducted in male-only and female-only samples (Table 2).

Meta-Analysis on the Relationship Between Right-Hand 2D:4D Ratio and Depression Four previous studies that examined the relationship between right-hand 2D:4D ratio and depression were identified and are summarized in Table 3. Meta-analysis that included these four studies and the present results was conducted. The results are presented in Table 4. We found no significant association between right 2D:4D ratio and depression in the total sample, male-only sample, and female-only sample. Ó 2017 Hogrefe Publishing

This study

Smedley et al. (2014)

336 university Scanning students (135 males and 201 females)

Photocopier

Bailey and Hurd (2005) Scanning

CESD

201 DASS – depression subscale .969

.068 r = .213

135 r = .041 .696

.405 r = 0.120

335 r = 0.020

.004

r = .022

Current study

r = .253

.822

BDI-II 77 .017 51 r = .274 .724 128 r = .005 r = .244

0.51

NEO-PI 149 .083 149 r = .002 298 r = 0.17 NA NA C

.004

SDS 86 .16 79 r = .16 .22 0.14 165 r = .067 r = .03 B

Study

Austin et al. (2002) Vernier callipers

Vernier callipers

102 depressed and nondepressed residents (52 men and 50 women) 165 undergraduate students (79 male, 86 female) 298 students (149 males and 149 females) 128 undergraduate students (51 males and 77 females) Right-hand digit ratio BDI 50 .95 .09 52 b = .024 2.46 102 b = NA A

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Discussion

Measurement method No. of participants Hand Scale n p-value Effect Study

p-value Effect Effect p-value

Analysis of females Analysis of males Analysis of entire population

Table 3. Summary of the five studies of their relationship between right-hand 2D:4D ratio and depression for meta-analysis

Martin et al. (1999)

L. Au Yeung & W. S. Tse, Why Does Digit Ratio Research Fail

Findings based on our sample showed no significant association between moods and digit ratios that might reflect the underlying lack of association among depression, PA and NA, and prenatal testosterone exposure effects on prenatal organization effects. Debatably, the lack of association could be attributed to the small sample size of the current studies. However, 355 participants could detect r = 0.20 at α = 0.05 and β = 0.20. To further confirm that this lack of association was not an idiosyncratic result, a meta-analysis that included four previous studies was conducted, which also showed no significant association between the right-hand digit ratio and depression scores. This lack of association can also be explained by the fact that the digit ratio is not a suitable biomarker for prenatal testosterone exposure, as proposed by Breedlove (2010). Seven arguments were presented to advocate rethinking of the use of digit ratio as an alternative measurement for prenatal androgen effects. The present findings replicated those observed in previous studies in Chinese samples, which showed that young male adults were more likely to be depressed than female (Sun, Buys, & Wang, 2011; Wang, Sun, An, Hao, & Tao, 2013). However, a recent meta-analysis showed the lack of gender difference in depression (Lei, Xiao, Liu, & Li, 2016). Notably, in the meta-analysis that concluded the lack of gender difference in depression, over half of the studies were not included in the gender analysis (Lei et al., 2016). Meanwhile, 11 out of the remaining 19 studies reported male adults had higher depression prevalence rate than female adults. In addition, more studies on gender difference in depression were reported in Chinese written journals, which might lead to bias in the meta-analysis results. Thus, the conclusion of lack of gender difference remains uncertain. In a single-child policy, male children would experience more academic pressure compared with female children, and thus, would be more vulnerable to depression. Furthermore, with a skewed gender population, which contained more males than females, young male adults would experience more difficulties in finding a lifelong partner. Therefore, males are more vulnerable to depression than females in the Chinese population (Liu, Li, & Feldman, 2013).

Absence of Within-Sex Analysis and Inappropriate Use of Covariate First, the issue is related to the importance of within-sex analysis and the problem of statistical control of sex effect in a study involving amniotic fluid testosterone and digit ratio of the frequently cited classic study conducted by Journal of Individual Differences (2017), 38(1), 36–45

L. Au Yeung & W. S. Tse, Why Does Digit Ratio Research Fail

Table 4. Results of meta-analysis examining the relationship between right-hand 2D:4D ratio and depression based on total sample, maleonly sample and female-only sample using Hunter and Schmidt (2004)’s method No. of studies

(A)

Pooled correlations

Total

0.06927504

Male

0.021835749

Female

0.084594542

Lutchmaya et al. (2004). According to the Web of Science, this classic study has been cited 373 times as of 2015. The aforementioned study demonstrated that the digit ratio of 33 children, measured at age 2, was negatively correlated to the ratio of prenatal testosterone and estradiol levels obtained from the amniotic fluids of mothers, as measured during the second trimester of pregnancy. The result remains significant with the statistical control of the effect of sex. To test the relationship between prenatal testosterone and digit ratio, within-sex analysis is necessary because male fetuses produce more than 2.5 times the levels observed in female fetuses (Beck-Peccoz et al., 1991; Finegan, Bartleman, & Wong, 1989), and a false relation can emerge when data from males and females are pooled together (Constantinescu & Hines, 2012; Reichardt & Bormann, 1994). However, within-sex analysis was not adopted in the study of Lutchmaya et al. (2004). Instead, the authors applied multiple regression to “remove” the effect of sex when sex was a correlated covariate with treatment groups (i.e., the level of prenatal testosterone exposure was dependent on sex), which was suggested to be an incorrect method (Evans & Anastasio, 1968; Lee & Lee, 1989; Thompson, 1992; Suckling, 2011) that would lead to unpredictable results and false conclusions. Miller and Chapman (2001) discussed in detail the inappropriate statistical control of pretreatment group difference and suggested that “the pooled regression is inappropriate as a basis for ‘correcting’ for the covariate” (p. 40). In addition, no statistical mean exists to accomplish this “control” (Lord, 1969). Miller and Chapman (2001) illustrated how this method was inappropriate for controlling gender differences. We summarized the ideas of these researchers and applied them to explain the inappropriateness of the statistical method to remove the effect of sex in the analysis conducted by Lutchmaya et al. (2004) in the following section. Applying the idea of Miller and Chapman (2001), we illustrated the effects of controlling “sex” under the true experiment (Figure 1A) and quasi-experiment (Figure 1B), which suggested that two possible relationships existed between the treatment groups (Grp) (e.g., testosterone administration in the true experiment or testosterone level in amniotic fluid in the quasi-experiment), covariate (COV) Journal of Individual Differences (2017), 38(1), 36–45

(B)

Figure 1. Two possible relationships among the treatment group (Grp.), covariate (COV), and dependent variable (DV) (adopted from Miller & Chapman, 2001). (A) True experiment; (B) Quasi-experiment.

(e.g., sex), and dependent variable (DV) (e.g., digit ratio). The darkened overlapping gray areas indicated shared variance and nonzero correlation. In a true experimental design with random assignment (Figure 1A), the variances are not overlapping between covariate (COV) and treatment (Grp), which indicates that treatment is independent from the covariate. In the regression analysis that controlled for COV (e.g., sex), the areas shared by COV and Grp were removed; consequently, Grp was equal to Grp res (in the right panel: Area 3 + 6). The only effect would be the removal of certain variances from the dependent variable (DV) (Area 4), which was simply noise/error to Grp. Accordingly, Grp was correlated more highly with DV res than with DV. A larger effect size was obtained. This method renders the removal of covariate using a legitimate and an appealing noise reduction technique (Miller & Chapman, 2001). However, in a quasi-experiment (Figure 1B) similar to that conducted by Lutchmaya et al. (2004), variances were overlapped among COV, DV, and Grp. In the regression analysis that controlled for COV (sex), part of the variance from Grp (Areas 2 and 5) would be removed in addition to Ó 2017 Hogrefe Publishing

L. Au Yeung & W. S. Tse, Why Does Digit Ratio Research Fail

the variance of noise from DV (Area 4). This approach leads to Lordâ&#x20AC;&#x2122;s paradox (Lord, 1969), and the regression adjustment may produce a spurious association between digit ratio and hormonal data (Elashoff, 1969).

(A)

Assumption of Testosterone in Amniotic Fluid as a Good Alternative The general assumption is that testosterone in amniotic fluid is a good alternative for monitoring testosterone in fetal blood (Lutchmaya et al., 2004; van de Beek, Thijssen, Cohen-Kettenis, van Goozen, & Buitelaar, 2004). However, Rodeck, Gill, Rosenberg, and Collins (1985) demonstrated the lack of significant association between testosterone measured in amniotic fluid and fetal plasma in fetuses between 15 and 23 weeks of gestation. This finding limited the validity of the use of amniocentesis to evaluate the hormonal organizational effect in fetuses during the prenatal period (Finegan et al., 1989; Judd, Robinson, Young, & Jones, 1976). Further investigation is necessary to demonstrate a direct relationship between hormonal levels in amniotic fluid and fetal blood to confirm that testosterone level in amniotic fluid can be an effective index of hormonal organizational effect, thereby challenging the assumption that digit ratio can reflect prenatal androgen effects.

(B)

(C)

Digit Ratio Is Insufficiently Sensitive for Practical Use Digit ratio cannot be easily interpreted as the sole effect of androgen (Dean & Sharpe, 2013). It can be related to the ratio of testosterone to estradiol in amniotic fluid or amniotic fluid testosterone. However, whether digit ratio is related to the ratio between testosterone and estradiol or testosterone alone remains unclear. Moreover, in the study of Lutchmaya et al. (2004), the ratio of testosterone to estradiol in amniotic fluid could be explained by 27% variance in the right-hand digit ratio, which left 73% residual variance. Therefore, the use of digit ratio as a surrogate index of prenatal testosterone exposure is problematic. The Venn diagram in Figure 2A illustrates a hypothetical situation in which prenatal testosterone explains most of the variance of digit ratio (i.e., > 80%). The figure shows that the variance of the studied trait overlapping with digit ratio may also overlap with the variance of prenatal testosterone. However, if prenatal testosterone is moderately associated with digit ratio, which only explains approximately 30% of the variance of digit ratio, then the situations in Figures 2B and 2C show resemblance. In the situation represented by Figure 2B,

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Figure 2. Three hypothetical situations in which digit ratio explains the variance of prenatal testosterone exposure mostly (A) or minimally (B and C). (A) Large overlapping variance; (B) Moderate overlapping in variances with all of the three were overlapping; (C) Moderate overlapping in variance but they are not all overlapping with each other.

digit ratio, prenatal testosterone, and the studied trait were interrelated to one another. In the scenario represented by Figure 2C, digit ratio is suggested to be related to prenatal testosterone and the studied trait. However, no relationship is observed between prenatal testosterone and the studied trait (Constantinescu & Hines, 2012). Whether the associative data of digit ratio represents the situation in Figure 2B or Figure 2C is difficult to determine under a moderate correlation coefficient.

