SPJI 2010 by Student Psychology Journal of Ireland

Student Psychology Journal Trinity College Dublin

VOLUME I

Published by the Student Psychology Journal C/O Department of Psychology, Trinity College, Dublin 2, Republic of Ireland. All rights reserved. Copyright ÂŠ Contributors to the Student Psychology Journal All views expressed herein are those of the authors and do not necessarily reflect the views of the editors or sponsors. All correspondence or complaints should be addressed to: The Editor, Student Psychology Journal, C/O Department of Psychology, Trinity College Dublin, Republic of Ireland. or email: journal@tcd.ie Printed by Brunswick Press Ltd. The Student Psychology Journal is also available online at: www.tcd.ie/psychology/SPJ

MAIN SPONSOR We would like to thank the Trinity College Dublin Association and Trust for their generosity in providing a grant to fund the establishment of this journal. Without their invaluable support, this journal could not have been printed or launched this year. We are proud to be the first ever committee of the Student Psychology Journal and we are grateful to the Trinity College Dublin Association and Trust for making this academic endeavour possible.

SPONSORS The Psychological Society of Ireland * The Open University * Graduate Studies Office, Trinity College * School of Psychology, Trinity College * Trinity Publications

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PEER REVIEWERS We would like to extend our immense gratitude to the peer reviewers for their time and invaluable input.

Ms Ashling Bourke * Ms Aoife De Brún * Mr Simon Dunne * Dr Michael Gormley * Dr David Hevey * Prof Malcolm MacLachlan * Dr Elizabeth Nixon * Prof John O’Hagan * Mr Joseph Stephen Plowman * Dr Jean Quigley * Prof Ian Robertson * Dr Lorraine Swords

Student Psychology Journal Trinity College Dublin PRESIDENT Dr. Jean Quigley EDITOR Jason Somerville DEPUTY EDITORS Áine Ní Choisdealbha David Lydon GENERAL MANAGER Clare Delargy FINANCE OFFICER Owen McLoughlin SPONSORSHIP OFFICER Jennifer Finn JUNIOR COMMITTEE Magdalena Michalewska Róisín White Tara O’Halloran John McGeever Owen Sheehy

A MESSAGE FROM THE DEAN OF GRADUATE STUDIES PROFESSOR VERONICA CAMPBELL

The Student Psychology Journal is an excellent initiative to highlight the pertinent issues in Psychology today and to provide students with the opportunity to showcase their work. The Student Psychology Journal may have fuelled your interest in research and further postgraduate study in the Psychology field. If so, I invite you to visit the Graduate Studies website http://www.tcd.ie/ Graduate_Studies/ to find out about the range of postgraduate courses we offer in this area or email us with your queries at gradinfo@tcd.ie The Graduate Studies Office is delighted to support the inaugural Student Psychology Journal and wishes the editorial team every success with this new venture.

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Network of psychology students in Ireland Opportunity to network with professionals in your field Variety of membership benefits, including great deals to be had on car insurance through Glennon Reduced rates at PSI events Automatic subscription to, the Irish Psychologist, ten issues per year delivered to your door

Only €25 annual subscription Become a student subscriber now. For details, go to: http://www.psihq.ie/SSApp2010.pdf

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BEST ESSAY AWARD

HARNESSING THE BRAIN’S CAPACITY FOR PLASTICITY Siobhán Harty

TABLE OF CONTENTS Preface

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Editor’s Introduction

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The effect of “hot” (System 1) and “cold” (System 2) cognitive processing on time prediction accuracy. -Bridget Finnegan

An analysis of discourse used by General Patton to motivate the soldiers of the Third Army to fight for America in the Second World War. -Teresa Corbett

Mood dependent memory for self-generated words using a musical mood induction procedure. -Melissa Daly

An investigation of the effects of Neuroticism and Extraversion on musically-induced emotions -Jean Herlihy

Irish secondary school students’ intention to pursue higher education: an investigation to identify the strongest predictors -Catherine Rock

TABLE OF CONTENTS REVIEW ARTICLES Harnessing the brain’s capacity for plasticity -Siobhán Harty

What can psychoanalysis tell us about depression? -Sheila Armstrong

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Gene-environment interactions in determining criminality. -Laura Mangan

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Seeing through the body: The effects of visual and sensorimotor experience on the analysis of hands. -Áine Ní Choisdealbha

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The effect of extracurricular activities on career outcomes: A literature review. -Lisa Keenan

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Childhood obesity: Contributions of developmental research to interventions. -Bridget Finnegan

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Psychosocial factors impacting on treatment adherence in diabetes -David Lydon

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PREFACE Welcome to the first volume of the Trinity College Student Psychology Journal. This journal has been established to provide an outlet for the outstanding contributions undergraduate students offer to our understanding of human behaviour. There is no comparable journal for psychology students in Ireland, and we feel that it is necessary that the considerable academic achievements of students be recognised in print. During the course of their studies, undergraduate students produce original and exceptional work but often their potential contributions to our body of knowledge are left unrealised. We are excited and proud to offer an insight into the minds of Irelandâ&#x20AC;&#x2122;s psychology undergraduates. Psychology can play an instrumental role in shaping society and seeking an understanding of the behaviour and choices which have affected Ireland recently. Recent psychology graduates face a different future on leaving college than that of graduates a few years ago. The insights of the new generation have never been more important, these are the people who will be rebuilding Ireland. The skill set developed during the undergraduate years means that psychology students are uniquely capable of doing this. The role psychology plays in society and public affairs can only increase in the future, and we believe that those published in this journal will play an integral part in doing so. The journal committee would like to thank everyone who has helped since our inception. In particular, our President, Dr. Jean Quigley, who has been a constant source of advice and encouragement. Many thanks also to the TCD School of Psychology for their financial and administrative support, to our Academic Peer Reviewers and the academics who helped us to attract sponsorship. Our thanks also to Dr. Liam Delaney for agreeing to launch the journal for us. To everyone who submitted to the journal, and those who are published in the first edition, thank you all for your contributions and congratulations on your excellent submissions. I would like extend our gratitude to our sponsors the TCD Association and Trust, Open University, TCD Graduates Office and Psychology Society of Ireland for supporting and having faith in a fledgling journal. xiii

Lastly, I have to thank our wonderful committee. From the Editor Jason and his assistant editors Áine and David to the Sponsorship Manager Jen and finance manager Owen, you have all worked extremely hard over the past six months and this journal is a credit to your endeavour and resourcefulness. I would also like to recognise the work of this year’s Junior Committee Roisin, Tara, Magda, Owen and John; I wish you all the best of luck with next year’s journal. Working with you all to create this journal has been a pleasure. I hope you enjoy the 2010 Student Psychology Journal, Clare Delargy General Manager, 2010

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EDITOR’S INTRODUCTION Over the past twelve months, it has been my great pleasure to see the creative insights of undergraduates here at Trinity College find their way to publication. When we first set out to produce this journal we did not know what to expect. To my great delight the response from students and staff has been tremendous and the articles presented here represent the hard work of two committees, dozens of authors, a psychology department, six generous sponsors and countless others. The Journal is comprised of two sections. The first focuses on the original research designs undertaken by undergraduates. This year we have presented both quantitative and qualitative analyses that cover the board spectrum of the discipline. From a discourse analysis of General Patton’s speech to the Third Army to an investigation of students’ intentions to pursue higher education, I hope that academics, students and enthusiasts in general enjoy the papers presented here. The second section concentrates on review papers in which undergraduates give fresh perspectives on various topics in psychology. It is here where the creativity of undergraduates really shines, covering areas as diverse as neuroscience, cognition, development, social psychology, economics, psychoanalysis and biomedicine. Analysis of this sort is crucial in shaping the direction of psychology as a discipline, and we hope that the papers presented here will make a valuable contribution in this endeavour. The selection process for this year’s journal was an exceptionally difficult task. The quality of submissions received was exceptional and this inevitably led to a lot of lively debates amongst the editorial team. On that note, I’d like to extend my most sincere gratitude to this year’s assistant editors, Áine Ní Choisdealbha and David Lydon. Without their commitment to academic excellence and a meticulous attention to detail, the first volume of this journal would not have met such a high standard. I would also like to extend my sincerest gratitude to the president of the journal, Dr Jean Quigley. Her guidance throughout the year has been instrumental in getting this journal off the ground and without her assistance this project may have remained an unfulfilled ambition.

The analyses presented here are a true testament to the authorsâ&#x20AC;&#x2122; determination and professionalism. I am confident that the first volume of the Student Psychology Journal meets the standard set out 12 months ago and will earn its place alongside the many outstanding publications the undergraduate students of Ireland. Jason Somerville, Editor, 2010

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Hypotheses are nets; only the one who casts will catch - Novalis

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THE EFFECT OF “HOT” (SYSTEM 1) AND “COLD” (SYSTEM 2) COGNITIVE PROCESSING ON TIME PREDICTION ACCURACY Bridget Finnegan Graduate 2010, Psychology finnegb@tcd.ie

ABSTRACT The purpose of the present study was to investigate how “hot” (System 1) and “cold” (System 2) cognitive processes influence accuracy of temporal predictions. One hundred university students (34 male, 66 female) were randomly assigned to one of five experimental conditions - hot processing, cold processing, positive affect, negative affect and control. After each participant’s cognitive processing mode was manipulated, they were asked to estimate the duration of an essay formatting task, complete the task, and then retrospectively estimate its duration. Actual completion times were recorded, and the discrepancy between estimated and actual task duration was calculated for each participant. Results of a between-groups ANOVA indicated marginally significant differences between experimental conditions in terms of directional prospective discrepancy scores. A second ANOVA on absolute prospective discrepancy scores revealed the negative affect condition made significantly less biased predictions than the control condition. Results revealed a statistically significant positive correlation between absolute prospective discrepancy scores and absolute retrospective discrepancy scores. A statistically significant positive correlation was also found between estimated and actual task durations. Overall, the current findings tentatively support the hypothesis that dual-process accounts offer a partial explanation for the planning fallacy, with affect also emerging as a factor underlying people’s ability to estimate task duration. Support for the memory bias account of the planning fallacy also emerges.

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INTRODUCTION The current study investigated how different modes of cognitive processing may influence time prediction accuracy. Individuals, organisations, and governments all commonly plan projects and estimate when they will be completed. It is a well-documented phenomenon that in many cases these estimates are overly optimistic. This tendency to underestimate future task duration, despite experience that prior estimates were inaccurate, is known as the planning fallacy (Kahneman & Tversky, 1979). Given the potential gravity of temporal misestimation, it is essential to gain an understanding of why the planning fallacy occurs. Kahneman & Tversky (1979) suggest that when making temporal predictions, people adopt a singular, “inside” perspective and focus on specific aspects of the task, as opposed to a distributional, “outside” perspective, which takes into account factors such as past duration of similar tasks. Several findings support this perspective (Buehler et al., 1994). However, not all are consistent with this approach (Byram, 1997; Hinds, 1999). Kruger & Evans (2004) offer an opposing approach to the planning fallacy, suggesting it results from not taking enough of an inside perspective. They found that when prompted to unpack tasks into various subcomponents, participants provided less biased estimates of task duration. Another possible explanation is the memory bias account (Roy, Christenfeld, & McKenzie, 2005), which proposes that inaccurate memories, rather than failure to use memory appropriately, lead to error. In accordance with this, underestimation of future duration may be due to underestimation of past duration (König, 2005; Thomas, Handley, & Newstead, 2004, 2007). Providing feedback on task duration can improve accuracy of prospective temporal predictions (Roy, Mitten, & Christenfeld, 2008). A related approach is the anchoring perspective (Thomas, Newstead, & Handley, 2003), which proposes that misestimation occurs because previous task duration influences predictions that are insufficiently adjusted for the current task. Planning fallacy processes remain puzzling. Few studies have investigated the factors that mediate prediction processes. The current study proposes that the planning fallacy could be explained by another relatively recent product of the cognitive paradigm - dual-processing accounts of reasoning, judgement, and social cognition (Evans & Over, 4

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1996). Over the past two decades the field of judgement and decision making has moved away from the traditional focus on “cold” deliberative decision making, and has begun investigation of “hot”, intuitive processes (Peters, Västfjäll, Gärling, & Slovic, 2006). Although many dual-process theories have developed (Epstein, 1994; Kahneman & Frederick, 2002; Sloman, 1996), they commonly share the distinction between two cognitive systems. System 1 (also known as heuristic or experiential) processing is evolutionarily old, shared with animals, and operates automatically and rapidly via parallel processing. System 1 is thought to solve problems using prior knowledge, beliefs and heuristic processes (Evans, 2003). In contrast, System 2 (also known as analytic or rational) processing is evolutionarily recent and distinctly human. It facilitates abstract reasoning and hypothetical thinking, but is constrained by working memory capacity and intelligence (Stanovich & West, 1997). Researchers in the field of reasoning also emphasise the inhibitory role of System 2 in suppressing heuristic processing, default knowledge and belief-based responses (Evans, 2003). Dual-process accounts have received good empirical support. Studies have found a shift from logical to belief-based reasoning under severe time pressure (Evans & Curtis-Holmes, 2005) and under concurrent working memory load (De Neys, 2006). Analytical thinking is more likely when individuals display a critical disposition (Stanovich, 1999). According to developmental research, System 2 abilities are more strongly associated with children’s age and intelligence (Klaczynski, 2001) and decline more with old age, relative to System 1 (Gilinsky & Judd, 1994). More recently neuropsychological research has implicated anatomically distinct brain regions in different types of reasoning (Goel & Dolan, 2003). Dual-processing accounts show potential to explain several findings concerning the planning fallacy. For example, one dual-process theory proposes that heuristic processes cause bias in judgements by selectively focusing attention on task features and prior experiences that appear relevant, until analytic processing intervenes (Evans, 2006). Similarities can be identified between this approach and both inside/outside and memory bias accounts of the planning fallacy. Additionally, findings that analytic processing may be cued by strong deductive reasoning instructions (Pretz, 2008) are akin to findings that temporal underestimation is reduced when people are prompted to unpack tasks 5

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(Kruger & Evans, 2004). Many intuitive biases associated with System 1 reasoning have also been associated with the planning fallacy. For example, some theorists suggest that the availability bias (Kahneman & Tversky, 1982) explains why people do not consider possible disruptions when making temporal estimations (Byram, 1997). A central aspect of dual-processing account is the role of affect in cognitive processing. “Affect” refers to the specific quality of “goodness” or “badness” of a stimulus (Slovic et al., 2007). Zajonc (1980) proposes that automatic affective reactions to stimuli guide subsequent information processing and judgement. People may use affective representations held within a mental “affect pool” as decision-making cues, just as they utilise heuristics such as representativeness (Kahneman et al., 1982) to conserve limited mental resources. This mental shortcut has been labelled the Affect Heuristic (Finucane et al., 2000). Affect is explicitly linked with the experiential system - System 1 (Epstein, 1994), an idea supported by neurological findings (Lieberman, 2003). Given the established importance of affect in everyday-decision making (e.g. Damasio, 1994; Loewenstein, Weber, Hsee & Welch, 2001), it follows that affect may play a role in judgements such as duration prediction. Potential links can be drawn between research on affect and research investigating the impact of motivation and incentives on the planning fallacy. For example, desire to finish quickly, overestimation of personal skill, and monetary incentives (all of which are affect-laden consequences) have been thought to increase the planning fallacy (Byram, 1997). One interesting trend to emerge from a review of the literature is the discernible inconsistency between theoretical and empirical evidence regarding the individual influences of positive and negative affect. While some theorists argue that valence of affect is important (Forgas, 1995; Frederickson, 2001; Isen, 2000; Leith & Baumesiter, 1996; Wright & Bower, 1992), others propose that positive and negative affect do not necessarily exert opposite effects on cognition (Cahir & Thomas, 2010; Caruso & Shafir, 2006). Overall, the literature offers a highly incoherent account of the role of affect on judgements. Methodological limitations such as the simultaneous comparing of negative and positive affect (Yuen & Lee, 2003) and the validity of induction techniques (Isen & Erez, 2007)

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may partially explain this inconsistency. Further systematic research is required to clarify matters. The purpose of the current study was to build on planning fallacy research by investigating how different modes of cognitive processing influence accuracy in estimates of task duration. If predictions are influenced by mode of cognitive processing, use of System 2 reasoning should produce less biased estimates than those using System 1. This prediction was tested using an experiment involving five conditions. One experimental group was manipulated to use “cold” (System 2) processing via direct instructions. A cognitive load task was used to induce “hot” (System 1) processing in another condition. The labels “hot” and “cold” were applied to the first two experimental conditions as these were considered neutral terms, and avoided endorsement of any particular dualprocess theory. In order to investigate the influence of affect on temporal predictions, as well as the role of affect within dual-systems accounts, standardised induction stimuli were used to induce positive and negative affect respectively in two other conditions. A control condition, which received no intervention, was included to establish which mode of cognitive processing was most indicative of prediction processes underlying “natural” misestimation. On the basis of previous research it was anticipated that participants using “hot” processes would produce more biased estimates than those using “cold” processes. Since affect is considered part of the experiential system (Epstein, 1994), it was expected that, similar to the hot group, participants in affect conditions would underestimate more than those using cold, logical reasoning. Given the inconsistency in the literature surrounding the individual influences of positive and negative affect, no specific predictions were made about potential differences between positive and negative affect conditions. Based on both the memory bias account and dual-process accounts, it was predicted that participants who made less accurate prospective estimates of task duration, would also make less accurate retrospective estimates, since the same mode of cognitive processing should be applied to both. This exploratory study offers a novel integration of three contemporary issues in cognitive psychology - the planning fallacy, dualsystems accounts, and the role of affect in cognition. The results of the study may add to the current body of knowledge, by determining if dual7

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systems theories of cognitive processing can account for the planning fallacy. They will also help determine if and how positive and negative affect contribute to the thinking processes underlying peopleâ&#x20AC;&#x2122;s ability to estimate how much time tasks will take to complete.

METHODS Design A univariate, between-groups design was used, with participants being randomly assigned to one of five conditions. Prior to estimating duration of a task, the type of cognitive processing each group engaged in was manipulated as follows: Group 1: Cold processing, Group 2: Hot processing, Group 3: Positive affect, Group 4: Negative affect, Group 5: Control- no manipulation. The discrepancy between predicted and actual task duration was recorded for each participant, as was the discrepancy between retrospectively estimated duration and actual duration. Participants The sample consisted of one hundred (66 female, 34 male) undergraduate students, aged 18 to 59 years (Mean (SD) age=21.46(5.75)). Materials Different materials were used to induce cognitive processing modes across participants. System 2 induction technique Participants in the cold condition were instructed to follow a set of 6 instructions while they viewed the task prior to making their estimate. These were designed to induce consideration of both singular and distributional information about the task. 1. 2. 3. 4.

Consider the different subtasks involved in formatting the essay Break the task down into segments Estimate how many spelling mistakes or formatting errors may be in each segment Consider your own past experiences of essay formatting and proofreading

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5. 6.

Identify things which may speed up or slow down your performance Consider how this task is similar or different to tasks you have performed in the past

System 1 Induction Technique While viewing the task, participants in the hot group simultaneously completed a cognitive load task. This consisted of an auditory digit search task, adapted from a visual task used by Green Morelli, Lowenberg, Nystrom & Cohen (2008). The task required participants to listen to a 3 minute recording of sequences of numbers between 1 and 20, and press the control key (ctrl) each time they heard the number 5. They were advised their performance would be assessed at the end of the session. Numbers were presented at a rate of one every two seconds for the first 1.5 minutes, after which the rate increased to 1 number per second, to avoid practice effects (Greene et al., 2008). The number 5 was presented 20% of the time. Affect induction technique The International Affective Picture System (IAPS) is a collection of standardised emotionally suggestive photographs which have been rated for emotional valence and arousal (Lang, Bradley, & Cuthbert, 2005). These ratings were used to select 20 positive (valence rating M=7.44) and 20 negative images (valence rating M=2.59), on the basis of generating two distinct affective states of comparable magnitude. Selected images were presented using Microsoft PowerPoint, with each image displayed for ten seconds. Affect Manipulation Check The Positive and Negative Affect Schedule (PANAS) is a 20-item selfreport measure of positive and negative affect developed by Watson, Clark, and Tellegen (1988b). It was used to assess baseline positive and negative affect in all groups, as well as post-induction affect in the positive and negative affect conditions. This measure has been used in extensive and diverse previous research. In the current study, the positive and negative affect subscales achieved Cronbachâ&#x20AC;&#x2122;s Alphas of .92 and .85 respectively.

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Essay Formatting Task A Microsoft Word essay formatting task of typical college assignment length (2,500 words) was used to generate predicted and actual task completion times. Materials are available upon request from the researcher. The formatted version was presented as a hard copy on white A4 paper. The unformatted version was presented as a Microsoft Word document on a computer. The task required participants to make 203 formatting changes to the unformatted version using Microsoft Word, so that it exactly matched the formatted copy. Stopwatches were used to record task completion times. Procedure Participants were tested in pairs in a computer laboratory. No timepieces were accessible. Participants were asked to provide details of age, gender and course of study, and complete a PANAS scale. Next, participants in the positive and negative affect groups viewed PowerPoint presentations containing 20 positive or negative images respectively, followed by a second PANAS scale. All participants were informed they must complete an essay formatting task, and their accuracy would be assessed at the end of the session. Before completing the task they would be given three minutes to view both versions of the essay after which they would be required to make some judgements about their anticipated performance on the task. Participants were unaware that they would be required to estimate task duration specifically. After the viewing period, participants were asked to estimate how long they expected the task to take without returning to look at the task. They were advised they would be able to compare the formatted and unformatted essays as they undertook the task. Once estimates had been made, participants were instructed to begin formatting. Actual completion times were recorded. On completing the task, participants were asked to retrospectively estimate how long the task had taken. Participants in all conditions were then debriefed, with participants in the negative affect condition shown a PowerPoint presentation of 20 positive images before debriefing.

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RESULTS Dual-process account The aim of this experiment was to investigate the potential influence of different modes of cognitive processing on estimates of temporal duration. Discrepancy scores were used as the principal measure of misestimation. Directional discrepancy scores were calculated by subtracting actual from estimated task duration. A zero score indicates perfect accuracy, while positive and negative scores denote overestimation and underestimation of duration respectively. Absolute discrepancy scores were also computed to indicate degree of bias, regardless of direction of misestimation. Predicted and retrospective durations were underestimated in all groups. Data in all variables (directional and absolute prospective and retrospective discrepancy scores) were normally distributed with equality of variance among conditions. Descriptive statistics of mean directional prospective discrepancy scores, absolute prospective discrepancy scores, directional retrospective discrepancy scores and absolute retrospective discrepancy scores for each experimental condition are provided in Table 1. A univariate between-groups analysis of variance (ANOVA) was conducted on directional prospective discrepancy scores across groups to explore the possible impact of different modes of cognitive processing on prediction accuracy. No statistically significant main effect of processing mode was found, F (4, 95)=2.34, p=0.06, η²=0.09. A second univariate between-groups ANOVA was conducted on absolute prospective discrepancy scores, revealing a statistically significant main effect of processing mode, F(4,95)=2.95, p<0.05, η² 0.11. Post hoc comparisons using the Tukey’s HSD test indicated that the mean absolute prospective discrepancy score for the negative affect condition was significantly lower than the mean discrepancy score for the control condition.

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Table 1. Mean (SD) directional prospective discrepancy, absolute prospective discrepancy scores, directional retrospective discrepancy scores and absolute retrospective discrepancy scores in minutes per group Memory bias account The hypothesis that degree of misestimation in retrospective estimates scores would be associated with degree of misestimation in prospective estimates was investigated using Pearson product-moment correlation coefficient. This revealed a positive relationship with a medium effect size between the two variables (r=.39, n=100, p<0.01), with variation in absolute retrospective discrepancy scores explaining 15.21% of variance in absolute prospective discrepancy scores (r2=0.1521). A medium, positive relationship between estimated and actual completion times (r=.35, n=100, p<0.01) was also found, with higher estimates of task duration associated with higher actual duration (see Figure 1).

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Figure 1. Predicted duration, actual duration, absolute prospective discrepancy scores and absolute retrospective discrepancy scores per group

DISCUSSION Dual-process accounts Over the past two decades dual-process accounts have become a major contemporary topic in cognition. The current study investigated how this approach might be applied to the planning fallacy. Results suggest a possible influence of mode of cognitive processing on temporal estimates. General trends observed in the descriptive statistics offered tentative support for the hypothesis that participants using cold (System 2) processing would make more accurate estimates of task duration than those using hot (System 1) processing. Similarly, if excessive reliance on System 1 processing was responsible for the planning fallacy, it would be expected that participants in the control group would show most similarity with the hot group in terms of underestimation. This was indeed the case. Directional prospective discrepancy scores approached significance. It is possible that with a larger sample size, and subsequently, more statistical power, a statistically significant result could be achieved. 13

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Conversely, given the admittedly small effect size, one might question the practical significance of such a finding. Inferential statistics relating to absolute prospective discrepancy scores (i.e. bias regardless of direction of misestimation) did indicate statistically significant differences between groups. However, differences between hot and cold conditions were not significant. The lack of a significant difference between hot and cold groups may be due to failure of the study to induce the desired mode of cognitive processing to a high enough extent. Alternatively, this result could reflect the perhaps underestimated ability of System 1 processing to produce equally accurate estimates relative to System 2. Indeed, several studies have reported that â&#x20AC;&#x153;hotâ&#x20AC;? processes do not always lead to biased cognition, and in some cases holistic, intuitive processing has been shown to outperform analytical processing (e.g. Dijksterhuis, 2004, p555; as cited in Pretz, 2008). The role of affect Descriptive statistics concerning directional prospective discrepancy scores do not support the hypothesis that participants in the positive and negative affect group would underestimate task duration more than participants in the cold condition. Given the repeated emphasis in the literature that affect plays a central role in the experiential system (e.g. Slovic et al., 2005), one could infer that when making predictions, affective groups should experience increased reliance on beliefs, specific task features, and intuition, resulting in more biased predictions. Conversely, group means concerning directional prospective discrepancy move in an opposite pattern to what was expected. Positive and negative affect groups made the most accurate predictions, relative to all other conditions, although this pattern changes somewhat when one considers absolute discrepancy scores. What is especially interesting is the apparent similarity in accuracy between positive and negative affect conditions. Due to inconsistency in the literature, the current study made no specific prediction in this regard. The observed pattern is consistent with ideas put forward in recent literature that positive affect and negative affect are not necessarily polar opposites in terms of their influences on cognition (Cahir & Thomas, 2010; Caruso & Shariff, 2006). 14

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Although analyses of directional prospective discrepancy scores indicated differences between groups which were not statistically significant, subsequent analysis of absolute prospective discrepancy scores indicated that the negative affect condition generated significantly less biased estimates than the control condition. The observed trends imply that affect may not play the central role in the experiential system that the literature suggests, and may in fact have a more dominant role in analytical, logical processing. Neurological evidence, however, does not support this view (Lieberman, 2003). Alternatively, with reference to the dual-systems account, results may offer further support for the previously discussed viewpoint that analytic processes may not in fact be superior to experiential processes in judgement and reasoning. This outlook is supported by previous findings that affective state can increase the accuracy and efficiency of the decision process (Damasio, 1994). The observed disparity between directional discrepancy scores for hot and affect conditions highlights the benefit of taking an integrative approach. While experiential or hot processing initially appears error prone, further analysis suggests that some aspects of System 1 processing have the potential to generate relatively accurate reasoning. Only very tentative conclusions can be drawn from these trends. One interesting anomaly is the apparent disparity in accuracy of predictions between the control group (who reported highest positive affect and produced most biased estimates) and the positive affect group (who reported next highest positive affect, yet produced lowest directional discrepancy scores). It is unclear why the control group reported the highest positive affect. Socially desirable responding is one possible explanation (Paulhus & Reid, 1991). Additional research is clearly required to further investigate the role of affect in temporal misestimation. Memory Bias Account Results indicated a possible relationship between prospective and retrospective accuracy. It could be argued that the significant positive correlation found between retrospective discrepancy scores and prospective discrepancy scores may lend support for the memory bias account. This finding is consistent with the hypothesis that participants who displayed greatest misestimation when predicting duration, would 15

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subsequently display the greatest tendency to retrospectively misestimate duration. Although a causal relationship cannot be inferred from these findings, it is plausible to extrapolate that subjects who retrospectively underestimated duration of a task they had just completed, were also more likely to have underestimated duration of similar tasks in the past. As a consequence, when estimating duration of a future task, consideration given to prior experiences was likely to be biased. Further support for the memory bias account is offered by the medium positive correlation between predicted and actual duration. This is consistent with findings from previous research (Buehler et al. 1994), and suggests that although participants displayed a systematic underestimation of task duration, they appeared to have a good idea of how long the task would take, regardless of which mode of cognitive processing was induced. It could be argued that these findings lend support for the dualprocess account, since many dual-process theorists (e.g. Evans, 2006) argue that bias in judgements are due to a selective focus on prior beliefs (i.e. System 1 processing), as well as lack of System 2 intervention to inhibit mental short-cuts. However, they must be interpreted with caution, since discrepancy in retrospective estimates shared little variance with discrepancy in predictions of task duration, suggesting that other factors must be present. Future Research To further investigate the possibility that modes of cognitive processing may play a role in temporal misestimation, it would be advisable for future research to explore more explicit ways to induce desired modes of processing. For example, alternative methods of inducing hot processingsuch as time constrains when viewing the task (Evans & Curtis- Holmes, 2005) may produce more significant differences. It may also be worthwhile to investigate the role of individual differences in time prediction accuracy. Asking participants to provide retrospective verbal reports concerning the kind of information they used as a basis for their prediction have proved useful in other studies (Thomas & Handley, 2008) and could serve as a manipulation check.

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Conclusions In summary, this exploratory study has found tentative support for the hypothesis that dual-process accounts of reasoning, judgement and social cognition could offer a partial explanation for the planning fallacy. General trends imply that individuals utilising cold, System 2 processes generally make more accurate time estimates than those using hot, System 1 processes. On average, the most accurate predictions were made by the positive and negative affect conditions, with statistically significant differences evident between the negative affect and control conditions. This study also offers support for the memory bias account. There is considerable scope for continued research in this area. Given the cost of misestimating, and more importantly, the potential gains of accurately predicting task duration, it is essential to gain a more comprehensive understanding of the processes involved in the time estimation process. Furthermore, the apparent lack of empirical testing of many dual-process concepts indicates the need for exploratory research such as the current study to apply this intuitively logical theory to reallife phenomena.

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REFERENCES Buehler, R., Griffin, D., & Ross, M. (1994). Exploring the "Planning Fallacy": Why People Underestimate Their Task Completion Times. Journal of Personality and Social Psychology, 67(3), 366-381.

Decisions Focused on Mood. Journal of Behavioral Decision Making, 19(2), 155-169.

Buehler, R., Griffin, D., & Ross, M. (2002). Inside the planning fallacy: The causes and consequences of optimistic time predictions. In T. Gilovich, D. Griffin & D. Kahneman (Eds.), Heuristics and biases: The psychology of intuitive judgment. (pp. 250-270). New York, NY US: Cambridge University Press.

De Neys, W. (2006). Dual Processing in Reasoning: Two Systems but One Reasoner. Psychological Science, 17(5), 428433.

Byram, S. J. (1997). Cognitive and motivational factors influencing time prediction. Journal of Experimental Psychology: Applied, 3(3), 216239. Cahir, C., & Thomas, K. (2010). Assymetrical effects of positive and negative affect on decision making. Psychological Reports, 106(1), 1-12. Caruso, E. M., & Shafir, E. (2006). Now that I Think about It, I'm in the Mood for Laughs: 18

Damasio, A. R. (1994). Descartes' Error: Emotion, Reason and the Human Brain. New York: Avon.

Epstein, S. (1994). Integration of the cognitive and the psychodynamic unconscious. American Psychologist, 49(8), 709-724. Evans, J. S. B. T. (2003). In two minds: Dual-process accounts of reasoning. Trends in Cognitive Sciences, 7(10), 454-459. Evans, J. S. B. T. (2006). The heuristic-analytic theory of reasoning: Extension and evaluation. Psychonomic Bulletin & Review, 13(3), 378-395. Evans, J. S. B. T. (2008). Dualprocessing accounts of reasoning, judgment, and social cognition.

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Annual Review of Psychology, 59, 255-278. Evans, J. S. B. T., & CurtisHolmes, J. (2005). Rapid responding increases belief bias: Evidence for the dual-process theory of reasoning. Thinking & Reasoning, 11(4), 382-389. Evans, J. S. B. T., & Over, D. E. (1996). Rationality and reasoning. Oxford England: Psychology/Erlbaum (Uk) Taylor & Fr. Finucane, M. L., Alhakami, A., Slovic, P., & Johnson, S. M. (2000). The affect heuristic in judgments of risks and benefits. Journal of Behavioral Decision Making, 13(1), 1-17. Forgas, J. P. (1995). Mood and judgment: The affect infusion model (AIM). Psychological Bulletin, 117(1), 39-66. Francis-Smythe, J. A., & Robertson, I. T. (1999). On the relationship between time management and time estimation. British Journal of Psychology, 90(3), 333-347. Fredrickson, B. L. (2001). The role of positive emotions in positive psychology: The

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study of affect. In A. D. Ong & M. H. M. van Dulmen (Eds.), Oxford Handbook of Methods in Positive Psychology (pp. 250265). New York: Oxford University Press. New York: Oxford University Press. Kahneman, & Frederick, S. (2002). Representativeness revisited: Attribute substitution in intuitive judgment. In T. Gilovich, D. Griffin & D. Kahneman (Eds.), Heuristics and biases: The psychology of intuitive judgment. (pp. 49-81). New York, NY US: Cambridge University Press. Kahneman, & Tversky, A. (1982). Judgement under Uncertainty: Heuristics and Biases. Cambridge: University Press. Kahneman, D., & Tversky, A. (1979). Intuitive prediction: Biases and corrective Procedures. TIMS Studies in Management Science, 12, 313327. Kahneman, D., & Tversky, A. (1982). Judgement under Uncertainty: Heuristics and Biases. Cambridget: University Press.

