Executive Functions and Deception: an Exploration of the Relationship Between Cognitive Skills and the Ability to Deceive in University Students

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How to cite this thesis

Surname, Initial(s). (2012) Title of the thesis or dissertation. PhD. (Chemistry)/ M.Sc. (Physics)/ M.A. (Philosophy)/M.Com. (Finance) etc. [Unpublished]: University of Johannesburg. Retrieved from: https://ujcontent.uj.ac.za/vital/access/manager/Index?site_name=Research%20Output (Accessed: Date).

Executive Functions and Deception: An Exploration of the Relationship between Cognitive Skills and the Ability to Deceive in University Students

Nevenka Tenji

Submitted in fulfilment of the requirements for the degree of

Master of Arts in Psychology

in the Faculty of Humanities at the

University of Johannesburg

Supervisor: TL AUSTIN

30 January 2017

Declaration

I hereby declare that this dissertation is my own work and that all the sources used have been acknowledged. It has not been submitted for any other degree at another university or educational institution.

______

Nevenka Tenji

30 January 2017

Abstract

A number of cognitive functions are critical in the process of deception and some theorists postulate that deception is more cognitively demanding than being truthful. Furthermore, it has been theorised that enhanced cognitive functioning allows for better deceptive abilities. However, the possibility of a cognitive basis for proneness to deception has not been thoroughly investigated. This study addressed this gap in the literature and investigated whether people’s cognitive abilities are related to a tendency toward deception. A comparative study was conducted between two groups, comprised of individuals who are highly deceptive and those who are not prone to deception. The Balanced Inventory of Desirable Responding (BIDR) was completed by voluntary participants, who were comprised of Psychology students from the University of Johannesburg. Of these, 26 participants were selected for further testing by a third party (the supervisor) based on their scores. 14 of these were high scorers and 12 were low scorers. The following cognitive tests were administered to the selected participants: the Rey-Osterrieth Complex Figure Test (RCFT), the Rey Auditory Verbal Learning Test (RAVLT), Babcock Story Recall Test, Controlled Oral Word Association Test (COWAT), Comprehension Test, Digit Span Test, Trail Making Test (TMT) and the Stroop Colour Word Test. The results of the cognitive tests of low deceivers and high deceivers were compared by applying the Mann-Whitney U Test, as well as the Chi-square and Fisher’s Exact Test, in order to establish whether there is any significant difference between their cognitive abilities. The findings showed no significant relationship between cognitive ability and propensity for deception, as only two of the test conditions revealed significant findings (whereby low deceivers performed significantly better). Thus, although cognitive functions are a critical component of deception, an individual’s cognitive abilities would appear to have no influence on their tendency to be deceptive. Based on previous research in the field, alternate explanations could be that cognitive functioning are more closely associated with aptitude at deception rather than proneness to deception. Likewise, proneness to deception may find its fundamental origins from personality traits more so than cognitive abilities.

Acknowledgements

A number of individuals were instrumental in the successful completion of this study, both academically and morally. I wish to thank everyone that contributed to this process.

I would like to thank Dr. Austin for her input in this study. Thank you for the continuous support and guidance throughout the research process, which surpassed the expectations of a supervisor.

I would further like to acknowledge the people who provided the moral support that enabled me to persevere and bring this dissertation to fruition. James, thank you for your patience and understanding. To my family, thank you for the encouragement and the unrelenting belief in me.