Journal of Individual Differences (2017), 38(1), 36â&#x20AC;&#x201C;45

Lack of Converging Evidence From Androgen Receptor Gene Studies Exon 1 of the androgen receptor (AR) gene contains a variable number of cytosine-adenine-guanine (CAG) repeats. Long CAG repeats constitute loss-of-function mutation, which is suggested to reduce AR transcriptional activity, and thus, increase digit ratio (Hönekopp, 2013). However, a meta-analysis based on 18 retrievable studies (N = 2,909) did not support this prediction. It reported no significant association between the length of CAG repeats and digit ratio on both hands (Voracek, 2014) despite the influences of CAG polymorphism on androgenicity in various tissues and psychological traits among men being well documented (Singh, Singh, & Thangaraj, 2007; Zitzmann, 2009). In addition, two large-scale genome-wide association studies (N = 979 and N = 3,659) (LawranceOwen et al., 2013; Medland et al., 2010) found similar results. Together, these results cast doubt on the use of digit ratio as a biomarker for prenatal testosterone exposure.

Developmental Issue and Sexual Dimorphisms of Digit Ratio Inconsistent Degree of Sexual Dimorphism If digit ratio is a biomarker for prenatal testosterone level, then the magnitude of gender difference in prenatal testosterone should be proportioned to that in digit ratios (Dressler & Voracek, 2011). Finegan et al. (1989) reported that gender differences in prenatal testosterone level were extremely large (d = 2.7), and the means (SD) between the two groups were nonoverlapping (Judd et al., 1976). However, the meta-analysis of Hönekopp and Watson (2010) indicated that gender difference in the right-hand digit ratio was only moderate (d = 0.46), and the means (SD) of digit ratio between males and females were highly overlapping (Knickmeyer, Woolson, Hamer, Konneker, & Gilmore, 2011). Postnatal Instability of Digit Ratio One of the assumptions for using digit ratio as a biomarker for prenatal testosterone exposure is that digit ratio is independent of postnatal influences (Manning, Scutt, Wilson, & Lewis-Jones, 1998). However, the postnatal developmental path of digit ratio is not as stable as it has been assumed. Two longitudinal studies reported that digit ratios increased from infancy to adulthood (McIntyre, 2006; Trivers, Manning, & Jacobson, 2006). Moreover, a longitudinal study that focused on digit ratio during the time overlapped with postnatal testosterone surge (0–2 years old) found that the interaction of salivary testosterone at 3 months and CAG repeats predicted the right-hand digit ratio at 12 months. This result suggests that digit ratio is not as Journal of Individual Differences (2017), 38(1), 36–45

L. Au Yeung & W. S. Tse, Why Does Digit Ratio Research Fail

stable as it was believed to be and reflects both neonatal and prenatal testosterone exposure (Knickmeyer et al., 2011).

Research on Hormonal-Transfer Hypothesis Cannot be Used to Validate Digit Ratio Research on digit ratios typically uses studies related to hormonal-transfer hypothesis, which suggests that the perfusion of amniotic fluid testosterone from male fetuses to neighboring female fetuses in the opposite sex (OS) twin situation and OS twins to provide evidence for the effects of prenatal testosterone exposure on digit ratio: females from OS dizygotic twin pairs present lower (masculinized) 2D:4D compared with females from samesex (SS) dizygotic twin pairs (van Anders, Vernon, & Wilbur, 2006). Despite several small-scale studies reporting significant differences (van Anders et al., 2006; Voracek & Dressler, 2007), most of the results showed no difference in digit ratio between OS and SS twins. Medland, Loehlin, and Martin (2008) found no difference in digit ratio among 867 OS twins and SS siblings. Similarly, Hiraishi, Sasaki, Shikishima, and Ando (2012) reported no significant difference in digit ratio between female twins from OS and SS pairs. The finding agrees with the results reported by Cohen-Bendahan (2005), who found no significant difference in digit ratio in a group of female twins from the Netherlands where 29 were from OS pairs and 26 were from SS pairs.

Equivocal Evidence From Clinical Samples to Support Digit Ratio Patients with complete androgen insensitivity syndrome (CAIS) present no effective androgen exposure in utero because of absent or dysfunctional androgen receptors and are suggested to present feminine digit ratios (Breedlove, 2010). However, XY women with CAIS show modestly higher digit ratios than male controls (d = 0.61, p < .04), and their digit ratios were insignificantly different from those of female controls, who present considerably higher levels of androgen exposure compared with individuals with CAIS (Berenbaum, Bryk, Nowak, Quigley, & Moffat, 2009). Congenital adrenal hyperplasia (CAH) is a condition that exposes fetuses to elevated levels of androgens before birth. The largest study on CAH and digit ratio indicated that the digit ratio in 66 females with CAH was not more masculinized than those in 69 female controls (Buck, Williams, Hughes, & Acerini, 2003). Regardless of this finding, a meta-analysis of four existing studies showed that Ó 2017 Hogrefe Publishing

L. Au Yeung & W. S. Tse, Why Does Digit Ratio Research Fail

individuals with CAH presented masculinized digit ratios compared with control individuals (Hönekopp & Watson, 2010). These studies support the relationship between digit ratio and androgen. However, one concern is that patients with CAH can exhibit complex hormonal changes and have received chronic treatments that may have altered the development of digit ratio (Dean & Sharpe, 2013; Speiser & White, 2003). Nevertheless, studies on CAH patients appear to be the only remaining evidence of digit ratio.

Limitation The present study did not find any significant association between digit ratio and depression, and this association would be least likely attributable to an inadequate sample size or an idiosyncratic result. However, this finding might be attributable to the specific characteristics of the sample in the present study; hence, the participants were all recruited from a single university. In addition, the convenient sampling method would limit the validity of the conclusion. Furthermore, the reliability of digit ratio was based on ten random samples of the participants, which might limit the reliability of the measurement. However, intra-class correlation reached satisfactory levels at ICC = 0.792. Nevertheless, the present finding replicates previous results based on a sample of Chinese university students and provides support for the validity of the data.

Conclusion Over recent decades, numerous research findings reported a significant relationship between digit ratio and behavior (e.g., personality and mood). Echoing other previous meta-analyses, the present study did not replicate findings from previous studies and showed that digit ratio was not associated with mood. While analyzing seven arguments that support the use of digit ratio as a putative biomarker for prenatal testosterone exposure, nearly all the arguments were found to present a stronger counterargument to question the assumption behind the use of digit ratio to reflect the organizational effects of prenatal testosterone exposure. Our current results and analyses cast doubt on the validity of using digit ratio to serve as a biomarker for organizational effect of prenatal androgen exposure. Additional biological evidence of the organizational effect of prenatal androgen exposure is valuable to evaluate the basic principle of the organizational effect. For example, medial preoptic nucleus (MPON) was found to be larger in rats exposed to higher testosterone during prenatal Ó 2017 Hogrefe Publishing

period (Gorski, Gordon, & Shryne, 1978). Accordingly, we can determine whether a relationship between digit ratio and MPON size exists in human beings; and if existent, whether such relationship is more influenced by plasma testosterone level. This comparative study will help evaluate the extent to which digit ratio can serve as the key marker for organizational effects. Acknowledgments We would like to thank Kelvin Tsoi to conduct the metaanalysis for this study.

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Psychology: An International Quarterly, 13, 3–18. doi: 10.1080/ 027027192130101 Trivers, R., Manning, J., & Jacobson, A. (2006). A longitudinal study of digit ratio (2D:4D) and other finger ratios in Jamaican children. Hormones and Behavior, 49, 150–156. doi: 10.1016/ j.yhbeh.2005.05.023 van Anders, S. M., Vernon, P. A., & Wilbur, C. J. (2006). Finger-length ratios show evidence of prenatal hormonetransfer between opposite-sex twins. Hormones and Behavior, 49, 315–319. doi: 10.1016/j.yhbeh.2005.08.003 van de Beek, C., Thijssen, J. H., Cohen-Kettenis, P. T., van Goozen, S. H., & Buitelaar, J. K. (2004). Relationships between sex hormones assessed in amniotic fluid, and maternal and umbilical cord serum: What is the best source of information to investigate the effects of fetal hormonal exposure? Hormones and Behavior, 46, 663–669. doi: 10.1016/j.yhbeh. 2004.06.010 Voracek, M. (2014). No effects of androgen receptor gene CAG and GGC repeat polymorphisms on digit ratio (2D:4D): A comprehensive meta-analysis and critical evaluation of research. Evolution and Human Behavior, 35, 430–437. doi: 10.1016/ j.evolhumbehav.2014.05.009 Voracek, M., & Dressler, S.G. (2007). Digit ratio (2D:4D) in twins: Heritability estimates and evidence for a masculinized trait expression in women from opposite-sex pairs. Psychological Reports, 100, 115–126. doi: 10.2466/pr0.100.1.115-126 Wang, X., Sun, Y., An, J., Hao, J. H., & Tao, F. B. (2013). Gender difference on depressive symptoms among Chinese children and adolescents. Zhonghua, Liu Xing Bing Xue Za Zhi, 34, 893–896. https://www.ncbi.nlm.nih.gov/pubmed/24331965. Watson, D., Clark, L. A., & Tellegen, A. (1988). Development and validation of brief measures of positive and negative affect: The PANAS scales. Journal of Personality and Social Psychology, 54, 1063–1070. doi: 10.1037/0022-3514.54.6.1063 Zarrouf, F. A., Artz, S., Griffith, J., Sirbu, C., & Kommor, M. (2009). Testosterone and depression: Systematic review and meta-analysis. Journal of Psychiatric Practice, 15, 289–305. doi: 10.1097/01.pra.0000358315.88931.fc Zitzmann, M. (2009). The role of the CAG repeat androgen receptor polymorphism in andrology. Frontiers of Hormone Research, 37, 52–61. doi: 10.1159/000175843 Received February 4, 2016 Revision received July 25, 2016 Accepted August 2, 2016 Published online February 10, 2017 Wai S. Tse Department of Educational Psychology The Chinese University of Hong Kong Shatin, N.T. Hong Kong tsewai11@hotmail.com

Journal of Individual Differences (2017), 38(1), 36–45

Original Article

The General Factor of Personality Is Stronger and More Strongly Correlated With Cognitive Ability Under Instructed Faking Carolyn MacCann,1 Nicola Pearce,2 and Yixin Jiang1 1

School of Psychology, The University of Sydney, Australia

School of Psychology, The University of Cardiff, UK

Abstract: A General Factor of Personality (GFP) can be derived by extracting one factor from a broad range of personality dimensions. Researchers are divided on whether the GFP represents social desirability or an evolved trait with survival value. The current paper tests a social desirability interpretation of the GFP by comparing one-factor models of the HEXACO under standard versus fake-good instructions (N = 185 undergraduates). Analyses include both principal components analyses (PCA) and a comparison of factorial invariance of a hierarchical one-factor model. Compared to standard instructions, fake-good instructions showed: (a) significantly higher correlations between domain scale scores for 10 of 15 cases; (b) significantly higher component loadings in the PCA; (c) significantly more variance explained by the GFP (in both principal components and invariance analyses); and (d) significantly higher correlations with a cognitive g factor derived from six indicators. Results support a social desirability interpretation of the GFP. Keywords: general factor of personality (GFP), response distortion, faking, factor analysis, invariance analysis, personality

The recent proposal of a general factor of personality (GFP) holds that individual differences in personality can be explained by one broad dimension that aggregates the common variance in lower-level personality traits such as the Big Five (Musek, 2007). In this theory, the first principal component extracted from a battery of personality tests represents an evolutionary adaptive trait with a survival advantage to those who possess more of it (e.g., Rushton, Bons, & Hur, 2008). An alternative viewpoint is that the GFP represents social desirability rather than a substantively meaningful factor (Ashton, Lee, Goldberg, & de Vries, 2009; Bäckström, Björklund, & Larsson, 2009; Comensoli & MacCann, 2013). However, to our knowledge, no one has yet examined the social desirability hypothesis of the GFP using an instructed faking paradigm. The current study addresses this gap in the literature by testing the invariance of a hierarchical one-factor model of the HEXACO measure under two sets of instructions: (a) answer honestly and (b) fake good (see Figure 1). We also consider the relationship of the GFP with a general factor of intelligence (g).