Klaczynski, P. A. (2001). Framing effects on adolescent task representations, analytic and heuristic processing and decision making. Implications for the normative/descriptive gap. Journal of Applied Developmental Psychology, 22(3), 289-309. Kรถnig, C. J. (2005). Anchors Distort Estimates of Expected Duration. Psychological Reports, 96(2), 253-256. Kruger, J., & Evans, M. (2004). If you don't want to be late, enumerate: Unpacking reduces the planning fallacy. Journal of Experimental Social Psychology, 40(5), 586-598. Lang, P. J., Bradley, M. M., & Cuthbert, B. N. (2005). International affective picture system (IAPS): Affective ratings of pictures and instruction manual (Technical Report, No. A-6). University of Florida, Gainesville, FL. Leith, K. P., & Baumeister, R. F. (1996). Why do bad moods increase self-defeating behavior? Emotion, risk tasking, and selfregulation. Journal of

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AN ANALYSIS OF DISCOURSE USED BY GENERAL PATTON TO MOTIVATE THE SOLDIERS OF THE THIRD ARMY TO FIGHT FOR AMERICA IN THE SECOND WORLD WAR. Teresa Corbett Senior Sophister, Psychology corbett@tcd.ie

ABSTRACT The present analysis examines the discourse used by General George Patton in a motivational speech from World War II, given to “the Third Army" on June 5th, 1944, before the Allied invasion of France. The investigation explores the techniques used by the General to motivate his troops to fight for their country. The main themes identified were issues of home or America, masculinity, pride, teamwork, the future, advancement and superiority over the enemy. The techniques used by Patton echo those found in consequent psychological research on motivational methods used in the army. These include the discussion of congregationalism by Wainhouse (1956), Griffith and Perry‟s (1993) findings on sense of duty and obligation to the Army, and the importance of troop affiliation (Rogers, 2007). Limitations are identified within the current research, recognising the need to further investigate the characteristics of Patton.

INTRODUCTION General Patton (1885-1945) “Live for something rather than die for nothing.” This analysis examines one of the most famous speeches given during World War II; the speech given by General George Patton to “the Third Army" on June 5th, 1944, before the Allied invasion of France, an operation named "Overlord".

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Patton was born in California in 1885 to a family steeped in military history. He developed an interest in warfare from an early age, in particular, an interest in the U.S. Civil War. Patton was educated at West Point Military Academy and following his graduation he was involved in WW1. Following the 1941 attack on Pearl Harbour, Patton commanded the Western Task Force. As leader of the U.S. Seventh Army, he played a key role in the U.S. invasions of North Africa and Sicily in 1942. Patton was by all accounts a controversial character. His colourful personality earned him the nickname „Old Blood and Guts‟ and he was renowned for his quick-temper. He was a stubborn, out-spoken disciplinarian, but earned respect from his troops as a result of his willingness to get involved and his capacity for self-sacrifice (Montefiore, 2006). The speech to be analysed in this article was of tremendous importance and its sole purpose was to motivate the troops who had just arrived from America. Many of those present had never experienced real combat before and were about to be thrown into the thick of battle. The troops were about to embark on 281 days of combat in France, which eventually led them to Germany and to the end of the war (Montefiore, 2006). Patton, a respected general, had to remind them why they were there, who they were fighting for and to instill the courage needed for the challenges that lay ahead. Patton was renowned for improvising when speaking to the troops. He rarely, if ever, rehearsed or prepared his speeches, preferring instead to speak from the heart. He combined anecdotes with his beliefs and morals, avoiding the empty, generalised rhetoric of many other generals. He told them of the lessons he had learned during his career that would help them survive in battle. Patton spoke to his soldiers using a down-to-earth linguistic style that they would understand, never displaying a sense of superiority. To Patton, they were all part of the war together and for this, he earned the respect of those around him. (Province, 1982) The discourse to be examined in this report relates primarily to the question “How does a General motivate his troops to fight for their country?” The methods used by General Patton in his famous speech will be assessed. For Patton, and the other leaders, it was of paramount importance that the soldiers realised that they were fighting for something greater than themselves and that others relied on them. Other speeches 24

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from the era, including Eisenhower‟s rallying calls to the troops (see Appendix 4*), emphasise the duty of the soldiers to protect the free people of the world. However, those on the ground would have known that such rhetoric would have been of little use in motivating the troops. Generals such as Patton would have realised the importance of emphasising home, America, loved ones, and so on. Talk of the importance of American values and ideologies would have inspired the soldiers far more readily than appealing to universal principals. Any motivational speech would have had to engage in that sort of discourse in order to get the soldiers to respond as required. The rest of this paper will analyse the language used in this particular speech, with special reference to the motivational techniques used by the general. In motivating the troops to fight for their country, one would expect that Patton would mention and make reference to America. He should use a style of discourse emphasising duty, honour, superiority and bravery. These ideas of freedom and honour have been central to American values since the time of the War of Independence. He would be expected to make it clear that the troops are not fighting for an individual purpose, but for something that extends beyond them. Patton‟s language should highlight the rewards or consequences that may occur in victory or defeat, in order to motivate the soldiers to persist in times of uncertainty. A speech like this is tremendously important as it may have been the difference between life of death for many of the troops. A selfish, negative point of view could have been detrimental to the soldiers themselves and to those around them. Patton‟s speech had to inspire, motivate and command respect from the troops. The goal of discourse analysis is to approach a topic and engage in a process of selection, focusing, simplifying and abstracting the raw data. In a data set such as the one presented, categories of themes are extracted in order to develop a model and to establish the function in the discourse. In the realm of Social Psychology, an analysis of discourse relates to the function of the words used rather than the type or form of the words. Edwards and Potter (1992) highlight that the study of language should relate to naturally occuring speech. Therefore, emphasis will be placed on *

See www.tcd.ie/psychology/spj for appendices 25

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the context and social action of constructing and communicating an idea via language. Most improtantly however, it is always necessary to uncover the motives, intentions and goals of the speaker (Abrams & Hogg, 1990).

ANALYSIS Throughout the speech (Appendix 1) General Patton emphasises certain themes (Appendices 2 and 3). These include America, masculinity, pride, teamwork, the future, advancement and superiority over the enemy. Each of these themes relate to the General‟s attempts to motivate an army to fight for America. Patton wants to inspire these men to be true American heroes, like those of the past: “the champion marble player, the fastest runner, the toughest boxer, the big league ball players, and the All-American football players...” The speech is delivered from the point of view of an American General who is on the ground with his men. His language (use of profanities and personal pronouns such as “we” and “you”) indicates closeness with his troops. Were he speaking from an office or simply giving orders from afar, these aspects would not be present. As an American, his main focus is on his country. Other speeches from the era (for example, those given by Eisenhower- see Appendix 4) refer to a global motive for America‟s involvement in the war. Patton does not appear to care for any other nations at this moment and time; the focus is entirely on America. It is America‟s obligation to clean up the “mess” and it is the duty of “real American men” to fight for their country. Everything he says relates back to fighting for home and for country. They need to work as a team and be proud so that they can overcome the enemy and move forward into the future. The excerpts that follow highlight these themes. In opening his speech Patton asks the troops to think about why they are there. In the first paragraph alone, Patton mentions America 10 times. He also refers to “home” and “country.” It is clear that he wants them to realise that they are not there for themselves, but are part of a greater scheme of things. All of America is relying on them and as true Americans, they should serve their country. He also uses words such as “true” and “real” to emphasise this. It is not 26

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enough to be an American citizen or to have been born in America, a “true” American will fight for their country: “Americans love to fight, traditionally. All real Americans love the sting and clash of battle… Americans love a winner. Americans will not tolerate a loser. Americans despise cowards. Americans play to win all of the time. I wouldn't give a hoot in hell for a man who lost and laughed.” “That's why Americans have never lost nor will ever lose a war; for the very idea of losing is hateful to an American.” Patton also wants the troops to realise that they are relying on each other. If one man were to stop fighting, those around would suffer. This again relates to the idea of the „true American‟ discussed earlier. Patton wants to motivate the soldiers to be selfless and determined in battle. He repeats the words “every” and “all” throughout the speech indicating that each individual is important. He uses a metaphor of a great chain, each link is important and if they are not connected, the chain will fall apart. “Every single man in this Army plays a vital role. Don't ever let up. Don't ever think that your job is unimportant. Every man has a job to do and he must do it. Every man is a vital link in the great chain. The cowardly bastard could say, "Hell, they won't miss me, just one man in thousands". But, what if every man thought that way? Where in the hell would we be now? What would our country, our loved ones, our homes, even the world, be like? No, Goddamnit, Americans don't think like that. Every man does his job. Every man serves the whole. Every department, every unit, is important in the vast scheme of this war.” “An Army is a team. It lives, sleeps, eats, and fights as a team. This individual heroic stuff is pure horse shit!”

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“They were part of a team. Without team effort, without them, the fight would have been lost. All of the links in the chain pulled together and the chain became unbreakable.” Patton also emphasises masculinity. To him, a man is fearless, determined and will never quit. Again, he repeats words such as “true” and “real” to emphasise that masculinity is more than gender, it is how one acts on a battlefield. Patton refers to masculinity approximately 85 times in total throughout his speech, through the use and repetition of words such as „man‟, „he‟, „manhood‟ and so on. Not only is masculinity seen as something important in battle, but he also describes it as a key trait of a „real‟ American man. This serves to motivate the men to be true to their country and to those around them because anyone who fails to live up to this ideal is an outsider, a coward and a disgrace to their battalion and country. “Americans pride themselves on being He Men and they ARE He Men.” “The real hero is the man who fights even though he is scared…But a real man will never let his fear of death overpower his honor, his sense of duty to his country, and his innate manhood.” Another motivational technique evident in the discourse used by Patton relates to pride. He tries to convince the soldiers that Americans are the best and that they will win the war. He uses words such as “best” and “finest.” Although he never dismisses the strength of the opponents, Patton‟s positivity would have been inspiring to the troops. Believing they were among the best would motivate them to work harder and to help each other. “We have the finest food, the finest equipment, the best spirit, and the best men in the world.” The sense of superiority he instills would also foster a belief that they could, and would defeat the enemy. 28

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“We'll win this war, but we'll win it only by fighting and by showing the Germans that we've got more guts than they have; or ever will have...” “Why, by God, I actually pity those poor sons-of-bitches we're going up against. By God, I do.” His language often becomes racist when talking about the enemy. This would motivate the men to see the enemy as inhuman, lesser, unequal beings rather than as soldiers like themselves. Patton describes the war as a „mess‟ that requires cleaning up. He insults the Japanese, Hitler and the German army in order to motivate the troops. He also uses vulgar language and violent images to inspire his soldiers against the enemy. “The quicker we clean up this Goddamned mess, the quicker we can take a little jaunt against the purple pissing Japs and clean out their nest.” “And when we get to Berlin, I am personally going to shoot that paper hanging son-of-a-bitch Hitler. Just like I'd shoot a snake!” “We're not going to just shoot the sons-of-bitches, we're going to rip out their living Goddamned guts and use them to grease the treads of our tanks. We're going to murder those lousy Hun cocksuckers by the bushel-fucking-basket. War is a bloody, killing business. You've got to spill their blood, or they will spill yours. Rip them up the belly. Shoot them in the guts.” He sees the violence of war as necessary. If the soldiers do not do their job and be violent against the enemy, those they care about will suffer. He plays on the emotions the soldiers are feeling before going into battle. Not only are they fighting for their loved ones at home, they are fighting for the men and women they have become friends with throughout their training. As an experienced General, Patton realises that there is a bond within a battalion and uses this knowledge to encourage the troops. 29

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“When shells are hitting all around you and you wipe the dirt off your face and realize that instead of dirt it's the blood and guts of what once was your best friend beside you, you'll know what to do!” He uses words relating to moving forwards. It is only through battle that they can reach the higher plain of peace and glory. By repeating such ideas, Patton motivates the troops to persist and to continue moving forward. “We are advancing constantly… Our basic plan of operation is to advance and to keep on advancing regardless of whether we have to go over, under, or through the enemy.” “I believe in the old and sound rule that an ounce of sweat will save a gallon of blood. The harder WE push, the more Germans we will kill. The more Germans we kill, the fewer of our men will be killed. Pushing means fewer casualties.” Just as he began the speech with reference to America, Patton cleverly ends on a similar note. Instead of going back to the old ideals of America, however (as he did at the start), Patton looks to the future. He tells of how the soldiers will be respected when the battle is fought and won. He tries to make them believe that they will see home again and will live long into old age. His positive view of the outcomes allows the soldiers to look forward to going home to a country free from war. Instead of being disgraced for being cowards, these soldiers will be proud to say they fought in the war. “There is one great thing that you men will all be able to say after this war is over and you are home once again. You may be thankful that twenty years from now when you are sitting by the fireplace with your grandson on your knee and he asks you what you did in the great World War II, you WON'T have to cough, shift him to the other knee and say, "Well, your Granddaddy shoveled shit in Louisiana." No, Sir, you can look 30

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him straight in the eye and say, "Son, your Granddaddy rode with the Great Third Army and a Son-of-a-Goddamned-Bitch named Georgie Patton”

DISCUSSION Patton was a colourful character and this is reflected throughout his speech. Shortly before this speech was given, Patton had been reprimanded following what became known as „the slapping incident.‟ Patton had slapped a soldier in a hospital - for being what he termed a „coward.‟ It later emerged that the soldier had malaria and Patton apologised. However, Patton was then relegated to serving as little more than a decoy in the War, until he was given command of the Third Army in 1944. Calling the soldier a coward demonstrates Patton‟s belief in bravery and this is echoed in the speech. He did not believe that one should ever give in, and he tried to motivate the soldiers by repeating these ideals when speaking. Another aspect of Patton‟s character was his tendency to use profane language. While many found it offensive, Patton reportedly once said that such colourful language was necessary when he needed his men to remember something “to really make it stick, I give it to them double dirty… it helps my soldiers to remember. You can‟t run an army without profanity” (Patton, 1944 [2008]). This tactic is used throughout the speech and not only would it have helped to convey the message, but also Patton‟s use of such language would have helped the soldiers to relate to him. If he had used a cold, formal linguistic style, the soldiers may not have listened. Patton was a commander that believed in getting involved and fighting with his troops. This helped him earn the respect of his soldiers. One of the core elements identified in Patton‟s speech relate to the motivational techniques employed to get the troops to fight for their country. Wainhouse (1956) examined an army‟s use of congregationalism to prioritise the group over the individual (Patton also emphasises this in order to motivate his troops). Griffith and Perry (1993) found that new enlistees intend to fulfill their obligations to the Army. Although this study took place long after Patton‟s speech, attempts to invoke the importance of duty and of finishing the task are evident throughout the speech. Britt et al. (2004) found that the leader can play an important role 31

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in reducing stress among soldiers. They emphasised factors such as roleclarity and self-efficacy. As a leader, Patton‟s speech clearly defines the role each soldier must play in the Army and promotes a sense of positive self-worth and ability. Affiliation was found by Rogers (2007) to be an important factor of leadership. Patton identifies with the troops and uses terms such as “we” and “us” to demonstrate this. He also tells them of the role he will play in this fight. Although Patton may not have even realised that the message he gave was full of motivational techniques, he knew that he had to inspire his troops. On December 9, 1945, in Germany, Patton was in a road accident and later died as a result of his injuries (Potter, 2010). In keeping with his wishes and his oath of loyalty to his men, Patton is buried among his troops of the Third Army in Luxembourg (American Battle Monuments Commission, 2010). Although he died soon after the war ended, Patton‟s words continue to leave a mark on the historical landscape. The speech captures both a moment and the emotions of an era, along with sentiments and aspirations of the troops.

CONCLUSION Due to limitations in the scope of current research, this article serves merely as a starting point for the investigation into the discourse used by General Patton to motivate the soldiers. A more nuanced analysis should focus on Patton‟s upbringing, religious beliefs, previous roles, family status and so on, in order to gain a more complete insight into how and why he came to give this speech in the manner which he did. As with all accounts of history, it must be noted that the story is all too often marred with the apparent benefits of hindsight. Were it not for the Allied victory- if indeed, there is a such thing as „victory‟ in warPatton‟s words could have been labelled the empty bravado of a fallen leadar, attempting to inspire blind-faith and hope in his troops. The world had changed after the war and the America the troops returned to could never have been the same old America that the General referred to. However, Patton‟s speech is more than hollow rhetoric. It is a product of his beliefs and the time in which he lived. Furthermore, it is essential to note that „truth‟ is merely a result of who controls the discourse (Selden, 1985) 32

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REFERENCES Abrams, D.A., & Hogg, M.A.M (1990). The context of discourse: Let‟s not throw out the baby with the bathwater. Philosophical Psycholology, 3, 219-225.

http://www.abmc.gov/cemeteries /cemeteries /lx.php

Britt, T.W., Davison, J., Bliese, P.D., and Castro, C.A. (2004). How Leaders Can Influence the Impact That Stressors Have on Soldiers, Military Medicine, 169(7), pp. 541-545

Patton, G. S. (1944/2008). Patton’s speech to the Third Army – June 5th, 1944. Retrieved October 30, 2010 from http://greatspeeches.wordpress.c om/2008/09/30/pattons-speechto-the-third-army-june-5th1944/

Edwards, D. & Potter, J. (1992). Discursive Psychology. London: Sage. Forrester, M. A. (1997). Psychology of Language: A Critical Introduction. London: Sage. Griffith, J. & Perry, S. (1993). Wanting to Soldier: Enlistment motivations of Army Reserve Recruits Befroe and After Operation Desert Storm, Military Psychology, 5(2), pp.127-139. Luxembourg American cemetery and memorial (2010). Retrieved October 30, 2010 from

Montefiore, S. S. (2006). Speeches That Changed The World. China: Quercus Publishing.

Potter, J. (2010). Biography of general George S. Patton, Jr. Retrieved October 30, 2010 from http://www.generalpatton.com /biography.html Province, C.M. (1982). The Unknown Patton. University of Michigan, US: Hippocrene Books. Selden, R. (1985). A Reader’s Guide to Contemporary Literary Theory. Hemel Hempstead: Harvester Press. Wainhouse, Motivating

E.R.

(1956). „Ivan:‟ 33

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Indoctrination in the Soviet Army, Military Review, 35(12), pp.48-54.

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MOOD DEPENDENT MEMORY FOR SELF-GENERATED WORDS USING A MUSICAL MOOD INDUCTION PROCEDURE Melissa Daly Graduate 2010, Psychology dalyme@tcd.ie

ABSTRACT The present study investigated Mood Dependent Memory for selfgenerated words using a Musical mood induction procedure. 75 participants (25 males, 50 females) took part in this study. Testing took place over two sessions, two days apart. During the first session participants were induced into a positive or negative mood before generating a list of 16 words in a word-association task. Two days later participants were induced into either a congruent or incongruent mood and were given five minutes to freely recall the words. It was predicted that in the presence of strong, stable moods, participants whose moods at both sessions (encoding and retrieval) were congruent would remember more words than participants whose moods were incongruent. Subsequent analyses of data did not support the MDM hypothesis. However, stronger mood at encoding predicted a higher rate of recall, and greater discrepancy between encoding and retrieval moods predicted a lower rate of recall, providing moderate support for the associative network theory. It is inferred that in accordance with the associative network theory, strong, stable moods produce a greater mood dependent effect. In addition, as mood declined significantly after the free recall task it is suggested that future research should focus on alternative recall tasks to improve mood stability.

INTRODUCTION “Mood dependent memory refers to the phenomenon of a person‟s emotional state serving as part of the context that becomes associated with ongoing events, so that memory for those events is best obtained when that emotional context is reinstated” (Bower & Forgas, 2000, p.93). 35

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In other words, if an individual learns information in a particular mood they should remember this information better at a later date if they are in the same or a similar mood. One of the most dominant theories in mood and memory research is the associative network theory (Bower, 1981) which was proposed to explain the relationship between mood and memory and, more specifically, MDM. According to the associative network theory, there are six basic emotion nodes in memory where moods are represented. When an emotional event occurs, these nodes are activated above a threshold and activation spreads throughout the network including the associated memory structures to which it is linked. Therefore, when an event is encoded while the emotion nodes are activated, the event and the individualâ&#x20AC;&#x;s mood become associated in memory. At a later date, activation of the same emotion node spreads activation to the event node enabling the event to be more easily recollected (Bower, 1981). Thus, associative network theory assumes that people will have a heightened ability to remember information that they have learned in a particular mood when this mood is later reinstated. Despite an abundance of cognitive theories, with the addition of early promising experimental (e.g. Bower et al., 1978) and clinical research (e.g. Weingartner, Miller, & Murphy, 1977) to support the reality of a mood dependent effect on memory, the literature to date fails to present a clear, consistent picture of whether MDM actually exists (Eich & Macaulay, 2000). In light of this it could be argued that researchers should accept that MDM is a non-existent phenomenon and to discontinue in their pursuit of its demonstration. On the contrary however, it is of vital importance that the problem of MDM is rectified as it would have implications for clinical psychology as MDM has been argued to play a causal role in memory disturbances associated with clinical disorders such as traumatic amnesia (Schacter & Kihlstrom, 1989), dissociative experiences (Kanayama, Sato, & Ohira, 2008), borderline personality disorders (Cauwels, 1992), multiple personality disorders (Bower, 1994) and bipolar depression (Szostak, Lister, Eckardt & Weingartner, 1994). Taking into account the huge implications that reaching a consensus on MDM would have for psychology, rather than concentrating on simply demonstrating mood state dependency, a number of researchers have focused on establishing the conditions under which a mood dependent 36

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effect is most likely to occur (e.g. Eich, 1995). Three of these conditions: (a) the nature of the mood induced, (b) the nature of the words to-beremembered, and (c) the nature of the recall task are considered below. It has been argued that in order for a mood dependent effect to be demonstrated the moods induced must be strong and stable (Eich, 1995). Bower (1981) maintained that strong moods are a necessary precondition for MDM. He argued that strong moods result in stronger associations with the target information so that when mood at retrieval matches mood at encoding mood serves as a more potent cue to recall the target information (Bower, 1981, 1992). One of the problems outlined by Kenealy (1997) with regards to experimentally demonstrating MDM is that many researchers did not include a mood manipulation check in their studies with the result that there was no way to establish whether the mood dependent effect was not demonstrated due to its nonexistence or due to an inadequate mood induction procedure (Kenealy, 1997). In the current study, the Positive and Negative Affect Schedule (PANAS; Watson, Clark, & Tellegen, 1988) was used to measure mood before and after mood induction to ensure that the desired mood was successfully induced. With regards to stability of moods, de lâ&#x20AC;&#x;Etoile (2002) argued that if the mood change fades easily the individual does not have sufficient time to form a meaningful connection between the learned material and their mood state and a mood dependent effect is therefore less likely to occur. In a pilot study, Eich and Metcalfe (1989) found that unstable moods did not produce a mood dependent effect. Therefore, it could be argued that many studies which failed to find a mood dependent effect may have induced moods which were strong in the beginning but faded quickly. In light of this research, it could be inferred that if mood dependent memory is to be demonstrated the moods induced must be strong and must last for the duration of encoding and retrieval tasks. Unlike previous studies, as well as measuring mood before and after mood induction, the present study measured mood at the end of encoding and retrieval sessions using the PANAS to investigate whether mood remained stable. The nature of the to-be-remembered target items has been argued to contribute greatly to whether MDM will be demonstrated (Eich, 1995). For instance, Eich and Metcalfe (1989) suggested that internal items (i.e. those generated by the participants themselves through the mental 37

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processes of thought, reasoning and imagination), may be more likely to be associated with the participant‟s mood in memory than would external items (i.e. where the participant is simply presented with a list of unrelated words to remember). The present study made use of a word association task adapted from one used by Eich and Metcalfe (1989) so that the to-be-remembered target items were internally generated and therefore assumed to be more closely associated with mood in memory. Eich (1995) posited that a mood dependent effect is more likely to arise in a free recall task, which is characterised by the absence of external retrieval cues. This is in accordance with the associative network theory (Bower, 1981), which argues that in the absence of external retrieval cues, the participants‟ mood acts as an internal retrieval cue, activating the memory network where the information is encoded thus enabling the individual to remember the material once mood at encoding and retrieval match (Bower, 1981). In support of this Eich and Metcalfe (1989) demonstrated that although differences in mood at learning and recall impaired the free recall of generated items, differences in mood did not impair the recognition of either generated or read items. In other words, MDM was observed in a free recall task but not in a recognition task. Although some research has found that recognition tasks support a mood dependent effect (e.g. Beck & McBee, 1995) there is little consistent evidence of this nature. Taking this research into consideration, a free recall task was used in the present study to measure participants‟ memory for self-generated words. Kenealy (1997) maintained that a large proportion of MDM studies failed to measure levels of initial or baseline learning without mood induction with the result that it was impossible to detach the influence of mood on learning from the influence of mood on recall. De l‟Etoile (2002) investigated the effect of mood on learning and found that participants who took part in musical mood induction prior to encoding and recall remembered more words than participants who did not take part in any mood induction. The present study also took this factor into consideration by using a control group where memory for self-generated words was measured in the absence of a mood induction procedure. In this way a base-line measure of learning could be obtained so as the potential effects of music or mood on learning and recall could be examined.

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A musical mood induction procedure was used in the present study. Musical Mood induction has been found to be effective in inducing positive and negative mood states in MDM studies (e.g. de l‟Etoile, 2002; Kenealy, 1997). In addition, it has been argued to have a high success rate, with 100 percent of participants displaying the critical degree of mood change after mood induction (Clark, 1983). Compared with other mood induction procedures, the musical mood induction was found to be less prone to demand effects (Kenealy, 1997). Demand effects (i.e. where participants make an effort to respond according to how they believe the experimenter expects/wishes them to respond) were a key flaw in many previous studies demonstrating MDM so this was an important factor to take into consideration when choosing a mood induction procedure. In the present study, the conditions outlined by previous research (i.e. (a) mood strength and stability, (b) self-generated target words and (c) free recall)were taken into account and used as the three main criteria under which MDM should be demonstrated. It was hypothesised that under these conditions participants whose mood at encoding and retrieval matched would remember more words than participants whose mood at encoding and retrieval did not match. Firstly, it was predicted that the positive and negative congruent mood groups would remember more words than the positive and negative incongruent groups and that, in accordance with de l‟Etoile‟s (2002) findings, all groups would remember more words than the control group. Secondly, it was predicted that the more effective the mood induction procedure was in producing strong, stable moods, the greater the mood dependent effect would be. Finally, it was predicted that in keeping with the MDM hypothesis, the greater the difference between mood at encoding and mood at retrieval the less words that would be remembered.

METHOD Design A 2(Mood at encoding: Positive, Negative) x 2(Mood at retrieval: Positive, Negative) between subjects design was used. In addition, an independent control group was used that did not receive a mood manipulation. Participants were randomly assigned to one of the four mood groups or to

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the control group. Participants‟ memory for self-generated words was measured. Participants 75 undergraduate psychology students and members of the public participated in this study, of which 50 (67%) were female and 25 (33%) were male. Participants were between 18 and 45 years of age (mean age=24.7). 53 (71%) were students and 22 (29%) were non-students. Materials The Positive and Negative Affect Schedule (PANAS; Watson, Clark, & Tellegen, 1988) was used to measure mood. Eight pieces of music rated positive and negative in a pilot study (see procedure) were used for the Musical mood induction procedure (see Appendix D)*. Four of the pieces chosen were classical (two positive, two negative), and the other four pieces (two positive, two negative) were labelled as „alternative‟ which included post-rock and soundtrack music. Participants listened to the 2 minute piece of music using „Windows Media Player‟ on a PC through AKG headphones in a quiet, well-lit testing room in the Psychology department of Trinity College Dublin. A word association task was adapted from a task used by Eich & Metcalfe (1989) in order for participants to learn and remember internally generated words (see Appendix E). A stop-watch was used to ensure that each participant was allocated exactly five minutes to complete the free recall task in the second testing session. Procedure A pilot study was carried out a number of weeks before the study commenced in order to choose a set of songs for the musical mood induction procedure. Six participants listened to a total of 16 pieces of classical and alternative music and rated them on a Likert scale where “1”=extremely negative and “10”=extremely positive in terms of affect (see Appendix F). Eight of the most positively and most negatively rated songs were chosen for the Musical mood induction procedure. *

See www.tcd.ie/psychology/spj for appendices

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In the present study, participants were randomly assigned to one of five mood groups which included an independent control group without mood induction. Of the four groups where mood was manipulated participants were either assigned to a positive or negative mood induction at encoding followed by either a congruent or incongruent mood at retrieval. Testing Session 1: Encoding Participants were first presented with instructions for completing the PANAS. Participants were then randomly assigned to a piece of positive or negative, classical or alternative music (see Appendix D). Participants were not informed as to whether the piece of music was positive or negative or that it was intended to induce mood, so as to minimise demand effects. Participants were first given a few seconds to adjust the volume of the music to their preferred listening level. Music was terminated at the two minute point in the piece. After listening to the music, participants were instructed to fill out the PANAS so that the difference in mood before and after mood induction could be calculated. Participants were then given instructions for completing the word association task. Next they were presented with a list of sixteen similar word associations (see Appendix E). Participants were not informed that they would later have to remember the words they generated. Although there was a high likelihood of participants generating the same words, any unexpected words were recorded by the experimenter for use as correct responses in the subsequent recall task. After the word association task participants were instructed to complete the PANAS once more. Testing Session 2: Retrieval After a two day retention interval participants returned and the same procedure was carried out again. Participants initially recorded their baseline mood on the PANAS. They were then induced into a positive or negative mood (either congruent or incongruent with their mood in the first session) via the musical mood induction procedure. They listened to the same genre of music (i.e. classical or alternative) at each session. Participants completed a mood manipulation check in the form of the PANAS. Following this participants were given five minutes timed on a stop-watch to recall the words they had generated in the word-association 41

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task in the first testing session. Participants then filled out the PANAS again. They were fully debriefed about the nature of the study and what it aimed to measure in the form of a debriefing sheet (see Appendix J). Control Group Participants in the control group did not take part in the musical mood induction procedure. Similar to participants in the experimental groups they generated 16 words in the word association task at encoding and recalled them in a free recall task at retrieval. Participants also filled out the PANAS before and after testing on each session in order to ensure that mood remained stable in the absence of mood induction.

RESULTS Mood dependent Memory As can be seen in Table 1 below, the mean for words recalled was higher in the Negative-Negative group (M=4.5, SD=2.9) than in the NegativePositive group (M=4.1, SD=2.1), and was lowest in the control group (M=3.6, SD=1.8). The mean for words recalled in the Positive-Positive group (M=3.8, SD=2.4) was lower than in the Positive-Negative group (M=4.3, SD=1.3)†. A one way between subjects ANOVA was carried out to compare the effect of mood on memory for 16 words across the four matched and mismatched positive and negative mood groups and the control condition without mood induction. The assumption of homogeneity of variance was violated so the Welch F-ratio is reported. There was not a significant effect of mood on memory at the p<.05 level for each of the five conditions; F (4, 34)=.468, p>.05. To investigate whether there was an interaction between positive or negative mood at encoding and positive or negative mood at retrieval for words remembered, a 2x2 between subjects factorial ANOVA was carried out. Important to note is that the assumption of homogeneity of variance was violated‡. The main effect of mood at encoding was not statistically All data was found to be normally distributed. However, Howell (2007) argued that ANOVA is a robust statistical procedure and can handle minor violations of parametric assumptions without any major effects. † ‡

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significant; F (3, 56)=.16, p>.05, η²=.003, the main effect of mood at retrieval was also not significant; F (3, 56)=.55, p>.05, η²=.010, and there was no significant interaction between the two variables; F (3, 56)=.03, p>.05, η²=.001. Group 1: Mood

Mean Words Recalled

Positive-Positive

3.8 (SD=2.4) (n=15)

Positive-Negative

4.3 (SD=1.3) (n=15)

Negative-Negative

4.5 (SD=2.9) (n=15)

Negative-Positive Control

4.1(SD=2.1) (n=15) 3.6 (SD=1.8) (n=15)

Table 1: Mean words remembered in the four mood groups and the control group. Effectiveness of Musical Mood Induction The summed scores for positive and negative affect on the PANAS were subtracted to get a single mood score for each time the PANAS was administered. As illustrated in Figure 1 below, mood after mood induction increased in the positive groups and decreased in the negative groups. Mood decreased after cognitive tasks at both encoding and retrieval with a notable drop in mood especially after free recall. A mixed factorial ANOVA was carried out on the mean mood scores before mood induction, after mood induction and after cognitive tasks at encoding and retrieval sessions for each of the four congruent and incongruent mood groups. There was a significant main effect of mood §; F (3, 181)=9.82, p<.01, η²=.15, but the main effect of group was not significant; F (3, 56)=.49, p>.05, η²=.02. There was no significant interaction between the two variables; F (10, 181)=1.16, p> .05, η²=.07. Pairwise comparisons with Bonferroni adjustments indicated that the mean score for mood after free recall (M=12.55, SD=11.25) was significantly lower at the p <.05 level than mood before mood induction at encoding (M=17.42, SD=7.29), mood after mood induction at encoding The assumption of sphericity was violated so the Greenhouse-Geisser correction is reported. §

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(M=19.02, SD=8.08), mood after word generation (M=16.83, SD=9.66) and mood after mood induction at retrieval (M=17.68, SD=9.66). Mood after free recall was also lower than mood before mood induction at retrieval (M=15.90, SD=8.19) and this difference approached statistical significance (p=.05). All other comparisons were not statistically significant.

Fig. 1: Mean mood scores on PANAS for participants within each mood group. Mood ratings in the control group were considered separately. A repeated measures ANOVA was conducted to compare the differences in mean mood ratings on the PANAS before and after cognitive tasks at encoding and retrieval sessions. A significant main effect of mood was found; F (2, 25)=3.95, p<.05. Pairwise comparisons with Bonferroni adjustments indicated that mood after word generation (M=12.27, SD=6.68) was greater than mood after free recall (M=8.87, SD=7.37). This difference approached statistical significance (p=.07). All other comparisons did not approach statistical significance.