Table of Contents

Declaration 2

Abstract 3

Acknowledgements 4

Table of Contents 5

List of Tables 10

Chapter 1: Introduction 12

Chapter 2: Literature Review 17

2.1 Introduction 17

2.2 The Evolution of Deception 17

2.3 Propensity for Deception 19

2.3.1 Gender 20

2.3.2 Age 20

2.3.3 Individual differences 21

2.3.3.1 Manipulativeness 21

2.3.3.2 Impression management 22

2.3.3.3 Sociability 22

2.3.3.4 Socialization and responsibility 23

2.3.3.5 Relationship quality 23

2.4 Prosocial Deception 24

2.5 Impression Management 25

2.5.1 Motives of impression management 27

2.5.2 Impression construction 29

2.5.3 Strategies of impression management 31

2.5.4 Distinguishing between impression management and self-deception 32

2.6 Self-deception 32

2.6.1 Types of self-deception 33

2.6.1.1 Biased information search 33

2.6.1.2 Biased interpretation 34

2.6.1.3 Misremembering 35

2.6.1.4 Rationalization 35

2.6.1.5 Convincing the self that the deception is the truth 36

2.6.2 Psychological and cognitive processes of self-deception 37

2.6.2.1 Implicit and explicit memory 38

2.6.2.2 Implicit and explicit attitudes 39

2.6.2.3 Automatic and controlled processes 39

2.7 Cognition of Deception 40

2.7.1 Cognitive load 41

2.7.2 Executive functions 42

2.8 Cognitive Theories of Deception 43

2.8.1 Four-Factor theory of deception 43

2.8.2 Interpersonal Deception Theory 43

2.8.3 Neural-cognitive theory of deception 44

2.8.4 Preoccupation Model of Secrecy 44

2.8.5 Activation-Decision-Construction Model 45

2.8.5.1 Activation 46

2.8.5.2 Decision 46

2.8.5.3 Construction 47

2.9 Cognitive Functions involved in Deception 48

2.9.1 Memory 49

2.9.2 Response inhibition 51

2.9.3 Attention 51

2.9.4 Planning and judgement 52

2.9.5 Verbal efficiency 52

2.10 Conclusion 52

Chapter 3: Research Methodology 54

3.1 Introduction 54

3.2 Research Design 54

3.3 Participants and Sampling 54

3.4 Measuring Instruments 55

3.4.1 Biographical Questionnaire 55

3.4.2 Balanced Inventory of Desirable Responding (BIDR) 55

3.4.3 Rey-Osterrieth Complex Figure Test (RCFT) 56

3.4.4 Rey Auditory Verbal Learning Test (RAVLT) 58

3.4.5 Babcock Story Recall Test 61

3.4.6 Controlled Oral Word Association Test (COWAT) 62

3.4.7 Comprehension Test 63

3.4.8 Digit Span Test 65

3.4.9 Trail Making Test (TMT) 66

3.4.10 Stroop Colour Word Test 67

3.5 Procedure 69

3.6 Data Analysis 69

3.7 Ethical Considerations 70

Chapter 4: Results 71

4.1 Introduction 71

4.2 Descriptive Statistics 71

4.2.1 Age 72

4.2.2 Gender 73

4.2.3 Race 74

4.3 Inferential Statistics 75

4.3.1 Mann-Whitney Test 75

4.3.2 Chi-Square 79

4.4 Conclusion 97

Chapter 5: Discussion and Conclusion 98

5.1 Introduction 98

5.2 Demographic Frequency 98

5.3 Trends 99

5.4 Explanation 100

5.5 Theoretical and Practical Implications 102

5.6 Limitations 103

5.7 Concluding Remarks 104

References 105

Appendix

Appendix A: Biographical Questionnaire 140

Appendix B: Balanced Inventory of Desirable Responding (BIDR) 141

Tables

Chapter 4: Results

Table 1: Age of participants

Table 2: Gender of participants

Table 3: Race of participants

Table 4: Mann-Whitney Test ranks results

Table 5: Summary of findings of the Mann-Whitney Test

Table 6: Results on the RAVLT Immediate Recall Trial

Table 7: Calculation of Chi-Square Test for the RAVLT Immediate Recall Phase

Table 8: Results on the RAVLT T1-T5

Table 9: Calculation of Chi-Square Test on the RAVLT T1-T5

Table 10: Results on the RAVLT Distractor Trial

Table 11: Calculation of Chi-Square on the RAVLT Distractor Trial

Table 12: Results on the RAVLT Trial 6

Table 13: Calculation of the Chi-Square Test on the RAVLT Trial 6

Table 14: Results on the RAVLT Delayed Recall Trial

Table 15: Calculation of the Chi-Square Test on the RAVLT Delayed Recall Trial

Table 16: Results on the RAVLT Repetition Condition

Table 17: Calculation of the Chi-Square Test on the RAVLT Repetition Condition

Table 18: Results on the Babcock Immediate Recall Trial

Table 19: Calculation of the Chi-Square Test on the Babcock Immediate Recall Trial