Journal of Individual Differences (2017), 38(1), 46–54 DOI: 10.1027/1614-0001/a000221

Background to the GFP Digman (1997) noted that the broad personality traits of the Big Five tended to correlate with each other, and proposed that two higher-order factors (Alpha and Beta) could explain these relationships. Noting that Alpha and Beta factors were themselves intercorrelated, subsequent researchers used meta-analysis to empirically verify the proposal that all personality traits could be modeled as one overarching general factor (van der Linden, te Nijenhuis, & Bakker, 2010; Rushton & Irwing, 2008). The idea of a GFP has attracted controversy since. Several researchers reported that a GFP is not empirically recoverable (e.g., Donnellan, Hopwood, & Wright, 2012; Hopwood, Wright, & Donnellan, 2011; de Vries, 2011), though others presented evidence that it is (e.g., Erdle & Rushton, 2011; van der Linden, Tsaousis, & Petrides, 2012; van der Linden et al., 2010; Veselka et al., 2009). Still others have proposed that a GFP may be attributable to a general factor of social desirability or response distortion that runs through all personality items

Ó 2017 Hogrefe Publishing

C. MacCann et al., Faking and The General Factor of Personality

An alternative method for studying response distortion is to experimentally manipulate socially desirable responding using instructed faking. Schermer and MacDougall (2013) suggested examining the factor structure of the GFP under fake-good situations to test the influence of social desirability. The current research takes up this suggestion, making a unique contribution to the GFP debate by using an instructed faking paradigm to compare the evidence for a GFP under honest responding versus faking. If the evidence for a GFP is stronger under faking instruction compared to honest responding (Hypothesis 1), this provides some empirical evidence that the GFP represents social desirability. There were three associated expectations: (a) HEXACO domain scores would be more strongly correlated in the faking condition than the honestresponse condition; (b) loadings onto a GFP factor would be stronger in the faking condition than the honest-response condition; and (c) more variance would be explained by the GFP in the faking condition than the honest-response condition.

General Factors of Personality and Intelligence

Figure 1. Depiction of the hierarchical model tested for invariance across fake-good versus answer-honestly conditions.

(e.g., Ashton et al., 2009; Bäckström & Björklund, 2016; Bäckström et al., 2009; Danay & Ziegler, 2011). In fact, research demonstrates that although the GFP correlates significantly with social desirability scales (e.g., Erdle & Rushton, 2011; van der Linden et al., 2012; Rushton & Erdle, 2010; Schermer & MacDougall, 2013), loadings on the GFP remain salient and significant after controlling for social desirability scores (Erdle & Rushton, 2011; Rushton & Erdle, 2010). However, social desirability scales are not an accurate way to measure socially desirable responding (e.g., MacCann, Zeigler, & Roberts, 2011). Research has shown that social desirability scores correlate with Emotional Stability, Agreeableness, Conscientiousness, and, especially, the Honesty-Humility dimension of the HEXACO personality measure (Li & Bagger, 2006; Ones, Viswesvaran, & Reiss, 1996; de Vries, Zettler, & Hilbig, 2014; Zettler, Hilbig, Moshagen, & de Vries, 2015). As such, controlling for social desirability scale scores removes some relevant personality-related variation, and may not necessarily assess whether participants are engaging in response distortion. Ó 2017 Hogrefe Publishing

As desirable characteristics for survival, it has been proposed that the GFP has coevolved alongside the general factor of intelligence (g) first proposed by Spearman (1927), and so should be highly intercorrelated (Rushton et al., 2008). A number of studies have reported significant small-medium, positive g-GFP correlations (e.g., Dunkel & de Baca, 2016; Irwing, Booth, Nyborg, & Rushton, 2012; Schermer & Vernon, 2010). This association has not been found with social desirability scales, which are unrelated to g (Schermer & Vernon, 2010). These studies suggest that the g-GFP correlation is evidence that the GFP represents evolutionary fitness rather than social desirability, representing a real and substantial phenomenon. Therefore, the present study uses the GFP-g correlation as evidence of the validity of the GFP. It was hypothesized that GFP factor scores will show a stronger correlation with cognitive g under the faking condition than the honestresponse condition, if the substantive meaning of the GFP is due to response distortion (Hypothesis 2).

Method Participants Participants were first- and third-year psychology students at the first author’s institution (N = 185, 73% female). Journal of Individual Differences (2017), 38(1), 46–54

First-year students were given course credit for their participation and third-year students participated as part of their in-class coursework for a psychological assessment class.

Materials The HEXACO Personality Inventory Revised, 100-item version (HEXACO-PI-R; Lee & Ashton, 2004) This 100-item scale assesses the 6 HEXACO domains (16 items per domain) and the 24 HEXACO facets (4 items per facet), rated on a 5-point scale from 1 (= strongly disagree) to 5 (= strongly agree). The scale includes an additional 4-item facet (Altruism) that does not load onto any HEXACO domain. Letter Series (Stankov, 1997) This 5-min test presented 15 letter series, whereby participants had to provide the next letter in a series based on pattern deduction (e.g., J K L M N O P Q?–––––––). Letter Counting (Stankov, 1997) In this 15-trial test, participants had to count how many times the letters R, S, and T were presented on screen. Each trial presented between 6 and 10 letters at 1-s intervals. Syllogistic Reasoning (Ekstrom, French, Harman, & Derman, 1976) Each of the 15 items of this 4-min timed test presents a syllogism and asks participants to evaluate whether the conclusion represented good or poor reasoning. For example, “All horses have wings. No turtles have wings. Therefore no turtle is a horse. Is this good reasoning or poor reasoning?” Analogical Reasoning (Schulze, MacCann, & Roberts, 2010) This 15-item timed test presents a pair of words in a particular relationship and asks participants to select which of five other word-pairs represented the same relationship. For example, “happy:sad, (a) hot:sun, (b) cold:water, (c) hot:cold, (d) blue:sky, (e) red:cold.” Vocabulary (Ekstrom et al., 1976) This 6-min timed test presents 24 items, each asking which of 5 alternatives is closest in meaning to a target word. For example, “Cottontail: (a) squirrel, (b) poplar, (c) boa, (d) marshy plant, (e) rabbit.” General Knowledge (Amthauer, Brocke, Liepmann, & Beauducel, 2000) This 6-min timed test consists of 20 general knowledge questions. For example, “How many states make up the United States of America? (1) 54, (2) 62, (3) 38, (4) 50, (5) 48. Journal of Individual Differences (2017), 38(1), 46–54

C. MacCann et al., Faking and The General Factor of Personality

Procedure All participants completed the HEXACO-PI-R under two conditions: (a) answer honestly and (b) fake good. The fake-good instructions were taken from Heggestad, Morrison, Reeve, and McCloy (2006). The order of instruction sets was counterbalanced, with 91 participants receiving the “fake-good” instructions first whereas 94 participants received “answer-honestly” instructions first. After completing the HEXACO under both instruction sets, participants then completed the cognitive tests. The order of administration of cognitive tests was also counterbalanced. All protocols were approved by the Human Research Ethics Committee of the first author’s institution. Data obtained from the same protocols have also been reported in MacCann (2013).

Results Reliability and Descriptive Statistics Table 1 shows the reliability, descriptive statistics, and correlations for the intelligence scores and the HEXACO under both fake-good and honest conditions, along with the mean difference on the HEXACO scores between the conditions. Reliability for the intelligence measures ranged from .50 to .76. Reliability of the six HEXACO domains was similar across conditions, but reliability for the 24 facet scores tended to be lower in the fake condition. Faking resulted in significantly lower means for Emotionality and significantly higher means for the other five domains. All six domain scores and 22 of the 24 facet scores had significantly different means across conditions. For the domain scores, effect sizes ranged from 0.49 to 1.08.

Correlations Between Domain Scores Table 2 shows the correlations between the six raw scores on the HEXACO domains for both answer-honestly and fake-good conditions. The magnitude of correlation under faking instructions was higher for 13 of the 15 correlation coefficients and was significantly higher for 10 of the 15 correlation coefficients (based on Fisher’s z-test). This supports Hypothesis 1a (greater support for a GFP under instructed faking than answer-honestly conditions).