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Mood Strength Scores for mood on the PANAS before and after mood induction at encoding and retrieval were subtracted to get a difference score for mood at each session. Correlations were carried out for the difference in mood at each session and words remembered. It was predicted that words remembered would be positively correlated with mood change at encoding and retrieval. At encoding, a significant positive correlation for words remembered and mood change was observed; r=+.294, n=60, p<.05, one tailed. At retrieval, a positive correlation for words remembered and mood change did not prove to be statistically significant; r=+.002, n=60, p>.05, one tailed. Difference between encoding and retrieval moods Mood after mood induction at encoding and mood after mood induction at retrieval was subtracted to get a difference score for each participant. It was predicted that in keeping with the MDM hypothesis, fewer words would be remembered as the difference between encoding and retrieval moods increased. A significant negative correlation between words remembered and the overall mean difference between mood after mood induction at encoding and mood after mood induction at retrieval was observed; r=-.218, n=60, p<.05, one tailed. Reassignment to groups according to PANAS scores Participants were assigned to new mood groups according to their actual mood scores on each of the six measures of the PANAS. Participants were placed in positive, negative or fail groups according to whether their mood increased, decreased or stayed the same from before to after mood induction. As shown in Table 2, the mean words remembered were highest in the Negative-Negative group (M=5.57, SD=2.51) and the NegativePositive group (M=4.36, SD=2.25) and were lowest in the Control group (M=3.60, SD=1.88). The Fail group (M=3.86, SD=2.86) remembered fewer words than the other four mood groups but more words than the control group. In contrast with the initial analysis, the mean words remembered in the Positive-Positive group (M=3.96, SD=1.9) was greater than in the 45

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Positive-Negative group (M=3.86, SD=1.95). A one way between subjects ANOVA was carried out to compare the mean words remembered by participants according to their actual mood scores in newly assigned groups. None of the differences between groups reached statistical significance; F (5, 69)=.919, p>.05. Group 2: Mood

Mean Words Remembered

Positive-Positive

3.96 (SD=1.90, n=25)

Positive-Negative

3.86 (SD=1.95, n=7)

Negative-Negative

5.57 (SD=2.51, n=7)

Negative-Positive

4.36 (SD=2.25, n=11)

Fail

3.86 (SD=2.86, n=10)

Control

3.60 (SD=1.88, n=15)

Table 2: Mean words remembered in the four reported mood groups, the fail group and the control group. To investigate whether there was an interaction between mood at encoding and mood at retrieval for words remembered a 2x2 between subjects factorial ANOVA was carried out. The analysis revealed that the main effect of mood at encoding was not statistically significant; F (1, 46)=2.5, p>.05, η²=.05 and the main effect of mood at retrieval was also not statistically significant; F (1, 46)=.68, p>.05, η²=.015. In addition, the interaction between the two variables was not statistically significant; F (1, 46)=.96, p>.05, η²=.02.

DISCUSSION The primary purpose of the present study was to demonstrate mood statedependent memory (MDM). It was predicted that participants would remember more words when moods at encoding and retrieval were congruent than when they were incongruent. The present findings do not support the MDM hypothesis. Results indicate that mood at encoding and retrieval had no effect on memory for self-generated words and no 46

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significant differences were found between the average words recalled in each group. Furthermore, although recall was found to be higher in the Negative-Negative group than in the Negative-Positive group and lowest in the Control group, contrary to what was predicted, recall in the Positive-Positive group was lower than in the Positive-Negative group. When participants were assigned to groups according to their reported mood scores, mood was still found to have no effect on memory. In contrast to the initial analysis however, the trend for recall complied with the original prediction and participants in the Positive-Positive group remembered more words than participants in the Positive-Negative group. Although the possibility of this trend occurring purely by chance cannot be ruled out, its consistency with the MDM hypothesis is worth noting and deserves further speculation. While the initial findings appear to rule out the existence of a mood dependent effect on memory, in agreement with the prediction that stronger moods would show a greater mood dependent effect, a significant positive correlation was found between words remembered and the difference in mood before and after mood induction at encoding. Therefore, as the difference in mood increased, the number of words remembered increased also. This result supports Bower (1981)â&#x20AC;&#x;s claim that in the context of the associative network theory, stronger moods allow more meaningful associations to be formed between the mood and the target material. As no significant correlation was found between words remembered and the difference in mood before and after mood induction at retrieval it could be inferred that mood strength is only an important precondition for mood dependent memory at encoding when the initial associations are formed between mood and the to-be-remembered material. This is interesting and deserves further investigation as it shows that there may be differential effects between mood at learning and mood at recall. It was also predicted in line with the mood dependent memory hypothesis that the greater the discrepancy between mood at encoding and mood at retrieval the fewer words that would be remembered. In support of this prediction, a significant negative correlation was found between words remembered and the difference in mood after mood induction at encoding and retrieval. That is, as the difference in moods between encoding and retrieval sessions increased the number of words 47

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remembered decreased. This result provides tentative support for the MDM hypothesis but due to its correlational nature no indication of why this effect occurs is specified and so further research is called for. Collectively these findings indicate that if stronger moods were induced and if the differences between mood induced by positive and negative music had been greater perhaps a mood dependent effect would have been observed. It could, therefore, be argued that the mood induction procedure may not have been capable of producing an adequate level mood change in participants for a mood dependent effect to be demonstrated. Findings indicate that although mean mood scores showed an increase or decrease after mood induction as expected depending on whether positive or negative music was played, results were not statistically significant. This shows that the moods induced were not strong overall which according to previous research (e.g. Bower, 1981; Eich 1995) is a necessary precondition for a mood dependent effect to occur. Moreover, in contrast with Clark and Teasdale (1983)‟s findings that the musical mood induction procedure was effective in inducing mood with 100 percent of participants, in the present study 10 participants failed to produce any mood change whatsoever from before to after mood induction at encoding and retrieval. Therefore, it cannot be inferred with absolute certainty from the present study that the mood dependent effect is unreliable as the conditions outlined by previous research were not satisfied. In further support of this argument, significant differences were found between mood after free recall and mood at each of the other five instances when mood was measured. This shows that not only did mood fail to remain stable after mood induction but it actually decreased from the baseline measure of mood at the start of the experiment. Although this decline in mood may be partly due to the mood induction‟s failure to produce a strong and stable mood change, this does not explain why mood after recall differed significantly from baseline mood. Taking this factor into account, it could be argued that the sharp decline in mood after free recall was due to the nature of the memory test. For instance, the deceptive and unexpected nature of the memory test may have disrupted participants‟ mood and caused stress when the words did not immediately spring to mind. 48

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In the control group, decreases in mood approaching significance were also observed between mood after word generation and mood after free recall. This provides additional evidence that the free recall task may have caused a decline in mood which eliminated the mood dependent effect. According to previous research by Eich and Metcalfe (1989), stable moods were required for MDM to be demonstrated. Taking these results and the results of the present study into consideration it may be useful to investigate MDM using less demanding implicit recall tasks such as wordstem completion or fragment completion tasks (Graf & Mandler, 1984; Jacoby, Toth & Yonelinas, 1993). As a whole, the results of the present study do not support the MDM hypothesis and appear to be in accordance with the null findings which are highly characteristic of previous MDM research (e.g. Bower & Mayer, 1989; Mueller et al, 1991). This reflects negatively on the associative network theory (Bower, 1981) which maintains that memory for information learned in a particular mood should be greater when this mood is reinstated. In addition, contrary to Eichâ&#x20AC;&#x;s (1995) claim that MDM occurs when words are internally generated by participants and retrieved using free recall, no mood dependent effects were found in the present study using these same conditions. However, a few interesting findings were uncovered, leading to the conclusion that had strong, stable moods been induced with a sufficient difference between positive and negative moods, a mood dependent effect could have been demonstrated. Furthermore, the finding that participantsâ&#x20AC;&#x; mood declined significantly after the recall task is particularly interesting as it could indicate that failures to demonstrate MDM in previous research were due to the nature of the recall task used. Instead of being a necessary precondition for MDM as maintained by Eich (1995), the free recall task appears to have decreased the likelihood of MDM occurring. Although the present study did not demonstrate MDM, the results provide preliminary evidence that a mood dependent effect exists and that strong stable moods are a key factor in demonstrating it. Therefore, the present findings contribute to both cognitive and clinical research in clarifying some of the assumptions of the associative network theory (Bower, 1981), outlining that the nature of the mood induced may have been a key flaw in previous studies, and demonstrating that mood strength may be more important at encoding than at retrieval. Moreover, 49

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these findings provide a new path for future MDM research in striving to maintain the stability of moods. It is suggested that in light of these findings future research should focus in particular on achieving mood strength and stability in MDM investigations and make use of alternative methods of recall as discussed above.

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Bower, G. H., & Mayer, J. D. (1989). In search of mooddependent retrieval. Journal of Social Behaviour and Personality, 4, 133-168. Bower, G. H., Monteiro, K. P., & Gilligan, S. G. (1978). Emotional mood as a context for learning and recall. Journal of Verbal Learning and Verbal Behaviour, 17, 573-585. Clark, D. M. (1983). On the induction of depressed mood in the laboratory: Evaluation and comparison of the Velton and musical procedures. Advances in Behaviour Research and Therapy, 5, 27-49. Cauwels, J. C. (1992). Imbroglio: Rising to the Challenge of Borderline Personality Disorder. New York: Norton. De lâ&#x20AC;&#x;Etoile, S. K. (2002). The effect of a musical mood induction procedure on mood state-dependent word retrieval. The Journal of Music Therapy, 39, 145-160. Eich, E., & Metcalfe, J. (1989). Mood dependent memory for internal versus external events. 51

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memory reconsidered. The Quarterly Journal of Experimental Psychology, 50, 290-317. Kihlstrom, J.F. (1989). On what does mood-dependent memory depend? Journal of Social Behavior and Personality, 4, 2332. Leventhal, H., & Tomarken, A. J. (1986). Emotion: Today's problems. Annual Review of Psychology, 32, 565-610. Mecklenbrauker, S., & Hager, W. (1984). Effects of mood on memory: Experimental tests of a mood state dependent retrieval hypothesis and a moodcongruity hypothesis. Psychological Research, 46, 335376. Morris, C. D., Bransford, J. D., & Franks, J. J. (1977). Levels of processing versus transfer appropriate processing. Journal of Verbal Learning and Verbal Behaviour, 16, 519-533. Mueller, J. H., Grove, T. R., & Thompson, W. B. (1991). Mooddependent retrieval and mood awareness. Cognition and Emotion, 5, 331-349.

Schacter, D. L., & Kihlstrom, J. F. (1989). Functional amnesia. In F. Boller & J. Grafman, (Eds.), Handbook of Neuropsychology (pp. 209-231). Amsterdam: Elsevier Publications. Szostak, C, Lister, R., Eckardt, M., & Weingartner, H. (1994). Dissociative effects of mood on memory. In R. M. Klein & B. K. Doane (Eds.), Psychological Concepts and Dissociative Disorders (pp. 187-206). Hillsdale, NJ: Erlbaum. Tulving, E. (1983). Elements of Episodic Memory. Oxford: Oxford University Press. 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. Weingartner, H., Miller, H. & Murphy, D. L. (1977). Moodstate-dependent retrieval of verbal associations. Journal of Abnormal Psychology, 86, 276284.

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Westermann, R., Spies, K, Stahl, G., & Hesse, F. W. (1996). Relative effectiveness and validity of mood induction procedures: a meta-analysis. European Journal of Social Psychology, 26, 557-580.

Williams, J. M. G., & Markar, H. R. (1991). Money hidden and rediscovered in subsequent manic phases: A case of action dependent on mood state? British Journal of Psychiatry, 159, 579-581.

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AN INVESTIGATION OF THE EFFECTS OF NEUROTICISM AND EXTRAVERSION ON MUSICALLY-INDUCED EMOTIONS Jean Herlihy Graduate 2010, Psychology jherlihy@tcd.ie

ABSTRACT The Geneva Emotional Music Scale (GEMS) is one of the first domainspecific models of musically-induced emotion. In order for it to be established as a valid research tool, the causes of inter-listener variance on the scale must be identified. The effects of Extraversion and Neuroticism levels on listener responses to the GEMS were examined within an undergraduate sample. Participants were randomly assigned to one of two groups, with 41 participants in the experimental condition presented with musical excerpts of varying genres, while 40 control participants listened to excerpts of elevator music. Extraversion was found to be significantly, positively correlated with emotional response to music in the experimental condition. In contrast with previous research, a weak, negative correlation was observed between Neuroticism and musically-induced emotions in both groups. Additional individual characteristics such as gender and mood also influenced responses on the GEMS. Overall, the emotional responses to control and experimental stimuli were comparable. Further research is required to account for the effects of the experimental setting on the relationship between personality and musically induced emotions.

INTRODUCTION Music has long been an important social phenomenon and, with recent developments in technologies and software, its prevalence within society is likely to increase. Listening to music is considered one of the most important leisure activities within everyday life (Rentfrow & Gosling, 2003), with research suggesting that, on average, people listen to music several times a day (Juslin & Laukka, 2004; Juslin et al., 2008). 55

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One of the most commonly cited explanations for the prominence of music is its perceived effect on emotion. Juslin and Laukka (2004) found that the majority of participants listen to music in order to regulate, enhance or otherwise change the qualities and level of their experienced emotion. The perception of music as an effective means of emotion induction is empirically supported in the music psychology literature. Brain regions previously implicated in reward, emotion and arousal have been activated in response to music (Brown, Martinez & Parsons, 2004; Mitterschiffthaler et al., 2007; Blood & Zatorre, 2001). Physiological measures, such as blood pressure, may also be influenced by music (Blood & Zatorre, 2001). Indeed, music has been shown to influence a variety of behaviours, from cognitive tasks such as lexical processing (Ferraro et al., 2003) to instances of helping behaviour in a field study (North, Tarrant & Hargreaves, 2004). Scherer (2004) argued that a domain-specific model of musical emotions is required in order to adequately capture the complexity of musical emotions. While attempts at this approach have been made, research in this area has been hindered by several shortcomings, such as a confusion between perceived and experienced emotions, (cf. Griffiths, Warren & Dean, 2005; Mathews et al. 2009; Juslin, 2009), a failure to include stringent criteria for the collating of affect terms, as well as the use of selective listener samples and music excerpts (Zentner et al., 2008). The development of the Geneva Emotional Music Scale (GEMS) was an attempt to address many of these limitations. Research supports the GEMS as a more effective means of identifying these emotions than either the discrete or dimensional models (Zentner et al., 2008) however some drawbacks remain. Although inter-listener agreement improved significantly using the GEMS model, a considerable amount of variation remains. As the authors state, the less adequate an instrument is at measuring emotions, the poorer inter-judge agreement should be (Scherer, 2004; Zentner et al., 2008). Therefore, accounting for this variance is an important step in establishing the GEMS as a reliable tool for measuring music emotions. Some evidence suggests that personality may influence the typical emotion patterns experienced by people in response to music. For example, people with high neuroticism levels typically experience elevated levels of emotional affectivity (Eysenck & Eysenck, 1991). It is plausible 56

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that this trend continues into reactivity to music. Kallinen and Ravaja (2004), for instance, found indications of higher levels of positive activation among participants with higher neuroticism levels, on both cardiovascular and self-report measures. These results are supported by research in a more naturalistic setting in which neuroticism scores were found to be positively correlated with emotions falling within the „pleasant-enjoyment‟ range (Juslin et al, 2004). Similarly, Chamorro-Premuzic and Furnham (2007) found that neuroticism levels were related to a tendency to use music as a means of emotion regulation; results which were later replicated using a different cultural sample (Chamorro-Premuzic et al., 2009). A lack of emotional regulation strategies and a propensity to self-reflect have also been associated with the emotional use of music (Greenwood & Long, 2009), and even within the general population, listening to music is related to a reduction in stress and anxiety (Davis & Thaut, 1989). Finally, studies have shown that musicians tend to display higher levels of neuroticism than the general population (Kemp, 1996). The „Extraversion-Introversion‟ dimension of personality has produced more conflicting results. Eysenck‟s theory of personality (Eysenck & Eysenck, 1985) describes introverts as having higher resting levels of arousal. Chamorro-Premuzic and Furnham (2007) suggest that this may make them more susceptible to the effects of music. Kallinen and Ravaja (2004) found that participants with high Behavioural Inhibition System (BIS) sensitivity, a characteristic of both introversion and neuroticism (Gray, 1991), responded with particularly high positive activation to music. Meanwhile, studies using music as a distraction to an unrelated cognitive task suggest that participants with high scores on an extraversion scale were less affected in their performance of the task (Furnham & Bradley, 1997). Other researchers take the opposing view of the relationship between extraversion and emotion, suggesting that extraversion is related to a stronger emotional reaction to music. For example, in their examination of music emotions within a real-life setting, Juslin et al. (2008) found that the overall prevalence of music emotions increased with extraversion scores. However, individually these effect sizes were small, with few reaching significance

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The relationship between extraversion and particular music uses has also been disputed. Chamorro-Premuzic and Furnham (2007) predicted a positive correlation between extraversion and use of music as a background activity or distraction. This was not borne out by the results. They did, however, find a negative correlation between extraversion and emotion regulation. When the study was replicated, extraversion was found to have a positive correlation between both emotional use and use of music as background or distraction (Chamorro-Premuzicet et al. 2009). Other individual factors may also have played a role in the variance between responses on the GEMS. For example, several studies have found gender differences in self-reported and physiological measures of musically-induced emotion, with female participants displaying higher responses than males (Panksepp, 1995; Sutherland et al., 2009). Familiarity with a particular piece of music may heighten the emotional experience (the „Darling, they‟re playing our song‟ phenomenon; Davies, 1978). Similarly, preference for a particular genre (e.g. classical) has been shown to increase the emotional response to excerpts of this style (Kreutz, et al., 2008). The present study investigates the influence of extraversion and neuroticism levels on the emotional response to music excerpts as measured by the GEMS. It was hypothesized that neuroticism levels would positively correlate with stronger, more positive emotional responses. The relationship between extraversion levels and music emotion is more contentious, with some findings inferring a positive and some a negative correlation with musically-induced emotions. The effects of mood, gender, and musical experience on the emotional response to music were also examined. It was hypothesized that female participants would report stronger reactions to the excerpts, and that higher arousal levels would increase the strength and type of emotional response. The effect of musical experience on reaction to music was more difficult to predict, and it was anticipated that the present results would contribute to a clearer picture of such effects. In contrast to Zentner and colleagues‟ (2008) study, musical excerpts of various genres were used, rather than a sole reliance on classical instrumental music. This necessarily runs the risk of confounding the response to the music with that to the lyrics; however, research suggests that music has a larger impact on the emotional reaction of listeners 58

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(Konecni, 1984). Consequently, music preferences were examined to assess their effect on the emotional experience of music. It was expected that liking for a particular genre would positively correlate with strength and positivity of emotional response. Finally, a control group was included in order to assess the effects of explicitly instructing participants to assess and report their emotional response to the music. The control group was presented with excerpts of elevator music in place of the experimental stimuli. It was expected that the control stimulus would elicit a weaker response, with less variation between excerpts.

METHOD Design A between-subjects, single-blind design was used, with participants randomly assigned to either the experimental or control condition. The experimental group listened to music excerpts of different genres, while the control group listened to excerpts of elevator music. Both groups were asked to indicate their emotional response to each excerpt. Measures of participantsâ&#x20AC;&#x; personality, music preferences, mood and demographic variables were taken in order to assess their impact on their emotional response to the stimulus. Participants Eighty-one participants took part in the study, twenty-two male (27.25%) and fifty-nine female (73.75%). Particpants ranged from between 18 to 50 years of age. The study was advertised by emails circulated through mailing lists in Trinity College, Dublin. Undergraduate psychology students were given research credits, a requirement for their course, as an incentive for participation. Materials Stimuli The eight experimental stimuli were chosen to represent each of Rentfrow and Goslingâ&#x20AC;&#x;s (2003) music dimensions (see Appendix 1).

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Moreover, an attempt was made to choose pieces which the majority of participants would be unlikely to recognise. Five of the excerpts were chosen from those used in previous research on musical emotion. Due to the limited range of music genres included in previous research, and in order to create an optimally varied set of stimuli, the remaining three excerpts were chosen from Rentfrow and Gosling‟s (2003) lists of prototypical songs of each dimension. Two different genres were chosen from each dimension, apart from „Upbeat and Conventional‟, where it was felt that the status of pop music in modern culture, over such genres as gospel or country, justified two excerpts from this style being included in the present study. The six control stimuli consisted of elevator music taken from Tom Salem‟s CD, “The World‟s Greatest Elevator Music” (see Appendix 1). Both the experimental and control excerpts were approximately two minutes long and ended with a fade-out. The cutting and modification to the ending was achieved using the „Audacity‟ audio editor and recorder. Scales The Geneva Emotional Music Scale (GEMS; Scherer et al., 2008) was used to measure participants‟ emotional response to the music excerpts. The Eysenck Personality Questionnaire-Revised (EPQ-R; Eysenck & Eysenck, 1991) was used to measure Extraversion and Neuroticism. Mood was measured using the Brief Mood Introspection Scale (BMIS; Mayer & Gaschke, 1988). Music preferences were assessed using the Short Test of Music Preferences Revised (STOMP-R; Rentfrow & Gosling, 2003). Procedure* The procedure followed the same pattern for both the experimental and control conditions. The first stage involved questions relating to demographic variables such as gender, age and nationality, and to musical experience. Participants were asked whether they played a musical instrument or sang, and if yes, to state how long they had partaken in this activity: less than six months, six months to one year, one to two years, three to five years, six to ten years, and over ten years. Musical training was examined with the question “Have you ever taken music lessons? If *

See www/tcd.ie/psychology/spj for apendicies

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yes, for how long?â&#x20AC;? with answers given using the same categories as the previous question. When this was completed, participants filled out the BMIS. Following this, the listening section of the experiment began. Participants were asked to read through the instructions page before turning over the page and pressing play on their computer screens. The excerpts then played through to the end. Participants in the experimental group listened to eight excerpts of varying genres, while the control group listened to six excerpts, all from the elevator music genre. To control for order effects, music excerpts were played in two different orders of presentation in both groups. Each excerpt was repeated, with a clip of birdsong played before the start of a new excerpt, in order to minimise any carryover effects. The first time the excerpt was played, participants were asked to listen to the music and assess their emotional response, without filling out the GEMS until the repeat of the excerpt. In addition to completing the GEMS for each excerpt, both control and experimental conditions were asked to add any affect terms which were not already included in the GEMS but which they felt appropriately described their emotions. Participants were also asked to indicate whether or not they recognised each excerpt. After the listening task, participants were asked to fill out the Short Test of Music Preferences, and the Eysenck Personality Questionnaire Revised. Once the experiment was over, participants were given a debriefing sheet explaining the research question, and emphasizing the anonymous and confidential nature of the study. RESULTS Emotional response to the stimuli On average, the experimental excerpts induced higher Wonder, Transcendence, Power, Joyful Activation and Tension, while the control group experienced higher Tenderness, Nostalgia and Peacefulness. However, the difference between groups was small, ranging from 0.02 (Wonder and Peacefulness) to 0.2 (Power)

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EXCERPTS Extraversion and emotional response A Spearman rank order correlation coefficient revealed a tendency for extraversion to positively correlate with emotional response to the experimental excerpts. The largest number of significant correlations was found for Transcendence, which significantly correlates with extraversion on six excerpts, ranging in strength from the jazz excerpt, r = .337, n = 41, p <0.05, to the soul excerpt, r = 0.53, n = 41, p < 0.001. Conversely, extraversion scores were significantly correlated with Peacefulness on the electronica excerpt alone, r = .408, n = 40, p < 0.01. WD Class Jazz Metal

.364*

.595**

.348*

.318*

.493** .398*

.401** .337*

Altern. .369* Pop bal. Fast Pop Soul

.420**

.443** .496**

.336*

.436** .369*

.388*

.443**

.315*

.454**

.402**

.455**

.349*

.376*

.478*

.548**

.327*

.524**

.469** .530** .525**

Electro .325*

.429** .321*

.408**

.474** .472** ns

ns ns

Table 1: Correlations (r) between extraversion scores and reported emotions for each experimental excerpt * p < .05 (N = 41). ** p < .01 (N = 41) ns = non-significant (WD = Wonder, TS = Transcendence, PW = Power, TD = Tenderness, NT = Nostalgia, PC = Peacefulness, JA = Joyful Activation, SD = Sadness, TN = Tension) 62

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The classical music excerpt appeared to be most influenced by extraversion scores, with six significant correlations observed across its induced emotional response, from Joyful Activation, r = .337, n = 39, p < 0.05, to Nostalgia, r = .530, n = 39, p < 0.001. The response to the heavy metal excerpt seemed to be the least affected by extraversion, with just two correlations reaching significance; Transcendence, r = .42, n = 40, p < 0.01, and Sadness, r = .443, n = 40, p < 0.005. In the control group, a Spearman rank orders correlation revealed no significant correlations between scores on the extraversion scale and ratings of emotion factors for any of the six excerpts. Neuroticism and emotional response In the experimental group, a Spearman‟s rank order correlation revealed a weak correlation between neuroticism levels and emotional response, with just three correlations reaching significance. These correlations were found on the Energetic and Rhythmic music excerpts. Neuroticism scores negatively correlated with ratings of the Wonder factor (r = -.386, n = 41, p <.05), and positively correlated with Tension ratings (r = .325, n = 41, p < 0.05) on the soul excerpt. The latter correlation, however, was made insignificant once outliers were removed (r = .239, n = 39, p > 0.05). A negative correlation was found between neuroticism and scores on the Peacefulness factor (r = -.343, n = 40, p < 0.05) for the electronica excerpt. In the control condition, neuroticism levels were significantly negatively correlated with the response to three excerpts. In Excerpt 2, scores on the neuroticism scale were negatively correlated with ratings on the Transcendence(r = -.361, n = 40, p <.05) and Peacefulness factors (r = -.326, n = 40, p < 0.05), while on Excerpt 4, a negative correlation was identified with Joyful Activation (r = -.326, n = 40, p <0.05). On Excerpt 3, neuroticism levels were negatively related to Nostalgia (r = -.325, n = 40, p < 0.05), although significance was removed once outliers had been eliminated (r = -.305, n = 37, p > 0.05). Conversely, the correlation between Transcendence and neuroticism achieved significance once outliers were removed (r = -.344, n = 38, p < 0.05). Gender A one-tailed Mann-Whitney U test revealed significant differences between males‟ and females‟ responses to four excerpts. As Figure 1 shows, 63

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female participants reported the strongest emotional response for each factor where a significant difference existed. Wonder was most frequently affected by gender differences. Statistically significant differences occurred on three excerpts, with the largest impact found for the soul excerpt (female Md = 1.8, n = 29: male Md = 1.25, n = 12), U = 98.5, z = -2.176, n = 41, p < 0.05.

Figure 1: Significant differences in responses between male and female participants

Musical experience and training A Kruskall-Wallis test revealed significant differences between participants according to how long they had been playing music. Statistically significant differences were observed for Joyful Activation factor on the alternative excerpt, χ² (2, n = 41) = 11.11, p < 0.05, and Wonder, χ² (5, n = 41) = 12.325, p < 0.05, and Transcendence, χ² (5, n = 41) = 11.281, p < 0.05 on the jazz excerpt. The largest response for the three factors occurred in the „1-2 years‟ category (Joyful Activation Md = 2.0; Wonder Md = 4.15; Transcendence Md = 3.1). A Kruskall-Wallis test revealed statistically significant differences in emotional responses to the soul and jazz excerpts between participants at different levels of musical training. Specifically, groups differed in their

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reporting of Joyful Activation on the classical excerpt, χ² (6, n = 39) = 13.13, p < 0.05, and of Nostalgia on the soul excerpt, χ² (6, n = 41) = 14.677, p < 0.05. Figure 3 shows the stronger response of the „over ten years‟ group on both the Joyful Activation (Md = 2.55, n = 6) and the Nostalgia factor (Md = 3.4, n = 6). In the control group, a Kruskall-Wallis test revealed no significant differences between participants of varying musical training, or according to how long they have been playing music (6mths – 1 yr, n = 1; 1-2 years, n = 2; 3-5 years, n = 3; 6-10 years, n = 7, over 10 years, n = 6). Mood The relationship between mood state and emotional responses to music was investigated using Spearman rank order correlation coefficient. Pleasant mood and arousal levels influence responses in the GEMS in both the control and experimental groups, to much the same extent. Pleasant affect was negatively correlated with “sad” emotions across two experimental excerpts (Nostalgia: r = -.417, n = 39, p < 0.01; Sadness, r = -.355, n = 34, p < 0.05). Conversely, pleasant affect exhibited a medium sized, positive correlation with “happy” emotion factors in the control group (Transcendence: r = .317, n = 40, p < 0.05; Joyful Activation; r = .521, n = 40, p < 0.005). Excerpt Heavy Metal Jazz† Control excerpt 2 Control excerpt 4

Emotional response Nostalgia Sadness Transcendence Joyful activiation

Correlation -.417** -.355 .317 .521**

Table 2: Significant correlations between emotional response and pleasant mood in experimental and control groups

**p<.005 †Ouliers removed (±3 SD) Arousal levels were positively correlated with levels of Power, Joyful Activation and Tension in both groups, with the strongest correlation found for feelings of Tension on the soul excerpt (r = .410, n = 40, p < 0.01).

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Excerpt Soul Jazz Electronica Pop Ballad Control excerpt 2 Control excerpt 5 Control excerpt 3 Control excerpt 6 Control excerpt 6 **p<0.005

Emotional response Power Joyful activation Tension Power Joyful activation Tension Sadness Power Power Tension Tension Transcendence

Correlation .375 .379 .410** .351 .399 .510 .398 .334 .385 .398 .328 .317

Table 3: Significant correlations between emotional response and arousal levels in experimental and control groups

Music preferences The relationship between music preferences and emotional responses to excerpts was investigated using Spearman rank order correlation coefficient. Results are presented in Table 3. While reactions to the electronica excerpt did not correlate with preference for the Energetic and Rhythmic dimension, increased correlations were observed between reactions and preferences for the specific genre. Wonder is most frequently correlated with preferences, with correlations ranging from the electronica genre (r = .361, n = 38, p < 0.05) to the Intense and Rebellious dimension (r = .420, n = 37, p < 0.05). Excerpt Jazz

Heavy Metal

Response Wonder Tenderness Peacefulness Joyful Activation Wonder Power Nostalgia

Correlation .401 .450** .438** .431 .420 .380 .382

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Joyful Activation .479** Tension -.415** Wonder .361 Transcendence .444** Tenderness .362 Nostalgia .328 Peacefulness .351 Table 4: Correlations between emotional response to excerpts and preference for the particular style of music. † responses to electronica excerpt are correlated with a liking for the electronica genre. For other excerpts the illustrated correlation is with preference for the relevant music dimensions. **p<0.005 Pop Ballad Electronica†

Partial correlations A Spearman‟s rank order coefficient revealed a medium-sized, negative correlation between neuroticism scores and pleasant mood state, r = -.355, n = 40, p < 0.05. Partial correlation was used to explore the relationship between neuroticism and emotional responses to the experimental excerpts, while controlling for pleasantness of mood. Overall, results did not differ significantly from initial investigation without controlling for mood. However, even after transformation and the removal of outliers, data was, in many cases, still skewed and violating the assumptions of normality. Therefore, these results must be interpreted with caution. Neuroticism scores were positively correlated with preference for the Intense and Rebellious music dimension (r = .342, n = 38, p < 0.05). DISCUSSION The prediction that higher neuroticism levels would result in a stronger and more positive reaction to the music was not supported by the outcomes of this study. In contrast to previous findings of a positive correlation (Juslin & Laukka, 2008; Kallinen & Ravaja, 2006), neuroticism levels were, in general, weakly and negatively correlated with emotional response. Extraversion levels were found to be strongly and positively correlated with emotional reactions to the music excerpts. Such results support previous findings of a positive association between extraversion 67

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levels and music emotions (Chamorro-Premuzic et al, 2009; Juslin & Laukka, 2008), while opposing the proposal of a relation between extraversion and background use (Chamorro-Premuzic et al, 2009, Furnham & Bradley, 1997). The relationship between extraversion and increased music emotions also contradicts findings that introverts are more sensitive to the effects of music as a distracter (Furnham & Bradley, 1997). However, it may be the case that the ability to perform separate tasks alongside music is independent of the experience of music as the sole activity. This view is supported by research showing that extrovertsâ&#x20AC;&#x; superior performance in the presence of distraction is not limited to the presence of musical distractions alone (Ylias & Heaven, 2003). Gender differences and mood effects were also found for some excerpts, supporting the predictions that both female participants, and participants experiencing elevated general moods, would report stronger emotional reactions. The existence of such gender effects within music emotions is widely supported (Sutherland et al, 2009), while the influence of mood in the present study also supports previous research (Dibbens, 2004). The association between musical experience, preferences and emotion, however, were less straightforward, with differing effects shown for length of time participants have been involved in musical activities, and length of time they have been receiving musical training. These results may be due, at least in part, to how the questions were phrased: verbal feedback at the time of testing showed that participants who had previously been involved in musical activities, but had not played or sung in some time, varied in their responses when asked if they played an instrument or sang. Music preferences also showed a considerable degree of variation in their relationship to emotional experience of music. A liking for the Intense and Rebellious music dimension and for the Reflective and Complex dimension were positively correlated with responses to the heavy metal and jazz excerpts, respectively, while liking of electronica music, but not the corresponding Energetic and Rhythmic dimension increased emotional response to the electronica excerpt. Responses to the remaining excerpts were not related to preferences of either associated dimension or the specific genre involved.