Table 20: Results on the Babcock Delayed Recall Trial

Table 21: Calculation of the Chi-Square Test on the Babcock Delayed Recall Trial

Table 22: Results on the RCFT Copy Phase

Table 23: Calculation of the Chi-Square Test on the RCFT Copy Phase

Table 24: Results on the RCFT Immediate Recall Phase

Table 25: Calculation of the Chi-Square Test on the RCFT Immediate Recall Phase

Table 26: Results on the RCFT Delayed Recall Phase

Table 27: Calculation of the Chi-Square Test on the RCFT Delayed Recall Phase

Table 28: Results on the Stroop Test

Table 29: Calculation of the Chi-Square Test on the Stroop Test

Table 30: Results on the Digits Forward Test

Table 31: Calculation of the Chi-Square Test on the Digits Forward Test

Table 32: Results on the Digits Backwards Test

Table 33: Calculation of the Chi-Square Test on the Digits Backwards Test

Table 34: Results on the TMT – Part A

Table 35: Calculation of the Chi-Square Test on the TMT – Part A

Table 36: Results on the TMT – Part B

Table 37: Calculation of the Chi-Square Test on the TMT – Part B

Table 38: Results on the Comprehension Test

Table 39: Calculation of the Chi-Square Test on the Comprehension Test

Table 40: Results on the COWAT

Table 41: Calculation of the Chi-Square Test on the COWAT

Chapter 1:

Introduction

Despite the fact that deception if often viewed as a negative trait, and honesty is valued within most societies (Kashy & DePaulo, 1996; Nyberg, 1993; Saarni & Lewis, 1993; Saxe, 1994; Walczyk, Roper, Seemann, & Humphrey, 2003), it is a common occurrence within everyday life and is an intrinsic part of being human (Abe, 2011; Carrion, Keenan, & Sebanz, 2010; DePaulo & Kashy, 1998; DePaulo, Kashy, Kirkendol, Wyer, & Epstein, 1996; Dunbar et al., 2016; Ennis, Vrij, & Chance, 2008; Gombos, 2006; Hayashi et al., 2014; Kashy & DePaulo, 1996; Knapp, 2008; Levine & McCornack, 2014; Lewis, 2015; Martinez-Gonzalez, Lopez, Iglesias, & Verdejo-Garcia, 2016; Talwar & Crossman, 2011; Visu-Petra, Miclea, Bus, & Visu- Petra, 2014; Walczyk et al., 2003; Zagorin, 1996). It is a critical aspect of social interaction and is often used in a number of settings as a method to define social relationships, as a source of polite communication, in order to avoid conflict, or to enhance social acceptance (Abe, 2011; DePaulo & Kashy, 1998; DePaulo et al., 1996; Dunbar et al., 2016; Ennis et al., 2008; Gombos, 2006; Hayashi et al., 2014; Kashy & DePaulo, 1996; Lindskold & Han, 1986; Lindskold & Walters, 1983; Talwar & Crossman, 2011; Zagorin, 1996). Nietzche (1968) stated that lies are necessary to continue engaging in life and to prevail over the harsh nature of reality.

There is no universally accepted definition of deception and it is often used interchangeably with lying within the literature (Ennis et al., 2008; Mahon, 2007, 2008). It is therefore essential to make a distinction between lying and deception from the outset. For the purpose of this study, deception is regarded as a psychological process whereby a person consciously and knowingly attempts to mislead another individual to believe what the deceiver knows to be false with the use of an action, verbal statement, or any other means (Abe, 2011; Dunbar et al., 2016; Gombos, 2006; Hayashi et al., 2014; Levine, 2014; Mahon, 2007; Talwar & Crossman, 2011; Walczyk et al., 2003). Vrij, Fisher, Mann and Leal (2008) looked at various forms of deception and formulated the following definition thereof: “a successful or unsuccessful deliberate attempt, without forewarning, to create in

12 another a belief which the communicator considers to be untrue” (p.15). Deception could entail omitting the truth, exaggerating the truth or casting doubt on the truth (Ennis et al., 2008; von Hippel & Trivers, 2011).