Principal Components Analyses For both the honest-response and fake-good conditions, the first principal component was extracted from the 24 HEXACO facet scores. This component explained 18.96% and 31.22% of the variation for honest-response and fake-good Ó 2017 Hogrefe Publishing

C. MacCann et al., Faking and The General Factor of Personality

Table 1. Descriptive statistics and reliability for the six intelligence markers and for the HEXACO domain and facet raw scores under “answerhonestly” and “fake-good” instructions (N = 185 for the HEXACO, 166 for intelligence markers). Comparisons across conditions are Cohen’s d and Pearson’s r Honest condition

Fake condition

Compare conditions

Mean

Honesty/Humility

3.31

0.63

.76

3.59

0.52

.65

Emotionality

3.37

0.56

.68

3.05

0.50

.70

0.60**

.67**

eXtraversion

3.37

0.60

.83

3.93

0.54

.87

0.97**

.35**

Agreeableness

3.09

0.58

.80

3.55

0.53

.79

0.83**

.39**

Conscientiousness

3.48

0.58

.76

4.08

0.54

.86

1.08**

.36**

Openness

3.45

0.63

.76

3.80

0.51

.77

0.61**

.66**

3.14

0.81

.69

3.41

0.71

.52

0.35**

.49**

3.58

0.92

.74

4.19

0.74

.66

0.73**

.40**

2.97

0.91

.82

3.16

0.84

.78

0.21**

.62**

3.54

0.77

.73

3.61

0.67

.56

0.10

.64**

3.04

0.81

.67

2.63

0.73

.58

0.54**

.63**

3.63

0.75

.63

3.00

0.82

.70

0.80**

.43**

3.26

0.78

.69

3.09

0.60

.33

0.26**

.59**

3.54

0.77

.70

3.50

0.66

.52

0.06

.68**

3.73

0.63

.64

4.16

0.52

.68

0.75**

.39**

2.91

0.86

.73

3.69

0.79

.78

0.95**

.35**

3.44

0.77

.71

3.87

0.68

.70

0.61**

.46**

3.43

0.75

.75

3.99

0.63

.72

0.82**

.38**

2.71

0.81

.68

3.31

0.68

.48

0.80**

.40**

3.34

0.69

.66

3.58

0.63

.56

0.37**

.33**

3.04

0.69

.54

3.55

0.73

.70

0.72**

.43**

3.27

0.81

.70

3.76

0.67

.61

0.66**

.46**

3.36

0.94

.78

4.15

0.73

.79

0.96**

.40**

3.69

0.71

.70

4.32

0.62

.75

0.95**

.36**

3.63

0.70

.66

4.07

0.61

.62

0.67**

.50**

3.25

0.72

.69

3.79

0.64

.61

0.80**

.34**

3.36

0.94

.78

4.15

0.73

.60

0.42**

.65**

3.69

0.71

.70

4.32

0.62

.64

0.68**

.58**

3.63

0.70

.66

4.07

0.61

.68

0.42**

.64**

3.25

0.72

.69

3.79

0.64

.33

0.32**

.67**

Letter series

4.62

2.98

.69

–

Letter counting

8.36

2.31

.76

–

Syllogistic reasoning

6.49

2.51

.54

–

Analogies

7.37

2.99

.72

–

Vocabulary

11.98

3.69

.69

–

General knowledge

10.98

2.58

.50

–

d 0.49**

r .56**

Notes. Effect size was calculated as Cohen’s d, and negative values indicate scores are lower under faking. Significance of mean differences was calculated with a two-tailed t-test. **p < .01.

conditions, respectively. Component loadings, shown in Table 3, were negative for Emotionality facets and positive for the other five domains, with a similar pattern of loadings across conditions (Congruence coefficient = .975). The average magnitude of factor loadings was significantly higher for fake scores (M = .53, SD = 0.20) than honest scores (M = .41, SD = 0.14; t = 4.220, df = 23, p = .013), supporting Hypothesis 1b (larger GFP loadings under faking). Ó 2017 Hogrefe Publishing

Structural Invariance of a Hierarchical Six-Factor Model Figure 1 shows a hierarchical 6-factor model where the 24 HEXACO facets define the 6 HEXACO domain factors, which in turn load onto a general factor of personality. We tested the invariance of this model across fake-good and answer-honestly conditions in a series of six steps: (1) configural invariance; (2) measurement weights; (3) structural Journal of Individual Differences (2017), 38(1), 46–54

C. MacCann et al., Faking and The General Factor of Personality

Table 2. Correlations between HEXACO scale scores for standard instruction set and faking instruction set (faking instruction set shown in parentheses) H

.03

(.06)

.17

(.32**)#

.44**

.23*

.17

( .57**)##

(.42**)

.28**

( .49**)##

.30**

(.63**)##

(.34**)#

.08

( .34**)##

.27**

(.62**)##

.16

(.17)

.03

( .13)

.15

(.33**)

Notes. Correlations for faking and honest conditions are significantly different at p < .05. different at p < .01. *p < .05; **p < .01 (two-tailed).

.22*

(.59**)##

.26**

(.22*)

.09

(.30**)##

Correlations for faking and honest conditions are significantly

Table 3. Standardized factor loadings for honest and fake-good responses from principal components analysis (PC) and from structural equation modeling (SEM; both first-order loadings onto the HEXACO and second-order factor loadings onto the GFP are shown) Honest

Fake-good SEM

1st-order

SEM 2nd-order .51

1st-order

.37

.60

.26

.51

.48

.63

.58

.72

.37

.66

.25

.42

.30

.66

.26

.47

.34

.68

.54

.65

.50

.59

.63

.79

.36

.19

.48

.26

.42

.09

.64

.04

.32

.60

.70

.74

.77

.46

.66

.77

.79

.34

.61

.60

.66

.61

.87

.77

.84

.69

.79

.65

.71

.50

.60

.54

.60

.49

.62

.64

.73

.56

.71

.65

.72

.44

.68

.67

.79

.53

.74

.75

.84

.38

.60

.63

.71

.36

.61

.64

.71

.40

.78

.42

.77

.41

.60

.53

.67

.20

.57

.43

.71

.31

.74

.29

.63

.44

.82

.46

.31

weights; (4) structural covariances; (5) structural residuals; and (6) measurement residuals. We evaluated invariance using the Chi-square difference test. Fit indices for each of the six invariance conditions are shown in Table 4. Configural Invariance When there were no equality constraints, the comparative fit index (CFI) indicated poor fit (CFI = .798) whereas the Journal of Individual Differences (2017), 38(1), 46â&#x20AC;&#x201C;54

2nd-order .62

.73

.91

.83

.80

.49

root mean square error of approximation (RMSEA) indicated good fit (RMSEA = .060). Inspection of the modification indices indicated some correlated error terms (particularly within domains) and cross loadings of facets onto multiple domains. However, as these were not consistent across fake-good versus answer-honestly conditions, we did not make adjustments to the model. Standardized factor loadings onto the HEXACO domains and the general factor of personality are shown in Table 3. Ă&#x201C; 2017 Hogrefe Publishing

C. MacCann et al., Faking and The General Factor of Personality

Table 4. Fit statistics testing the invariance of the six-factor hierarchical model representing the HEXACO domains with an overarching GFP factor Δw2

CFI

1. Unconstrained

1,136

492

.798

.060

1,352

2. Measurement weights

1,170

510

.793

.059

1,350

3. Structural weights

1,175

515

.793

.059

1,345

5.105

4 .Structural covariances

1,182

516

.791

.059

1,350

6.751**

Model

RMSEA

AIC

33.921*

5. Structural residuals

1,240

522

.775

.061

1,396

57.927**

6. Measurement residuals

1,429

546

.723

.066

1,537

189.311**

Notes. *p < .05; **p < .01 (two-tailed).

Measurement Weights Constraining the factor loadings of the facets onto the HEXACO domains to be equal across conditions produced a significant decrease in fit. In general, loadings under faking were lower for Honesty/Humility, higher for eXtraversion, and higher for Conscientiousness (see Table 3). Structural Weights Constraining the loadings of the HEXACO domains onto the GFP to be equal across conditions did not decrease fit. This is contrary to Hypothesis 1b, which would predict higher GFP loadings under faking. However, although the invariance analysis did not indicate a significant difference, GFP loadings were higher in all cases (averaging .36 in the honest condition versus .49 for the faking condition, see Table 3). Structural Covariances Constraining the variance of the GFP to be equal across conditions significantly decreased model fit. The variance of the GFP was significant for the faking condition (0.028, SE = 0.011, p = .012) but not for the answerhonestly condition (0.024, SE = 0.016, p = .137). This result supports Hypothesis 1c, that more variation in the GFP would be explained under faking than under honest responding. Structural Residuals Constraining the variance of HEXACO’s error terms to be equal across conditions significantly decreased model fit. Error terms were larger for the answer-honestly condition, indicating that less variance in the six HEXACO factors could be explained by the GFP. Measurement Residuals Constraining the error terms of the 24 facets to be equal across conditions significantly reduced model fit. Residuals were higher for the answer-honestly condition for 21 of the 24 cases. Relationship of the GFP to Psychometric g Intelligence test scores on all six tests were available for 163 participants. The first principal component of these Ó 2017 Hogrefe Publishing

six scores explained 41.12% of the variance. Component loadings were .67, .38, .61, .50, .73, and .85, respectively, for Vocabulary, Syllogisms, Letter Series, Letter Counting, General Knowledge, and Analogies. A component score was used as a single measure of g in order to calculate the correlation between g and GFP factor scores. Factor scores for the GFP were calculated for both the honest and the fake conditions, based on the factor score coefficients from the unconstrained model. The GFP factor scores under the two different conditions shared a significant but small correlation (r = .177, p = .024). Under the fake-good condition, the GFP was significantly correlated with g (r = .217, p = .005). Under the answer-honestly condition, the GFP was not significantly correlated with g (r = .045, p = .567). The difference between the two correlations with g was significant (Hotelling William t = 1.735, p = .042). Results were similar for the GFP calculated from principal components analysis: GFP-g correlations were .218 for fake-good versus .044 for honest responding. That is, the GFP showed a stronger association with cognitive g under faking than under honest responding, supporting Hypothesis 2.

Discussion The current study provided support for the idea that the GFP may be at least partly explained by social desirability. Both principal components analyses and invariance tests showed that when participants faked the HEXACO, the six factors became more strongly related and the amount of variation explained by the GFP increased. In addition, GFP factor loadings were higher for fake-good instructions than answer-honestly instructions (this difference was significant for the PCA loadings but not when tested with invariance analysis). More tellingly, the GFP showed greater evidence of construct validity when participants completed personality under faking instructions, with significantly higher relationships to cognitive g. The current results differ from those of previous studies that controlled for social desirability using social desirability scales, which had little effect on the size of the loadings of Journal of Individual Differences (2017), 38(1), 46–54

the GFP (Erdle & Rushton, 2011; Rushton & Erdle, 2010). This could be attributed to the different definitions of social desirability inherent to the two methods. Social desirability scales are assumed to assess response distortion (whether conscious or unconscious), rather than the quality of being a socially desirable person. However, correlations of social desirability scales with personality traits indicate that social desirability items may well assess both descriptive and evaluative elements – that is, genuine personality traits relating to being a socially desirable person, in addition to response distortion (Li & Bagger, 2006; Ones et al., 1996; de Vries et al., 2014; Zettler et al., 2015). In fact, the substantive meaning proposed for the GFP is essentially the quality of being a socially desirable person – having characteristics of evolutionary fitness. With such an interpretation, correlations between the GFP and social desirability scales might constitute evidence for a meaningful GFP, rather than a GFP that is a method effect of response distortion on personality scales. Because of the uncertainty over what social desirability scales actually assess, the use of different methods such as instructed faking is particularly important. Results from the current study demonstrate that some of the common variance contributing to a general factor is due to response distortion. This converges with the results of other studies that suggest the GFP is based on social desirability using methods such as comparing self- versus other-reports, or manipulating the social desirability/evaluative content of items (Bäckström & Björklund, 2016; Bäckström et al., 2009; Danay, & Ziegler, 2011). The GFP explained more variance under the faking condition, suggesting that the factor is in part due to test-takers intentionally distorting their responses to create a socially desirable (specifically, employer-favorable) impression. Arguably, this could reflect either a nonmeaningful method effect or an actual individual differences phenomenon, such as the motivation to strive toward ideal behavior (Bäckström & Björklund, 2016). The present empirical evidence cannot determine whether the GFP obtained under faking versus honest responding represents substantive versus methodological variance. However, the results clearly show that instructed faking results in a stronger GFP. Moreover, the GFP obtained in the fake-good condition showed a significant positive relationship to g, a proposed characteristic of the GFP (Rushton et al., 2008). This is stronger evidence that the GFP proposed in other studies, which correlates with g, is actually based on response distortion. This result also suggests that more intelligent individuals are more able to distort their responses to be socially desirable under evaluative conditions. Furthermore, the GFP was unrelated to g under the answer-honestly condition, contrary to some previous studies (e.g., Dunkel