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It may be that the jazz, heavy metal and electronica excerpts are more prototypical examples of their music type, or, alternatively, that liking for such music genres is relatively niche compared to other genres such as pop or classical. On the other hand, music choices, in general, may have little to do with emotional experience of music; as Zentner et al. (2008) note, emotional reactions to music are not universal. It is also possible that social desirability effects came into play when examining music preferences. Research has uncovered a strong relationship between music preferences and identity (North & Hargreaves, 1999; Rentfrow & Gosling, 2006); the desire to uphold this identity may affect reported music preferences, without necessarily affecting the experience of the music. The results of the current study, therefore, partially support previous research of music emotions, with the effects of gender, musical experience and mood on responses to the GEMS all being, to some extent, predicted by the initial hypotheses and supporting previous research. Furthermore, gender, extraversion and musical experience had a stronger influence on reactions to the experimental, rather than the control stimuli, suggesting that such effects were not merely experimental artefacts, and may generalize to the emotional experience of music outside the laboratory setting. Conversely, the comparably weak correlations between neuroticism levels and emotional responses to stimuli in the experimental and control groups throws doubt on whether such a result is indicative of a true association between neuroticism and reactions to music, or whether it reflects a result of the particular experimental paradigm used. The lack of normality within the data set, however, restricted the degree to which this interaction could be investigated â&#x20AC;&#x201C; a more sophisticated analysis could throw further light on this effect. An important factor which is missing in the current design, and indeed in many experimental investigations into music emotions, is the individualâ&#x20AC;&#x;s motives for listening to the music (Behne, 1997). ChamorroPremuzic and Furnham (2007) note the intentionality which typifies the mood regulation involved in emotional use of music. Removing the individualâ&#x20AC;&#x;s ability to choose both the music and context within which the music is experienced, may therefore inherently alter the perceived relationship between individual and emotional experience of the music. 69

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This observation may partly explain the weak relations between neuroticism and emotional experience, and the similar patterns observed for both experimental and control stimuli. A comparison between self-reported emotional levels in the control and experimental groups also reveal remarkable similarities between groups. Overall, the emotional reactions in both groups were noticeably small, contradicting the prediction that experimental excerpts would induce stronger and more varied responses. This outcome also appears to contradict previous portrayals of music as rich in emotive value (Heaton & Allen, 2009; Juslin & Laukka, 2004), and may be due, in part, to the laboratory setting and close observation of emotional reactions (Konecni, 1982; Sloboda & Juslin, 2001). The low response may also have been due to the relatively large number of music genres presented to participants. When listening to music individuals are unlikely to experience such a range of musical genres. Emotionally, people may not have the capacity to react to such an artificial range of musical types. A dislike or lack of familiarity with a particular style of music may have decreased the emotional reaction to an excerpt, thus lowering the overall median in the experimental group. Initially, it was decided to include several music genres in order to counter the over-reliance on classical music throughout the music and emotion research (North & Hargreaves, 2008), and, indeed, results indicate that music of varying styles may be used to influence emotions. However, the influence of participant characteristics on the emotional reaction varies between excerpts to an extent that makes it difficult to come to reliable conclusions regarding the exact nature of the relationship between individual characteristics et cetera, and the type and strength of emotions elicited by music. It may have been more beneficial to attempt to control the variation between excerpts in order to gain clearer insights into the influence of the individual in the emotional experience of music. Further limitations are also noted in the present design. Control participants were exposed to fewer excerpts than the experimental group, which may have resulted in lower fatigue levels and boredom, and positively influenced emotional reactions. Additionally, participants were not asked to report whether or not they liked a particular excerpt, information that may have added to the understanding of music emotions 70

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and how individual differences impact on them. For instance, liking of the excerpts may have resulted in a positive correlation between neuroticism and emotional reaction. Moreover, it cannot be ruled out that participants in the control group did, in fact, enjoy some of the excerpts, which changes the implications of the similarity of overall group responses. Another confounding variable may be amount of time participants normally spend listening to music. Future investigations should include a measure of this variable. . Finally, the inclusion of only two orders of presentation meant that the effects of order of excerpt cannot be wholly ruled out. It is worth noting that, due to very high number of statistical analyses conducted, it is highly likely that at least some of the significant results found were anomalous due to the probability of committing a type 1 error. The present results highlight the need for future research to use a more naturalistic setting for music emotions in order to determine whether the emotions presented on the GEMS scale are of more or less use within the context of motives for listening, typical listening settings, presence of others, and so forth. Investigations of this kind may prove to be of more validity than the artificial task of listening excerpts of experimenterselected music. The establishment of a domain-specific emotion model, such as the GEMS, is an important step toward understanding the quality, range, and other characteristics of musically-induced emotions (Scherer, 2004). Interlistener agreement is necessary in order to validate the scale as a useful tool of emotion measurement, and the present study offers some direction for future research attempting to identify the causes of inter-listener variation. The relationship between musically induced emotions and personality traits has important implications for the use of music within a therapeutic and clinical setting (Forsblom, Laitenen & Tervaniemi, 2009; Ziv et al., 2008), within a workplace or retail situation (North & Hargreaves, 2008), as well as providing a broader insight into an important everyday behaviour (Juslin et al, 2008). This study provides preliminary support for an association between extraversion levels and emotional responses to music using the GEMS scale; however further research is needed to examine the relationship between personality traits and musical emotions outside of the laboratory setting. 71

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Eysenck, H. J., & Eysenck, S. B. G. (1991). Manual of the Eysenck Personality Scales. London: Hodder & Stoughton.

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Ferraro, F. R., Ronning, B., Pekarski, K. &amp; Risan, J. (2003). Effects of induced emotional state in lexical processing in younger and older adults. The Journal of Psychology, 137, 262-272.

Grewe, O., Kopiez, R., & Altenmuller, E. (2009). Chills as an indicator of individual emotional peaks. The Neurosciences and Music III Disorders and Plasticity, 1169, 351-354.

Forsblom, A., Laitinen, S., Sarkamo, T., & Tervaniemi, M. (2009). Therapeutic role of music listening in stroke rehabilitation. The Neurosciences and Music III - Disorders and Plasticity, 1169, 426-430.

Grewe, O., Nagel, F., Altenmuller, E., & Kopiez, R. (2009). Individual emotional reactions towards music: Evolutionary-based universals? Musicae Scientiae, Special Issue, 261-287.

Furnham, A., & Bradley, A. (1997). Music while you work: the differential distraction of background music on the cognitive test performance of extroverts and introverts. Applied Cognitive Psychology, 11, 445-455.

Griffiths, T. D., Warren, J. D., & Dean, J. L. (2004). When the feeling's gone: a selective loss of musical emotion. Journal of Neurology, Neurosurgery & Psychiatry., 7, 341-345.

Gray, J. A. (1991). Neural systems, emotion and personality.

Hargreaves, D. J., Macdonald, R. & Miell, D. (1995). How do people communicate using music? Oxford: Oxford University 73

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Press. Harrer, G. H., H. (1977). Music, emotion, and autonomic function. London: William Heinemann Medical Books. Heaton, P., & Allen, R. (2009). With concords of sweet sounds: New perspectives on the diversity of musical experience in autism and other neurodevelopmental disorders. The Neurosciences and Music III - Disorders and Plasticity, 1169, 318-325. Juslin, P. N. (2009). Emotional responses to music. Oxford: Oxford University Press. Juslin, P. N., & Laukka, P. (2004). Expression, perception and induction of music emotions: a review and a questionnaire study of everyday listening. Journal of New Music Research, 33, 217-238. Juslin, P. N., Liljestrom, S., Vastfjall, D., Barradas, G., & Silva, A. (2008). An experience sampling study of emotional reactions to music: listener, music and situation. Emotion, 8, 668-683.

Kallinen, K., & Ravaja, N. (2004). The role of personality in emotional responses to music: Verbal, electrocortical and cardiovascular measures. [Article]. Journal of New Music Research, 33(4), 399-409. Konecni, V. J. (1982). Social interaction and music preference. New York: Academic Press. Konecni, V. J. (1984). Elusive effects of artists' messages. Amsterdam: North-Holland Press. Kreutz, G., Ott, U., Teichmann, D., Osawa, P., & Vaitl, D. (2008). Using music to induce emotions: influences of music preferences and absorption. Psychology of Music, 36, 101-126. Lundqvist,L.O.,Carlsson,F.,&Hi lmersson,P.(2000).Facial electromyography, autonomic activity, and emotional experience to happy and sad music. International Journal of Psychology, 35, 225. Mathews, B. R., Chang, C., May, M. D., Engstrom, J., & Miller, B. L. (2009). Pleasurable emotional response to music: a case of neurodegenerative generalized

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auditory agnosia. Neurocase, 15, 248-259. Mayer, J. D., Allen, J. P., & Beauregard, K. (1995). Mood inductions for four specific moods: a procedure employing guided imagery vignettes with music. Journal of mental imagery, 19, 135-150. Mitterschiffthaler, M. T., Fu, C. H., Dalton, J.A., Andrews, C. M., & Williams, S. C. (2007). A functional MRI study of happy and sad affective states induced by classical music. Human Brain Mapping, 28, 1150-1162. North, A. C., & Hargreaves, D.J. (1999). Music and adolescent identity. Music Education Research, 1, 75-92. North, A. C., Tarrant, M., & Hargreaves, D.J. (2004). The effects of music on helping behaviour: A field study. Environment and Behaviour, 36, 266-275. Panksepp, J. (1995). The emotional source of 'chills' induced by music. Music Perception, 13, 171-207. Rentfrow, P. J., & Gosling, S. D.

(2003). The do re mi's of everyday life: The structure and personalitiy correlates of music preferences. Journal of Personality and Social Psychology, 84, 1236-1256. Rentfrow, P. J., & Gosling, S. D. (2006). Message in a ballad - The role of music preferences in interpersonal perception. Psychological Science, 17(3), 236242. Scherer, R. (2004). Which emotions can be induced by music? What are the underlying mechanisms? And how can we measure them? Journal of New Music Research, 33, 239-251. Sloboda, J.A.,& Juslin, P.N.(2001).Psychological perspectives on music and emotion. New York: Oxford University Press. Sutherland, M., Grewe, O., Egermann, H., Nagel, F., Kopiez, R., & Altenm端ller, E. (2009). The influence of social situations on music listening. Annals of the New York Academy of Sciences, 1169, 363-367. Zentner, M., Scherer, Grandjean, D., & Scherer, K. R. (2008). 75

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Emotions Evoked by the Sound of Music:, Characterization, Classification,and Measurement. Emotion, 8, 494-521. Ziv, N., & Keydar, E. (2009). The Relationship Between Creative Potential, Aesthetic Response to Music, and Musical Preferences. Creativity Research Journal, 21(1), 125-133.

Ziv, N., Rotem, T., Arnon, Z., & Haimov, I. (2008). The Effect of Music Relaxation versus Progressive Muscular Relaxation on Insomnia in Older People and Their Relationship to Personality Traits. Journal of Music Therapy, 45(3), 360-380.

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IRISH SECONDARY SCHOOL STUDENTSâ&#x20AC;&#x2122; INTENTION TO PURSUE HIGHER EDUCATION: AN INVESTIGATION TO IDENTIFY THE STRONGEST PREDICTORS Catherine Rock Graduate 2010, Psychology rockc@tcd.ie

ABSTRACT The present study aimed to identify the strongest predictors of intention to pursue higher education (HE) among a sample of Irish secondary school students. The predictors under investigation were school socio-economic status (SES), parental occupation, parental education, gender, family structure, and academic self-efficacy. One hundred and thirty nine participants took part in the study, with an even gender breakdown (70 females and 69 males) and a mean age of 16.04 years. Standard multiple regression analysis revealed that school SES was the only statistically significant predictor, explaining 11% of the variance in intention to pursue HE. Specifically, low SES schools differed from both medium and high SES schools on intentions to pursue HE but medium and high SES schools did not differ from each other. The other predictor variables did not contribute significantly to the predictive ability of the model. This provided only partial support for the hypothesis. Implications for research in the area and future directions are discussed.

INTRODUCTION Higher education (HE) in Ireland refers to the tertiary education system which includes seven universities, 14 institutes of technology, and numerous colleges of education and private institutions. HE in Ireland has undergone a massive expansion in recent times. Participation rates of school-leavers jumped from 20% in 1980 to 60% in 2005 (Byrne, 2009). The present study aimed to identify the strongest predictors of intention to attend HE among a sample of Irish secondary school students, aged 1617 years. The predictors under investigation were socio-economic status

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(SES) of school, parental occupation, parental level of education, gender, family structure, and academic self-efficacy. While 80% of school-leavers from professional SES backgrounds progressed onto HE in 2007, that figure was just 45% for those from unemployed and manual backgrounds (Byrne, McCoy & Watson, 2009). Students from farming and employer/managerial SES backgrounds also display relatively high rates of HE progression at 70% and 65% respectively. In 2004, just 12% of new entrants to HE came from a designated disadvantaged school (McCoy, Byrne, O’Connell, Kelly, & Doherty, 2010) even though 30% of all school-leavers attended this school type. Conversely, of the top 50 feeder schools in Ireland, approximately 60% are fee-paying schools (The Irish Times, 2009). When it is considered that only 7% of Irish secondary schools are fee-paying (Smyth, 2009) and that their students have the highest rate of HE participation (O’Connell, Clancy, & McCoy, 2006), the disparities become clear. Indeed, despite the removal of HE tuition fees in 1996, social inequality in accessibility was actually greater in 1998 than at the beginning of the 1980s (McCoy & Smyth, 2003). This phenomenon of unequal access to HE is not unique to Ireland and has been well documented internationally (OECD, 2008; Shavit, Arum, & Gamoran, 2007; Shavit & Blossfeld, 1993). Discussion on inequality in HE has focused on students’ SES background, as demonstrated in the research presented above. The concept of SES is often abstract and, by its very nature, is rooted in a national and regional economic and cultural system. Partially due to these reasons, there are conflicting views on what to base the variable of SES on within this field of research. This results in different indicators and scales being used across different studies. This inconsistency between studies makes it difficult to generalise from research findings and significantly hampers comparison between studies. For the purpose of this study, school SES and parental occupation were analysed as separate predictor variables. Thus, instead of an aggregate SES category, the relevant contribution of each could be assessed. This was done with a view to assessing the usefulness of SES indicators used in the literature. While it has been consistently found that economic constraints present one of the major barriers to HE for those from low SES backgrounds, Lynch and O’Riordan (1998) have also highlighted the influence of social, cultural and psychological factors on Irish HE 78

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progression rates. Therefore, an investigation of other variables is warranted. Evidence indicates that children’s level of education and cognitive development are positively related to the education level of their parents (Wolfe & Haveman, 2002). Overall, students whose parents have a degree are almost four times as likely to participate in HE than others (McCoy et al., 2010). Interpretation of the relevant literature, however, is somewhat complicated as parental education is sometimes modelled as a key causal variable, sometimes as a mediating factor, and other times as a control. The present study employed it as a predictor variable in a multiple regression model to assess its unique relative contribution to students’ intention to pursue HE. Caution in analysis is warranted due the correlation between parental education and parental occupation which has previously been found in the literature (Card, 1999). In Ireland, there is a consistent gender imbalance in students participating in HE. This imbalance has been present since the mid-1990s, and, currently, approximately 64% of female school-leavers progress to HE, compared to 57% of males (Smyth & Hannan, 2000). While this pattern may be partially explained by superior Leaving Certificate performance by girls, it does not entirely explain the disparity (Byrne et al., 2009). Similar HE gender patterns have been noted in the UK, America, and other Western countries (HEFCE, 2005; Snyder & Dillow, 2007). Gender can represent both a demographic and psychological variable and, due to its ease of measurement, provided the present study with a reliable and valid comparison to previous research findings. Within the literature, family structure represents a distal influencing factor on a student’s progression to HE. As such, it has rarely been explicitly studied, especially not in an Irish context. When gender, race, and SES are controlled for, family structure is the single greatest predictor of academic achievement (Jeynes, 2005). However, this finding is not Irish, not specific to HE progression, and hasn’t always been replicated. In addition, studies often fail to control for other variables identified as being correlated with both family structure and HE progression, such as parental education (Lerman, 1996). As such, the present study required adequate statistical controls to control for this (and any other) possible inter-correlation. In keeping with much of the research, and due to sample

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size limitations, the present study identified family structure based on a one or two-parent distinction. The concept of academic self-efficacy, which this project employed as a predictor variable, was devised by Albert Bandura (Bandura, 1977). This is a domain-specific form of the original global self-efficacy concept proposed by Bandura and is defined as a personâ&#x20AC;&#x2122;s convictions about undertaking a given academic task at a designated level. Within the literature, academic self-efficacy has been examined in relation to subsequent academic performance, usually within an immediate or close temporal proximity. It has also been found that students high in academic self-efficacy set higher academic goals (Zimmerman, Bandura, & Martinez-Pons, 1992) and willingly choose more challenging academic tasks (Bandura & Schunk, 1981). In the present study, academic selfefficacy was employed in a novel situation; to be entered as a predictor variable for studentsâ&#x20AC;&#x2122; intention to attend HE. Theoretically, it could be predicted that those higher in self-efficacy and who set higher academic goals for themselves, would be more likely to intend to purse HE than those students lower in self-efficacy. The overarching theoretical framework, within which psychological researchers place HE progression studies, is the Ecological Systems Theory (Bronfebrenner, 1979). This model acknowledges the interactions between variables and how they operate at different levels of influence. For example, researchers working within this framework investigate the impact of proximal and distal factors and direct and mediating variables. The ecological framework also acknowledges other influences on the measure of interest, even though they may not be under direct inspection in a specific study at the time. The research on HE progression stems from diverse disciplines; psychology, sociology, economics, and, thus, the ecological framework remains practically relevant. This model allows for disparate literature to be nested together and integrated into a common context, allowing for further interpretation and analysis. Thus, the Ecological Systems approach remains a useful theoretical model in which to place the present research. With the exception of academic self-efficacy, previous studies have ascertained the relationship between the presently employed factors and HE pursuit. However, very few studies have attempted to define which factors exercise the strongest influence in this regard. Therefore, the aim 80

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of the present study was not to identify potential predictors of studentsâ&#x20AC;&#x2122; intention to pursue HE, the aim was to assess the strength of influence that each of the respective factors has on studentsâ&#x20AC;&#x2122; intentions. The predictors employed by the study ranged from the very well established (school SES, parental occupation), to the established but unclear (parental education, family structure), and also the novel (academic-self efficacy). This was done to incorporate research from separate fields and to elucidate any potentially interesting patterns. In addition to this somewhat novel analysis, the present study provides a prospective view to HE progression research. The overwhelming majority of research in this field takes a retrospective approach, focusing on the characteristics of students who are already participating or not in HE. This study focused on secondary school students providing data on future intentions. This approach was deemed suitable as it was felt that the retrospective methodology could be missing out on important and interesting findings. The students who were the focus of this study were aged 16-17 years. This chosen age range was due in part to ensure that the participants could provide accurate answers on the demographic questionnaire. However, it was also guided by both theory and empirical research. Findings suggest that up until approximately 15 years of age, teenagers are somewhat unduly influenced by their emotional state, displaying overtly negative attitudes towards education. This is before their emotions and opinions stabilise at 16 years (Maras, Carmichael, Patel, & Wills, 2007). Therefore, a small age bracket of upper-secondary school students could potentially control for this developmental consideration. It was hypothesised that school SES and parental occupation would be the strongest predictors of intention to pursue HE. Also, it was hypothesised that parental education and academic self-efficacy would be positively correlated with intentions and that females and students from two-parent families would have higher intentions to pursue HE than males and those from one-parent families.

METHOD Participants Participants comprised of 139 secondary school students. The age range was 16-17 years with a mean age of 16.04 years. The sample had an almost 81

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even gender balance, consisting of 70 females and 69 males. Participants were recruited voluntarily through their respective schools, all of which were located in the Dublin area. Both same-sex and mixed schools took part. Three school categories were sought to represent the school SES variable. These consisted of schools with official DEIS status (low SES), schools representing the median Irish SES (medium SES), and fee-paying schools (high SES). Approximately equal numbers of students were recruited from each school SES category (low SES = 50, medium SES = 43, high SES = 46). Materials The Attitudes to Higher Education Questionnaire (AHEQ) (Appendix E *) is a 62-item self-report measure. In the present study, this provided the dependent variable of intention to pursue HE. The AHEQ had never before been used with an Irish sample, but was judged to be a suitable measure due to the similarity of the cultural and educational systems between Ireland and the countries in which it was developed. The Perceived Academic Efficacy Scale (Appendix F) was adopted from the Multidimensional Scales of Perceived Self-Efficacy (Bandura, 1990). In the present study, the Perceived Academic Efficacy Scale was utilized to gain a measure of studentsâ&#x20AC;&#x2122; academic self-efficacy construct. The questionnaire assesses self-efficacy in nine domains. These are; enlisting social resources, academic achievement, self-regulated learning, leisure-time skills and extracurricular activities, self-regulatory efficacy (to resist peer pressure for high risk behaviors), self-efficacy to meet othersâ&#x20AC;&#x2122; expectations, social self-efficacy, self-assertive efficacy, and enlisting parental and community support. Bandura (Bandura, Barbaranelli, Caprara, & Pastorelli, 2001) combines the two sub-scales of self-regulated learning and academic achievement to form its own miniscale of Perceived Academic Efficacy and this is the measure which the present study employed. A demographic questionnaire (Appendix G) was designed specifically for the current research. It provided predictor variable data (parental occupation, parental education, gender, and family structure). The questionnaire consisted of questions relating to the participants *

See www.tcd.ie/pscychology/spj for appendices

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themselves (e.g. age, gender, nationality, family structure) and also asked for information in relation to their parents’ employment situation and level of education. The categories for parental occupation (e.g., student, unemployed, individual stated occupation) were based on the methodology used in the New Entrants Data 2004 survey (McCoy, et al., 2010). The responses are coded into pre-defined parental occupation categories (manual, semi-skilled, skilled, and professional/managerial). These categories are often used as an index of general SES status and are based on data from the Census of Population (1996). The highest ranking occupation was taken as the index. The parental education categories were adopted from those used in the Annual School Leavers Surveys (Byrne et al., 2009; McCoy, Kelly, & Watson, 2007). As with parental occupation, the highest ranking education level was taken as the index. Family structure could be described as either one-parent or two-parent family. Procedure Schools were contacted on the basis of their general SES status. The low and high SES schools were identified from a database of DEIS and feepaying secondary schools, respectively, on the Department of Education’s website. As no other school SES grading system exists, the medium SES schools were identified according to their location in areas in Dublin which represent near national-average median SES. This was determined by analysing the “Social Class and Socio-economic Group” information from Census 2006 located on the Central Statistics Office website (Central Statistics Office, 2007). When permission from the individual schools was obtained, students aged 16 and 17 years were invited to take part in the study. Either the researcher or a teacher within the school carried out the fieldwork within a school classroom. When a teacher carried this out they were provided with explicit written instructions by the researcher (Appendix D). Detailed information was provided to prospective participants (Appendix A) and consent was obtained prior to their taking part (Appendix B). Each participating student filled out the questionnaires. Students were debriefed (Appendix C) and thanked for their participation. All data was collected and statistically analysed using SPSS 16.0.

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RESULTS Preliminary analyses were performed, where applicable, to confirm normality, linearity, homogeneity of variance, and homoscedasticity. A two-tailed correlation matrix (Pearsonâ&#x20AC;&#x2122;s) including all variables (intention to pursue to HE-measured by scores on AHEQ, school SES, parental occupation, parental education, gender, family structure and academic self-efficacy) was produced. Significant positive correlations were observed for intention to pursue HE and school SES, r = .37, n = 139, p < .01; parental occupation and school SES, r = .19, n= 139, p < .05; parental education and school SES, r = .2, n = 139, p < .05. The positive correlation between intention to pursue HE and parental education was approaching significance at the 5% level (r = .15, n = 139). There were no significant correlations between intention to pursue HE and parental occupation, gender, family structure and academic self-efficacy. A one-way between-groups ANOVA compared intention to pursue HE across three levels of school SES (low SES, medium SES and high SES). A statistically significant difference was found; F(2, 136) = 12.17, p < .001. Post-hoc comparisons using the Tukey HSD test indicated that the mean score for low SES (M = 31.52, SD = 4.41) was significantly different from both medium SES (M = 34.49, SD = 3.94) and high SES (M = 35.15, SD = 3.03). Medium and high SES did not differ significantly. This effect is illustrated in Figure 1. On the basis of the correlation matrix finding, a one-way betweengroups ANOVA was carried out to compare the effect of parental occupation (manual, semi-skilled, skilled and professional/managerial) on school SES. There was no statistically significant difference found, F (3, 135) = 1.85, p > .05.Also, on the basis of the correlation matrix results, a one-way between groups ANOVA was conducted to explore the impact of parental education (primary, lower secondary, upper secondary, plc, cert/diploma, degree) on school SES. There was a statistically significant difference found in school SES for the six parental education levels, F (5, 133) = 2.85, p. <.05. A one-way between-groups ANOVA was carried out to compare the effect of parental education on intention to pursue HE. There was no statistically significant difference found: F (5, 133) = 0.95, p > .05.

Intention to pursue HE (scores on AHEQ)

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36 35 34 33 32 31 30 29 Low

Medium

High

School SES Figure 1. Mean scores of intention to pursue HE (Measured on AHEQ) across school SES.

Due to the statistically significant effect of school SES on intention to pursue HE, in addition to the statistically significant effect of parental education on school SES, an ANCOVA was performed. This would assess, and potentially control for, the possible mediating effect of parental education on intention to pursue HE. Additional preliminary checks ensured presence of homogeneity of regression slopes and reliable measurement of the covariate. After controlling for parental education there was still a statistically significant difference between school SES type and intention to pursue HE, F ( 1, 27) = 10.67, p < .001. A standard multiple regression was used to assess the ability of the six measures (school SES, parental occupation, parental education, gender, family structure and academic self-efficacy) to predict level of intention to pursue HE. For the purpose of multiple regression, preliminary analysis ensured there was no violation of multicollinearity and sample size ratio requirements. As a whole, the model explained 16% of the total variance in intention to pursue HE, F (6, 132) = 4.2, p <.01. However, the only significant predictor was school SES, with its unique contribution explaining 11% of the variance (Î˛ = .35, p < .001). No other measures predicted a statistically significant unique variance in intention to pursue HE.

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CONCLUSION The purpose of the present research was to identify the strongest predictors of intention to pursue HE among a sample of Irish secondary school students. The results of the study provide only partial support for the hypotheses put forward in the introduction. Only school SES was a statistically significant predictor of intention to pursue to HE, explaining 11% of the variance, while the others did not contribute significantly to the predictive ability of the model. Low SES schools differed from both medium and high SES schools on intentions to pursue HE, but medium and high SES schools did not differ from each other. Parental occupation and parental education were positively correlated with school SES but they did not impact upon school SESâ&#x20AC;&#x2122;s relationship with intention to pursue HE. When placing the present findings in the context of previous research it is necessary to be aware that most findings have been extrapolated from retrospective studies of students, whereas the present study is based on their prospective intentions. Therefore, findings need to be interpreted with extra caution. The findings highlight the need for clarification with regard to the SES indicators used in studies. Some studies use parental occupation alone as indication of a studentâ&#x20AC;&#x2122;s SES background, others use school SES measures alone, while other studies use different measures again. This study found that different SES indicators (school SES and parental occupation), while correlating with each other, do not have the same impact on intention to pursue HE. The former was predictive of the outcome, while the latter was not. While research has found a consistent relationship between level of parental education and participation in HE, that relationship was not evident from the present findings. Although the cited relevant Irish research has been retrospective, the relationship found is strong enough to advise against discounting parental education as a predictor in future research. Possible explanations as to the lack of relationship found in the present study relate to the small sample size compared to other HE research and the number of parental education coding categories employed. The lack of a relationship between gender and intention to pursue HE is also in contrast to previous research, both prospective and

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retrospective. The issue of superior Leaving Certificate performance by females may warrant further investigation. Family structure has not been previously examined in an Irish prospective study, and so the lack of a relationship with the outcome variable needs consideration. Family structure is acknowledged as playing a mediating role on HE participation and due to the comparatively small sample size it may be the case that this relationship was not detected. Also due to the small sample size was the inability to record the many varied family types found in Ireland today. Instead, they were coded into either one or two-parent family, and this could result in reduced statistical power masking indirect effects. While there is a plethora of research linking academic self-efficacy and academic performance, the operation of variables in the present study was novel. The self-efficacy measured in the present study was domainspecific and assessed using an established measure. While it may be premature to discount its effect on the basis of one study (with its inherent limitations), no tangible evidence of a relationship with intention to pursue HE was found. The method used to measure intention to pursue HE has been specially designed for use in HE progression research and so could be regarded as reliable and valid. However, it is necessary to bear in mind that no measure can capture a particular concept in its entirety, especially an intangible one such as intentions. The results of the present research can be integrated within the Ecological Systems Theory model. The aim of this model is not to find a â&#x20AC;&#x153;perfect fitâ&#x20AC;?, but to acknowledge and synthesise findings in order to build an understanding of a given phenomena. As stated previously, this model does not exclude the recognition of other influencing variables, even though they may not be under direct investigation by a given study at the time. Based on the present findings, and in addition to previous research, this theoretical concept can be appreciated. This is because it allows a wider interpretation in relation to the variables that were not under investigation which may be incorporated into future research. This becomes particularly obvious with the use of regression analysis, as even highly predictive models cannot explain all the variance on a particular outcome. Future research within the Ecological Model could focus on peer and sibling influences and the macro-societal context.

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The results from the study regarding the predictive value of school SES and parental occupation may have implications regarding the measurement of studentâ&#x20AC;&#x2122;s SES background in future studies. However, caution in interpretation is needed. As outlined previously, there are various methods for streaming various jobs into particular SES groups. This study employed a method used by the New Entrants Data 2004 survey (McCoy et al., 2010) which is comprised of four categories. There are other methods frequently used by Irish studies which contain six (Central Statistics Office, 2006) and eight categories (McCoy et al., 2007). These provide a greater level of specificity which the present study was unable to attempt due to sample size limitations. This specificity may provide a greater predictive ability of parental occupation, a hypothesis which may be tested in future research. The only variable which showed a significant difference in intention to pursue HE was school SES and only a difference between low SES and both medium and high SES schools was shown. This raises interesting questions about the school processes taking place within the respective institutions. This issue remains relatively understudied in the literature. However, an Irish study by Smyth and Hannan (2007) found that flexible subject choices, good career guidance, and the general expectational climate of the school resulted in higher HE applications. Importantly, this was found in spite of studentsâ&#x20AC;&#x2122; family background. Further research is merited to clarify and expand on these findings. In contrast to previous research, parental occupation, parental education and gender did not have an effect on intention to pursue HE. As mentioned above, interpretation must acknowledge that this study was prospective in nature, as opposed to retrospective. An important theoretical and practical consideration can be raised from this observation; that of the intention-behaviour gap. While it is acknowledged that intentions are the best available predictors of actual behaviour (Azjen, 1991), analysis has revealed that they explain only 28% of future behaviour variance (Sutton, 1998). So it may be the case that students whose parents are in lower status occupations, have lower levels of education, and are themselves male, intend on pursuing HE, but in their actual subsequent behaviour, do not. This is a tentative postulation based on the present prospective study. Future longitudinal research could test these predictions. 88

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The prospective methodology adopted in the present study aimed to contribute a somewhat novel approach in a field filled with retrospective data. However, further research is merited on the basis of inherent methodological issues and the recognition of alternative proposals and explanatory factors. This is noted in recognition of the potential contribution to policy formation and service provision.

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REFERENCES Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50, 179-121. Bandura, A. (1977). Selfefficacy: Toward a unifying theory of behavioral change. Psychological Review, 84, 191215. Bandura, A. (1990). Multidimensional Scales of Perceived Self-Efficacy. California: Stanford University Press. Bandura, A., Barbaranelli, C., Caprara, G., & Pastorelli, C. (2001). Self-efficacy beliefs as shapers of children's aspirations and career trajectories. Child Development, 72, 187-206. Bandura, A. & Schunk, D. (1981). Cultivating competence, self-efficacy, and intrinsic interest through proximal selfmotivation. Journal of Personality and Social Psychology, 41, 586–598. Berger, J., Motte, A. & Parkin, A. (2007). The Price of Knowledge 2006–07. Montreal: 90

The Canada Millennium Scholarship Foundation. Bong, M., & Clark, R. (1999). Comparison between selfconcept and self-efficacy in academic motivation research. Educational Psychologist, 34, 139–154. Bronfenbrenner, U. (1979). The Ecology of Human Development: Experiments by Nature and Design. Cambridge, MA: Harvard University. Byrne, D. (2009). Inclusion or Diversion in Higher Education in the Republic of Ireland? Dublin: ESRI. Byrne, D., McCoy, S. & Watson, D. (2009). School Leavers' Survey Report 2007. Dublin: ESRI and Department of Education and Science. Card, D. (1999). The causal effects of education on earnings. In O. Ashenfelter & D. Card (Eds.), Handbook of Labor Economics (pp. 1801–1863). London: North-Holland.

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Central Statistics Office (2007). 2006 Census Reports. Retrieved 3 December, 2009, from http://www.cso.ie/census/Census 2006.

Lerman, R. (1996). The impact of the changing US family structure on child poverty and income inequality. Economica, 63, 119-139.

Central Statistics Office (2008). Quarterly National Household Survey: Educational Attainment. Dublin: CSO.

Lynch, K. & O’Riordan, C. (1998). Inequality in higher education: A study of class barriers. British Journal of Sociology of Education, 14, 445478.

Dearden, L., Machin, S. & Reed, H. (1997). Intergenerational mobility in Britain. Economic Journal, 107, 47-66. Dubois, D. (2001). Family disadvantage, the self, and academic achievement. In B. Biddle (Ed.), Social Class, Poverty, and Education (pp. 133– 173). New York: RoutledgeFalmer. Higher Education Funding Council for England (HEFCE). (2005). Young Participation in Higher Education. Bristol: HEFCE. Jeynes, W. (2005). Effects of parental involvement and family structure on the academic achievement of adolescents. Marriage & Family Review, 37, 99-116.

Maras, P. (2007). “But no one in my family has been to University”. Aiming higher: School students’ attitudes to higher education. Australian Educational Researcher, 34, 1–90. Maras, P., Carmichael, K., Patel, S. & Wills, J. (2007). The trouble with Year 10: 13-16 year old school students’ attitudes to higher education. Social Psychology of Education, 10, 375397. McCoy, S., Byrne, D., O'Connell, P., Kelly, E. & Doherty, C. (2010). Hidden Disadvantage? A Study of the Low Participation in Higher Education by the Non Manual Group. Dublin: Higher Education Authority.

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McCoy, S., Kelly, E. & Watson, D. (2007). School Leavers' Survey Report 2006. Dublin: ESRI and Department of Education and Science. McCoy, S. & Smyth, E. (2003) Educational expenditure: Implications for equality. In T. Callan, A. Doris & D. McCoy (Eds.), Budget Perspectives 2004 (pp. 65–97). Dublin: ESRI and the Foundation for Fiscal Studies,. O’Connell, P., Clancy, D. & McCoy, S. (2006). Who Went to College in 2004: A National Survey of New Entrants to Higher Education. Dublin: Higher Education Authority. Organisation for Economic Cooperation and Development (OECD). 2008. Higher education to 2030, Volume 1: Demograph. Paris: OECD. Schunk, D. & Swartz, C. (1993). Goals and progress feedback: Effects on self-efficacy and writing achievement. Contemporary Educational Psychology, 18, 337-354. Shavit, Y., Gamoran, 92

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R. & (2007).

Stratification in Higher Education: A Comparative Study. California: Stanford University Press. Shavit., Y. & Blossfeld, H. (1993). Persistent Inequality: Changing Educational Attainment in Thirteen Countries. Boulder, CO: Westview Press. Snyder, T. & Dillow, S. (2007). Digest of Educational Statistics 2006. Washington, DC: National Center of Educational Statistics. Smyth, E. (2009). Buying your way into college? Private tuition and the transition to higher education in Ireland. Oxford Review of Education, 35, 1–22. Smyth, E. & Hannan, D. (2000) Education and inequality. In B. Nolan, P. O’Connell & C. Whelan (Eds.), Bust to boom? The Irish Experience of Growth and Inequality (pp.109-126). Dublin: Institute of Public Administration. Smyth, E. & Hannan, C. (2007). School processes and the transition to higher education, Oxford Review of Education, 33, 175-194.