In contrast, lying is considered to be the process whereby a person deliberately makes a statement which he/she believes to be false, with the intention of misleading another individual (Bok, 1999; Dunbar et al., 2016; Gert, 2004; Levine, 2014; Mahon, 2007; 2008; Metts, 1989; Williams, 2002). Lying is an aspect that falls under the umbrella of deception because it communicates deception through means of a verbal statement. For the purpose of this research, a lie is defined as a “deliberate false statement that the speaker warrants to be true” (Carson, 2010, p.15). Therefore, this study pertains to deception because it does not focus exclusively on misleading others in the form of verbal statements, but also includes behaviour and one’s own personal deceptive beliefs about oneself (deVries, Zettler, & Hilbig, 2014; Moomal & Henzi, 2000; Visu-Petra et al., 2014). However, in order to establish an all-encompassing understanding of deception, the literature on lying has been included, as it forms a constituent of deception (Bok, 1999; Carson, 2010; Dunbar et al., 2016; Gert, 2004; Levine, 2014; Mahon, 2007; 2008; Metts, 1989; Williams, 2002).

There are many different types of deception, which can usually be classified as antisocial or prosocial (Abe, 2011; Bryant, 2008; DePaulo & Kashy, 1998; DePaulo et al., 1996; Dunbar et al., 2016; Guthrie & Kunkel, 2013; Hayashi et al., 2014; K. Lee, 2013; Lindskold & Han, 1986; Lindskold & Walters, 1983; Talwar & Crossman, 2011; Vrij, 2000), and social guides exist as to when deception is acceptable and when it is not (Bryant, 2008; DePaulo et al., 1996; Dunbar et al., 2016). Research suggests that there are factors that influence the likelihood of deception being chosen over honesty. These include the social context, the nature of the relationship between the people within the interaction and the information available in memory (Gombos, 2006; K. Lee, 2013; Levine & McCornack, 2014; Tyler & Feldman, 2004; Walczyk et al., 2003). Furthermore, there are traits that characterise a good liar (Vrij, Granhag, & Mann, 2010), and individual differences in the propensity for deception, including

13 age, gender and certain personality traits (DePaulo, Epstein, & Wyer, 1993; DePaulo et al., 1996; Dunbar et al., 2016; Kashy & DePaulo, 1996; Levine & McCornack, 2014; Serota & Levine, 2015; Serota, Levine, & Boster, 2010).

Many psychologists have theorized about the cognitive processes involved in deception and the behavioral manifestations thereof (Buller & Burgoon, 1996; Gombos, 2006; Lane & Wegner, 1995; Mohamed et al., 2006; Seigman & Reynolds, 1983; Vrij & Mann, 2001; Walczyk et al., 2003; Zuckerman, DePaulo, & Rosenthal, 1981). There is a growing belief that deception is more cognitively demanding than being truthful due to the number of cognitive functions necessary in the process of deceiving (Carrion et al., 2010; Debey, Ridderinkhof, De Houwer, De Schryver, & Verschuere, 2015; Gombos, 2006; Johnson Jr., Barnhardt, & Zhu, 2004; McCornack, 1997; Visu-Petra et al., 2014; Vrij, 2000; Vrij et al., 2010; Vrij et al., 2008; Walczyk, Harris, Duck, & Mulay, 2014). Among the cognitive functions that are involved in deception, executive processes are a crucial factor. They are associated with cognitive activities such as directed attention, memory and response inhibition, all of which are involved in deception (Botvinick, Braver, Barch, Carter, & Cohen, 2001; Buller & Burgoon, 1996; Carter et al., 1998; Gehring & Knight, 2000; Gombos, 2006; Johnson Jr. et al., 2004; Lane & Wegner, 1995; Mohamed et al., 2006; Talwar & Crossman, 2011; Turken & Swick, 1999; Visu-Petra et al., 2014; Walczyk et al., 2003; Zuckerman et al., 1981).