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& de Baca, 2016; Irwin et al., 2012; Schermer & Vernon, 2010). Critical to the argument that GFP is a substantive phenomenon, the factor is proposed to have coevolved alongside g and should be highly correlated (Rushton et al., 2008). However, even though previous studies have found a significant GFP-g correlation, the size of the association tends to be small, which led Irwing et al. (2012) to conclude that they may involve largely separate evolutionary processes. This is further substantiated by Loehlin et al.’s (2015) large-scale international twin study, which found near-zero genetic correlations between g and GFP. The phenotypic covariation may instead be attributed to non-substantive factors, and the present study suggests that response distortion may serve as one such explanation.

Limitations and Future Directions The current paper provided evidence from one model of personality (the HEXACO), for one measurement technique (self-reports) for one form of instructed faking (obtain a desired job). Ideally, findings should be replicated across different personality models, measurement different methods of measurement (e.g., other reports, adjective checklists, situational judgment tests), and different instruction sets (e.g., attract a desirable partner on a dating website; get accepted into medical school, etc.). In addition, the limited sample size for intelligence markers meant it was not feasible to run a full structural model where the GFP predicted psychometric g.

Conclusions Some of the commonality across different personality traits is clearly due to test-takers considering the evaluative content across one key dimension. Thus, when a general factor is extracted from a number of different personality indicators, at least some of the variation captured by this factor relates to the evaluative content of the items. Moreover, it is this evaluative component of the variance that relates to cognitive g, suggesting that a social desirability explanation for the GFP is more compelling than an evolutionary explanation.

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Bäckström, M., & Björklund, F. (2016). Is the general factor of personality based on evaluative responding? Experimental manipulation of item-popularity in personality inventories. Personality and Individual Differences, 96, 31–35. doi: 10.1016/ j.paid.2016.02.058 Bäckström, M., Björklund, F., & Larsson, M. R. (2009). Five-factor inventories have a major general factor related to social desirability which can be reduced by framing items neutrally. Journal of Research in Personality, 43, 335–344. doi: 10.1016/ j.jrp.2008.12.013 Comensoli, A., & MacCann, C. (2013). Misconstruing methods and meaning in the General Factor of Personality. International Journal of Psychology, 48, 625–630. doi: 10.1080/00207594. 2012.688134 Danay, E., & Ziegler, M. (2011). Is there really a single factor of personality? A multirater approach to the apex of personality. Journal of Research in Personality, 45, 560–567. doi: 10.1016/ j.jrp.2011.07.003 de Vries, R. E. (2011). No evidence for a General Factor of Personality in the HEXACO Personality Inventory. Journal of Research in Personality, 45, 229–232. doi: 10.1016/j.jrp. 2010.12.002 de Vries, R. E., Zettler, I., & Hilbig, B. E. (2014). Rethinking trait conceptions of social desirability scales: Impression management as an expression of Honesty-Humility. Assessment, 21, 286–299. doi: 10.1177/1073191113504619 Digman, J. M. (1997). Higher-order factors of the Big Five. Journal of Personality and Social Psychology, 73, 1246–1256. doi: 10.1037/0022-3514.73.6.1246 Donnellan, M. B., Hopwood, C. J., & Wright, A. G. C. (2012). Revaluating the evidence for the General Factor of Personality in the Multidimensional Personality Questionnaire: Concerns about Rushton and Irwing (2009). Personality and Individual Differences, 52, 285–289. doi: 10.1016/j.paid.2011.10.018 Dunkel, C. S., & de Baca, T. C. (2016). Replication of the association between general intelligence and the general factor of personality using the California Child Q-set. Intelligence, 56, 35–37. doi: 10.1016/j.intell.2016.02.007 Ekstrom, R. B., French, J. W., Harman, H. H., & Derman, D. (1976). Kit of reference tests for cognitive factors. Princeton, NJ: Educational Testing Service. Erdle, S., & Rushton, J. P. (2011). Does self-esteem or social desirability account for a general factor of personality (GFP) in the Big Five? Personality and Individual Differences, 50, 1152–1154. doi: 10.1016/j.paid.2010.12.038 Heggestad, E. D., Morrison, M., Reeve, C. L., & McCloy, R. A. (2006). Forced-choice assessments of personality for selection: Evaluating issues of normative assessment and faking resistance. The Journal of Applied Psychology, 91, 9–24. doi: 10.1037/0021-9010.91.1.9 Hopwood, C. J., Wright, A. G. C., & Donnellan, M. B. (2011). Evaluating the evidence for the general factor of personality across multiple inventories. Journal of Research in Personality, 45, 468–478. doi: 10.1016/j.paid.2011.06.029 Irwing, P., Booth, T., Nyborg, H., & Rushton, J. P. (2012). Are g and the General Factor of Personality (GFP) correlated? Intelligence, 40, 296–305. doi: 10.1016/j.intell.2012.03.001 Lee, K., & Ashton, M. C. (2004). Psychometric properties of the HEXAO Personality Inventory. Multivariate Behavioral Research, 39, 329–358. doi: 10.1207/s15327906mbr3902_8 Li, A., & Bagger, J. (2006). Using the BIDR to distinguish the effects of impression management and self-deception on the criterion validity of personality measures: A meta-analysis. International Journal of Selection and Assessment, 14, 131–141. doi: 10.1111/j.1468-2389.2006.00339.x

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Loehlin, J. C., Bartels, M., Boomsma, D. I., Bratko, D., Martin, N. G., Nichols, R. C., & Wright, M. J. (2015). Is there a genetic correlation between general factors of intelligence and personality? Twin Research and Human Genetics, 18, 234–242. doi: 10.1017/thg.2015.28 MacCann, C. (2013). Instructed faking of the HEXACO reduces facet reliability and involves more Gc than Gf. Personality and Individual Differences, 55, 828–833. doi: 10.1016/j.paid. 2013.07.007 MacCann, C., Zeigler, M., & Roberts, R. D. (2011). Faking in personality assessment: Reflections and recommendations. In M. Ziegler, C. MacCann, & R. D. Roberts (Eds.), New perspective on faking in personality assessment (pp. 309–329). New York, NY: Oxford University Press. Musek, J. (2007). A general factor of personality: Evidence for the Big One in the five-factor model. Journal of Research in Personality, 41, 1213–1233. doi: 10.1016/j.jrp.2007.02.003 Ones, D. S., Viswesvaran, C., & Reiss, A. D. (1996). Role of social desirability in personality testing for personnel selection: The red herring. The Journal of Applied Psychology, 81, 660–679. doi: 10.1037/0021-9010.81.6.660 Rushton, J. P., Bons, T. A., & Hur, Y. M. (2008). The genetics and evolution of a general factor of personality. Journal of Research in Personality, 42, 1173–1185. doi: 10.1016/j.jrp.2009.01.005 Rushton, J. P., & Erdle, S. (2010). No evidence that social desirability response set explains the general factor of personality and its affective correlates. Twin Research and Human Genetics, 13, 131–134. doi: 10.1375/twin.13.2.131 Rushton, J. P., & Irwing, P. (2008). A general factor of personality (GFP) from two meta-analyses of the Big Five: Digman (1997) and Mount, Barrick, Scullen, and Rounds (2005). Personality and Individual Differences, 45, 679–683. doi: 10.1016/j.paid. 2008.07.015 Schermer, J. A., & MacDougall, R. (2013). A general factor of personality, social desirability, cognitive ability, and the survey of work styles in an employment selection setting. Personality and Individual Differences, 54, 141–144. doi: 10.1016/ j.paid.2012.08.012 Schermer, J. A., & Vernon, P. A. (2010). The correlation between general intelligence (g), a general factor of personality (GFP), and social desirability. Personality and Individual Differences, 48, 187–189. doi: 10.1016/j.paid.2009.10.003 Schulze, R., MacCann, C., & Roberts, R. D. (2010, July). Evidence supporting the use of multimedia assessments of emotional abilities. International Congress of Applied Psychology, Melbourne, NSW, Australia. Spearman, C. (1927). The abilities of man: Their nature and measurement. New York, NY: Macmillan. Stankov, L. (1997). Gf–Gc quickie test battery. Sydney, Australia: E-ntelligence Testing Products. van der Linden, D., te Nijenhuis, J., & Bakker, A. B. (2010). The general factor of personality: A meta-analysis of Big Five intercorrelations and a criterion-related validity study. Journal of Research in Personality, 44, 315–327. doi: 10.1016/j.jrp. 2010.03.003 van der Linden, D., Tsaousis, I., & Petrides, K. V. (2012). Overlap between general factors of personality in the Big Five, Giant Three, and trait emotional intelligence. Personality and Individual Differences, 53, 175–179. doi: 10.1016/j.paid. 2012.03.001 Veselka, L., Schermer, J. A., Petrides, K. V., Cherkas, L. F., Spector, T. D., & Vernon, P. A. (2009). A general factor of personality: Evidence from the HEXACO model and a measure of trait emotional intelligence. Twin Research and Human Genetics, 12, 420–424. doi: 10.1375/twin.12.5.420

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Zettler, I., Hilbig, B. E., Moshagen, M., & de Vries, R. E. (2015). Dishonest responding or true virtue? A behavioral test of impression management. Personality and Individual Differences, 81, 107–111. doi: 10.1016/j.paid.2014.10.007 Received December 3, 2014 Revision received August 24, 2016 Accepted August 25, 2016 Published online February 10, 2017

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Carolyn MacCann Brennan MacCallum Building School of Psychology The University of Sydney Sydney NSW, 2006 Australia carolyn.maccann@sydney.edu.au

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Alternatives to traditional self-reports in psychological assessment “A unique and timely guide to better psychological assessment.” Rainer K. Silbereisen, Research Professor, Friedrich Schiller University Jena, Germany Past-President, International Union of Psychological Science

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Enablers and Inhibitors, Practical Applications, International Cinema, and a Summary. Watching the films recommended in this book will help the reader to practice the skill of strengths-spotting in themselves and others, inspiring self-improvement. Practical resources include a suggested syllabus for a complete positive psychology course based on movies, a list of suitable movies for children, adolescents, and families as well as a list of questions for classroom and therapy discussions. Positive Psychology at the Movies is conceived for educators, students, practitioners, and researchers, but anyone who loves movies and wants to change their lives for the better will find it inspiring and relevant. Read this book to learn more about positive psychology – and watch these films to become a stronger person!