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Sutton, S. (1998). Predicting and explaining intentions and behaviour: How well are we doing? Journal of Applied Social Psychology, 28,1317-1338. The Irish Times. The top feeder schools (2009, November 26). The Irish Times. Retrieved 25 December, 2009, from http://www.irishtimes.com

Zimmerman, B., Bandura, A. & Martinez-Pons, M. (1992). Selfmotivation for academic attainment: The role of selfefficacy beliefs and personal goal setting. American Educational Research Journal, 29, 663â&#x20AC;&#x201C;676.

Wolfe, B. & Haveman, R. (2002) Social and Non-market benefits from Education in an Advanced Economy. Boston: Federal Reserve Bank.

REVIEW SECTION The important thing in science is not so much to obtain new facts as to discover new ways of thinking about them. - William Bragg

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HARNESSING THE BRAIN’S CAPACITY FOR PLASTICITY Siobhán Harty Senior Sophister, Psychology sharty@tcd.ie ABSTRACT Modern investigations in the field of neuroscience have revealed that, contrary to long held beliefs, the brain has a remarkable capacity to adapt its structure and function throughout the life span. These adaptations are mediated by experience induced changes in the synaptic strength of neural connections, a process referred to as neuroplasticity. This review presents evidence of how knowledge of the brain’s plastic property can be applied to ameliorate deficits resulting from acquired brain damage and neurodevelopmental disorders, as well as to counter the neural degeneration associated with normal ageing. A vast number of promoting and constraining factors can modulate the extent and efficiency of neuroplasticity. This review examines the current state of knowledge of three of these variables: the degree of damage, the timing of interventions, and the attentional and motivational states of the individual. These variables are discussed in terms of how they can serve to facilitate or inhibit neuroplasticity. Furthermore, it is described how a detailed understanding of the neural mechanisms underlying the influence of these variables can be translated to clinical research and practice, and ultimately optimise functional outcome.

INTRODUCTION Until the end of the 20th century, the scientific community generally converged on the notion that the human brain was immutable, fixed by genes and early experience. It was believed that the brain was structured like a machine, with each region performing one specific function, in one specific location. If an individual was born with a neurological disorder, or acquired brain damage during life, there was little hope for any form of remediation. Modern investigations in the field of neuroscience however, 97

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have yielded, and continue to accumulate, compelling evidence that negates this dogma. It is now widely acknowledged that the brain is a dynamically changing organ, with an ability to adapt and reorganise its structure and function in response to internal and external pressures, long after early development (Horner & Gage, 2000). This phenomenal attribute is known as neuroplasticity. It is through this process of neuroplasticity that the young brain develops, encodes experiences, and learns new behaviours over the life span (Pascual-Leone et al., 2005). It is additionally through this capacity that the brain compensates, recovers and relearns in response to acquired brain damage, stroke or disease (Kolb & Whishaw, 1989; Robertson & Murre, 1999). While there are many long established rehabilitation strategies that have proven to enhance daily functioning at a behavioural and social level, and are thus deemed clinically valid, this newly emerging knowledge of the brain’s plasticity, in conjunction with advances in neuroimaging techniques, has proffered reason to critically appraise many of these treatment approaches. It is now apparent that although many techniques may appear effective, analysis at neural level can reveal that some of them may not be as beneficial as hitherto believed. Some may actually even compromise restitution (Kapur, 1996; Robertson & North, 1994). The aim of this review is to illustrate how contemporary knowledge of the brain’s malleability and a detailed understanding of the underlying processes can be used to promote adaptive plasticity and revolutionise how neuropsychological disorders are treated.

PRINCIPLES OF NEUROPLASTICITY Learning is a critical component of brain adaptation, in both the intact and damaged brain. As first postulated by Hebb (1949), and since espoused by several others (e.g., Caporale & Dan, 2008; Rose, 1991), for every new learning event, there is a concomitant change in the strength of connections between neurons to support the learning. This change in synaptic strength is dependent on the rapid firing of a neuron that triggers the firing of a connected neuron. Repeated firing of this nature results in a reduction in the required ‘threshold,’ such that from then on, the second neuron fires more readily in reaction to the first neuron. This process is referred to as long-term potentiation (LTP), or long-term depression (LTD), when the connection is inhibitory. It is widely accepted that LTP 98

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is the fundamental basis of human learning (e.g., Bi & Poo, 2001; Rose, 1991). It is additionally advanced that this form of Hebbian learning is central to the reorganisation that mediates functional recovery in the damaged brain (Kolb & Whishaw, 1989; Robertson & Murre, 1999). Thus, neuroplasticity is powered by learning, which is dependent on repeated sensory, behavioural, and cognitive experiences. A substantial literature presents evidence that differential experience can induce cerebral changes. Pascual-Leone et al. (1995) examined the cortical area representing motor movement of the hand over a period of 5 days, while participants learned a finger movement exercise on the piano. Transcranial magnetic stimulation (TMS) mapping revealed that as participants improved at the task, the magnitude of the cortical motor representation of the hand enlarged. This pioneering study demonstrates how repeated physical motor sequences result in a behavioural improvement of performance, which is concurrent with an expansion in the amount of cortical space representing the motor commands (Roche & Commins, 2009). Furthermore, it has also been discovered that the human adult hippocampus and olfactory bulbs are capable of neurogenesis, the production of new neurons (Eriksson et al., 1999; Gage, 2000). Interestingly, this process also appears to be experience-dependent; it has been found that physical exercise and enriched environments enhance hippocampal cell genesis (Gage, 2000; Gould et al., 1999). These findings serve to elucidate that the brain is not ‘hard-wired,’ but rather, amenable to reorganisation, and even regeneration, well beyond early childhood. On a comparable note, failure to engage a specific neural region or network, can lead to cell atrophy and a reduction in the associated cortical representation. This robust finding has been popularised with the adage ‘use it or lose it.’ Hubel and Wiesel (1965) demonstrated that depriving a kitten of light resulted in a reduction of neuronal responses to light in the visual cortex. This finding has since been extended to humans, whereby functional imaging evidence has illustrated that sensory deprivation causes the cortical area representing the deprived sensory input to shrink in the visual (Kourtzi & DiCarlo, 2006), auditory (Merzenich and Sameshima, 1993), and motor cortices (Giraux, Sirigu, Schneider & Dubernard, 2001). Kelly, Foxe, and Garavan (2006) assert that there are differences 99

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between the mechanisms through which plastic changes arise in sensory and motor regions, and those that occur within the frontal ‘higher-order’ circuitry. They explain that because higher-order cognitive functions recruit more distributed networks, the activation patterns are much more diffused, and therefore training effects are less specific. Despite the differences, this concept of use-dependent plasticity appears to be comparably pertinent to these higher-level functions. For instance, in the case of normal ageing, which is generally associated with widespread synaptic and neuronal atrophy, and consequent cognitive decline (Burns & Zaudig, 2002), there is compelling evidence to suggest that frequent participation in cognitively stimulating activities (e.g. reading or solving puzzles) is associated with preserved cognitive functioning (Shimamura et al., 1995) and a reduced risk of Alzheimer’s disease (Wilson et al., 2002). Even more convincing evidence for this plasticity in cognitive functions has been presented by Basak et al. (2008), who trained elderly participants (average age 69) with limited prior exposure to videogames, at a strategy-based videogame (Rise of Nations, Gold Edition). They reported that the participants improved at game performance over time, proving that the capacity to learn a new skill persists into late life. But even more impressive, they found that skills developed by playing the game, also transferred to other executive functions. Specifically, they noted significant improvements at task-switching, mental rotation, visual short-term memory and working memory. Additional benefits, albeit more limited, were seen in inhibition and reasoning skills. This demonstrates that plasticity is also a characteristic of executive functions, and further corroborates the evidence that this extends beyond early childhood, across adulthood, and into old age.

PLASTICITY TO PRACTICE This knowledge of the brain’s use-dependent plasticity has proved very valuable for treating individuals with neuropsychological disorders. For instance, Limb Activation Training (LAT) (Robertson et al., 2002), is a treatment for unilateral neglect patients directed at promoting neural reconnections and recovery by having the patients make small movements of the affected side of the body. The somatosensory spatial cortical map is activated by the use of the limbs. This map also has connections with the peripersonal spatial map affected in neglect, thus these limb movements 100

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additionally indirectly stimulate the damaged brain tissue, and promote the re-establishment of connections (O’Connell & Robertson, in press). A randomised controlled study of this treatment has found that the effects of LAT were still evident up to 18-24 months after the training had ceased (Robertson et al., 2002). The concept of use-dependent plasticity is also the theoretical basis of several Cognitive Remediation Training (CRT) programs (O’Connell & Robertson, in press). To date, there has been hesitance to forthrightly profess the efficacy of CRT with respect to rehabilitating executive deficits following acquired brain damage, but its effectiveness with respect to alleviating the symptoms of neurodevelopmental disorders has proved very promising (O’Connell & Robertson, in press). To offer one example, Klingberg et al. (2005) conducted a randomised controlled clinical study to test whether Cogmed, a form of CRT, could help improve working memory performance in children with ADHD. Following 20 days of training, Klingberg and colleagues found that training working memory using Cogmed enhanced the childrens’ performance on untrained tasks tailored to assess working memory, as well as on tasks assessing complex reasoning and response inhibition. These benefits were still evident 3 months later. The generalised improvements were further distinguishable based on parent’s ratings of their children’s ADHD symptoms. These findings illuminate how knowledge of the brain’s ability to reorganise at a cellular level has laid the foundations for developing treatments that reap gains in clinical settings. And even more important, these gains are generalisable, ultimately enhancing the daily functioning of individuals with neuropsychological disorders.

PLASTICITY CAN BE MALADAPTIVE Roche and Commins (2009) emphasise the optimistic outlook that this knowledge of the brain’s plasticity imparts. They posit that these findings imply that, through repeated engagement in a physical or mental activity, intact brain tissue is capable of establishing, and re-establishing circuits through the growth of neuronal connections, even following serious damage and cell atrophy. Based on the above evidence, their optimism is well founded. However, there are several reports of how this malleability can be a negative attribute. In short, examples include cases where experience-induced plasticity actually exaggerates deficits (Kapur, 1996); 101

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the plasticity mediating addiction (Everitt & Wolf, 2002); the maladaptive plasticity that underlies neurological conditions such as phantom limbs and focal dystonia (Ramachandran & Hirstein, 1998; Tamura et al., 2009); aberrant plasticity has also been identified as being critically involved in Alzheimerâ&#x20AC;&#x2122;s disease (Arendt, 2001); and a final example, neural plasticity is also deemed accountable for delaying the appearance of symptoms of Parkinsonâ&#x20AC;&#x2122;s disease, rendering early detection and preventing progression very difficult (Bezard, 2003).

GUIDING ADAPTIVE PLASTICITY The extent to which adaptive plasticity and restitution can occur through experience and training is contingent on a constellation of factors. Some of these include: age and IQ levels (Robertson & Murre, 1999); nutrition (Robinson, Ijioma & Harris, 2010); the specificity and intensity of training (Nudo, 2003; Pascual-Leone et al., 1995); stress levels (McEwan, 1999); pharmacological agents (Kirkwood at al., 1999); and the natural biochemical environs of the brain, particularly, levels of neurotransmitters such as glutamate, acetylcholine and noradrenaline (Benarroch, 2010). Space does not permit a review of all the modulatory factors, so this section proceeds with a focus on three: the size of the lesion and the degree of connectivity loss (Robertson & Murre, 1999); the timing of interventions (Biernaskie, Chernenko, & Corbett, 2004; Nudo, Wise, SiFuentes, & Milleken, 1996); and the Patientâ&#x20AC;&#x2122;s attentional and motivational states (Robertson et al., 1997; Stefan, Wycislo & Classen, 2004). Size matters Robertson and Murre (1999) propose a theoretical triage that categorises the potential for recovery, and the nature by which it will occur, according to the severity of brain damage. Individuals with small lesions and a limited loss of neural connections can be expected to self-repair, through the aforementioned Hebbian learning principles. In contrast, individuals with severe brain damage and a profound loss of connectivity are unlikely to initiate autonomous repair and are even unlikely to benefit from extensive attempts at retraining and restitution. For these individuals compensation is a favourable option. Compensation may vary widely in nature, from encouraging different brain tissue to achieve the same 102

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behavioural ends by alternate means (Thomas, 2003), to restructuring the individualâ&#x20AC;&#x2122;s environment to mitigate the extent to which their deficits interfere with their daily lives (Robertson, 1999). Between these two levels of severity, there is an intermediate group, who have moderate brain damage, but partially preserved functioning. This group has the potential to regain a substantial degree of normal functioning, but only through guided recovery strategies that are specifically tailored to induce the coactivation of disconnected neurons, and thus stimulate Hebbian-based reconnections. As Robertson and Murre (1999) note, the brain has a propensity to self-repair. It is thus important that a clinician is cognisant that a brain which they may be attempting to reorganise with rehabilitative training, is likely to have already been driven to adapt by compensatory behavioural strategies (Adkins, Voorhies & Jones, 2004). For example, Adkins et al. (2004) describe how, subsequent to unilateral cerebral damage, reliance on the functional side of the body for daily life demands, gives rise to considerable neuronal growth and restructuring in the undamaged hemisphere. These self-initiated strategies can limit the tendency to engage in behaviours that improve mobility in the affected side of the body (Mark & Taub, 2004), which consequently inhibits restitution at the cellular level. Such knowledge has been harnessed to form the theoretical basis of the rehabilitative approach, Constraint Induced Movement Therapy (CIMT) (Taub & Wolf, 1997). This therapy combines rehabilitative training with the constraint of the ispsilateral limbs in individuals who have suffered unilateral strokes. This improves the function and movement of the affected limbs and fosters greater associated activation in the residual regions of the injured hemisphere. Time matters The timing of interventions is a major determinant of the efficacy of rehabilitative strategies such as CIMT. CIMT aims to prevent or reverse the process, termed â&#x20AC;&#x2DC;learned non-use,â&#x20AC;&#x2122; but the longer the patient has had the chance to persist with the bad habit of non-use, the more difficult it is to retrain the brain (Mark & Taub, 2004). In line with this, Biernaskie et al. (2004) reported that rehabilitation over a 5-week period, initiated 30 days after focal ischaemia in rats was far less effective at enhancing functional outcome and promoting the growth of cortical dendrites, than 103

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the equivalent regimen initiated just 5 days post focal ischaemia. Nudo et al. (1996) have also described how lesions in squirrel monkeys can result in a further loss of synaptic connectivity over time, but found that this could be precluded by providing timely stimulation to the susceptible networks. Drawing on this evidence, it may be inferred that the longer a brain damaged individual experiences their dynamic environment without sustaining strategic rehabilitation, the greater the scope for aberrant plasticity and the acquisition of unfavourable compensatory behaviours. Or, as suggested by Roberston and Murre (1999), there may in fact be critical periods within which strategic interventions must be implemented to ensure the survival of adjoining regions. Thus early intervention seems favourable. However, Greisbach Gomez-Pinilla and Hovda (2004), report evidence of the contrary; an early intervention (which entailed voluntary wheel running), within the first 6 days after TBI in rats, reduced the prevalence of hippocampal plasticity-related molecules, whereas, exercise that was postponed until 2 weeks after the injury resulted in enhanced expression of these molecules, and also improved outcome in spatial memory tests. It has been suggested that the negative effects of these early interventions may be due to stimulation-induced neurotoxicity (Kozlowski, James, & Schallert, 1996). This evidence serves to refute the premise that early intervention is always optimal, but it is, nonetheless, consistent with the former studies on the notion there may be optimal time-windows. This again, exemplifies how increasing our knowledge of the plastic property of the brain has the potential to revolutionise treatment approaches, as it is evident that a comprehensive understanding of the neural processes underlying this time-dependent sensitivity may provide scientific justification for hastening or delaying attempts to remediate damage, and consequently improve the outcomes of interventions. Attention matters Recently, there has been a proliferation of research detailing how the adaptability of the brain can be conditional on levels of attention, arousal, and motivational states. Stefan et al. (2004) used a paired associative stimulation (PAS) protocol to demonstrate attentional modulation of plasticity. The PAS paradigm consisted of repeated application of low104

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frequency stimulation to the median nerve in the right hands of participants, paired with TMS over the contralateral motor cortex. This PAS induces neuroplasticity. Stefan and colleagues reported that the PAS-induced plasticity was greatest when the participants viewed their hand during stimulation, but interestingly, this plasticity was attenuated when they only felt their hand. Even more fascinating again, however, was that PAS-induced plasticity was completely suppressed when participants directed their attention towards the opposite hand, or when they were required to focus on a cognitive task. This demonstrates that neuroplasticity in the human motor cortex is decisively dependent on topdown input from attentional circuits (Stefan et al., 2004). Consistent with this, an earlier study by Robertson et al. (1997) ascertained that motor recovery subsequent to stroke, over a 2-year period, was predictable based on measures of sustained attention that were taken 2 months post right hemisphere stroke. Thus, just as active attention plays a critical role in learning and forming connections in the intact brain, it is equally imperative for recovery in the damaged brain. Such findings are immensely significant from a clinical perspective, especially considering that deficits in attention and goal directed behaviours, as well as the condition termed anosognosia, a lack of awareness of deficits, frequently manifest as TBI sequelae (McAvinue, Oâ&#x20AC;&#x2122;Keeffe, McMackin & Robertson, 2005; Moore, 1996). This research confers reasoning for preferentially targeting executive dysfunctions, as it is clear that they may interfere with the extent to which restitution can occur in non-cognitive domains (Oâ&#x20AC;&#x2122;Connell & Robertson, in press). If an individual is not aware of their deficit, they will not be motivated to direct attention to the task or intervention aimed at remediating the brain damage, and thus plastic reorganisation is unlikely to occur (Robertson & Murre, 1999). The above evidence also insinuates that it may be important to reconsider the duration of therapy sessions, as active attention often lapses within periods of seconds and minutes (Temple et al., 2000). Hence sessions that last the conventional 40 to 60 minutes may not be as beneficial as if the time was divided across a greater number of shorter sessions.

CONCLUSIONS The burgeoning knowledge of the brainâ&#x20AC;&#x2122;s adaptability reviewed above is of 105

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monumental significance. The evidence that lifelong learning and physical activity can foster preservation and regeneration has potentially enormous implications alone. If this is embraced and embedded into our culture, where quiescence and inertia are far too often simply accepted as corollaries of retirement and old age, we may witness a reduction, or at least a considerable delay, in the onset of cognitive senescence and dementia-related disorders. These disorders are currently draining, and look set to overwhelm, European economic and healthcare resources (Jonsson, & Wimo, 2009). With respect to how neuropsychological disorders are treated, it has been clearly demonstrated that the increasing application of information derived from cellular-level analysis to guide methods of rehabilitation has proved constructive, and can only possibly continue to be even more advantageous. Many long established rehabilitation approaches have been sorely lacking in theoretical reasoning (Robertson, 2005), failing to offer explanations of why methods were successful, and blind to how the training interacted with neural processes, with changes brought about by compensatory strategies, and with variables such as age, attention, the biochemical milieu, and other concurrent treatments. It is crucial to understand the interactions of these, as well as all other modulatory factors, as they evidently have pivotal influences on the nature and variability of recovery in patients. This review has also highlighted the importance of being aware of the time windows during which rehabilitation strategies can be safely and optimally implemented, and how long these interventions should endure. This can only be discerned by attaining a detailed understanding of how, why, when, and where plastic changes occur in the brain. The momentum with which we are currently gaining in this knowledge, and the increasing realisation of the importance of applying it to develop theories of recovery, in synchrony with ongoing advances in neuroimaging technology, heralds revolutionary improvements to the way neuropsychological disorders are treated.

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REFERENCES Adkins, D. L., Voorhies, A. C., Jones, T. A. (2004). Behavioral and neuroplastic effects of focal endothelin-1 induced sensorimotor cortex lesions. Neuroscience, 128(3), 473–486. Arendt, T. (2001). Alzheimer’s disease as a disorder of mechanism underlying structural brain selforganization. Neuroscience, 102(4), 723–765. Basak, C., Boot, W. R., Voss, M. W., & Kramer, A. F. (2008). Can training in a real-time strategy videogame attenuate cognitive decline in adults? Psychology and Aging, 23(4), 765–777. Benarroch, R. (2010). Glutamate transporters: Diversity, function, and involvement in neurologic disease. Neurology, 74(3), 259-264. Bezard, M. (2003). Presymptomatic compensation in Parkinson's disease is not dopamine-mediated. Trends in Neuroscience, 26(4), 215-21. Biernaskie, J., & Corbett, D. (2001). Enriched rehabilitative

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Klingberg, T., Fernell, E., Olesen, P. J., Johnson, M., Gustafsson, P., Dahlstrom, K., Gillberg, C.G., Forssberg, H., & Westerberg, H. (2005). Computerized training of working memory in children with ADHD - a randomized, controlled trial. Journal of the American Academy of Child and Adolescent Psychiatry, 44(2), 177. Kolb, B., & Whishaw, I. Q. (1989). Plasticity in the neocortex: mechanisms underlying recovery from early brain damage. Progress in Neurobiology, 32(4). 235–276. Kourtzi, Z., & DiCarlo, J. J. (2006). Learning and neural plasticity in visual object recognition. Current Opinion in Neurobiology, 16(2), 152-158. Kozlowski, D. A., James, D. C., & Schallert, T. (1996). Usedependent exaggeration of neuronal injury after unilateral sensorimotor cortex lesions. Journal of Neuroscience, 16(15). 4776–4786. Kwakkel, G., Kollen, B.J., & Lindeman E. (2004). Understanding the pattern of

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WHAT CAN PSYCHOANALYSIS TELL US ABOUT DEPRESSION? Sheila Armstrong Senior Sophister, Psychology and English armstrse@tcd.ie

ABSTRACT Early psychoanalytic investigations of depression in Civilisation and its Discontents (Freud, 1929) and in much of the work of Karl Abraham offer a framework for understanding depression which may be applicable to modern model of the disease. The emphases on modern living and interpersonal relationships are especially fruitful. The current paper details psychoanalytic approaches to depression and reviews how they may be applicable to current understanding and treatments of the causes and symptoms of depression.

INTRODUCTION What is the meaning of life? The all-encompassing and perhaps melodramatic question has been the subject of universal debate from mankind’s beginnings. Freud, in Civilization and its Discontents (1929), argues that the question itself is context-dependant. In his view, religion is the only institution that attempts to account for a meaning behind everyday life. Freud asks, instead, what it is that mankind actually wants, and the answer appears to be simple – happiness. It seems, therefore, more appropriate to ask where happiness comes from. In psychoanalytic work, the mechanism that dominates the mental apparatus and is the source of all happiness is the pleasure principle. Says Freud, “[what] we call happiness in the strictest sense comes from the (preferably sudden) satisfaction of needs which have been dammed up to a high degree” (1929, p. 264). However, in our modern society, depression rates are rising. According to the World Health Organisation, depression affects about 121 million people globally and is among the leading causes of disability worldwide (WHO, 2010). The search for happiness, clearly, is not proving to be fruitful. 113

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Psychoanalytic theory of melancholia, referred to nowadays as depression, began mainly with the work of Karl Abraham and Sigmund Freud in the early 1900’s. The seminal work in this area was Freud’s Mourning and Melancholia, published in 1917, in which he draws on clinical experience in order to explain the state of melancholia. He draws parallels between this and the natural state of mourning, and uses this comparison to explore the psychic mechanisms of depression. Abraham (1927) also looks at the melancholic condition and details some factors necessary for its psychogenesis. Since its beginnings in the work of these early theorists, psychoanalytic models of depression have been expanded and refined to offer insights into the cause, symptoms and treatment of depression.

CAUSES Freudian theory offers two possible explanations for the apparent general unhappiness of the global population: the surplus of pleasure in our society, and the state of civilization itself. The first of these – the surplus of pleasure – is again linked to the pleasure principle, and the possibility of over-exposure, meaning that “[when] any situation that is desired by the pleasure principle is prolonged, it only produces a feeling of mild contentment” (Freud, 1929, p. 264). In a developed Western society such as ours, for the majority of people, every need or desire can be satisfied with minimal effort. As Goethe tells us - and Freud quotes - “nothing is harder to bear than a succession of fair days”. Modern life has become a succession of “fair days”, with standards of living rising in Western countries along with rates of depression. According to the WHO’s 2004 report on the Global Burden of Disease, “depression makes a large contribution to the burden of disease, being at … eighth place in lowincome countries, but at first place in middle- and high-income countries” (WHO, p.5). Freud’s concept of overexposure, based on the pleasure principle, can offer one explanation for the prevalence of depression in developed countries. According to this theory, pleasure is, on one hand, omnipresent, and on the other, unattainable, as we have become almost deadened to the experience. Freud’s second explanation for the universal feeling of malaise involves looking at society itself and its effect on the individual. In Civilization and its Discontents (1929), he states that there are three 114

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sources of suffering for a human being. The first is the suffering that is inflicted by the body itself, which is inevitably subject to disease and aging and is prone to feelings of pain and anxiety. The second is the suffering provided by the natural world and external influences. And the third, and most painful, is the hurt that comes from relationships with other human beings. The first two of these sources, in Freud’s opinion, are unchangeable and must be accepted. However, the hurt caused by social relationships, he argues, comes about as a result of the state of civilization. He believes that civilization places restrictions on our basic instincts. This is related to Freud’s three part construction of the unconscious: the id, which is comprised of our basic and most primal desires; the ego, which controls the desires of the id and translates them into behaviours that are expressible in the real world; and finally, the superego, which internalizes the moral and cultural rules of the society we live in. With the development of the superego, and the cultural norms that we are forced to follow, we are not free to satisfy the primal drives of the id, as we have accepted the rules of society as binding, and to go against them is to risk expulsion from this society. Primal pleasure has been exchanged for the security and stability that living in a civilized society offers us. In a way, it is as if satisfying the id would be to fight for a large slice of a small cake, while obeying the superego offers us a smaller slice of a larger cake. Being a part of a society ensures that our needs can be satisfied on a regular basis. In response to this acceptance of the rules of civilization, some psychoanalysts see depression as a form of protest against society, a way of saying “no” to what we are meant to be (Leader, 2009). Taking civilization as the cause of a universal feeling of discontent, it is not surprising that, in our modern society, in which individuals depend largely on social relationships and a sense of community, depression has become more and more prevalent. Although these theories offer an explanation for depression in the general population, Freud and Abraham also suggest some theories for the psychogenesis of depression in a specific individual. Freud (1917) notes the similarities between the states of mourning and melancholia. He describes mourning as a response to an actual loss of a love-object, such as a person, or even an ideal. On the other hand, in melancholia, the patient cannot consciously grasp what he or she has lost, or else knows what it is, but not 115

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what it is about the object that they have lost. Abraham (1927) also offers some possible causes for depression, based on his clinical work. He sets out four factors that are necessary for the psychogenesis of depression. The first is linked to the five stages of psychosexual development, which are oral, anal, phallic, latency and finally, genital. A child must successfully pass through each of these stages in order to become a psychologically healthy adult, while fixation at any stage can persist into later life and result in adult neurosis. Abraham believed that the melancholic patient is fixated on the oral stage, and thus overemphasises oral eroticism in later life. Secondly, the patient will also have experienced early and repeated childhood disappointments in love. Thirdly, the first of these disappointments is likely to have occurred before the Oedipal wishes – wherein the id of the child desires to do away with the father and reunite with the mother, but is constrained from doing so by the realism of the ego – have been resolved. Finally, a repetition of this primary disappointment in love is also likely to have occurred later in the life of a melancholic patient. These early psychoanalytic concepts draw on the clinical work of both Freud and Abraham in order to attempt to find exactly what causes melancholia. These theories work on both a societal and individual level and offer some explanations for the prevalence and causation of depression.

SYMPTOMS The symptoms of depression are well known and are often found to varying degrees in everyday life, but the pathological state has been defined diagnostically, originally by Freud and in modern times by the DSM. Freud, in Mourning and Melancholia (1917) describes the state of depression as “mentally characterized by a profoundly painful depression, a loss of interest in the outside world, the loss of the ability to love, the inhibition of any kind of performance and a reduction in the sense of self, expressed in self-recrimination and self-directed insults, intensifying into the delusory expectation of punishment” (p. 204). The modern diagnostic criteria for depression (as detailed in the DSM) draws on similar elements and describes the symptoms as follows: sadness, loss of interest in the outside world, under or over-eating, under or over-sleeping, loss of energy, feelings of worthlessness, and recurrent thoughts of death (APA, 2000). 116

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Taking a psychoanalytic approach to some of these symptoms can offer an insight into their causation. As has been noted, Freud believes that mourning and melancholia are both a response to a loss, whether it is a conscious or unconscious one. The apathy found in both states is due to the exclusive devotion to mourning that leaves no room for interest in the outside world. Both of these conditions result in inhibition and loss of interest, as the ego is absorbed in the work of mourning. This absorption of the ego also accounts for the sleeplessness commonly associated with depression, which is due to “the impossibility of effecting the general drawing-in of cathexes necessary for sleep … It can easily prove resistant to the ego’s wish to sleep” (Freud, 1917, p. 205). The most distinguishing symptom of melancholia is the loss of selfesteem that is characteristic of depressive moods. The mechanism behind this loss of self-esteem is explored in depth by Freud. In the course of normal life, an individual’s unconscious makes a choice of love-object, and a bond is formed between the individual’s libido and this object. If something should occur between the two, such as a slight or disappointment, this bond is subject to a shock. In a normal, nonmelancholic state, this shock would result in the withdrawal of the libido from the love-object and its transference to a new object. However, in the pathological state of depression, this extension of the libido is instead drawn back into the ego. This results in the identification of the ego with the hated and abandoned object. Thus, the ego, in seeing itself as comparable to the hated object, begins to equally revile itself, resulting in the self-reproach that is commonly observed. In this manner, Freud argues, all self-reproaches felt by the melancholic patient are, in fact, accusations against a love-object that have been transferred onto the patient’s own ego. Every negative feeling the patient feels towards themselves was originally aimed at another person. If this was not the case, the patient, who claims to feel unworthy and inferior, would undoubtedly act in a humble and submissive manner to those around them, which has consistently not been observed. Abraham (1923) argues for the emphasising of the sadistic element of melancholia as being the source of self-reproach. He, like Freud, believes that the depressive state comes from repressed hostile feelings towards the love-object. The subject constantly attempts to gain possession of the 117

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love-object, and is hypersensitive to its every slight. The subject then believes whole-heartedly in his or her own omnipotence, in that they have caused pain and suffering to their love object. As a result, the subject allows him or herself to be tormented by this love-object. According to Abraham, it is this process that is at the heart of melancholic selfpunishment. The feeling of being the worst person in the world, therefore, comes from two sources – the melancholic’s identification with the hated love-object, and the inner perception of being a source of great suffering to this love-object (Perelberg, 2005). Mourning and Melancholia emphasises the oral fixations of the melancholic, who has regressed to this stage of libidinal development. Regarding the love-object, the “ego wants to incorporate this object into itself, and, in accordance with the oral or cannibalistic phase of libidinal development in which it is, it wants to do so by devouring it” (1917, p. 249). Freud links this cannibalistic tendency of the ego to the rejection of food that so often accompanies melancholia. Abraham (1916) also supports this interpretation of this symptom. He believed that the patient refuses food as he or she is attempting to refrain from carrying out repressed impulses of symbolic cannibalism. The strangest and most interesting characteristic of melancholia is, for Freud, the suicidal tendencies that often accompany it. This appears to be in opposition to the strongest drive present in all living creatures: the drive towards pleasure, and, in effect, towards life itself. It is the self-love of the ego that creates in us the overwhelming drive to live, and it is the primal state from which instinctual life proceeds. In order to explain this, Freud explores the possibility of a second set of instincts that are in constant opposition to the libido. The initial dichotomy between the id and the ego was unable to account for some of his clinical experiences, such as patients with melancholia and post-war soldiers who constantly related their unpleasant experiences both while awake and in their dreams. Freud was puzzled by this apparent opposition to the pleasure principle, and was driven to reflect on the mysterious masochistic trends of the ego (Freud, 1920). He then proposed a “death instinct”, also known as Thanatos, suggesting that all instincts strive to return to the restoration of an earlier stage, that is, death. In his view, sadism is a death instinct that has been turned on the subject’s own ego.

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It is through the ego’s sadism that the suicidal urges characteristic of depression occur, the “indubitably pleasurable self-torment of melancholia” (Freud, 1917, p.211). Only by recognising the displacement of any negativity towards the love-object onto the patient’s own ego, and the sadism involved in this, can we understand how the ego could possibly overcome the most primal of drives and seek to kill itself.

TREATMENT Treatment for depression in psychoanalytic work was initially of a pessimistic nature and involved making the patient aware of his or her repressed impulses (Mendelson, 1974). Abraham (1924) believed that treatment should alleviate symptoms, but also protect against other attacks by getting rid of the patient’s regressive libidinal urges. However, Jacobson (1954) states that for some patients, it is not possible to carry the analysis to the point where their pre-Oedipal fantasies and impulses can be produced and interpreted. She believes that patients will inevitably undergo the phenomenon of transference, wherein the feelings and desires that were directed onto one person will inevitably be transferred to another. In this way, she believes that the depressed patient will make the therapist their central love-object and the focus of their pathological demands. Therapy for melancholic patients is understandably demanding. Fenichal (1945) summarized the difficulties that must be overcome in the therapeutic treatment of depression. The first is the oral fixation of the patient, which must be analysed through crucial infantile experiences. The second is the ambivalence of the transference of unconscious feelings to the therapist. The third is the inaccessibility, both emotional and communicative, of the depressed patient. Traditional psychoanalytic therapy for depression was an extended process which looked to reveal unconscious emotional material using free association techniques. The focus nowadays is on emotional catharsis in the context of a stable, long-term, and well defined patient/therapist relationship (Mays & Croake, 1997). However, if a treatment’s value is to be assessed in terms of its clinical use, then psychoanalytic therapy for depression must be found to be lacking, as its use as a stand-alone treatment is no longer common (DePaulo & Horvitz, 2002). 119

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CONCLUSIONS Psychoanalytic theory can offer some insights into the causes, symptoms and treatment of depression. However, there are some gaps in the literature that remain to be filled. Mendelson (1974), for example, notes that more modern literature largely ignores the treatment of depression by psychopharmalogical means. Psychoanalytic treatment overlooks the effectiveness of medication, which, although not a solution in itself, does raise some theoretical issues regarding the psychogenesis and symptomatology of depression. Another possible critique of the psychoanalytic treatment of melancholia is the oversimplification of its causes. Depression that has no apparent motivation is becoming more and more common and it is not plausible that each and every one of these sufferers has been subject to a loss or slight from their love-object. However, the rising numbers of sufferers could be attributed to the state of our modern society rather than to a specific object-loss. On the whole, psychoanalytic theory can offer at least some valuable insights into the causation, symptomatology and treatment of depression, but its use should not be relied upon to the exclusion of other methods of investigation.