It has further been hypothesized that people who possess high intelligence, fast mental processing, good planning, verbal eloquence and satisfactory memory tend to be good liars (Ekman & Frank, 1993; Vrij et al., 2010; Vrij & Mann, 2001). As such, various theories of deception predict that the limitation of these cognitive resources would significantly increase the difficulty of successfully deceiving another individual (Buller & Burgoon, 1996; DePaulo, & Rosenthal, 1981; Gombos, 2006; Lane & Wegner, 1995; Mohamed et al., 2006; Walczyk et al., 2003; Zuckerman et al., 1981). However, the possibility of a cognitive basis for proneness to deception has not been extensively investigated, and the cognitive and neural processes involved in deceptive tendency are as yet not thoroughly understood. There is little indication as

14 to whether superior cognitive abilities would, by making an individual better at deception, also make them more prone to deception.

There are numerous conceivable and practical implications of a more thorough understanding of the cognitive functions involved in deception. This study speaks to the gap in the literature on the underlying factors that determine propensity for deception. As deception is such an integral aspect of human interaction and social communication, a more thorough understanding into the cognitive functions involved in deception would add to the body of knowledge in areas such as social psychology and human communication (Abe, 2011; Carrion et al., 2010; DePaulo & Kashy, 1998; DePaulo et al., 1996; Dunbar et al., 2016; Ennis et al., 2008; Farrow, Burgees, Wilkinson, & Hunter, 2015; Gombos et al., 2006; Hayashi et al., 2014; Kashy & DePaulo, 1996; Knapp, 2008; Levine & McCornack, 2014; Martinez-Gonzalez et al., 2016; Talwar & Crossman, 2011; Visu-Petra et al., 2014; Walczyk et al., 2003; Zagorin, 1996).

Other areas that would benefit from further research into deception include developmental and forensic psychology (Gombos, 2006). One of the factors that have been linked to frequency of deception is age (DePaulo et al., 1996; Kashy & DePaulo, 1996; Serota & Levine, 2015). As a result of the link between cognitive ability and deception (Buller & Burgoon, 1996; Carrion et al., 2010; Debey et al., 2015; Gombos, 2006; Johnson Jr. et al., 2004; Lane & Wegner, 1995; McCornack, 1997; Mohamed et al., 2006; Seigman & Reynolds, 1983; Visu-Petra et al., 2014; Vrij, 2000; Vrij & Mann, 2001; Vrij et al., 2010; Vrij et al., 2008; Walczyk et al., 2003; Walczyk et al., 2014; Zuckerman et al., 1981), deceptive ability may change over time due to the decline in certain executive functions with old age (Gombos, 2006; Hasher & Zacks, 1988). Research on cognitive processing and deception can also be directly related to forensic psychology, with specific reference to interrogation methods and lie detection (Vrij, Granhag, Mann, & Leal, 2011; Vrij & Mann, 2001; Vrij et al., 2008). Such research can further facilitate an enhanced understanding of psychopathology (Farrow et al., 2015; Troisi, 2011).

By investigating the cognitive processes associated with deception, it is possible to gain further comprehension of abnormal conditions and the underlying cognitive processes thereof (Farrow et al., 2015; Troisi, 2011). Self-deception and impression management are pertinent to clinical psychiatry. Impression management may contain a component of psychopathic or antisocial behaviour, while self-deception plays a role in personal adjustment and ego psychology, as well as the conceptualisation of self-esteem. Munchausen’s syndrome and anorexia nervosa are two examples of disorders that involve such deceptive comportments (Farrow et al., 2015). Deception has also been linked to the psychological factors that are fundamental in disease simulation. For example, malingerers and individuals with factitious disorders simulate illness and feign physical symptoms in order to evoke sympathy from others and to benefit from the privileges that sick people are afforded by society. Similarly, self-deception is involved in somatoform disorders, whereby individuals display symptoms which cannot be explained by any clinical disorder (Farrow et al., 2015; Krahn, Bostwick, & Stonnington, 2008; Troisi, 2011). However, in this instance, individuals truly believe themselves to be ill (Krahn et al., 2008; Troisi, 2011).