Original Article

The Role of Distress Disclosure Tendencies in the Experience and Expression of Laboratory-Induced Sadness Jeffrey H. Kahn,1 Daniel W. Cox,2 A. Myfanwy Bakker,2 Julia I. O’Loughlin,2 and Agnieszka M. Kotlarczyk2 1

Department of Psychology, Illinois State University, Normal, IL, USA

Counselling Psychology Program, University of British Columbia, Vancouver, BC, Canada

Abstract: The benefits of talking with others about unpleasant emotions have been thoroughly investigated, but individual differences in distress disclosure tendencies have not been adequately integrated within theoretical models of emotion. The purpose of this laboratory research was to determine whether distress disclosure tendencies stem from differences in emotional reactivity or differences in emotion regulation. After completing measures of distress disclosure tendencies, social desirability, and positive and negative affect, 84 participants (74% women) were video recorded while viewing a sadness-inducing film clip. Participants completed post-film measures of affect and were then interviewed about their reactions to the film; these interviews were audio recorded for later coding and computerized text analysis. Distress disclosure tendencies were not predictive of the subjective experience of emotion, but they were positively related to facial expressions of sadness and happiness. Distress disclosure tendencies also predicted judges’ ratings of the verbal disclosure of emotion during the interview, but self-reported disclosure and use of positive and negative emotion words were not associated with distress disclosure tendencies. The authors present implications of this research for integrating individual differences in distress disclosure with models of emotion. Keywords: emotional expression, distress disclosure, sadness

Individual differences in the tendency to talk about distressing events have widespread relevance. For example, people who tend to talk about distress when distress is experienced (i.e., those high in distress disclosure; Kahn & Hessling, 2001) report greater social support (Greenland, Scourfield, Maxwell, Prior, & Scourfield, 2009), are more likely to have secure attachment (Wei, Russell, & Zakalik, 2005), experience less depression (Garrison & Kahn, 2010), are more likely to seek psychological help (Vogel & Wester, 2003), and experience better psychotherapeutic outcomes (Kahn, Achter, & Shambaugh, 2001) than people who tend to conceal their distress. Whereas gains have been made in understanding how distress disclosure tendencies relate to interpersonal relationships and well-being (see Kahn, Hucke, Bradley, Glinski, & Malak, 2012), studies have not investigated how they fit within models of emotion. In the modal emotion model (Gross & Thompson, 2007), emotion-eliciting Ó 2017 Hogrefe Publishing

situations lead to multiple psychological states – subjective experiences, expressive behaviors (e.g., facial, vocal), and physiological responses. Emotion regulation, or people’s efforts to control their emotional experiences and expressions, may occur before and/or after these psychological states are experienced (Gross & Feldman Barrett, 2011). Presently, it is unclear where distress disclosure tendencies fit within the modal model of emotion. Some clues as to the role of distress disclosure tendencies in this regard can be garnered from prior research. Most fundamentally, distress disclosure tendencies are positively related to individual differences in emotional expressivity (Barr, Kahn, & Schneider, 2008) and negatively related to restricted emotionality (Pederson & Vogel, 2007). Moreover, a laboratory study supported the link between distress disclosure tendencies and the verbal disclosure of emotion in response to a distressing film clip (Kahn, Lamb, Champion, Eberle, & Schoen, 2002). Daily diary studies Journal of Individual Differences (2017), 38(1), 55–62 DOI: 10.1027/1614-0001/a000222

have also shown that distress disclosure tendencies are predictive of verbal disclosure behaviors in response to unpleasant daily events (Garrison & Kahn, 2010; Garrison, Kahn, Miller, & Sauer, 2014; Garrison, Kahn, Sauer, & Florczak, 2012; Ryan & Kahn, 2015). Thus, consistent with views of emotional expressivity as being both verbal and nonverbal (Kennedy-Moore & Watson, 2001), distress disclosure tendencies capture the expression of emotion. Despite this evidence linking distress disclosure tendencies with emotional expressivity, there is a lack of understanding as to why this link exists. Drawing from the emotion-expression literature (e.g., Kennedy-Moore & Watson, 2001), there are two potential explanations for the association between distress disclosure tendencies and emotional expression. The first is that people with high distress disclosure tendencies have high levels of emotional reactivity. In other words, their subjective emotional experiences in response to emotion-eliciting stimuli may be greater than those with low distress disclosure tendencies, and this results in increased emotional expression. There has been limited research investigating this emotional-reactivity hypothesis. A correlational study indicated that distress disclosure tendencies are only weakly related to general positive and negative affect (Kahn & Hessling, 2001), and two diary studies found that distress disclosure tendencies are unrelated to self-reports of the emotional intensity of unpleasant events (Garrison et al., 2014; Ryan & Kahn, 2015). The second potential explanation for the association between distress disclosure tendencies and emotional expression is that people with high distress disclosure tendencies are more likely to use emotional expressivity as an emotion-regulation strategy (Kennedy-Moore & Watson, 2001). In other words, disclosing distress may be a response-focused emotion-regulation strategy for which the goal is to approach (and ultimately work through) one’s affect by describing it to another person (Kahn et al., 2012). Correlational research provides support for this emotionregulation hypothesis with studies indicating a negative association between distress disclosure tendencies and expressive suppression (Kahn & Garrison, 2009; Kahn et al., 2012). Thus, whereas people high in distress disclosure approach their affect as a way to work through it, people low in distress disclosure tendencies seem to be attempting to avoid their negative affect. Although extant research is more in line with the emotion-regulation hypothesis than the emotional-reactivity hypothesis, the predominance of naturalistic studies in this area is problematic for several reasons. First, individuals vary widely in the emotion-eliciting stimuli to which they are exposed in daily life. This between-person variability severely affects the conclusions one might draw concerning the link between distress disclosure tendencies Journal of Individual Differences (2017), 38(1), 55–62

J. H. Kahn et al., Distress Disclosure Tendencies

and the strength of people’s subjective emotional experiences. Second, people cannot reasonably gauge their own levels of emotional expression in an objective way. Most notably, people cannot comment on their own facial expressions without literally holding a mirror while experiencing an emotion, and even then people differ in their judgments about emotional expression. Third, retrospective reports inherent in generalized self-reports and diary studies cannot establish the temporal sequence of encountering a stimulus, experiencing the emotion subjectively, and expressing/disclosing the emotion. In the present study, we used a laboratory-based induction of negative mood via an unpleasant film clip. Examining emotional responses to a film clip in a structured setting alleviates the problems with naturalistic research on correlates of distress disclosure tendencies. As such, this study had the potential to shed light on how these individual differences map onto the specific components of an emotion in real time, something that has not previously been done. A laboratory study also allowed us to determine the degree to which distress disclosure tendencies predict facial expressions of emotion. Such an examination – which has not been reported in the literature – is critical because of questions about whether distress disclosure tendencies represent verbal disclosure exclusively or whether they tap into nonverbal expression as well (Kahn et al., 2012). The purpose of the present study was to determine the role of distress disclosure tendencies on people’s emotional reactions to an induced unpleasant event. First, we evaluated the emotional-reactivity hypothesis by testing whether distress disclosure tendencies would predict subjective experiences of emotion after watching the film. Consistent with the emotional-reactivity hypothesis, we expected distress disclosure tendencies to be negatively associated with positive affect, and positively associated with both negative affect and sadness, following the film. Given the potential role of social desirability on these self-reports of emotion, we controlled for self-deceptive enhancement and impression management (see Paulhus, 1991). Next, we evaluated the emotion-regulation hypothesis. To do this, we first examined the novel question of whether distress disclosure tendencies would predict – above and beyond positive and negative affect – emotion-expressive behavior, that is, nonverbal expressions of emotion. Consistent with the emotion-regulation hypothesis, we expected distress disclosure tendencies to be positively related to expressions of sadness and happiness. We then examined whether disclosure tendencies would predict the verbal disclosure of emotion during a brief post-film interview. Given that verbal disclosure is a form of emotional expression (Kennedy-Moore & Watson, 2001), we expected distress disclosure tendencies to be positively related to emotional Ó 2017 Hogrefe Publishing

J. H. Kahn et al., Distress Disclosure Tendencies

disclosure. As with the test of the subjective experience of emotion, we controlled for social desirability when predicting these verbal reports of emotion.

Method Participants Participants were 84 college students (62 women, 21 men, 1 transgender). Most (74%) were European American, 17% were African American, 6% were Latino/Latina, and 3% identified with other racial/ethnic groups. The mean age was 20.33 (SD = 1.78).

and unhappy were correlated with each other both pre-film, r = .98, and post-film, r = .76. We therefore created a 2-item sadness composite score. Emotion-Expressive Behavior We video recorded participants’ facial expressions while watching the film for later coding of facial expressions of emotion via Gross’s (1996) Emotion Expressive Behavior (EEB) coding system. Each minute of the 11-min video was coded for sadness expression and happiness expression on a 7-point scale, ranging from 0 (= none) to 6 (= strong and long). We computed the means of sadness and happiness across the 11 min to derive indices of sadness expression and happiness expression. Five psychology students coded the videos, yielding intraclass correlations of .93 for happiness and .64 for sadness.