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REFERENCES American Psychiatric Association. (2000). Diagnostic and statistical manual of mental disorders: DSM-IV-TR. Washington, DC: Author.

DePaulo, J. R., Horvitz, L. A. (2002). Understanding depression: what we know and what you can do about it. NY: John Wiley & Sons

Abraham, K. (1916). The first pregenital stage of the libido. In Douglas Bryan and Alix Strachey (Trans.), Selected Papers of Karl Abraham M.D. (248-279). London: Hogarth.

Fenichal O. (1945) The Psychoanalytic Theory of Neuroses. New York: WW Norton.

Abraham, K. (1923). Letter from Karl Abraham to Sigmund Freud, October 7, 1923. The Complete Correspondence of Sigmund Freud and Karl Abraham 1907-1925, 471-473. London: Karnac Books. Abraham, K. (1927). Melancholia and obsessional neurosis. In Douglas Bryan and Alix Strachey (Trans.), Selected Papers of Karl Abraham M.D. (422-432). London: Hogarth. Abraham, K. (1924/1994). A short study of the development of the libido. In Frankiel, R.V. (Ed.), Essential Papers on Object Loss. New York: New York University Press.

Freud, S. (1917/2001). Mourning and Melancholia. In James Strachey (Trans.), The Standard Edition of the Complete Psychological Works of Sigmund Freud, Volume XIV (19141916). London: Vintage. Freud, S. (1920/2001) Beyond the Pleasure Principle. In James Strachey (Trans.), The Standard Edition of the Complete Psychological Works of Sigmund Freud, Volume XVIII (19201922). London: Vintage. Freud, S. (1929/2001). Civilization and its Discontents. In James Strachey (Trans.), The Standard edition of the Complete Psychological Works of Sigmund Freud, Volume XXI (19271931). London: Vintage.

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Jacobson, E. (1954). Transference problems in the psychoanalytic treatment of severe depressive patients. Journal of the American Psychoanalytic Association, 2, 595-620. Leader, D. (2009).The New Black: Mourning, Melancholia and Depression. Minneapolis: Graywolf Press. Mays, M. Croake, J. W. (1997). Treatment of Depression in Managed Care. New York: Routledge. Mendelson, M. (1974). Psychoanalytic Concepts of Depression. New York: Spectrum Publishers.

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Perelburg, R. J. (2005). Freud: A modern reader. London: Karnac Books. Verhaeghe, P. (2008). On being normal and other disorders: a manual for clinical psychodiagnostics. London: Karnac Books. World Health Organisation. (2010). Depression. Retrieved from http://www.who.int/mental _health/management/depression/ definition/en/ on 4th April 2010. World Health Organization. (2004). The global burden of disease: 2004 update. Retrieved from http://www.who.int/health info/global_burden_disease/2004 _report_update/en/index.html on 17th November 2010.

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GENE-ENVIRONMENT INTERACTIONS IN DETERMINING CRIMINALITY Laura Mangan Senior Sophister, Psychology manganla@tcd.ie

ABSTRACT The determination of criminality is multifactorial as it involves the interaction of several different factors including individual, familial and social factors. Correlations between antisocial behaviour and impairment of the prefrontal cortices have been found (Eastman & Campbell, 2006). Socioeconomic deprivation has a strong link with subsequent criminality (Ferguson, Swain-Campbell & Horwood, 2004), as those from low SES backgrounds are three times more likely to engage in antisocial behaviour than individuals from high SES backgrounds. In contrast, both the Social Causation Perspective and Control Theories place the burden of criminal determination firmly on peer relations. Familial factors also have an important role in shaping whether an individual engages in criminal activity as they have the potential to exacerbate or moderate criminality in the developing child (Ferguson et al., 2004). In sum, neither genetic nor environmental factors alone are sufficient in explaining the determination of criminality. They must be combined in order to establish any causal relationship.

INTRODUCTION Among the most important factors in predicting criminal convictions are socioeconomic deprivation, poor parenting and an antisocial family (Farrington, 1990). These factors are necessary but not sufficient alone; the emergence of the antisocial behavioural phenotype necessarily must occur as a result of interactions between an individualâ&#x20AC;&#x;s genetic make-up and their environment (Beaver & Holtfreter, 2009). Genetic and environmental factors work separately and in tandem to create criminal behaviour phenotypes (Moffitt, 2005; Rutter, 2006), for example, if a child 123

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has both conduct disorder and hyperactivity then he is more likely to engage in antisocial behaviours (Farrington, 1990). Antisocial conduct itself has a moderate to strong association with genetic factors (Rhee & Waldmen, 2002). The importance of delinquent peer association is as such that it is not only a predictor of antisocial conduct but it is also linked with fraudulent behaviours (Beaver & Holtfreter, 2009). Children who suffer abuse or neglect are more likely to have Antisocial Personality Disorder (ASPD) as adults and are more likely to be arrested in adolescence (Wisdom, 1989). From these examples it is clear that criminality should be approached from a multifactorial perspective. The current essay endeavours to discuss the determinants of criminality from an individual, familial and societal level. Firstly, the individual‟s influence over his/her own criminality will be discussed. Personality disorder and genetic factors mediate an individual‟s entry into criminality. Secondly, familial influence is an important determinant of criminality. Factors such as maternal deprivation, parenting and attachment relationship are prominent determinants in the literature. Finally, socioeconomic status (SES) and peer influence are important societal determinants that contribute to the individual‟s level of criminal involvement.

ADOLESCENT AND ADULT OFFENDING: BIOSOCIAL MODELS According to Moffitt‟s developmental taxonomy (MDT) there are two types of offenders; life-course persistent (LCP) and adolescent-limited offenders (AL) (Moffitt, 1993). Delinquent involvement is quite common amongst adolescents and it is considered to be age normative (Farrington, 1986). Most adolescents engage in delinquency and only a very small percentage of adolescents abstain from delinquent involvement (Moffitt, 1993). Thus it could be assumed that delinquency in adolescence is not just a form of antisocial behaviour but somewhat of a rite of passage. Even if delinquency is a natural progression, only the minority of delinquents persist with their misconduct throughout the lifespan whereas the majority of delinquent adolescents „grow out of it‟ (Boutwell & Beaver, 2008). LCP offenders account for approximately 6% of the population but they account for a huge proportion of all crimes committed (Moffitt et al., 2002). For example, in America LCP offenders account for 50% of all crimes committed (Eme, 2010). Misconduct in these offenders 124

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emerges in early childhood and it remains stable throughout the lifespan (Moffitt et al., 2006). LCP offending has a causal relationship with two interlocking factors; neuropsychological deficits and adverse home life. In order for LCP offending to develop it is necessary to have neuropsychological deficits but if an individual has neuropsychological deficits this does not mean he must be an LCP offender (Boutwell & Beaver, 2008). Secondly, LCP offending is causally linked with an adverse home life. A criminogenic family and neuropsychological deficits work in tandem with each other and are conducive for chronic antisocial conduct. Thus the cause of LCP offending is biosocial. Biogenic risk factors (e.g. neuropsychological deficits) coupled with environmental risk factors (e.g. criminogenic family) creates LCP offenders (Boutwell & Beaver, 2008). AL offenders constitute the vast majority of delinquent offenders. They confine their criminal involvement to adolescence; they tend not to display antisocial behaviour in childhood and they do not offend as adults (Boutwell & Beaver, 2008). According to Moffitt (1993, 2006) the „maturity gap‟ is the main cause of AL offending. It occurs when the adolescent is biologically mature (i.e. physically, they resemble adults), but they are not permitted to engage in adult behaviours. Adolescents aim to reduce the disjuncture of the „maturity gap‟ by mimicking adult behaviours. These behaviours include consuming alcohol, smoking, having sex and they are expressed in order to portray social maturity. With age comes the privileges associated with adulthood and thus the maturity gap diminishes as does delinquent behaviour along with it (Moffitt, 2006). The cause of AL offending is biosocial because there is an interaction between biological (i.e. puberty onset) and social factors (i.e. restraints imposed by society) (Boutwell & Beaver, 2008).

NEURAL AND PERSONALITY FACTORS According to Eastman and Campbell (2006) there is a correlation between antisocial behaviour and impairment of the prefrontal cortices (PFC). Deception, for example, is linked with activation of the PFC and the anterior cingulate cortices. The PFC has a pivotal role in the regulation of behaviour. Frontal lobe damage in infancy results in impairments in decision-making and social and emotional regulation (Anderson, Damasio, Tranel & Damasio, 2001). PFC deficits are also greatly involved in the development of disruptive behavioural disorders such as hyperactivity, 125

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executive functioning and response inhibition deficits (Schachar & Logan, 1990). Specifically, lesions to the ventromedial PFC may result in impaired ability to adhere to social norms and attitudes (Moll et al., 2005). The social norms and attitudes affected by PFC impairment are directly linked to the laws that criminals tend to violate (Knabb, Welsh, Zieball & Reimer, 2009). Impairment in the limbic or paralimbic regions will affect moral behaviour. For example, rage, a lack of empathy or abnormal sexual behaviours will occur as a result of this type of impairment (Moll et al, 2005). Hence limbic dysfunction may contribute directly to antisocial behaviour (Knabb et al., 2009). According to Weber and colleagues (2008, p. 23) the “existing body of evidence tentatively supports the idea that psychopathy is associated with brain abnormalities in the prefrontal-tempero-limbic circuit”. Hesse (2010) has stated that Antisocial Personality Disorder (ASPD) and psychopathy are two related concepts that are used to describe the personality problems that may result in antisocial behaviour. In support of this statement, Coid and Ullrich (2010, p. 432) have found that psychopathy and ASPD are not distinct clinical syndromes but rather are both on a continuum of ASPD. Specifically, psychopathic ASPD is “a more severe form than ASPD alone” with a greater risk of violence (Coid & Ullrich, 2010, p. 432). In relation to brain abnormalities and ASPD, Vollm and colleagues (2004) have stated that ASPD suggests dysfunction of the frontal lobes. Research has found that the frontal lobe volume of ASPD patients was 11% smaller than that of the control group (Raine et al., 2000). Damasio and colleagues (1990) have used acquired brain injury as evidence of the association between PFC damage and antisocial behaviour. PFC damage is associated with higher rates of impulsivity and poor self-control which are the characteristics of ASPD. Individuals with Cluster B personality disorders (especially ASPD) display many different PFC and memory dysfunctions. Of all the personality disorders Cluster B is particularly associated with criminal activity (Moran, 1999). Additionally, there is a strong link between Cluster B and the risk of violence and recidivism (Moran, 2002). ASPD has a prevalence rate of between 2-3% in most Western countries (Coid, 2003) and at least 50% of UK prisoners meet DSM criteria for ASPD (Singleton et al., 1998). There is a strong relationship between ASPD and crime, including violent crime 126

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(Eronen, Hakola & Tiihonen, 1996). Thus there is a greater chance of committing a felony if one has ASPD (Thompson & Bland, 1995). There is little evidence to suggest a definite cause of ASPD but familial factors including early adverse events (e.g. childhood abuse) are involved in the development of personality disorders later in life (Farrington, 1993). The possible causes of personality disorders include genetic and neurobiological liability and structural brain abnormalities. A criticism would be that in the DSM-IV the definition of ASPD emphasises antisocial behaviour and thus there is an overlap between ASPD and criminality, while according to Robins (1998) the most common symptoms of ASPD include violence and marital problems but not criminality.

SOCIOECONOMIC FACTORS There is little doubt that individuals from socio-economically deprived backgrounds exhibit a greater propensity towards criminal involvement (Rutter, Giller & Hagell, 1998). According to Ferguson, Swain-Campbell and Horwood (2004) socioeconomic deprivation has a strong association with later criminal involvement. For example, they suggested that socioeconomic deprivation experienced as a child is related to higher rates of crime later in life. Also individuals with a low socioeconomic status (SES) are three times more likely to engage in criminal activity than those with a high SES (Ferguson et al., 2004). There are several theories relating the causes of crime to SES. Merton‟s (1938) strain theory aims to explain the relationship between social structures and deviance. Strain theory states that there is a dichotomy between societal expectations of desirable achievements and the possibility to actually achieve these within the society. The link between criminality and socioeconomic disadvantage is caused by these „strains‟ or imbalances which result in predisposed individuals engaging in antisocial behaviour in order to balance these stains. Hence the experience of low SES encourages criminal involvement (Kelly, 2000). According to the differential association theory of crime the higher rates of crime amongst individuals from socioeconomically deprived backgrounds are due to greater exposure to antisocial peers and environment (Ferguson et al., 2004). Ferguson and colleagues (2004) suggest that the differential association theory contrasts with strain theory via an emphasis on peer influence and motivation towards criminality. On the other hand, the social learning perspective theory 127

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claims that early exposure to maladaptive parenting and a lack of supervision encourage the development of crime (Rutter et al., 1998). Furthermore, Rutter and colleagues posit that differences in crime rates across differing social strata are directly linked with differing child rearing practices for each of the social stratum. Finally the social control theory states that the inclination towards deviance is a characteristic of all individuals but social bonds mediate these impulses (Gottfredson & Hirschi, 1990). These social bonds may include attachments to family and school however, deterioration of these bonds occurs as a result of socioeconomic disadvantage, thus leading to criminal activity (Kelly, 2000). Ultimately, individuals from low socioeconomic environments are at an increased risk of later criminal participation because of the accumulative effects of individual, familial and peer factors (Ferguson et al., 2004). Other intervening factors between socioeconomic deprivation and crime include marital conflict, parental hostility and poor parenting (Conger, Patterson & Ge, 1995).

FAMILIAL FACTORS Family influences are the greatest contributors to criminal involvement but conversely also have the greatest propensity to moderate criminal behaviours (Ferguson et al., 2004). Externalising problem behaviour is related to poor parenting (Shaw et al., 1998). Farrington (1990) found that there was a high risk of hyperactivity and conduct disorder as a result of parenting risk factors discussed below. Morrell and Murray (2003) postulated that conduct disorder requires environmental risk factors for the expression of the genetic factors that are associated with conduct disorder. Pattersonâ&#x20AC;&#x;s coercive family process model states that cycles of negative reinforcement are a risk factor for criminality. For example, this occurs when a child does not comply with the parentâ&#x20AC;&#x;s demands but is still rewarded by the parent giving in to them (Morrell & Murray, 2003). Poor quality parenting is a better predictor of poor attention at three to four years and hyperactivity at five years than biological or temperamental factors (Carlson, Jacobvitz & Scroufe, 1995). However, a positive relationship between parent and child is an effective method of prevention of conduct disorder (Pettit, Bates & Dodge, 1997). Maternal depression is another significant risk factor in whether the individual develops a disruptive behavioural disorder. Research has found that five years after 128

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postnatal depression was experienced there was a higher risk of behavioural problems in children of postnatally depressed mothers (Murray et al., 1999). Poor quality of attachment relationships is also another risk factor for criminality in later life. According to Lyons-Ruth (1989) the attachment relationship at 18 months is a predictor for an individual‟s later functioning. Externalizing problem behaviour is associated with low quality of attachment. Golder, Gillmore, Spieker and Morrison (2005) suggested that poor attachment security may foster poor psychosocial development and behavioural problems. Conversely, Stein, Milburn, Zane and Rotheram-Borus (2009) stated that high quality attachment, particularly to fathers, was protective against delinquent behaviour. In relation to the mother, “Primary attachment relationships provide a protective foundation for the child (and later adult) to explore his or her environment and to meet developmental changes” (Stein et al., 2009, p. 40). Stein and colleagues (2009) also found that homeless youths who engaged in antisocial behaviours lacked a „secure base‟ in the form of an attachment figure and therefore these problem behaviours developed as a consequence. In contrast, Robins (1998) criticised poor parenting as a determinant of criminality because a child‟s own behaviour is a better predictor of adult antisocial behaviour than rearing, family background or SES.

PEER FACTORS Finally, criminal behaviour is correlated with having criminal friends. Having criminal friends is positively linked with antisocial conduct and drug-taking (Warr, 2002). There are two opposing theories regarding peer influence over criminality. The Social Causation Perspective states that delinquent peers imprint delinquent values onto their friends because their behaviours‟ and values are mimicked and adopted by the other members of the social network (Akers, 1998). However, Control Theories state that delinquents produce traits that may instruct them to join a delinquent peer network (Gottfredson & Hirschi, 1990). Individuals self-select peers with similar traits and interests. According to Walsh (2002, p. 173) “We all seek environments that are compatible with our genetic dispositions” Interestingly, Beaver et al. (2008) posit that choosing to associate with a delinquent peer network is influenced by an individual‟s genotype. Hence the genotype chooses the environment that allows for optimum gene 129

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expression (Scarr, 1992). The phenomenon gene x environment correlation (rGE) posits that genotype and environment are inextricably intertwined. Thus genes that influence particular characteristics also influence the environment in order to achieve optimal expression (Beaver et al., 2008). For example, male adolescents with the 10R allele for DAT1 are significantly more inclined to be associated with delinquent peers than adolescent males without the allele. In families in high and low risk backgrounds the 10R allele increases the likelihood that male adolescents will associate with delinquent peers. However, low risk parents may be able to control for the effect of the gene via parenting strategies (Beaver et al., 2008).

CONCLUSIONS The issue surrounding the determination of criminality is essentially a nature-nurture debate. Separately, neither genetic nor environmental factors are sufficient in explaining the determination of criminality and thus a heuristic approach must be considered. According to Beaver and Holtfreter (2009) it is the interplay between environmental and genetic factors which determines expression of an antisocial behavioural phenotype. In essence, the independent influence of one or the other tends not to yield a strong causal effect however their combined influence has a stronger causal link for individual criminal involvement. Specifically, in the case of LCP offenders a causal relationship exists between neuropsychological deficits and adverse home life. It is necessary that these individuals possess neuropsychological deficits and combined with a criminogenic family, results in chronic antisocial behaviour (Boutwell & Beaver, 2008). In relation to ASPD, causal factors include familial influences (Farrington, 1993) and dysfunction of the frontal lobes (Vollm et al., 2004). These factors work in tandem and are conducive for the expression of the antisocial phenotype. Similarly, conduct disorders require environmental risk factors for the expression of the genetic factors that are associated with the disorder (Morrell & Murray, 2003). Presently, it is suggested that a positive parent-child relationship is the most effective preventative measure against conduct disorder (Pettit, Bates & Dodge, 1997) as high quality attachment relationships have been found to be protective against delinquent behaviour (Stein et al., 2009). Beaver and colleagues (2008) found that in families in high and low risk 130

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backgrounds that although the 10R allele increased the likelihood that male adolescents associated with antisocial peers, low risk parents may be able to control for the effect of the gene through appropriate parenting strategies. Further research is required to understand how to prevent conduct disorder in those at high risk. In sum, each determining factor â&#x20AC;&#x201C; such as familial, peer and genetic influences â&#x20AC;&#x201C; when assessed independently is insufficient in explaining the determination of criminality. Analyses of the interactions between genetic and environmental factors are therefore necessary for understanding who is at risk for criminal behaviour and how such behaviour arises, and also for developing and implementing preventative strategies.

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REFERENCES Akers, R. L. (1998). Social Learning and social Structure: A General Theory of Crime and Deviance. Boston: Northeastern University Press. Anderson, S. W., Damasio, H., Tranel, D., & Damasio, A. R., (2001). Long-term sequelae of prefrontal cortex damage acquired in early childhood. Developmental Neuropsychology, 18, 281-296. Beaver, K. M., & Holtfreter, K., (2009). Biosocial influences on fraudulent behaviours. The Journal of Genetic Psychology, 170(2), 101-114. Beaver, K. M., Wright, J. P., & DeLisi, M., (2008). Delinquent peer group formation: evidence of a gene x environment correlation. The Journal of Genetic Psychology, 169(3), 227244. Boutwell, B. B., & Beaver, K. M. (2008). A biosocial explanation of delinquency abstention. Criminal Behaviour and Mental Health,18, 59-74.

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Carlson, E. A., Jacobvits, D., & Sroufe, L. A., (1995). A developmental investigation of inattentiveness and hyperactivity. Child Development, 66, 37-54. Coid, J. W. (2003). Epidemiology, public health and the problem of personality disorder. British Journal of Psychiatry, 182(44), 3–10. Coid, J., & Ullrich, S. (2010) Antisocial personality disorder is on a continuum with psychopathty. Comprehensive Psychiatry, 51, 426–433. Conger, R. D., Patterson, G. R., & Ge, X. (1995). It takes two to replicate: A meditational model for the impact of parents‟ stress on adolescent adjustment. Child Development, 66, 80-97. Damasio, A., Tranel, D., Damasio, H., (1990). Individuals with psychopathic behaviour caused by frontal damage fail to respond automatically to social stimuli. Brain and Behaviour Research, 41, 81-94.

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Eastman, N., & Campbell, C., (2006). Neuroscience and legal determination of criminal responsibility. Nature Reviews Neuroscience, 7, 311-318. Eronen, M., Hakola, P., & Tiihonen, J., (1996). Mental disorder and homicidal behaviour in Finland. Arch General Psychiatry, 53, 497-501. Eme, R. (2010) Male LifeCourse-Persistent Antisocial Behavior. The Most Important Pediatric Mental Health Problem. Archives of Pediatrics and Adolescent Medicine, 164(5), 486-487. Farrington, D. P. (1986). Age and crime. In T. M. Morris (eds) Crime and Justice: An Annual Review of Research (pp. 189-250) Chicago: University of Chicago Press. Farrington, D. P., (1990). Implications of criminal career research for the prevention of offending. Journal of Adolescence, 13, 93-113. Ferguson, D., Swain-Campbell, N., & Horwood, J., (2004). How does childhood economic disadvantage lead to crime?

Journal of Child Psychology and Psychiatry, 45(5), 956-966. Golder, S., Gillmore, M. R., Spieker, S., & Momson, D. (2005). Substance use, related problem behaviors and adult attachment in a sample of high risk older adolescent women. Journal of Child and Family Studies, 14, 181-193. Gottfredson, M. R., & Hirschi, T., (1990) A General Theory of Crime. Stanford: Stanford University Press. Hesse, M. (2010) What should be done with antisocial personality disorder in the new edition of the diagnostic and statistical manual of mental disorders (DSM-V)? BMC Medicine, 66(8), 1-4. Kelly, M. (2000). Inequality and crime. The Review of Economics and Statistics, 82, 530-539. Knabb, J. J., Welsh, R. K., Ziebell, J. G., & Reimer, K. S., (2009). Neuroscience, moral reasoning, and the law. Behavioural Sciences and the Law, 27, 219-236. Luntz, B. K., & Wisdom, C. S., (1994). Antisocial personality 133

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disorder in abused and neglected children grown up. American Journal of Psychiatry, 151, 670674. Lyons-Ruth, K. (1991). Rapprochement or approchement: Mahler's theory reconsidered from the vantage point of recent research on early attachment relationships. Psychoanalytic Psychology, 8(1), 1-23. Merton, R. K. (1938). Social structure and anomie. American Sociological Review, 3, 672-682. Moffitt, T. E. (1993) Adolescents-limited and lifecourse-persistent antisocial behaviour: A developmental taxonomy, Psychological Review,100, 674-701. Moffitt, T. E. (2006). A review of research on the taxonomy of lifecourse-persistent versus adolescence limited antisocial behaviour. In F. T. Cullen, J. P. Wright, & K. P. Blevins (eds) Taking Stock: The Starus of Criminological Theory, 15,(pp. 277-311) New Brunswick: Transaction Publications.

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Moll, J., Zahn, R., OliveriraSouza, R., Krueger, F., & Grafman, J., (2005). The neural basis of human moral cognition. Nature Reviews Neuroscience, 6, 799-809. Moran, P. (1999) The epidemiology of antisocial personality disorder. Social Psychiatry and Psychiatric Epidemiology, 34, 231-242. Moran, P., (2002). Editorial: Dangerous severe personality disorder â&#x20AC;&#x201C; bad things from the UK. International Journal of Social Psychiatry, 48(1), 6-10. Morrell, J. & Murray, L. (2003). Parenting and the development of conduct disorder and hyperactive symptoms in childhood: a prospective longitudinal study from 2 months to 8 years. Journal of Child Psychology and Psychiatry, 44(4), 489-508. Murray, L., Sinclair, D., Cooper, P., Ducournau, P. & Turner, P., (1999). The socioemotional development of 5-year-old children of postnatally depressed mothers. Journal of Child Psychology and Psychiatry, 40, 1259-1271.

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Pettit, G. S., Bates, J. E., & Dodge, K. A., (1997). Supportive parenting, ecological context, and childrenâ&#x20AC;&#x;s adjustment: A seven-year longitudinal study. Child Development, 68, 908-923. Raine, A., Lencz, T., Bihrle, S., LaCasse, L., Colletti, P., (2000). Reduced prefrontal fray matter volume and reduced autonomic activity in antisocial personality disorder. Archives of General Psychiatry, 57, 199-127. Rhee, S. H. & Waldman, I. D. (2002). Genetic and environmental influences on antisocial behaviour: a metaanalysis of twin and adoption studies. Psychological Bulletin, 128, 490-529. Robins, L. N., (1998). The intimate connection between antisocial personality and substance abuse. Social Psychiatry and Psychiatric Epidemiology, 33, 393-399. Rutter, M,. (2006). Genes and behaviour: Nature-Nurture Interplay Explained. Maiden, MA: Blackwell.

Rutter, M. Giller, H., & Hagell, (1998). Antisocial Behaviour by Young People. Cambridge, UK: Cambridge University Press. Scarr, S. (1992). Developmental theories for the 1990s: Development and individual differences, Child Development, 63, 1-19. Schachar, R., & Logan, G., (1990). Are hyperactive children deficient in attentional capacity? Journal of Abnormal Child Psychology, 18, 493-513. Shaw, D.S., Winslow, E.B., Owens, E.B., Vondra, J.I., Cohn, J.F., & Bell, R.Q. (1998). The development of early externalizing problems among children from low-income families: A transformational perspective. Journal of Abnormal Child Psychology, 26, 95â&#x20AC;&#x201C;107. Singleton, N., Meltzer, H., Gatward, R., Coid, J., & Deasy, D. (1998). Psychiatric Morbidity Among Prisoners in England and Wales. London: HMSO. Stein, J. A., Milburn, N. G., Zane, J. I., Rotheram-Borus, M. J. (2009) Paternal and Maternal 135

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Influences on Problem Behaviors Among Homeless and Runaway Youth. American Journal of Orthopsychiatry, 79(1), 39-50. Thompson, A. H., & Bland, B. C., (1995). Social dysfunction and mental illness in a community sample. Canadian Journal of Psychiatry, 40, 5-20. Vollm, B., Richardson, P., Stirling, J., Elliott, R., Dolan, M., Chaudhry, I., Del Ben, C., McKie, S., Anderson, I., & Deakin, B., (2004). Neurobiological substrates of antisocial and borderline personality disorder: preliminary results of a functional fMRI study. Criminal Behaviour and Mental Health, 14, 39-54.

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Walsh, A. (2002). Essay review: Companions in crime: a biosocial perspective. Human Nature Review, 2, 169-178. Warr, M. (2002). Companions in Crime: The Social Aspects of Criminal Conduct. New York: Cambridge University Press. Weber, S., Habel, U., Amunts, K., & Schneider, F., (2008). Structural brain abnormalities in psychopaths- a review. Behavioural Sciences and the Law, 26, 7-28. Wisdom, C. S., (1989). The cycle of violence. Science, 244, 160166.

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SEEING THROUGH THE BODY: THE EFFECTS OF VISUAL AND SENSORIMOTOR EXPERIENCE ON THE ANALYSIS OF HANDS ﾃ（ne Nﾃｭ Choisdealbha Senior Sophister, Psychology & English nichoisa@tcd.ie

ABSTRACT The processes implicated in the mental rotation of hand stimuli argue strongly for reference to one's own body schema in the visual analysis of hands and, potentially, other body parts. Prolific work by Cooper and Shepard (1975) and by Parsons (1994; 1987) suggests that the motor action of rotating a hand is simulated mentally in these tasks, while more recent studies, especially with left-handed participants, have pointed to the role of stored visual representations in analysing hands (Gentilucci et al., 1998a; 1998b; Ionta & Blanke, 2009). This review assesses the evidence for the use of visual and sensorimotor experience with one's own hands in the mental rotation of hands, as well as exploring how sensorimotor and visual strategies are used in conjunction with one another to analyse hand stimuli effectively.

INTRODUCTION: VISUAL HAND ANALYSIS AND THE LATERALITY JUDGMENT TASK

People have extensive visual and sensorimotor experience with hands. Hands are used to manipulate and interact with the vast majority of objects encountered in day to day life, and are also used in social communication, for example when shaking hands or hailing a taxi. Furthermore, familiarity with hands is not restricted to the sensorimotor domain - they are also seen frequently. Others' hands are watched for social significance like in gesticulations during speech, while one's own hands may be watched when becoming familiar with a novel object or action sequence. It follows that the visual analysis of hands is important in interpreting the gestures made by others and in learning how to interact 137

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with previously unencountered objects. The primary task used in studies of hand perception and analysis is the hand laterality judgment task. In this task, participants are asked to judge whether a visually presented hand stimulus depicts a left hand or a right hand, either declaratively (e.g. Sirigu & Duhamel, 2001), by button-press (e.g. Gentilucci et al., 1998a) or by matching to another stimulus (e.g. Kosslyn et al., 1998). Prototypical left and right hands are identical, but mirrored. It is this mirroring which forms the basis of the hand laterality judgment task and requires the recruitment of various processes in order to determine the laterality of the presented hand in the absence of all differences but laterality. The position of the presented hand also modulates task difficulty, with views of the thumb taking less time than views of the little finger (Nico et al., 2004) and with views of the fingers pointing upwards taking less time than views of the fingers pointing downwards (Parsons 1994; Cooper and Shepard, 1975). These reaction time differences suggest the use of one of two strategies in the visual analysis of hand laterality. One is the referral to visual exemplars or representations of hands held in memory, with reaction times being longer when there is little visual experience with a particular posture or orientation (Gentilucci et al., 1998b; Ionta & Blanke, 2009). The other is the matching to the stimulus of a motor image based on the current body schema, with reaction times being longer when the motor image must rotate through a longer trajectory to match the stimulus, or when the body schema is disrupted during the task (Ionta et al., 2007; Parsons, 1987). Behavioural and neural evidence for the use of these strategies will be discussed and assessed throughout this review. The importance of one's own body schema and the ability to refer to one's hands during hand laterality judgment tasks and, indeed, in visual hand analysis in general, will also be explored.

SENSORIMOTOR EXPERIENCE: MENTAL HAND ROTATIONS, MOTOR IMAGES AND PROPRIOCEPTIVE FEEDBACK

Sensorimotor experience, for the purposes of this review, refers to the experience of having performed a particular motor action and having received sensory feedback, especially proprioceptive feedback, about that action. Sensorimotor experience can be derived from long-term experience with commonly-assumed, 'canonical' hand positions (e.g. Parsons, 1987; Cooper & Shepard, 1975) and with biomechanical constraints (de Lange et 138

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al., 2006; Parsons, 1994), or it can be based on both long- and short-term changes to the body schema (Ionta et al., 2007; Nico et al., 2004). Motor imagery and experiencing hands Early work on the topic of laterality judgments of visually presented hands put forward strong evidence for the use of motor images – imagined movements, recruiting sensorimotor rather than visual processes – in judging the laterality of hand stimuli. Cooper and Shepard (1975) found that, if participants are instructed to imagine their hand in a particular position before being presented with a laterality judgment trial, their reaction time and accuracy vary depending on whether the imagined position is congruent or incongruent with the stimulus position. Coupling this with the finding from the same study that reaction times vary as a function of how close the stimulus is to a prototypical or 'canonical' fingers-upright orientation, the authors suggested that participants in these tasks generate a “phantom” or motor image of one of their own hands and mentally move it into the stimulus position to determine whether or not there is a match. The authors note that some of their participants made reference to the physical awkwardness of some of the required mental movements, even though the task had no kinematic component. The work of Parsons (1987; 1994) elaborates on the role of kinematics and, by extension, of sensorimotor processes in analysing visual hand stimuli. Firstly, it was found that people simulate the rotation of their hands along imagined paths which mimic the paths used for physical movement of those body parts, even if said paths do not facilitate the most efficient mental rotations in a stimulus-centred approach (Parsons, 1987). This indicates that an egocentric, body-centred approach is taken to the mental rotation of hands, as motor hand images obey the kinematic constraints of one's own hands which suggests that these rotations are based on real, sensorimotor experience. The later finding that the time taken to physically assume a particular position or orientation from a baseline, 'canonical' position correlates with the time taken to mentally rotate a motor image into that position or orientation (Parsons, 1994) adds further credence to the idea that motor hand images are based on sensorimotor experience. Experience with biomechanical constraints also comes into play, as medial rotations – physical and mental – towards the midline of 139

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the body take less time than lateral rotations away from the midline, the reason being that lateral rotations have greater wrist joint constraints than medial ones (Parsons, 1994). From these early findings, it appears quite strongly that mental rotations are used to visually analyse the laterality of a presented hand stimulus and that these mental rotations are based on real, biomechanical trajectories and make reference to the bodily experience of those trajectories and the postures at their ends. More recent neuroimaging studies have complemented this behavioural research and presented further evidence for the use of sensorimotor processes in laterality judgment tasks. Kosslyn and colleagues (1998) found that regions of the brain implicated in planning, preparing for and executing movement, such as the premotor cortex and the supplementary motor area, were implicated in mental rotations of hands but not in mental rotations of 3-D abstract objects such as Shepard and Metzler‟s (1971) „cubes figures‟. This suggests that mental hand rotations are treated much like the rotations of real hands, as proposed in Parsons (1987) and Cooper and Shepard (1975). Furthermore, a study by de Lange and colleagues (2006) has shown that the premotor cortex activity present during the rotation of motor hand images is modulated by the biomechanical difficulty of the corresponding motor movement, indicating once again that bodily and motor experience with one's hands affects the strategies used in the visual analysis of hand stimuli. The current body schema and proprioceptive feedback It is arguable that sensorimotor experience is not exclusively the product of long-term use of one's hands, but is affected strongly by the current position of one's hands. Indeed, the “canonical” fingers-upright position referred to be Cooper and Shepard (1975) and by Parsons (1987) is also the posture assumed during hand laterality judgment tasks, as hands rest palm down, fingers pointing away from the body either on participants' laps (e.g. Ionta et al., 2007; Nico et al., 2006) or over response buttons (e.g. Gentilucci et al., 1998b; Parsons, 1987; Cooper & Shepard, 1975). This is significant as a number of studies have shown that the position of participants' hands affects their speed and accuracy in recognising the laterality of a presented hand. Ionta and colleagues (2007) found that if participants' hands are intertwined behind their back, their reaction times 140

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are slowed compared to when the hands are resting flat in participants' laps. Ionta and Blanke (2009) also found that manipulating just the right hands of right-handed participants affects their performance in the hand laterality judgment task in a way that manipulating their left hands does not. This finding suggests a particular reliance on the dominant hand in the generation of motor images. What these results indicate together is that past experience of how one's hands move is not sufficient to generate an effective motor image â&#x20AC;&#x201C; current proprioceptive feedback is also essential and when that feedback is interfered with by unnatural hand positioning, performance is affected. This could be due to the immediacy of sensorimotor feedback, with the current body schema interfering with or indeed trumping any past sensorimotor experience. There is also the possibility that strategies for hand laterality recognition which do not rely even partially on sensorimotor feedback are less developed so that there are no other efficient strategies to resort to when sensorimotor feedback is unreliable. Additional arguments for the role of the current sensorimotor body schema come from research with people with upper-limb amputations and corpus callostomy patients. Nico and colleagues (2004) found that relative to controls, people with these amputations are less accurate and slower at laterality judgments despite having had sensorimotor experience with the amputated arm at one point. However, the task did elicit phantom limb sensations in a number of participants, suggesting, firstly, that their motor system was not dormant during the task, and secondly, that they were able to rely at least partially on its representation to guide their responses. Thus, it seems that while past experience with the amputated limb does facilitate performance, the changed or changing body schema that comes with an amputation interferes with any prior representations. This suggests again that current proprioceptive feedback plays a particularly important role in generating effective motor images. Parsons and colleagues (1998) had corpus callostomy patients perform the laterality judgment task and found that when presented with a hand ipsilateral to the perceiving hemisphere, patients used the contralateral hand to guide their motor image and responded at chance levels, although performance was preserved when the presented hand was contralateral to the perceiving hemisphere. This suggests that access to a sensorimotor representation of the body â&#x20AC;&#x201C; confined to the contralateral side of the body 141

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to the perceiving hemisphere in callostomy patients â&#x20AC;&#x201C; determines the ability to generate a motor image and thus to perform the task in a satisfactory manner. There is strong behavioural and neural evidence for the importance of motor imagery and mental rotations in hand laterality judgments. However, recent research, especially with left-handed participants (Ionta & Blanke, 2009; Gentilucci et al., 1998b) and also with participants with deficits in motor imagery (Sirigu & Duhamel, 2001) has suggested that pictorial representations and visual experience with hands may also determine performance in the visual analysis of hand stimuli.