Therefore, this study aims to add to the body of knowledge within these spheres of psychology. The principal aim of this study, however, is to investigate whether there is a relationship between cognitive ability and proneness to deception. It does so by undertaking an extensive review of the available literature related to the topics in question. This is followed by a detailed explanation of the methodological procedure used to compare the cognitive abilities of individuals who are prone to deception with those of people who are less so inclined. The results are exhibited and then discussed with reference to the available literature, followed by concluding remarks.

Chapter 2:

Literature Review

2.1 Introduction

This chapter aims to explore the available literature on deception as a psychological construct and the cognitive processes involved therein. A discussion of the evolution of deception will be provided, followed by clarification on some of the factors that determine why certain individuals engage in deception more frequently than others. A thorough explanation of prosocial deception will be given, followed by an in depth investigation into the two types of deception that are most relevant to this study – impression management and self-deception. This will include a detailed look into the various models that explain the goals and strategies of each of these categories of deception. Cognitive theories of deception will be explored, with emphasis on the cognitive process involved in deception. The most prominent cognitive functions that emerged will then be outlined, with supporting evidence from the studies that have contributed to this knowledge. The chapter will conclude with a summation of the pertinent findings and how they relate to the current study.

2.2 The Evolution of Deception

Deception is a common phenomenon that takes place within daily living and is a normal part of human life (Abe, 2011; Carrion et al., 2010; DePaulo & Kashy, 1998; DePaulo et al., 1996; Dunbar et al., 2016; Ennis et al., 2008; Gombos, 2006; Hayashi et al., 2014; Kashy & DePaulo, 1996; Knapp, 2008; Levine & McCornack, 2014; Lewis, 2015; Martinez-Gonzalez et al., 2016; Talwar & Crossman, 2011; Visu- Petra et al., 2014; Walczyk et al., 2003; Zagorin, 1996). It has evolved as a strategy for reassuring survival and gaining resources (DePaulo & Kashy, 1998; Moomal & Henzi, 2000; Steinel & De Dreu, 2004; von Hippel & Trivers, 2011). Social acceptance is essential for the survival of the individual within their social environment and, as such, deception is often necessary to ensure the approval of one’s social group (Abe, 2011; DePaulo & Kashy, 1998; Ennis et al., 2008; Hayashi et al., 2014; Lindskold & Han, 1986; Lindskold & Walters, 1983; Moomal & Henzi,

2000; Talwar & Crossman, 2011; Talwar, Murphy & Lee, 2007). Social acceptance is also important for the maintenance of a positive self-concept (Dunbar et al., 2016; Leary & Kowalski, 1990; Mead, 1934; Tajfel & Turner, 1979).

Social identity theory suggests that the self-concept is moulded not only by an individual’s personality traits and unique characteristics, but is also significantly influenced by their relationships with their social groups. A fundamental supposition of social identity theory is that people endeavour to generate and sustain a positively distinguishing and dignified social identity that would enhance their self-worth (Dunbar et al., 2016; Tajfel & Turner, 1979). As deception is sometimes necessary to achieve social recognition, this can be expanded to also apply to a positive social identity (Dunbar et al., 2016). This kind of deception, known as prosocial deception, serves to protect the listener from a hurtful truth or make oneself appear better to them, therefore ensuring continued social approval (Abe, 2011; DePaulo & Kashy, 1998; Ennis et al., 2008; Hayashi et al., 2014; Kashy & DePaulo, 1996; Lindskold & Han, 1986; Lindskold & Walters, 1983; Moomal & Henzi, 2000; Serota & Levine, 2015; Talwar & Crossman, 2011; Talwar et al., 2007). Therefore, von Hippel and Trivers (2011) proposed that human psychology has evolved in such a way that people are prone to deception.

Since successful deception is such an important aspect of social acceptance and social identity, deceptive methods have had to evolve over time (von Hippel & Trivers, 2011). Successful deception can result in significant benefits for the deceiver, at the expense of the deceived (DePaulo, 2004; von Hippel & Trivers, 2011). On the other hand, unsuccessful deception can have negative consequences including retaliation and exclusion, as people often react with anger and other negative emotions when they discover that they have been deceived (Haselton, Buss, Oubaid, & Angleitner, 2005; Schweitzer, Hershey, & Bradlow, 2006; von Hippel & Trivers, 2011). Therefore, deceptive processes have evolved, as natural selection ensures that new methods of detection develop, while simultaneously new approaches to deception are established (Moomal & Henzi, 2000; Trivers, 2000, 2009; von Hippel & Trivers, 2011).