Measures Distress Disclosure Tendencies The 12-item Distress Disclosure Index (DDI) is a self-report measure of individuals’ tendencies to disclose negative emotions and thoughts (Kahn & Hessling, 2001). Participants rate their agreement with each item using a scale ranging from 1 (= strongly disagree) to 5 (= strongly agree). Higher scores reflect a greater tendency over time to disclose negative emotions and thoughts. Coefficient α for scores in the present study was .93. Social Desirability The Balanced Inventory of Desirable Responding (BIDR; Paulhus, 1991) is a 40-item measure of two components of socially desirable responding: (a) self-deceptive enhancement (SDE), which includes self-serving biases and use of denial, and (b) impression management (IM), which includes overt exaggeration and faking (Paulhus & Vazire, 2007). Participants rate each item on a 7-point scale ranging from 1 (= not true) to 7 (= very true). Coefficients α from the present data were .74 (SDE) and .76 (IM). Subjective Experience of Emotion The 20-item Positive and Negative Affect Schedule (PANAS; Watson, Clark, & Tellegen, 1988) measures momentary experiences of PA and NA. There are 10 emotions for each subscale (e.g., interested and excited for PA, distressed and upset for NA), and participants rate the extent to which each emotion was experienced “right now at this moment” on a 5-point scale ranging from 1 (= very slightly or not at all) to 5 (= extremely). Coefficients α in this study were .91 and .88 for trait PA and NA, respectively. We added two affect terms to the PANAS – sad and unhappy – to capture experiences of sadness that are not directly assessed with the PANAS. These items are rated on the same 5-point scale as the PANAS. Ratings of sad Ó 2017 Hogrefe Publishing

Verbal Disclosure of Emotion After the film, participants were interviewed by the research assistant to provide them an opportunity to engage in emotional disclosure. The structured interview consisted of six open-ended questions (e.g., “How did you feel while watching this”). Responses to each interview question were audio recorded, transcribed, and quantitatively coded by the same judges who coded the video recordings to attain a disclosure score ranging from 0 (= no emotional disclosure) to 2 (= high emotional disclosure) for each question. These ratings were then summed across questions. Indicators of high emotional disclosure included the use of emotion words, the personal relevance of the emotion, or verbalizing substantial emotional reactions such as wanting to cry. Intraclass correlations for each item ranged from .78 to .94, indicating strong inter-rater agreement. Participants also completed a 4-item measure of the degree to which they shared (vs. kept private) personal information and emotional reactions during the interview. These items were rated on a 7-point scale ranging from 1 (= not at all) to 7 (= completely). Item responses were summed. Coefficient α was .75. Third, we used the Linguistic Inquiry and Word Count (LIWC; Pennebaker, Chung, Ireland, Gonzales, & Booth, 2007) text-analysis software to count the number of positive-emotion and negative-emotion words the participant uttered in their interview. The LIWC performs counts of the frequency of words in linguistic and content categories. We used the positive and negative emotion categories which are expressed as percentages of the total number of words.

Procedure Participants were students in a psychology course who signed up for this study using an online system. This study Journal of Individual Differences (2017), 38(1), 55–62

was one of several possible research studies from which students could choose, and we did not target specific demographic groups; thus, consistent with the demographics of the participant pool, we had many more women than men participate. Participants did not know the aims of the study at the time they signed up. They earned course credit or extra credit for their participation. The participant entered the laboratory individually and was seated at a table in front of a computer monitor. After providing informed consent, which included agreeing to be video and audio recorded, the participant completed a questionnaire packet that included the DDI, BIDR, and PANAS (including the two additional items). The researcher then explained that the participant would view a brief film clip. The film clip, which was selected to induce sadness, was an 11-min segment from the movie Marley and Me which shows the euthanization of a family pet. The researcher left the room while the participant viewed the film clip. Using a webcam on the top of the monitor (located directly in front of the participant), the participant’s face was video recorded during the film presentation for later coding using the EEB. When the film clip ended, the researcher reentered the laboratory and administered the PANAS once again. The researcher then engaged the participant in the brief interview. This interview was audio recorded and later transcribed for coding and LIWC analysis. After the interview, the participant completed the self-report measure assessing how much she or he disclosed during the interview. At that point, the participant was debriefed and dismissed.

Results Efficacy of Sadness Induction Momentary ratings of sadness increased from before the film clip (M = 1.36, SD = 0.80) to after (M = 3.41, SD = 1.17), t(55) = 11.96, p < .001, d = 1.60. Momentary experience of positive affect, on the other hand, significantly decreased from M = 27.92 (SD = 8.26) to M = 19.88 (SD = 6.67), t(55) = 8.03, p < .001, d = 1.07, whereas momentary experience of negative affect did not significantly change (M = 15.50, SD = 6.17, pre-film, to M = 17.34, SD = 5.95, post-film), t(55) = 1.96, p = .06, d = .26. Thus, the film appeared to evoke sadness specifically but not negative affect in a general sense.

Predicting Subjective Experience of Emotion We examined whether distress disclosure tendencies predicted one’s subjective experience of emotion following Journal of Individual Differences (2017), 38(1), 55–62

J. H. Kahn et al., Distress Disclosure Tendencies

Table 1. Standardized slopes from multiple regression analyses predicting subjective experience of emotion Post-film measure Predictor

Positive affect

Negative affect

Sadness

Pre-film measurea

.49***

.32*

.29*

Self-deceptive enhancement

.00

.05

.02

Impression management

.01

.02

.21

Distress disclosure tendencies

.09

.02

.20

.27**

.11

.15

4, 51

Degrees of freedom

4, 51

Notes. aPre-film measure was the same measure as the post-film measure (e.g., pre-film positive affect predicting post-film positive affect). *p < .05; **p < .01; ***p < .001; two-tailed.

the film. In the prediction of post-film positive affect using the DDI, we controlled for social desirability and pre-film positive affect. The regression analysis revealed that, as would be expected, pre-film positive affect significantly predicted post-film positive affect, but, contrary to the emotional-reactivity hypothesis, distress disclosure tendencies did not (see Table 1). Thus, distress disclosure tendencies did not predict a decrease in positive affect. We conducted a similar analysis on negative affect. We controlled for pre-film negative affect and social desirability and found similar results as with the analysis of positive affect. Specifically, pre-film negative affect significantly predicted post-film negative affect, but distress disclosure tendencies did not (see Table 1). The prediction of sadness also showed similar results. Distress disclosure tendencies did not predict a change in sadness while controlling for social desirability (see Table 1). Distress disclosure tendencies not predicting changes in positive affect, negative affect, or sadness indicate that distress disclosure tendencies were not related to emotional reactivity.

Predicting Facial Expressions Our second purpose was to examine the degree to which distress disclosure tendencies predicted behavioral expressions of emotion via facial expressions, specifically, expressions of happiness and sadness in response to the unpleasant film. We conducted two regression analyses, one for happiness expression and one for sadness expression. We controlled for pre-film positive and negative affect given that dispositional affectivity might affect emotion displays. Neither positive affect nor negative affect predicted facial expressions of happiness, but distress disclosure tendencies did (see Table 2). Specifically, a greater tendency to disclose distress was associated with greater expressions of happiness. Likewise, distress disclosure tendencies significantly and positively predicted expressions of sadness, Ó 2017 Hogrefe Publishing

J. H. Kahn et al., Distress Disclosure Tendencies

Table 2. Standardized slopes from multiple regression analyses predicting emotion-expressive behavior Measure of emotionexpressive behavior Predictor

Happiness

Sadness

Positive affect

.20

.15

Negative affect

.07

.04

Distress disclosure tendencies

.34**

.27*

R2 Degrees of freedom

.15** 3, 73

.09 3, 73

Notes. *p < .05; **p < .01; ***p < .001; two-tailed.

controlling for positive and negative affect. Thus, distress disclosure tendencies were associated with increased facial expressions of both sadness and happiness above and beyond one’s subjective experience of emotion.

Predicting Verbal Disclosure of Emotions Our third purpose was to determine if distress disclosure tendencies predicted verbal disclosure of emotion. We examined self-reported disclosure, observer ratings of disclosure, and computer text analyses of disclosure (positive and negative emotions). Given that verbal disclosure of emotion is a form of self-report, we controlled for social desirability. We also controlled for happiness and sadness facial expressions during the film to see if distress disclosure tendencies could predict unique variance in verbal disclosure above and beyond that accounted for by nonverbal expressions of emotion. As Table 3 shows, self-deceptive enhancement and sadness facial expressions both positively predicted selfreports of emotional disclosure. Distress disclosure tendencies did not predict unique variance in disclosure self-reports. Observer ratings of verbal disclosure of emotion, on the other hand, were predicted by distress disclosure tendencies. This was the case even though both forms of impression management were predictive of observer reports (self-deceptive enhancement positively and impression management negatively) as well as happiness facial expressions being positively predictive of observer ratings of emotional disclosure. Note that self-reports and observer ratings are valence-free measures, that is, they simply measure disclosure of emotion, either positive or negative in valence. The two measures of valenced emotional disclosure – positive-emotion and negativeemotion counts from the LIWC – did not reveal any association between distress disclosure tendencies and verbal disclosure of emotion. Thus, observers did detect the higher levels of emotional disclosure from people who identify as trait disclosers, but these levels were not identified via self-reports nor computer text analyses. Ó 2017 Hogrefe Publishing

Discussion It has been firmly established that people often feel compelled to talk about the emotions that they experience (Rimé, 2009) and that individuals differ in their tendency to talk about distress in particular (Kahn et al., 2012). The specific process responsible for these individual differences has not been established, however. The aim of this study was to address two competing hypotheses about why individuals differ in distress disclosure. Our first purpose addressed how distress disclosure tendencies predict the subjective experience of sadness in response to a standardized emotion-eliciting stimulus. If distress disclosure tendencies reflect individual differences in emotional reactivity, then high distress disclosers should have reported more changes in affect in response to the film clip than low disclosers. We found that this was not the case. This lab-based finding, which is consistent with correlational (e.g., Kahn & Hessling, 2001) and diary studies (e.g., Ryan & Kahn, 2015), indicates that high distress disclosers do not simply have more distress to disclose. Whereas people may feel compelled to share emotions that they experience (Rimé, 2009), greater emotional reactivity does not seem to explain why individuals differ across time and situations in their tendency to disclose distress. Our second purpose addressed whether high and low distress disclosers differ in their emotion-regulation strategies. This hypothesis suggests that high distress disclosers attempt to down-regulate emotions by expressing them, whereas low distress disclosers attempt to down-regulate emotions by suppressing them (Gross & John, 2003). Consistent with this, high distress disclosers were rated by judges as showing more facial expressions of emotion than low distress disclosers (i.e., concealers). This finding, as well as prior evidence that distress disclosure tendencies and expressive suppression are negatively correlated (Kahn et al., 2012), indicates that distress disclosure tendencies reflect the strength of using both verbal and nonverbal expressions of emotion. We further note that distress disclosure tendencies, which by definition focus on negative affect, predicted the facial expression of both sadness and happiness. This suggests that distress disclosure tendencies are not valence specific, that is, disclosers may be as likely to disclose pleasant emotions as they are to disclose distressing emotions. Our third hypothesis was that distress disclosure tendencies would predict verbal expression of emotion. Only one prior laboratory study (Kahn et al., 2002) had investigated whether distress disclosure tendencies predicted verbal expressions of distress. In that study, disclosure tendencies did indeed predict the number of times distress was verbally acknowledged as well as judges’ Journal of Individual Differences (2017), 38(1), 55–62

J. H. Kahn et al., Distress Disclosure Tendencies

Table 3. Standardized slopes from multiple regression analyses predicting verbal disclosure of emotions Measure of verbal disclosure of emotion Predictor