VISUAL EXPERIENCE: INITIAL ANALYSES, DIFFERENCES IN DOMINANCE AND EXPERIENCE WITH OTHERS' HANDS Initial analyses Parsons (1987) interpreted his data to suggest that the mental rotation of a hand in a laterality judgment task is a confirmatory process. For it to be such, an initial visual analysis of the hand stimulus must be made in order to select the hand with which to generate the motor image. In order to test the initial visual analysis hypothesis, Gentilucci et al. (1998a) presented participants with images of hands of both lateralities showing common (e.g. fist; all fingers extended) and uncommon (e.g. thumb, index and middle fingers extended; index, middle and ring fingers extended) fingers configurations. Participants' ability to recognise the laterality of common configurations more quickly than uncommon configurations, but not necessarily to assume such configurations more quickly, suggests that an analysis of the visually presented hand does take place before the confirmatory mental rotation process. The authors propose that this initial analysis occurs unconsciously and is based on visual hand representations derived from seeing one's own and others' hands. The significance of visual familiarity with others' hands is discussed further below. In order to tease out the specific importance of the initial, implicit visual stage and the mental rotation stage in hand laterality judgments, Sirigu and Duhamel (2001) had patients with neuropsychological deficits in either motor imagery or visual imagery imagine either one of their own or of the examiner's hands in a specific posture and orientation. The 142

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patient with visual imagery deficits experienced particular difficulties when his hands were placed behind his back, due to his inability to generate an effective motor image in that condition (see earlier discussion of Ionta el al., 2007, for clarification). The patient with a motor imagery deficit, however, made few errors but showed no facilitation when asked to imagine his own hand versus the examiner's, indicating that although a purely visual strategy can be accurate, the sensorimotor, mental rotation process makes confirmation much quicker. The dissociability of the two stages illustrated in the above study has been shown to be affected by individual differences, especially in terms of hand dominance. Dominance Cooper and Shepard (1975) originally suggested that the hand used to generate motor images in mental rotations may be the dominant hand. Parsons (1987) pointed out that the pattern of reaction times is not extreme enough to support this, although there is some facilitation based on dominance, as right-handed participants are often significantly faster at recognising their dominant hand, whereas left-handed participants are not (Ionta & Blanke, 2009; Gentilucci et al., 1998b). Explanations for these differences include the greater lateralisation of right-handers than left-handers (Gentilucci et al., 1998a), as more extensive use of a particular hand for a wider range of activities may lead to greater sensorimotor experience with it and therefore faster mental rotations. They also include greater visual experience with others' right hands (Ionta & Blanke, 2009), as the majority of people are right-handed and therefore their right hands will be seen more often than their left, undercutting the effect of any increased sensorimotor experience of the dominant hand in left-handers while enhancing the same in right-handers. To return to the role of visual representations, it appears that lefthanded participants in laterality judgment tasks may use the sensorimotor and visual strategies to a different extent than righthanders. Gentilucci and colleagues (1998b) found that left-handed participants rely more on the initial, implicit visual analysis of the presented hand, whereas right-handers rely more on the mental rotation stage. Ionta and Blanke's (2009) comment on visual experience of hands sheds some light on this finding. They say that because right-handers use and therefore see their own right hand more frequently, right-handers are 143

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confronted visually with right hands most frequently, whereas lefthanders see both their own, dominant left hand and others' dominant right hands frequently. Left-handed people therefore have a wide variety of stored visual exemplars of hands and consequently may be able to rely on the visual stage more than right-handed participants. It is worth noting that the neuroimaging studies cited above (de Lange et al., 2006; Kosslyn et al., 1998) which illustrate the use of sensorimotor processes in mental hand rotation make use of right-handed samples exclusively. Although similar activation is probably present in left-handed people – the two-step visuo-sensorimotor process is present in all participants – activation may differ in strength or onset. To conclude discussion of visual strategies and processes in visual hand analysis, it appears, firstly, that implicit visual analysis and reference to stored exemplars is undertaken before beginning the confirmatory mental rotation and secondly, that reliance on visual versus sensorimotor strategies varies as a function of hand dominance as a result of either lesser lateralisation among left than right handers and/or greater visual familiarity with the right hands of others.

SELF

VS OTHER: EMBODIED PERCEPTION VERSUS REPRESENTATIONS IN VISUAL ANALYSIS OF BODY PARTS

OBJECT

From the discussion above, it is evident that a kind of embodied perception takes place in the visual analysis of hands needed to make laterality judgments. Essentially, this means that people make use of their own bodily experiences – affected by both the potential rotational trajectories and the current posture of their hands – to generate a motor image which they can match to a stimulus in order to determine the stimulus' laterality. This action is neurally represented in the premotor and supplementary motor cortices (Kosslyn et al., 1998; de Lange et al., 2006), suggesting that the rotation is not undertaken on a disembodied, allocentric object – instead, reference is made to one's own body and bodily experience is used to complete the task. Research into the extrastriate body area (EBA) is revealing that the brain might differentiate between self and other hands. The EBA is part of the visual cortex and shows activation in response to bodies and body parts. Its function differs from premotor cortex as it responds not to 144

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action but to body identity and view (Urgesi et al., 2007). It has been found that the right extrastriate body area responds differently to body parts presented from an allocentric versus an egocentric point of view (Chan et al., 2004; Saxe et al., 2006). Ego- and allocentric hands can be presented in the same plane and present with the same overall shape and because of this Saxe and her colleagues (2006) note that right EBA activation is stronger to stimuli which do not have this kind of flexibility – like feet – than it is to hands. Because of this particular feature of hands, the right EBA might not be able to elaborate much on the self-referencing involved in visual hand analysis. However, it is worth noting that the disembodied body part images used in this kind of research do not represent experience with hands outside the laboratory and thus may not tap into the „real-world‟ functioning of the EBA. The question of whether the same region of cortex can differentiate between body parts with a 'self' identity and those with an 'other' identity based on specific features rather than overall shape or viewpoint has been tackled recently. Chan and colleagues (2004) found that the right EBA did not differentiate between images of a participant's body parts and those of another, however Myers and Sowden (2008), using fMR-A, a newer neuroimaging technique, found greater adaptation in the right EBA to images of two separate others' hands than to similarly interleaved images of the participant's own and one other's hands. Thus, there appears to be a mechanism which differentiates between self and other hands. Whether this has any relevance for visual analysis of the overall shape of a hand, as in the hand laterality judgment task, remains to be seen. Future research could use this finding from neuroimaging to develop a behavioural task wherein laterality judgments are performed on photographic images of one's own and others' hands. Results could determine whether visual familiarity with one's own or others' hands play a differential role, especially in the early implicit visual analysis stage of laterality judgments, or whether visual familiarity is, unlike sensorimotor familiarity, non-embodied and object- rather than body-centred.

CONCLUSIONS The studies discussed in this paper represent a very small subset of the studies which explore how different perceptual modalities interact with each other and make one another more efficient through Bayesian 145

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information-gathering processes. This particular subset is important, as illustrated throughout this review, in exploring how the sensorimotor body schema can be used effectively in ostensibly visual tasks. Reviewing the various idiosyncracies of laterality judgments of hands discovered in research conducted over the past 30 years, it appears that one‟s own bodily experiences directly inform one‟s ability to make such judgments. Sirigu and Duhamel‟s (2001) work, although limited in its participants, illustrates nicely the interaction of visual and sensorimotor strategies in judging hand laterality – purely visual recognition strategies can result in quite accurate responding, but using motor imagery as well facilitates the speed of these responses. Indeed, in healthy participants, impaired access to a motor imagery strategy can result in increased inaccuracy (e.g., Ionta et al., 2007), most likely due to the fact that these participants will have less experience with purely visual hand analyses than Sirigu and Duhamel‟s motor imagery-impaired patient. The crux of this research and its importance lie in the fact that participants in these studies, even in the absence of instructions about using motor versus visual imagery, do not take an allocentric approach to the laterality judgment task. Instead, they think about the presented stimulus from a subjective point of view by rotating a motor image of their own hand, exactly as it would be rotated according to biomechanical restraints (Parsons, 1987), into a position which matches that of the hand onscreen. This self-referential, motor strategy is so strong that the previously extinguished phantom sensations of some upper limb amputees are re-elicited by the task (Nico et al., 2004). This strategy is effective, and appears to be automatic, indicating that there may be cross-modal circuits encompassing the EBA, which codes a bodily stimulus, and the premotor cortex, which is used to perform motor transformations on that stimulus, something which could be addressed by future research.

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REFERENCES Chan, A. W-Y., Peelen, M.V., & Downing, P.E. (2004). The effect of viewpoint on body representation in the extrastriate body area. Neuroreport, 15(15), 2407-2410.

Ionta S, & Blanke, O. (2009). Differential influence of hands posture on mental rotation of hands and feet in left and right handers. Experimental Brain Research, 195(2), 207-217.

Cooper, L.A., & Shepard, R.N. (1975). Mental transformations in the identification of left and right hands. Journal of Experimental Psychology: Human Perception and Performance, 1(1), 48-56.

Ionta, S., Fourkas, A.D., Fiorio, M., & Aglioti, S.M. (2007). The influence of hands posture on mental rotation of hands and feet. Experimental Brain Research, 183(1), 1-7.

de Lange, F.P., Helmich, R.C., & Toni, I. (2006). Posture influences motor imagery: An fMRI study. Neuroimage, 33(2), 609-617. Gentilucci, M., Daprati, E., & Gangitano, M. (1998a). Implicit visual analysis in handedness recognition. Consciousness and Cognition, 7(3), 478-493. Gentilucci, M., Daprati, E., & Gangitano, M. (1998b). Righthanders and left-handers have different representations of their own hand. Cognitive Brain Research, 6(3), 185-192.

Kosslyn, S.M., DiGirolamo, G.J., Thompson, W.L., & Alpert, N.M. (1998). Mental rotation of objects versus hands: neural mechanisms revealed by positron emssion tomography. Psychophysiology, 35(2), 151161. Myers, A., & Sowden, P.T. (2008). Your hand or mine? The extrastriate body area. Neuroimage, 42(5), 1669-1677. Nico, D., Daprati, E., Rigal, F., Parsons, L., & Sirugu, A. (2004). Left and right hand recognition in upper limb amputees. Brain, 127(1), 120-132.

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Parsons, L.M. (1994). Temporal and kinematic properties of motor behaviour reflected in mentally simulated action. Journal of Experimental Psychology: Human Perception and Performance, 20(4), 709730. Parsons, L.M. (1987). Imagined spatial transformations of one's hands and feet. Cognitive Psychology, 19(2), 178-241. Parsons, L.M., Gabrieli, J.D.E., Phelps, E.A., & Gazzaniga, M.S. (1998). Cerebrally lateralised mental representations of hand shape and movement. The Journal of Neuroscience, 18(16), 6539-6548. Saxe, R., Jamal, N., & Powell, L. (2006). My body or yours? The effect of visual perspective on cortical body representations. Cerebral Cortex, 16(2), 178-182.

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Shepard, R. N., & Metzler, J. (1971). Mental rotation of threedimensional objects. Science, 171, 701â&#x20AC;&#x201C;703. Sirigu, A., & Duhamel, J., R. (2001). Motor and visual imagery as two complimentary but neurally dissociable processes. Journal of Cognitive Neuroscience, 13(7), 910-919. Urgesi, C., Candidi, M., Ionta, S., & Aglioti, S.M. (2007). Representation of body identity and body actions in extrastriate body area and ventral premotor cortex. Nature Neuroscience, 10(1), 30-31.

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THE EFFECT OF EXTRACURRICULAR ACTIVITIES ON CAREER OUTCOMES: A LITERATURE REVIEW Lisa Keenan Senior Sophister, Sociology & Economics likeenan@tcd.ie

ABSTRACT Although much attention has already been devoted to the benefits of extracurricular activities (ECAs) in general – both from a developmental and from a social perspective – little time has been devoted to a complete academic study of the effects of university ECAs in particular. This review draws on insights from psychology, social psychology, economics and sociology in an attempt to develop a holistic perspective on the effects of college ECAs on labour market outcomes and career success. The various shortcomings of this research area are highlighted with additional considerations for future research.

INTRODUCTION Although initially regarded as a distraction, extracurricular activities (ECAs) are now recognised as an essential part of the college experience (Conway, 2009). These ECAs provide highly structured leisure environments (Huang & Carlton, 2003) which can confer a range of benefits on participants. Some are social: Schuh and Laverty (1983) argue that it creates better citizens, while Mahoney and Stattin (2000) find that it reduces rates of delinquency; some are personal and psychological: Geraghty (2010, p. 14) notes that it “enhances the student experience, aids academic performance, helps students to develop certain skills…improves their self-confidence” and also contributes to “student engagement, peer interaction, leadership, faculty interaction and student retention.” While these findings are important, this paper is interested only in the way that career success can result from participation in college ECAs. As such this

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paper examines only those effects produced by participation which contribute to career success. Research into the effects of participation in ECAs has been inconclusive so far. Initially, researchers shared Coleman‟s (1961) negative view of participation in ECAs. According to his zero-sum model of time allocation, students were faced with a situation in which they had a limited endowment of time to split between academic pursuits and structured and unstructured leisure activities. Coleman (1961) argued that the allocation of time to leisure activities resulted in poorer academic outcomes. Although this kind of thinking was heavily influential, today researchers tend to take the view that there are a host of benefits which derive from participation in ECAs, making ECA participation an investment rather than a distraction (Swanson, 2002). Despite this more positive view, most studies stress that any benefits which stem from participation are heavily dependent on the nature of the activity (Eccles & Barber 1999; Barber, Eccles & Stone, 2001; Broh, 2002; Mahoney & Stattin, 2000)

REVIEW OF EXISTING LITERATURE ON OUTCOMES What follows is an attempt to link the existing literature on the benefits of participation in extracurricular activities with that of career success. Combining theories from different disciplines makes it apparent that the link between ECAs and career success is mediated by a whole host of psycho-social factors. According to the existing literature, participation in ECAs can theoretically produce an effect on career outcomes through the following channels: 1) by fostering academic abilities 2) a training effect 3) by nurturing desirable personality traits 4) by providing individuals with social contacts. The evidence for this linkage will be explored in more detail.

EXTRACURRICULAR ACTIVITIES GENERATE GOOD ACADEMIC OUTCOMES Gamp‟s (1990) study on academic achievement found that participation in student activities had a positive effect on grades – even when taking into account background variables. This position is strengthened by the fact that other researchers such as Huang & Carlton (2003) have found, and continue to find, such a relationship. Bartko and Eccles (2002) confirmed this result with their study of high school teenagers. 150

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One explanation of this finding comes from researchers who have developed identification or commitment models which state that students are more likely to do well when they engage in school-sponsored ECAs because they foster commitment to the school‟s goals and identification with the school‟s culture. Effectively, there is a socialization effect which makes participants more likely to adopt pro-school values (McNeal, 1995). Certain papers argue that this is due to the type of people that students mix with while participating (Eccles & Barber, 1999; Mahoney & Stattin, 2000; Feldman & Matjasko, 2005). Gilman (2004) states that ECAs put students in touch with “supportive social networks” and allow them to interact with “competent non-parental adults” (p.32). Being in contact with non-deviant peers and with adults who are inclined to support school culture has a socializing effect (Mahoney & Stattin, 2000). Marsh (1992) tests the participation-identification model outlined by Finn (1989) against the zero-sum model. Finn (1989) argues that a simple trade-off exists between extracurricular participation and positive academic outcomes. He found that total extracurricular participation does have the potential to increase students‟ commitment to school, although the effects were small. The study showed a positive effect on a series of psychological outcomes and other benefits such as “taking advanced courses, time spent on homework, the postsecondary aspirations, GPA…being on the academic track, college attendance.”(p. 557) These results suggest that there is reason to believe that commitment to school leads to academic success. In terms of the relationship between extracurricular activities and career success, it seems reasonable to assert that the contribution higher grades make to career outcome is an intuitive one. However, we must remark with Chickering (1994) that grades alone - specifically college grades - are poor predictors of success. He notes that “successful careers call for well-developed cognitive skills, interpersonal competence, and motivation” (p.51). Academic performance by itself does not speak to these qualities and therefore the non-academic effects of ECA participation must be considered.

EXTRACURRICULAR ACTIVITIES IMPROVE PARTICIPANTS’ SKILL SET Many studies reveal that one of the main goals of extracurricular activities is skill acquisition (Zaff, Moore, Papillo & Williams, 2003; Mahoney & 151

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Stattin, 2000; Gilman, 2004; Eccles & Barber, 1999). Candidates as well as recruiters believe that participation in ECAs is indicative of the quality of their skill set (Conway, 2009). What is interesting to note here is that even if the training aspect of participation in ECAs did not exist, this type of biodata would continue to be used in the selection process so long as both sides believed in its ability to signal superior skills. From this perspective, even if membership of clubs and societies did not lead to a better skill set, it would still be legitimate to use participation as a signal in the personnel selection game so long as participation was found to be due to underlying heterogeneity in individuals (i.e. individuals participate because they are skilled instead of being skilled because they participate). This issue is one which makes serious empirical investigation of ECA participation very difficult because of a „selection bias‟ which makes it difficult to compare those who participate with those who do not, because participation is itself evidence of underlying heterogeneities in the active group. In any event, there is some evidence to support the theory that engaging in ECAs enables participants to acquire skills which prepare them for the labour market. Howard (1986, p. 545) found that “participation in student government, the school paper, and debating teams were most likely to relate to meaningful performance criteria.” Although different researchers have found different effects for various activities (Barron, Ewing & Waddell,2000; Rubin, Bommer & Baldwim, 2002), the literature does broadly support the hypothesis that extracurricular experiences are relevant to career success because they teach and develop appropriate skills, with a caveat added by Howard (1986) which states that these experiences are relevant only insofar as they can be related to concrete skills.

EXTRACURRICULAR ACTIVITIES AID PSYCHOLOGICAL DEVELOPMENT Another channel through which ECA participation can result in career success is through its effect on a range of psychological outcomes. As Chickering (1994, p.51) states, successful careers also call for “welldeveloped cognitive abilities, interpersonal competence and motivation.” Although ECAs have been tied to general improvements in mental health and other psychological outcomes (Gilman, 2004; Feldman & Matjasko, 2005), three specific outcomes are of interest; positive effects on selfesteem (Feldman & Matjasko, 2005), emotional intelligence (Chia, 2005), 152

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and interviewing self-efficacy (Tay, Ang & Dyne, 2006). All of these have been linked with favourable outcomes in the labour market. Baumeister et al. (2003) suggest that self-esteem mediates the relationship between participation and success due to two benefits which result: 1) a stock of positive feelings, and 2) greater initiative. Firstly, possessing a stock of positive feelings makes individuals better able to cope with stress and to react to challenging situations. Although Baumeister et al. (2003) found that self-esteem had little or no direct effect on job performance, it affected persistence at tasks. The authors cite experiments in which confederates with high self-esteem made better use of situational cues in order to form adaptive strategies (i.e. problem solve), compared with those with low self-esteem. Interestingly, Ellis and Taylor (1983) found that those with low self-esteem tended to have lower search intensity and thus spent longer looking for a job, indicating that this ability can be put to good us in the job search process as well as in the workplace. Secondly, initiative has been found to be important both in the job search process and afterwards on the job, making it a good predictor of success (Ellis & Taylor, 1983). Larson (2000) points out that there is a limited opportunity for adolescents to experience both initiative and motivation in their daily lives. By contrast, structured voluntary activities represent a context within which initiative can develop. Those who possess high levels of initiative will tend to exercise it in order to achieve desired outcomes; this means that they have a proactive personality (Kraimer, Seibert & Crant, 2001). Studies have shown that proactive behaviour is directly related to career success, as well as indirectly related through improved job performance, tolerance for stress, leadership effectiveness, work team performance, and entrepreneurship (Kraimer, Seibert & Crant, 2001). In sum, high levels of self-esteem fostered by ECA participation can be linked to career progression through improved ability to cope with challenges and proactivity. The way in which emotional intelligence (EI) - “the ability to monitor one‟s own and other‟s [sic] feelings and emotions, to discriminate among them and to use this information to guide one‟s thinking and actions” (Chia, 2005, p. 76) – is related to work and interview success. Chia‟s (2005) study, which examined job offers of multi-national accounting firms to college graduates, showed that consideration of the so153

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called „soft-skills‟ of candidates was present at every level of the recruiting process. Candidates were initially screened and selected for the first round of job interviews using the information contained in their cover letter and CV. The author found that at this stage, the level of ECA participation which a candidate possessed was held to denote his or her level of EI. If the candidate made it through this initial round of interviews, it became clear that what was important in subsequent rounds was not the level of participation in ECAs but the experience which candidates gained from them - here EI was held to be a proxy variable for the benefits of participation in ECAs. The number of final job offers thus depended not only directly on ECA participation through the number of initial job offers received, but also indirectly due to its development of EI which determined the number of subsequent job interviews received by candidates and thus the number of final job offers. Finally, success in the job search is also determined by an individual‟s interviewing self-efficacy (ISE), that is, a candidate‟s personal judgement of his or her interviewing capabilities (Tay, Ang & Dyne, 2006). ISE is linked to personality and biographical characteristics (those who are more extraverted tend to have higher ISE) but can also be developed within the context of ECA participation. Tay, Ang and Dyne (2006) cite studies which have found that membership of certain clubs and societies in college predicts interview evaluations because the skills developed through this form of participation (social interactions, influence tactics, self-presentation and image management) all have direct relevance to those needed to be successful in an interview. Although there is a considerable body of evidence which notes that the developmental context of ECAs fosters the good psychological functioning which enables participants to achieve a host of labour marketrelated outcomes (Gilman, 2004; Feldman & Matjasko, 2005; Chia, 2005; Tay, Ang & Dyne, 2006) some researchers argue that these benefits may have been over-estimated (Fredricks & Eccles, 2006). For example, for certain aspects of career success (e.g. financial success) no link has been found with ECAs (Fredricks & Eccles, 2006). Nevertheless, there is sufficient evidence to support the hypothesis that ECAs result in psychological outcomes which are linked to career success.

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EXTRACURRICULAR ACTIVITIES GIVE ACCESS TO SOCIAL CAPITAL The final way in which ECA participation can lead to better career outcomes is through the development of social ties. Network theory emphasises the importance of the type of people which one comes into contact with. Granovetter‟s (1973) seminal work on the strength of weak ties highlighted the value of the acquaintances which individuals formulate. He argues that while strong ties (family and close friends) are a very important part of an individual‟s social network, links to those who are outside of this network and with whom the individual has infrequent contact (weak ties) have advantages that strong ties do not. This type of tie can provide a crucial source of information outside of that held by the high-density network and can be mobilised by the individual. Access to information outside of the individual‟s tightly-knit social circle can be instrumental in finding a job (Granovetter, 1974, 1983). Granovetter (1974) found that personal contacts were found to be superior to formal methods of job location and that of these personal contacts, weak ties were the most successful means of finding a job. In support of this theory, Langlois (1977) and Ericksen and Yancey (1980) found that college-educated people were more likely to depend on weak ties compared with those who were not college-educated. This suggests that the university is a site where individuals both develop and learn how to develop those contacts which will prove useful later on in life. Also, as well as facilitating job search, evidence has been found which suggests that the use of weak ties in the job search process is strongly associated with higher occupational achievement (Granovetter, 1983), suggesting that even after a job is found, weak ties may continue to be mobilised by individuals to achieve other career-related outcomes. Granovetter‟s (1983) theory has been subject to criticisms by other authors; Montgomery (1992), for example, stresses the need to focus on the structure of the network as well as the type of tie which is mobilised in the job search process. Seibert, Kraimer and Liden (2001) reviewed the empirical evidence on weak tie theory and in conclusion recommend that actors invest in weak ties in general before selectively strengthening them in order to mobilise the career-related benefits that come with good ones.

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ISSUES RAISED BY EXISTING RESEARCH This paper has shown that ECA participation is linked to career success through four channels: firstly, positive academic outcomes with participation; secondly, participation in ECAs has a training effect which results in the accumulation of skills which can be put to good use during job search and in the workplace; thirdly, participation results in a host of desirable psychological outcomes, which make the individual better adapted to achieve success. Finally, participation in ECAs allows individuals to accumulate social capital which can be mobilised in order to achieve desired career outcomes. Although the literature connecting extracurricular participation with career success is very rich, there are issues yet to be fully addressed. These must be confronted before further investigation into the topic proceeds. Firstly, it is important to note that the majority of the data which have been used by the researchers in their investigations has been taken from sources in the United States making it difficult to generalise findings outside of the US. Secondly, the vast majority of the studies cited above have been testing the relationship between participation in high school as opposed to college ECAs. It is clear that the context in which students find themselves in college is not the same as that of high schools. Furthermore, college students are probably more likely to be more involved in ECAs than high school students due to the wider range of activities on offer. In other words those students who were never interested in participation during their second-level education may still be able to reap the benefits associated with membership of clubs and societies despite the late development of their interest. Thirdly, there are various difficulties associated with taking career success as the outcome of interest. Measurement of this phenomenon is problematic with readily quantifiable outcomes such as salary and position in the firmâ&#x20AC;&#x;s hierarchy having been employed traditionally. However, Jencks, Perman and Rainwater (1988) found that nonmonetary characteristics need to be incorporated into the analysis when looking at career success. Gunz and Heslin (2005) outline the idea of the subjective career and explain that researchers need not shy away from including subjective criteria in their studies on career success since patterns of shared meaning emerge in subjective criteria of success because 156

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careers are socially constructed. Heslin (2003, 2005) also notes that selfand other-referent criteria of success should be incorporated in order to measure success in a meaningful way. Fourthly, it is crucial to note that the effects which ECA participation produces are not uniform or indeed all positive. Various researchers have found that the returns to extracurricular participation vary according to gender (Eccles & Barber, 1999; Long & Caudill, 1991), type of activity (Barber, 1999; Barber, Eccles & Stone, 2001; Broh, 2002), degree of structure of the activity (Mahoney & Stattin, 2000; Zaff, Moore, Papillo & Williams, 2003), and level of participation of the individual (Fredricks & Eccles, 2006). Participation can have negative effects on a host of developmental outcomes largely due to the peer group with which members associate themselves while engaging in the activity (Eccles & Barber, 1999; Barber, Eccles & Stone, 2001). Equally important is Marsh and Kleitman‟s (2002) finding that when it comes to extracurricular activities, there is evidence supporting a threshold model which states that moderate amounts of participation are beneficial to the participant but that beyond an optimal point they experience diminishing marginal returns to their investment in ECAs. As the authors put it, be aware of “the good, the bad and the non-linear” (Marsh & Kleitman, 2002). Finally, where positive effects have been found in empirical studies, they have been correlational and therefore subject to the criticism that they result from self-selection (Gilman, 2004; Feldman & Matjasko, 2005). Essentially, the issue here is that career success and participation in extracurricular activities could potentially be jointly determined by some other factor which is unobservable or unobserved. Although there are the usual econometric methods of addressing this difficulty in empirical research, it is important to be aware that, because of the voluntary nature of extracurricular activities, it will continue to be an issue.

CONCLUSION Despite the many problems associated with research into the link between ECA participation and career success, further research is worth pursuing because of its relevance to students, universities, recruiters and policymakers. Collecting new data and borrowing from ecological systems theory would be the two key features of a new approach which would attempt to blend the existing findings from economics, sociology, 157

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psychology, social psychology and careers literature in order to give a more comprehensive picture of the issue. Although this may appear overambitious, the final word should be reserved for Marsh and Kleitman (2002) who note that “whereas it is unlikely that one design or approach will ever provide a definitive solution…accumulating evidence using a variety of different approaches provides increasingly stronger support for the generalisabiltiy of the benefits of participation in extracurricular activity” (p. 506).

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REFERENCES Barber, B., Eccles, J. & Stone, M. (2001). Whatever happened to the jock, the brain, and the princess? : Young adult pathways linked to adolescent activity involvement and social identity. Journal of Adolescent Research, 16(5): 429-455. Bangerter, A., Kรถnig, C. & Roulin, N. (2008). Personnel selection as a signalling game. Working paper. Retrieved on June, 10, 2010 from http://www.hec.unil.ch/documen ts/Brownbag29th_september.pdf Bartko, W. & Eccles, J. (2002). Adolescent Participation in structured and unstructured activities: a person-oriented analysis. Journal of Youth and Adolescence. 32(4), pp. 233-241. Baumeister, R., Campbell, J., Kruger, J. & Vohs, K. (2003). Does high self-esteem cause better performance, interpersonal success, happiness, or healthier lifestyles? Psychological Science in the Public Interest, 14(1), pp. 1-44.

academic achievement: who benefits and why? Sociology of Education, 75(1), pp. 69-95. Chia, Y. (2005). Job offers of multi-national accounting firms: the effects of emotional intelligence, extracurricular activities and academic performance. Accounting Education, 14(1), pp. 75-93. Chickering, A. (1994). Empowering life-long selfdevelopment. The Journal of the National Academic Advising Association, 14(2), 50-53. Coleman, J. S. (1971, [1961]). The adolescent society: the social life of the teenager and its impact on education. London : CollierMacmillan. Conway, A. (2009). An investigation into the benefits of extracurricular activities like Clubs and Societies to students and colleges: Are these benefits evident in the opinions and perceptions of staff and students in DIT? B.Sc. Dublin Institute of Technology.

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Eccles, J. & Barber, B. (1999). Student council, volunteering, basketball, or marching band: what kind of extracurricular involvement matters? Journal of Adolescent Research, 14(1), pp. 10-43. Ellis, R. & Taylor, Role of self-esteem job-search process. Applied Psychology, 632-640.

M. (1983). within the Journal of 68(4), pp.

Feldman, A. & Matjasko, J. (2005). The role of school-based extracurricular activities in adolescent development: a comprehensive review and future directions. Review of Educational Research, 75(2), pp. 159-210. Fredricks, J. & Eccles, J. (2006). Is extracurricular participation associated with beneficial outcomes? Concurrent and longitudinal relations. Developmental Psychology. 42(4), pp. 698-713. Finn, J. D. (1989). Withdrawing from school. Review of Educational Research. 59(2), pp. 117-142.

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Gamp, W. (1990). Participation in student activities and achievement: a covariance structural analysis. The Journal of Educational Research, 83(5): 272-278. Geraghty, J. (2010). Investigation into awareness of and involvement in Trinity College societies. Trinity College Dublin: Central Societies Committee Gilman, R. (2004). Structured extracurricular activities among adolescents: findings and implications for school psychologists. Psychology in the Schools. Psychology in the Schools, 41(1), pp. 31-41. Granovetter, M. (1973). The Strength of Weak Ties. American Journal of Sociology, 78(6), pp. 1360-1380. Granovetter, M. (1974). Getting a Job: A Study of Contacts and Careers. Cambridge, MA: Harvard University Press. Granovetter, M. (1983). The strength of weak ties: a network theory revisited. American Sociological Association. 1(1), pp. 210-233.

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Gunz, H. & Heslin, P. (2005). Reconceptualising career success. Journal of Organisational Behaviour. 26(2), pp. 105-111. Heslin, P. (2003). Self- and other-referent criteria of career success. Journal of Career Assessment. 11(3), pp. 262-286. Heslin, P. (2005). Conceptualizing and evaluating career success. Journal of Organisational Behaviour. 26(2), pp. 113-136. Howard, A. (1986). College experiences and managerial performances. Journal of Applied Psychology, 71(3), pp. 530-552. Huang, C. & Carleton, B. (2003). The relationships among leisure participation, leisure satisfaction, and life satisfaction of college students in Taiwan. Journal of Exercise Science and Fitness. 1(2), pp. 129-132. Jencks, C., Perman, L. & Rainwater, L. (1988). What is a good job? A new measure of labour-market success. The American Journal of Sociology, 93(6), pp. 1322-1357.