Self-deception might be crucial to this co-evolutionary struggle for a number of reasons (von Hippel & Trivers, 2011). Self-deception makes it possible for deceivers to avoid detection efforts by convincing themselves that the deception in question is the truth, or that their reasons for deception are justified (Ceci, Loftus, Leichtman, & Bruck, 1994; Kay, Gaucher, Napier, Callan, & Laurin, 2008; Norris & Inglehart, 2004; Trivers, 2000, 2009; von Hippel & Trivers, 2011; Whitson & Galinsky, 2008; Zaragoza & Mitchell, 1996). By doing so, they would no longer exhibit the cues of consciously arbitrated deception (von Hippel & Trivers, 2011). Self-deception would also reduce the repercussions if the deception were to be uncovered. The intentions of the deceiver are fundamental in determining whether the deceived party reacts with anger and retribution. Thus, by deceiving oneself, the deception might be viewed as less malicious (Schweitzer et al. 2006; Stouten, De Crememer, & van Dijk, 2006; von Hippel & Trivers, 2011). Therefore, self-deception is an evolutionary by- product of interpersonal deception (Farrow et al., 2015; Trivers, 2011; von Hippel & Triver, 2011). However, not all people engage in deception with the same frequency (DePaulo et al., 1996; Kashy & DePaulo, 1996; Serota & Levine, 2015; Serota et al., 2010).

2.3 Propensity for Deception

There is a considerable amount of research done on people’s ability for successful deception and the cues that emerge as a result of deception (DePaulo & Rosenthal, 1979; Keating & Heltman, 1994; Riggio & Friedman, 1983). Researchers have also looked into the frequency of deception and provided estimates of between 0.59 to 1.96 lies per day (DePaulo et al., 1996; George & Robb, 2008; Hancock, Thom- Santelli, & Ritchie, 2004; Serota & Levine, 2015; Serota et al., 2010). Although little is known about the aspects that affect propensity for deception, research has found that some people do not engage in deception as often as others (DePaulo et al., 1996; Kashy & DePaulo, 1996; Serota & Levine, 2015; Serota et al., 2010).

In their study, Serota and colleagues (2010) examined a cross-section of the adult population of the United States, and discovered that 5% of the participants were responsible for 50% of the lies that were reported. DePaulo et al. (1996) confirmed

19 this, as their participants reported telling between 0 and 46 lies within the space of a week. Serota and Levine’s (2015) findings were in line with this, as their research established that most people do not lie often, while a small portion of the population reported more frequent deceptive behaviour. Some differences have been identified between people who engage in deception often and those that are less deceptive, including gender, age and certain individual differences, as discussed below (DePaulo et al., 1996; Kashy & DePaulo, 1996; Serota & Levine, 2015; Serota et al., 2010).

2.3.1 Gender. There is varying data in the literature on whether males or females tend to lie more. Some researchers have reported that men are more prone to deception (Serota & Levine, 2015; Serota et al., 2010). In contrast, DePaulo et al. (1996) found no difference in the propensity to lie between women and men, although they noted that women’s lies tend to be more selfless than that of men. This was consistent with the outcomes of other studies on the topic. Women tend to be deceptive in order to benefit others or to avoid offending the target (DePaulo et al., 1993). DePaulo and colleagues (1996) further revealed that this is particularly true when women interact with other women. Another factor that has been shown to have an impact on the tendency for deception is age (DePaulo et al., 1996; Serota et al., 2010; Serota & Levine, 2015).

2.3.2 Age. The ability to lie starts in early childhood and is associated with acquiring communication skills, perspective and theory of mind (Knapp, 2008; Vasek, 1986). As children reach adolescence, lying becomes more frequent and they become more adept at deceiving others (Jensen et al., 2004; Serota et al., 2010). However, lying becomes less acceptable in adulthood (Jensen et al., 2004; Kashy & DePaulo, 1996; Nyberg, 1993; Saarni & Lewis, 1993; Saxe, 1994; Walczyk et al., 2003). Research has found that the rate of lying decreases with age (DePaulo et al., 1996; Serota et al., 2010; Serota & Levine, 2015). Serota et al. (2010) suggested that aside from deception becoming less tolerable in adulthood, it is also possible that maturity deters people from using deception as a means to achieve one’s goals.