Self-report

Observer rating

LIWC positive emotion

Self-deceptive enhancement

.26*

.25*

.07

LIWC negative emotion .05

Impression management

.08

.23*

.24

.07

Happiness expressive behavior

.01

.22*

.23

.05

Sadness expressive behavior

.25*

.12

.16

.15

Distress disclosure tendencies

.02

.32**

.13

.11

.16*

.30***

.12

Degrees of freedom

5, 71

5, 70

.05 5, 70

Notes. *p < .05; **p < .01; ***p < .001; two-tailed.

rating of negative affect during a post-film interview. The present study replicated these findings; distress disclosure tendencies predicted judges’ ratings of participants’ disclosure during the post-film interview. We note that the judges’ ratings in our study operationalized disclosure quite broadly by considering emotion words used, the personal relevance of the emotions, as well as their verbalization of their emotional reactions. Therefore, we examined two other indicators of verbal disclosure – participant self-reports and counts of positive and negative emotion words. Despite prior research indicating that distress disclosure tendencies can predict self-reported disclosure of unpleasant events (Garrison et al., 2014) and that emotion word usage is indicative of emotional expression (Kahn, Tobin, Massey, & Anderson, 2007), we did not find an association between distress disclosure tendencies and either indicator of verbal disclosure. There are limits to the use of computerized text analyses in measuring emotion (e.g., falsely counting “not too upset” as negative emotion), but the nonsignificant finding for self-reports is difficult to explain. The reliability and validity of the selfreport measure did not seem to be in question because self-deceptive enhancement and sadness expressive behavior were predictive of these self-reports. Future research that investigates how participants and judges view participant disclosure may help to explain this unexpected result. For example, perhaps observers were better able to attend to participants’ vocal tones and that the acoustic properties of one’s verbalizations were therefore responsible for appraisals of emotional expression (Juslin & Scherer, 2005).

Limitations and Future Research Ideas This laboratory study had many strengths, such as the use of a standardized emotion stimulus and multiple methods of recording emotion, including self-report, observers’ coding of emotion-expressive behavior, observers’ coding

Journal of Individual Differences (2017), 38(1), 55–62

of verbal disclosure of emotions, and computerized text analysis of emotional disclosures. This study also had limitations that should be noted. First, the sample size may not have provided sufficient power to detect some small effects that were present. We also were not able to conduct any subgroup analyses based on gender or other potentially relevant variables. Second, the specific emotion we studied was sadness, but distress can take many forms. For example, the experience and expression of self-focused emotions such as shame or other-focused emotions such as anger might map onto distress disclosure tendencies in different ways. Future research on a wider variety of emotional states would be valuable. Third, we did not include a control group of participants who viewed an alternative film clip (e.g., a nonemotional film, an emotionally pleasant film). As such, we do not know if the indicators of emotion that we measured resulted strictly from the film clip. Fourth, the influence of the researcher/interviewer on the verbal disclosures of emotion was not assessed in this study. Nils and Rimé (2012) found that when listeners adopted a socio-affective mode, emotional disclosure was not as useful as compared to listeners using cognitive reframing. It would be useful to extend this research to see how the listener’s response mode might affect the depth of people’s verbal expressions of distress.

Conclusions In the literature, distress disclosure tendencies have been examined as they relate to a variety of applied issues such as psychological distress and willingness to seek counseling (see Kahn et al., 2012). This was the first study of which we are aware that has examined the more basic issue of how distress disclosure tendencies relate to the unfolding of the emotion process itself. Our findings suggest that distress disclosure tendencies do not arise because of individual differences in emotional reactivity. Instead, distress disclosure tendencies seem to result

Ó 2017 Hogrefe Publishing

J. H. Kahn et al., Distress Disclosure Tendencies

from the permeability of people’s filters between their subjective emotional experiences and their emotional expressions. Forms of emotional expressions that are predicted by distress disclosure tendencies include both verbal (to some extent) and nonverbal expressions, and they are not valence specific. Thus, distress disclosure tendencies may in fact reflect a general disposition to express affect and not a specific verbal expression of negative affect. This study therefore took an important step toward integrating research on this important individual-difference variable with fundamental theories of emotion. Acknowledgments We thank Lauren DiLorenzo, Agnes Strojewska, Emma Leonard, Rajan Hayre, and Johnny Lo for helping with data collection and coding.

References Barr, L. K., Kahn, J. H., & Schneider, J. W. (2008). Individual differences in emotional expression: Hierarchical structure and relations with psychological distress. Journal of Social and Clinical Psychology, 27, 1045–1077. doi: 10.1521/jscp. 2008.27.10.1045 Garrison, A. M., & Kahn, J. H. (2010). Intraindividual relations between the intensity and disclosure of daily emotional events: The moderating role of depressive symptoms. Journal of Counseling Psychology, 57, 187–197. doi: 10.1037/ a0018386 Garrison, A. M., Kahn, J. H., Miller, S. A., & Sauer, E. M. (2014). Emotional avoidance and rumination as mediators of the relation between adult attachment and emotional disclosure. Personality and Individual Differences, 70, 239–245. doi: 10.1016/j.paid.2014.07.006 Garrison, A. M., Kahn, J. H., Sauer, E. M., & Florczak, M. A. (2012). Disentangling the effects of depression symptoms and adult attachment on emotional disclosure. Journal of Counseling Psychology, 59, 230–239. doi: 10.1037/a0026132 Greenland, K., Scourfield, J., Maxwell, N., Prior, L., & Scourfield, J. (2009). Theoretical antecedents of distress disclosure in a community sample of young people. Journal of Applied Social Psychology, 39, 2045–2068. doi: 10.1111/j.1559-1816.2009. 00515.x Gross, J. J. (1996). Emotional expressive behavior (EEB) coding system. Stanford, CA: Stanford University. Gross, J. J., & Feldman Barrett, L. (2011). Emotion generation and emotion regulation: One or two depends on your point of view. Emotion Review, 3, 8–16. doi: 10.1177/ 1754073910380974 Gross, J. J., & John, O. P. (2003). Individual differences in two emotion regulation processes: Implications for affect, relationships, and wellbeing. Journal of Personality and Social Psychology, 85, 348–362. doi: 10.1037/0022-3514. 85.2.348 Gross, J. J., & Thompson, R. A. (2007). Emotion regulation: Conceptual foundations. In J. J. Gross (Ed.), Handbook of emotion regulation (pp. 3–24). New York, NY: Guilford.

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Juslin, P. N., & Scherer, K. R. (2005). Vocal expression of affect. In J. A. Harrigan, R. Rosenthal, & K. R. Scherer (Eds.), The new handbook of methods in nonverbal behavior research (pp. 65–135). New York, NY: Oxford University Press. Kahn, J. H., Achter, J. A., & Shambaugh, E. J. (2001). Client distress disclosure, characteristics at intake, and outcome in brief counseling. Journal of Counseling Psychology, 48, 203–211. doi: 10.1037/0022-0167.48.2.203 Kahn, J. H., & Garrison, A. M. (2009). Emotional self-disclosure and emotional avoidance: Relations with symptoms of depression and anxiety. Journal of Counseling Psychology, 56, 573–584. doi: 10.1037/a0016574 Kahn, J. H., & Hessling, R. M. (2001). Measuring the tendency to conceal versus disclose psychological distress. Journal of Social and Clinical Psychology, 20, 41–65. doi: 10.1521/jscp.20. 1.41.22254 Kahn, J. H., Hucke, B. E., Bradley, A. M., Glinski, A. J., & Malak, B. L. (2012). The Distress Disclosure Index: A research review and multitrait-multimethod examination. Journal of Counseling Psychology, 59, 134–149. doi: 10.1037/a0025716 Kahn, J. H., Lamb, D. H., Champion, C. D., Eberle, J. A., & Schoen, K. A. (2002). Disclosing versus concealing distressful information: Linking self-reported tendencies to situational behavior. Journal of Research in Psychology, 36, 531–538. doi: 10.1016/S0092-6566(02)00008-9 Kahn, J. H., Tobin, R. M., Massey, A. E., & Anderson, J. A. (2007). Measuring emotional expression with the Linguistic Inquiry and Word Count. The American Journal of Psychology, 120, 263–286. doi: 10.2307/20445398 Kennedy-Moore, E., & Watson, J. C. (2001). How and when does emotional expression help? Review of General Psychology, 5, 187–212. doi: 10.1037/1089-2680.5.3.187 Nils, F., & Rimé, B. (2012). Beyond the myth of venting: Social sharing modes determine the benefits of emotional disclosure. European Journal of Social Psychology, 42, 672–681. doi: 10.1002/ejsp.1880 Paulhus, D. L. (1991). Measurement and control of response bias. In J. P. Robinson, P. R. Shaver, & L. S. Wrightsman (Eds.), Measures of personality and social psychological attitudes (pp. 17–59). San Diego, CA: Academic Press. Paulhus, D. L., & Vazire, S. (2007). The self-report method. In R. W. Robins, R. C. Fraley, & R. F. Krueger (Eds.), Handbook of research methods in personality psychology (pp. 224–239). New York, NY: Guilford. Pederson, E. L., & Vogel, D. L. (2007). Measuring gender role conflict and willingness to seek counseling: Testing and mediation model on college-aged men. Journal of Counseling Psychology, 54, 373–384. doi: 10.1037/0022-0167.54.4.373 Pennebaker, J. W., Chung, C. K., Ireland, M., Gonzales, A., & Booth, R. J. (2007). The development and psychometric properties of LIWC2007. Austin, TX: LIWC.net. Rimé, B. (2009). Emotion elicits the social sharing of emotion: Theory and empirical review. Emotion Review, 1, 60–85. doi: 10.1177/1754073908097189 Ryan, M. B., & Kahn, J. H. (2015). Talking about daily emotional events: Psychological well-being moderates the intensitydisclosure link. Personality and Individual Differences, 83, 223–227. doi: 10.1016/j.paid.2015.04.027 Vogel, D. L., & Wester, S. R. (2003). To seek help or not to seek help: The risks of self-disclosure. Journal of Counseling Psychology, 50, 351–361. doi: 10.1037/0022-0167.50.3.351 Watson, D., Clark, L. A., & Tellegen, A. (1988). Development and validation of brief measures of positive and negative affect: The PANAS scales. Journal of Personality and Social Psychology, 54, 1063–1070. doi: 10.1037/0022-3514.54.6.1063

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Wei, M., Russell, D. W., & Zakalik, R. A. (2005). Adult attachment, social self-efficacy, self-disclosure, loneliness, and subsequent depression for freshman college students: A longitudinal study. Journal of Counseling Psychology, 52, 602–614. doi: 10.1037/0022-0167.52.4.602 Received May 24, 2016 Revision received July 29, 2016 Accepted September 4, 2016 Published online February 10, 2017

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J. H. Kahn et al., Distress Disclosure Tendencies

Jeffrey H. Kahn Department of Psychology Illinois State University Campus Box 4620 Normal, IL 61790-4620 USA jhkahn@ilstu.edu

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