Kraimer, M., Seibert, J. & Crant, J. (2001). What do proactive people do? A longitudinal model linking proactive personality and career success? Personnel Psychology. 54(2), pp. 845-874. Larson, R. (2000). Toward a psychology of positive youth development. American Psychologist. 55(1), pp. 170-183. Long, J. & Caudill, S. (1991). The impact of participation in intercollegiate athletics on income and graduation. The Review of Economics and Statistics. 73(3), pp. 525-531. Mahoney, J. & Stattin, H. (2000). Leisure activities and adolescent anti-social behaviour: the role of structure and context. Journal of Adolescence, 23, pp. 113-127. Marsh, H. (1992). Extracurricular activities: beneficial extension of the traditional curriculum or subversion of academic goals? Journal of Educational Psychology. 84(4), pp. 553-562.

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Marsh, H. & Kleitman, S. (2002). Extracurricular school activities: the good, the bad, and the non-linear. Harvard Educational Review, 72(4), pp. 464-514. McNeal, R. (1995). Extracurricular activities and high school dropouts. Sociology of Education, 68(1), pp. 62-80. Mirivis, P. & Hall, D. (1994). Psychological success and the boundaryless career. Journal of Organisational Behaviour, 15(4), pp. 365-380. Montgomery, J. (1992). Job search and network composition: implications of the strength-ofweak-ties hypothesis. American Sociological Review, 57(5), pp. 586-596. Rubin, R., Bommer, W. & Baldwin, T. (2002). Using an extracurricular activity as an indicator of interpersonal skill: prudent evaluation or recruiting malpractice? Human Resource Management, 41(4), pp. 441-454. Schuh, J. H., & Laverty, M. (1983). The perceived long-term influence of holding a significant student leadership position. 162

Journal of College Student Personnel, 24(1), pp. 28-32. Seibert, S., Kraimer, M. & Liden, R. (2001). A Social Capital Theory of Success. The Academy of Management Journal, 44(2), pp. 219-237. Swanson, C. (2002). Spending time or investing time? Involvement in high school curricular and extracurricular activities as strategic action. Rationality and Society, 14(4), pp. 431-471. Tay, T., Ang, S & Dyne, L. (2006). Personality, biographical characteristics, and job interview success: a longitudinal study of the mediating effects of interviewing self-efficacy and the moderating effects of internal locus of causality. Journal of Applied Psychology, 91(2), pp. 446-454. Zaff, J. ,Moore, K., Papillo, A. & Williams, S. (2003). Implications of extracurricular activity participation during adolescence on positive outcomes. Journal of Adolescent Research, 18(6), pp. 599-630.

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CHILDHOOD OBESITY: CONTRIBUTIONS OF DEVELOPMENTAL RESEARCH TO INTERVENTIONS Bridget Finnegan Graduate 2010, Psychology finnegb@tcd.ie

ABSTRACT Childhood obesity is a rising issue entailing both health and economic consequences. This paper looks to explore developmental research into childhood obesity with reference to risk factors, protective factors, and the social implications of overweight. Interventions that draw upon these factors are discussed limitations in the research are explored. Interventions that draw upon these factors are critically evaluated.

INTRODUCTION The prevalence of childhood obesity has doubled over the past few decades (Davison & Birch, 2001), with 15% of children overweight and 25% at risk of overweight (Patrick & Nicklas, 2005). Consequences of obesity include heart disease, sleep apnoea, hypertension, type 2 diabetes, cancer, and endocrine disorders, the treatment for which could be lifelong and costly (Lobstein, Baur, & Uauy, 2004). As estimated by the National Taskforce on Obesity (2005) the subsequent health expenses are â&#x201A;Ź30million annually. Developmental research can inform policy and practice around obesity. Factors influencing childhood obesity and suggested interventions targeting these factors are discussed.

RISK FACTORS AND PROTECTIVE FACTORS Research has made important contributions to our understanding of the factors associated with obesity. The ecological model, as described by Davison & Birch (2001), suggests that child risk factors for obesity include dietary intake, physical activity and sedentary behaviour. The impact of such risk factors is moderated by factors such as age, gender. Family characteristics - parenting style, parentsâ&#x20AC;&#x2122; lifestyles - also play a role.

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Environmental factors such as school policies, demographics, and parents’ work-related demands further influence eating and activity behaviours. Patrick and Nicklas’ (2005) review of the literature investigates factors behind poor diet and offers numerous insights into how parental factors may impact on obesity in children. They note that children learn by modelling parents’ and peers’ preferences, intake and willingness to try new foods. Availability of, and repeated exposure to, healthy foods is key to developing preferences and can overcome dislike of foods. Mealtime structure is important with evidence suggesting that families who eat together consume more healthy foods. Furthermore, eating out or watching TV while eating is associated with a higher intake of fat. Parental feeding style is also significant (Birch & Fisher, 1998). The author’s found that that authoritative feeding (determining which foods are offered, allowing the child to choose, and providing rationale for healthy options) is associated with positive cognitions about healthy foods and healthier intake. Interestingly authoritarian restriction of “junkfood” is associated with increased desire for unhealthy food and higher weight. Government and social policies could also potentially promote healthy behaviour. Research indicates taste, followed by hunger and price, is the most important factor in adolescents snack choices (Story et al., 2002). Other studies demonstrate that adolescents associate junk food with pleasure, independence, and convenience whereas liking healthy food is considered odd (Chapman & Maclean, 1993). This suggests investment is required in changing meanings of food, and social perceptions of eating behaviour. As proposed by the National Taskforce on Obesity (2005), fiscal policies such as taxing unhealthy options, providing incentives for the distribution of inexpensive healthy food and investing in convenient recreational facilities or the aesthetic quality of neighbourhoods can enhance healthy eating and physical activity. Another factor which contributes to obesity levels is sedentary behaviour, such as TV viewing. TV viewing can also impact children in terms of media effects. Story et al. (2002) discuss research which indicates the number of hours children spend watching TV correlates with their consumption of the most advertised goods, including sweetened cereals, sweets, sweetened beverages, and salty snacks. Despite difficulties in empirically assessing the media impact, other research discussed 164

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emphasises that advertising effects should not be underestimated. Media effects have been found for adolescent aggression and smoking and formation of unrealistic body ideals. Regulation of marketing for unhealthy foods is recommended, as is media advocacy to promote healthy eating.

SOCIAL IMPLICATIONS OF OVERWEIGHT Overweight may carry negative social implications which interventions could target in order to improve the lives of those with obesity. In one study, overweight adolescents received significantly fewer friendship nominations from peers, and sometimes even received no friendship nominations (Strauss, Harold, & Pollack, 2009). This is worrying as the importance of friendship for the promotion of mental health is well documented (Strauss et al. 2009). Another study (Janssen et al., 2004) found overweight youths were more likely to be bullied. Additionally, overweight boys and girls aged 15-16 years were more likely to bully others. The authors suggest that one reason for these findings may be that children are heavily influenced by stereotypes associated with physical cues. “Anti- fat” stereotypes were particularly evident in a study by Musher-Eizenman et al. (2004) which found even very young children hold negative attitudes towards overweight peers, particularly when they consider weight to be within one’s control. The experiences resulting from the social implications of obesity have serious consequences. Eisenberg, Newmark-Stainer and Story (2003) revealed that teasing about weight is associated with low bodysatisfaction, low self-esteem, and suicidal tendencies. It is consequently vital that research contributes to practical and effective interventions to target the negative social implications of obesity.

INTERVENTIONS Taking aforementioned research into account, several interventions have been developed to prevent and deal with issues arising from childhood obesity. Successful interventions generally highlight the importance of a multi-disciplinary approach. For example, Nemet et al.’s (2005) intervention suggested dietary changes, nutritional education, physical activity, behavioural modifications and parental involvement produced significant changes in weight, cholesterol levels and fitness after 3 months. 165

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Impressively, these changes persisted at the 1-year follow up. More recently Gentile et al. (2009) evaluated the Switch program, targeting reduced TV viewing, increased fruit and vegetable consumption and increased physical activity at home, school and community levels. Again the importance of targeting multiple levels of influence was evident. At the 6-month follow up, there were significant changes in TV viewing and consumption of fruit and vegetables, although no effect on physical activity or BMI. The authors emphasise that these results are not trivial; obesity is a multifactorial condition, and small changes can have large long-term benefits. Results also underline the importance of family involvement in interventions. Social consequences for overweight individuals may be improved through participation in sports or extracurricular activities (Strauss, et al., 2009). Since sports activities may appear intimidating to overweight youths, provision of alternative activities could be advisable. Eisenberg et al. (2003) suggest investment in support and skills training for overweight children who experience teasing. According to Janssen et al. (2004), school interventions involving awareness of bullying, increased supervision, and victim support can reduce bullying by 30â&#x20AC;&#x201C;50%. Musher-Eizenman et al. (2004) advise educating children about diversity of body-size. Similarly, research should investigate ways to influence internal attributions for weight by discussing low-responsibility conditions, e.g. genetic disorders (Musher-Eizenman, et al., 2004). While this research offers valuable insight, several limitations are apparent. Salient sources of teasing have yet to be identified (Eisenberg et al., 2003). Future research must assess the reliability and validity of friendship selection measures as well as compare childrenâ&#x20AC;&#x2122;s attitudes with actual friendship behaviour (MuscherEizenman et al., 2004). Qualitative research may be useful in clarifying why negative stereotypes are associated with overweight individuals.

LIMITATIONS OF RESEARCH While research indicates numerous methods for preventing obesity, critical evaluation has drawn attention to the lack of investigation of predictive factors across multiple levels of influence- home, school, etc. (Story, Neumark-Stainzer & French, 2002). Further research is required to identify factors which are most influential and amenable to change. Longitudinal studies, improved psychometric properties in measurements, 166

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and more direct observation of dietary behaviour are recommended to enhance the contribution of research to interventions (Story et al. 2002). Although informative, much of the research on intervention strategies is flawed. The distinction between statistical and clinical significance constitutes one issue requiring examination. Many studies fail to track the extent to which children, parents and teachers utilise advised strategies (Nemet et al., 2009). A review by Flodmark, Marcus & Britton (2006) revealed 41% of prevention interventions investigated produced positive effect indicating prevention of childhood obesity is possible. However this finding is of little practical benefit since characteristics of effective studies were not identified. Some frequent methodological limitations of unsuccessful studies include inadequate sampling, inappropriate analysis, poor monitoring of â&#x20AC;&#x153;doseâ&#x20AC;? received by participants, and an acute lack of theoretical basis for intervention (Thomas, 2006). The question of statistical versus clinical significance is also raised.

CONCLUSION In conclusion, the research in this area is relatively beneficial in guiding practice. Based on the research discussed, key challenges facing clinicians include improving criteria for measuring overweight, development of interventions which alleviate negative social consequences of obesity, educating children, parents and teachers about consequences of unhealthy lifestyles, and how overweight can be avoided, revision of advertising standards, and further investigation of characteristics associated with successful interventions. An exploration of individual differences might also illuminate our understanding of childhood obesity. It is probable that interventions could benefit from research involving individual, emotional, and personality factors which may predispose young people toward overweight and obesity.

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REFERENCES Birch, L.L., & Fisher, J.O. (1998). Development of eating behaviours among children and adolescents. Pediatrics, 101, 539549. Chapman, G., & Maclean, H. (1993). "Junk food" and "healthy food": meanings of food in adolescent women's culture Journal of Nutrition Education and Behaviour, 25, 108-113. Davison, K.K., & Birch, L.L. (2001). Childhood overweight: a contextual model and recommendations for future research. Obesity Reviews, 2, 159171. Eisenberg, M., NeumarkStainzer, D., & Story, M. (2003). Associations of weight-based teasing and emotional well being among adolescents. Archives of Pediatrics and Adolescent Medicine, 157, 733-742. Flodmark, C., Marucs, C., & Britton, M. (2006). Interventions to prevent obesity in children and adolescents: a systematic literature review. International Journal of Obesity, 30, 579-589.

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Gentile, D., Welk, G., Eisenman, J., Reimer, R., Walsh, D., Russell, D., et al. (2009). Evaluation of a multiple ecological level child obesity prevention program: Switch what you do, view and chew. BMC Medicine, 7, 49. Janssen, I., Craig, W., Boyce, W., & Pickett, W. (2004). Associations between overweight and obesity with bullying behaviuors in school aged children. Pediatrics, 113, 11871194. Lobstein, T., Baur, L., & Uauy, R. (2004). Obesity in children and young people: a crisis in public health. Obesity Reviews, 5, 4-85. Musher-Eizenman, D., Holub, S., Barnhart-Miller, A., Goldstein, S., & EdwardsLeeper, L. (2004). Body size stigmatisation in preschool children: The role of control attributions. Journal of Pediatric Pscyhology, 29, 613-620. National Taskforce on Obesity (2005) Obesity: The Policy

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Challenges. Dublin: Department of Health and Children.

so modest. Health Education Research: Theory and practice, 21, 783-795.

Nemet, D., Barkan, S., Epstein, Y., Friedland, O., Kowen, G., & Eliakim, A. (2005). Short and long term beneficial effects of a combined dietary-behaviouralphysical activity intervention in the treatment of childhood obesity. Pediatrics, 115, 443-449. Patrick, H., & Nicklas, T. (2005). A review of family and social determinants of children's eating patterns and diet quality. Journal of the American College of Nutrition, 24, 83-92. Story, M., Neumark-Stainzer, D., & French, S. (2002). Individual and environmental influences on adolescent eating behaviours. Supplement to the Journal of the American Dietetic Association, 102, 40-51. Strauss, R., Harold, A., & Pollack, H. (2009). Social marginalisation of overweight children. Archives of Pediatrics and Adolescent Medicine, 157, 746-753. Thomas, H. (2006). Obesity prevention programs for children and youth: Why are their results 169

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PSYCHOSOCIAL FACTORS IMPACTING ON TREATMENT ADHERENCE IN DIABETES David Lydon Senior Sophister, Psychology & English dlydon@tcd.ie

ABSTRACT Diabetes is a chronic condition which, if left untreated, can lead to serious health and economic consequences. The current model of medicine, the biomedical model, has been successful in describing diabetes and identifying treatments. However, while the effectiveness of diabetes treatment has been proven in a number of studies, adherence to treatment is extremely low. The author suggests that a biopsychosocial model, with an explanatory focus beyond that of biology, may contribute to our understanding of treatment adherence in diabetes. This article explores ways in which two psychosocial factors – stigma and identity issues – impact on treatment adherence in diabetes.

AN OVERVIEW OF DIABETES Diabetes is a chronic medical condition characterised by abnormalities in glucose metabolism. There are two major types of diabetes: Type 1, often called insulin-dependent diabetes mellitus, and Type 2, often referred to as non-insulin dependent diabetes mellitus. Type 1 diabetes involves the pancreas losing its ability to produce insulin, resulting in uncontrolled elevations of blood glucose (Peyrot, McMurry, & Kruger, 1999). Insulin production in Type 2 diabetes is initially unimpaired, but cell tissues become resistant to the action of insulin. In response to the elevation of blood glucose, insulin levels increase and, for a period of time, compensate for insulin resistance. Following a number of years there is eventual damage to the pancreas due to an overworking of cells contained therein (Gonder-Frederick, Cox, & Ritterband, 2002). In the United States, diabetes is the seventh leading cause of death and the total direct and indirect costs due to diabetes in the United States have been estimated at €102 billion per year (Ciechanowski, Katon, 171

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Russo, & Walker, 2001). The prevalence of diabetes (particularly Type 2 diabetes, which composes 90% of diabetic patients; Nolan, 2006) is on the rise. A study conducted by Shaw, Sicree, and Zimmet (2010) found that the world prevalence of diabetes among adults aged 20 to 79 years by the end of 2010 will be 6.4%, or 285 million adults, and will increase to 7.7%, or 439 million adults, by 2030. Serious health complications are associated with both Type 1 and Type 2 diabetes including macrovascular damage, which can lead to heart attacks and strokes (Peyrot et al., 1999). Elevated blood glucose can also lead to microvascular damage, often resulting in kidney failure and blindness (Peyrot et al., 1999). In order to avoid such complications, lifelong treatment for diabetes is needed. The biomedical goal of modern diabetes treatment is to maintain blood glucose levels as near to normal as possible. Results from a study by the Diabetes Control and Complications Trial (DCCT Research Group, 1993), which followed over 1400 individuals with Type 1 diabetes over an average of 6.5 years, provided evidence that this treatment can delay or prevent the development of some of the serious long-term complications of diabetes. Follow-up studies have also found that the benefits of intensive diabetes management demonstrated by the DCCT Research Group continue to significantly delay or prevent such complications (Morales, 2009). Other studies have demonstrated the benefits of maintaining tight blood glucose control in Type 2 diabetes patients (Okhubo et al., 1995). While the benefits of treatment have been established, there is a low rate of treatment adherence in diabetes which leads to compromised health benefits and economic consequences (Bartels, 2004). DiMatteo (2004) examined treatment non-adherence in a number of diseases reported in studies between 1948 and 1998 and found that treatment adherence in diabetes was one of the lowest of any other disease worldwide. Adherence has been described as “the extent to which a person‟s behaviour – taking medication, following a diet, and/or executing lifestyle changes – corresponds with agreed recommendations from a health care provider” (WHO, 2003, p.3). Adherence, then, involves behavioural factors, an understanding of which requires the recognition of psychological and sociological factors which, as the following section will detail, are beyond the scope of the biomedical model.

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THE BIOMEDICAL MODEL OF HEALTH AND ILLNESS The emergence of the biomedical model The Enlightenment‟s emphasis on rationalism and the scientific method influenced the development of healthcare and led to the emergence of the biomedical model (Barrett et al., 2003). Ideas that set the groundwork for scientific medicine were positivism, reductionism, and the contribution of Descartes. Descartes stated that the mind “is entirely distinct from the body” (Descartes, 1993, p.19). This mind-body disconnection did not originate with Descartes – such a dualism was present in the work of ancient Greek philosophers such as Hippocrates (Adams, 1939) and Plato (Grosz, 1994) – but it has come to be referred to as Cartesian Dualism. Descartes introduced three important innovations to this dualism which affected the development of healthcare (Sarafino, 2002): he conceived of the body as a machine and described the mechanisms by which action and sensation occurred; he proposed that the mind and the body could communicate through the pineal gland; and believed that the human soul leaves the body at death (Sarafino, 2002). In this regard, the human body, to Descartes, was passive, mere res extensa – part of the physical world – with no intelligence or ability to self-control (Leder, 1984). Fascinated by the automatons of his day, which were able to imitate the behaviour of living things, he reconceived the human body as a machine (Leder, 1992). In contrast to the passive and mechanical body, the res cogitas – the mind – held the “essence of the self and the divine aspect of the human being” (Leder, 1984, p.29). Such a conception of dualism led many scholars of this period to regard the body as subject to the laws of mechanical causality like other components of the physical world and, thus, open to scientific experimentation (Leder, 1984). Furthermore, the Roman Catholic Church granted permission for the dissection of the body as the divine aspects of the human were now thought to be separate from the body. However, the corresponding freedom was not granted to the study of mind and behaviour as these areas of study were deemed only suitable for the domain of religion (Engel, 1977). Thus, mind-body dualism was further

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delineated through what was deemed an appropriate separation of mind and body into discrete areas of study. Following Cartesian Dualism, by the 1850s positivism and reductionism were joined to set a new agenda for medicine (Tauber, 2002). Reductionism may be defined as the practice of “analyzing and describing a complex phenomenon…in terms of its simple or fundamental constituents, especially when this is said to provide a sufficient explanation” (Oxford Dictionaries Online, 2010). The Cartesian view of the body as a machine could be considered reductionist as it suggested that all of the functioning of the body could be explained at the level of tissues and bones. With the conception of the body as machine, positivist principles could be applied to the body. Positivism holds that “the highest or only form of knowledge is the description of sensory phenomena” (Blackburn, 2005, p.284). A positivist methodology is linked to the assumption that “all of nature [is] of one piece, and the study of life [is] potentially no different in kind than the study of chemical reactions” (Tauber, 2002, p.182). The ability to apply scientific principles to the body due to the “radically materialistic thinking” that had developed was seen as a great advantage to the clinical sciences (Scheper-Hughes & Lock, 1987, p.9). The approach of the biomedical model Following the emergence of the mechanistic view of the human body, a scientific medicine emerged in the nineteenth century. Adhering to positivism and a mechanistic view of the body, this biomedicine was “characterized by scientific observation and raised on pathological anatomy” (Porter, 1999, p.306). The biomedical model attempted to remove subjective perception in favour of rational objectivity and Xavier Bichat‟s Anatomie Générale provides an insight into the way in which medicine at the beginning of the nineteenth century dismissed the subjective view of the patient in favour of objective analysis of the body. According to Bichat, taking notes at the patient‟s bedside leads to “a confusion of symptoms…a train of incoherent phenomena” and that only when the human body is dissected “this obscurity will…disappear” (Porter, 1999, p.307).

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This biomedical approach assumes that all illness has an underlying pathology that may be cured through medical intervention (Morrison & Bennett, 2006). In this way, the model privileges biological explanations at the expense of social, cultural, and biographical explanations (Atkinson, 1988). Indeed, as the biomedical model emerged from the Enlightenment‟s emphasis on science and rationalism, explanations of illness other than the biological are excluded from the model as they are “nonmaterial in form and not measureable, subjective and not objective” (Engel, 1996, p.426). This approach led Samuel Taylor Coleridge in a letter to Charles Lloyd in 1796 to say that doctors “are shallow Animals, having always employed their minds about Body and Gut, they imagine that in the whole system of things there is nothing but Gut and Body” (Griggs, 1971, p.256).

THE BIOMEDICAL MODEL AND DIABETES The biomedical model has been extremely effective at providing an understanding of diabetes. The model has also been successful in identifying treatments for diabetes. However, due to the biomedical model‟s explanatory focus, it cannot address behavioural issues impacting on adherence. This can be better understood when the treatment for diabetes is examined. The maintenance of blood glucose levels involves adherence to medication, a specific diet and exercise regime (Ciechanowski et al., 2001). The monitoring of blood glucose levels, several times a day, through the use of portable blood glucose monitors is also recommended by doctors in order to determine appropriate self-care actions (Peyrot et al., 1999). Thus, the treatment requires behaviour change and the incorporation of monitoring regimes into everyday life, aspects of treatment which the biomedical model cannot address due to its explanatory focus. George Engel‟s 1977 article, entitled “The need for a new medical model: A challenge for biomedicine”, advocated an extension of the biomedical model of health and illness to include psychological and sociological factors that impact on health and illness. Engel (1977) recognized the importance of biomedical knowledge and, as such, proposed a biopsychosocial model which would include psychological and sociological factors without abandoning valuable biomedical knowledge. Engel understood that the biomedical model was reductionist in 175

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“assum[ing] that the language of chemistry and physics will…suffice to explain biological phenomena” (Engel, 1977, p.130). His critique of the biomedical model included the observations that illness results from the interaction of diverse causal factors, that illness is not necessarily identical to a biochemical alteration, that psychological and sociological factors can determine the susceptibility to and the severity of an illness, that the sick role can be adopted in the absence of a biochemical alteration, and that the doctor-patient relationship is not one of observer and observed (Biderman, Yeheskel, & Herman, 2005). The biopsychosocial model conceives illness as resulting from interacting mechanisms at the “celluar, tissue, organismic, interpersonal, and environmental levels” and must include the “individual, his/her body and his/her surrounding environment” (Fava & Sonino, 2008, p.1). In this way, the model seeks to address many of the limitations of the biomedical model arising from its reductionist conception of illness. The model reconceptualizes the patient as a human being and values “the patient‟s subjective experience as an essential contributor to accurate diagnosis, health outcomes, and humane care” (Borrell-Carrio, Suchman, & Epstein, 2004, p.576).

DIABETES AND THE BIOPSYCHOSOCIAL MODEL A review of the diabetes literature conducted by the author highlighted a number of psychosocial factors, beyond the scope of the biomedical model, which impact on treatment adherence. This literature will be discussed with reference to a biopsychosocial model of health and illness, which has the potential to act as a framework within which to accommodate these psychosocial factors alongside biomedical knowledge. Due to the limited scope of this report, only two of the psychosocial factors that emerged from the study are explored. These are stigma and identity issues. Stigma was chosen as a factor to be explored as it is very common among the population, with some studies reporting the experience of stigma by all participants involved (Buchbinder et al., 2005). Issues of identity which have been relatively neglected in the research are also explored.

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PSYCHOSOCIAL FACTORS IMPACTING ON TREATMENT ADHERENCE IN DIABETES

Stigma Research has found that the experience of stigma is common among diabetics and often leads to treatment non-adherence. All participants in a study on adolescents with Type 1 diabetes based in the United States reported feeling stigmatized due to their diabetes (Buchbinder et al., 2005). The participants in this study were upset due to the reactions of their friends and strangers towards their diabetes. Some of the common social meanings attached to diabetes that lead to stigma include the conceptions that it is an infectious disease (Lin, Anderson, Hagerty, & Lee, 2008) and that it is a self-inflicted disease of individuals who “lack self-control, who eat to excess and are overweight” (Broom & Whittaker, 2004, p.2373). Certain forms of health promotion media have been found to reinforce the view that diabetics are “failing to take proper responsibility for their health” (Broom & Whittaker, 2004, p.2373). The treatment for diabetes can also lead to stigmatization. A participant in a study involving seven European countries (Vermeire et al., 2007) reported the experience of stigma as a result of the treatment‟s dietary requirements. One participant stated that others “make fun of [his] diet, bawling at [him]” (Vermeire et al., 2007, p.30). Additionally, the use of diabetes technology can often exacerbate stigma experienced by diabetics. Although diabetics have the choice of being able to conceal or disclose their diabetic status (Lin et al., 2008), diabetes technology can highlight diabetic status (Balfe & Jackson, 2007) and so lead them to experience stigma. Diabetes can also be confused with illegal drug use by the general public leading to stigmatisation. A study by Shiu and Wong (2002) found that the general public looked at their insulin-treated Hong Kong diabetic participants with contempt when they self-administered insulin in public places. These participants believed that the public mistook them as intravenous drug users due to the technology they used to self-administer insulin (Shiu, Kwan, & Wong, 2003). Broom and Whittaker (2004) also found this stigma due to the negative connotations which are a result of the injecting involved in insulin-administration even though the new insulin pens resemble a syringe to a lesser degree than before. 177

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Due to such stigmatizing effects of diabetes treatment, adherence to treatment is often more likely when it can be accomplished in private, hidden spaces. For instance, participants in Balfe and Jackson‟s (2007) study were more likely to carry diabetes technologies during the day when technologies could be hidden easily due to the tendency to wear more clothes and to carry larger bags than at night. Other individuals have reported that they preferred to administer insulin only while at home (Shiu et al., 2003), while some tried to avoid “other people‟s strange eyes” and inject in places such as public toilets (Shiu et al., 2003, p.150). The experience of stigma can also affect the type of technology opted for by the individual diabetes patient. For instance, one individual in Balfe and Jackson‟s (2007) study preferred injections over an insulin pump as she felt the pump would look “ugly” when she was going out (p.784). Additionally, 10 out of 12 participants in another study initially refused a change-over to insulin therapy after a recommendation from their doctor due to anxiety about stigma (Kwan, 2001; as cited in Shiu et al., 2003). Thus, individuals with diabetes often experience stigma, which can be exacerbated by aspects of diabetes treatment including dietary requirements and the use of technologies. This often results in decreasedadherence to treatment or non-adherence in order to avoid stigma. The biomedical model cannot account for psychosocial factors such as stigmatization towards diabetes. The biopsychosocial model, however, due to its consideration of the social environment and the experience of the patient, allows factors such as stigma to be taken into account. Within a biopsychosocial framework, focus can be drawn from biological to social factors in order to counter the experience of stigma. This can involve education of the general population in order to dispel myths about diabetes that lead to stigmatization. Mass media campaigns that educate the general public on the aetiology and treatment of diabetes may help to dispel negative attitudes towards diabetes and also clarify the differences between diabetics who self-administer insulin and intravenous drug users (Shiu et al., 2003). Secondly, Balfe and Jackson (2007) recommend that physicians talk to individuals using diabetes technology about the stigma they may experience when using their technologies and how best to deal with it. Finally, since health promotion has been found to reinforce negative stereotypes of diabetics (Broom & Whittaker, 2004), the language of media relating to diabetes health promotion and awareness 178

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should remain objective and refrain from perpetuating stereotypes concerning diabetes. Identity Issues Research on diabetes indicates that identity issues have a significant effect on treatment adherence. The need for identity coherence - the maintenance of personas exemplifying enduring conceptions of oneself (Swann & Bosson, 2008) – and the wish to attain one‟s desired identity affect diabetes self-management. Diabetes treatment plays an ambivalent role in identity issues, sometimes preventing individuals from achieving their identity goals - achieving their desired self and participating in activities integral to one‟s self-concept (Swann & Bosson, 2008) - and sometimes allowing individuals to attain their goals. Diabetes treatment involves the adoption of significant changes to lifestyle. The treatment and the illness itself introduce major disruptions to daily routines and activities (Mamykina, Miller, Mynatt, & Greenblatt, 2010). The experience of identity disruption can be anxiety-producing (Mendes & Akinola, 2006) and this may lead individuals to maintain a connection with their habits before they were diagnosed with diabetes in order to maintain a coherent identity between their pre- and post-diabetes perception of themselves (Mamykina et al., 2010). This practice of maintaining a sense of identity between pre- and post-diagnosis behaviours was evident in a study by Mamykina et al. (2010), which investigated the potential of a computer-based health-monitoring technology to help improve diabetes management skills. When the technology was used by individuals who had lived with diabetes for a number of years, the technology was used to record personal stories, many of which were not related to diabetes management. The stories recorded helped the individuals to maintain a consistent sense of self and to create a link between their lives with diabetes and before diagnosis. For example, one participant recorded having eaten fresh, bakery-baked bread as he and his family “usually never buy bread from the store” even though the bakery-baked bread was “a bit heavier on carbs” (Mamykina et al., 2010, p.5). Sticking to the family tradition of eating bakery-baked bread may have conflicted with the participant‟s treatment regime but, in the eyes of the participant, it was worth it. The researchers concluded that this behavioural continuity was a way of maintaining a coherent identity. This 179

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is one example of the way in which identity continuity is maintained and also highlights the way in which identity issues, factors beyond the scope of the biomedical model, can affect treatment adherence. Other research on diabetes highlights that the maintenance of a desired identity is often more important to the individual with diabetes than adhering to treatment. For example, a participant in a study by Smith, Frost, Albayrak, and Sudhakar (2006) showed the researchers a picture of her new tattoo saying That was my tattoo...that I wasn‟t supposed to get. Cause my doctor didn‟t think it‟d be a good idea. (p.316) Another participant who had recently had her nose pierced similarly stated that it was against the wishes of the doctor. For both these individuals, the desire to pursue their desired identity was more important than adhering to the doctor‟s recommendations. The wish to pursue a desired identity which conflicts with the treatment regime for diabetes has been studied at length in the university student population. Students pressure themselves to hold a „normal‟ identity (Litva, Peggs, & Moon, 2001). Indeed, research on university students with diabetes reflects this with participants in a study involving university students with diabetes desiring to be “normal” (Balfe, 2009). Balfe (2009) suggests this perceived “normality” implies pursuing the same activities as other students and preventing diabetes from affecting their student lives. Indeed, Balfe (2009) found that adherence to diabetes self-care routines became less stringent as students with diabetes participated in „normal‟ student activities such as staying up late, drinking, and going to clubs. Other research on identity issues in diabetes found that the extent to which students with diabetes adhered to their treatment regimes depended on the extent to which they accepted diabetes as part of their identities. A participant in a study by Balfe and Jackson (2007) integrated diabetes into her identity in an attempt to become „normal‟. The participant rebelled against her diabetes when she was younger by not adhering to the regimen at all. When she went to university, she accepted diabetes as part of her identity and regularly brought her testing equipment with her when she went out to drink. Bringing the technology with her, Balfe and 180

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Jackson (2007) suggest, was fuelled by a desire to feel that she was not different to others, that there was nothing wrong with diabetes or diabetes technologies. This demonstrates that accepting diabetes as part of her identity can allow patients to live as close to a „normal‟ student lifestyle as possible with the least detriment to the diabetes regime. Indeed, accepting and using the diabetes technology often enabled participants in Balfe and Jackson‟s (2007) study to fit their diabetes more easily into their student lifestyles. Technologies allowed participants to manage and control their bodies and participants acknowledged that the more control they felt they had over diabetes, the freer they felt from it (Balfe & Jackson, 2007). Participants‟ use of insulin injections, for example, allowed their “dysappearing bodies” (the dysfunctional appearance of the body; Williams, 1996) to return to a less problematic state of embodiment in which the body “is characterised by absence” (Leder, 1990, p.1). The unity between body and self may become disrupted in illness (Charmaz, 1995) as it may be difficult for individuals to lead the life they wish as they focus on their body instead of acting from it. Individuals in Balfe and Jackson‟s (2007) study were able to engage in activities without having to focus on their diabetes due to the control the diabetes technology granted them. Thus, accepting the treatment regime may allow individuals with diabetes to feel more liberated from their condition than when they reject the treatment and the technologies. As such, patients should be informed that although the treatment regime and the diabetes technology may disrupt their routines at the beginning, adherence to the treatment may allow better control of their diabetes and lead to them being freer from it. Thus, a variety of identity issues may affect the extent to which individuals adhere to their diabetes treatment regimens. The biomedical model has no framework with which to tackle or even recognize such issues as the patient is viewed as an object and the focus is centred on the underlying pathology of illness. The biopsychosocial model, in contrast, views the patient as a body-subject and recognizes the importance of psychological issues in the illness experience. This research suggests that interventions dealing with identity issues may improve levels of treatment adherence. Future research in this area could address the potential of such interventions to improve treatment 181

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adherence. For example, the research on diabetes has highlighted the way in which adherence to treatment may allow diabetes to recede into the background of the individuals life as the individual gains more control over it. As such, a pilot intervention in which the benefits of treatment adherence are discussed with in patients may prove fruitful.

CONCLUSIONS Both stigma and identity issues, psychosocial factors beyond the explanatory focus of the biomedical model, affect treatment adherence in diabetes. Taking these factors into account may increase treatment adherence. In order for this to occur, the explanatory focus of the current medical model must be expanded from one which focuses solely on the biological underpinnings of illness, to one, such as the emerging biopsychosocial model, which extends the foundations of the biomedical model to include psychological and sociological factors which impact on illness.

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