2.3.3 Individual differences. A number of personality traits have been identified that correlate with higher rates of deception (DePaulo et al., 1996; Kashy & DePaulo, 1996). Kashy and DePaulo (1996) found that people who have a higher tendency for lying are those that are manipulative, extroverted, exhibit higher levels of impression management, are less responsible, and have less rewarding same-sex relationships. Although their study relates to lying specifically, these findings could be extended to apply to deception as a whole, since lying is a form of deception (Bok, 1999; Dunbar et al., 2016; Gert, 2004; Levine, 2014; Mahon, 2007; 2008; Metts, 1989; Williams, 2002).

2.3.3.1 Manipulativeness. As previously noted, lying and deception can be used to achieve goals within social interactions, such as influencing people and gaining friends (Abe, 2011; DePaulo & Kashy, 1998; Ennis et al., 2008; Hayashi et al., 2014; Kashy & DePaulo, 1996; Lindskold & Han, 1986; Lindskold & Walters, 1983; Moomal & Henzi, 2000; Serota & Levine, 2015; Talwar & Crossman, 2011; Talwar et al., 2007), which is characteristic of manipulative individuals (Kashy & DePaulo, 1996). Vrij et al. (2010) indicated that manipulators lie frequently, have no moral principles when they are deceptive, are confident in their lies, and do not experience deception as cognitively demanding.

This manipulative use of deception is one of the core aspects of the personality construct of Machiavellianism. Individuals with high levels of Machiavellianism see others as pessimistic, are not concerned with morality in the conventional sense and openly admit to lying, cheating and manipulating people to achieve their goals (Christie & Geis, 1970; Falbo, 1977). An associated construct, social adroitness (Jackson, 1976, 1978), possibly reflects the interpersonal features of manipulativeness more accurately and with less negative implications (Kashy & DePaulo, 1996). By comparing the rate of lying with measures of social adroitness and Machiavellian, Kashy and DePaulo (1996) found that manipulative people lie more than those who are less manipulative.

2.3.3.2 Impression management. In contrast to manipulative people, who try to influence others according to their own agendas, people who are high in impression management manipulate themselves to appeal to other people (Cervellione, Lee, & Bonanno, 2009; Cole & Rozell, 2011; DePaulo et al., 1996; deVries et al., 2014; Farrow et al., 2015; Kashy & DePaulo, 1996; Leary & Kowalski, 1990; McGowan, Prapavessis, & Wesch, 2008; Schlenker, 1980; Visu-Petra et al., 2014). From the perspective that deception is an integral part of social life (Abe, 2011; DePaulo & Kashy, 1998; DePaulo et al., 1996; Dunbar et al., 2016; Ennis et al., 2008; Hayashi et al., 2014; Kashy & DePaulo, 1996; Lindskold & Han, 1986; Lindskold & Walters, 1983; Talwar & Crossman, 2011; Zagorin, 1996), impression management was found to be one of the most important predictors of lying tendency (Kashy & DePaulo, 1996).

This motivation to appear good to others, and attention to what other people think, could be summed up in the personality traits public self-consciousness (Fenigstein, Scheier, & Buss, 1975; Kashy & DePaulo, 1996) and other-directedness (Briggs, Cheek, & Buss, 1980). Kashy and DePaulo (1996) found that people who are more concerned with how they appear to others would be likely to tell more lies than people who are less conscious of themselves as social beings. They further argued that the social purposes of impression management and deception as a whole, such as making oneself seem more appealing or ensuring that others feel better, would be especially beneficial to more sociable people.

2.3.3.3 Sociability. With consideration to the viewpoint that deception is a crucial aspect in the facilitation of appropriate social relationships (Cervellione et al., 2009; DePaulo et al., 1996; deVries et al., 2014; Hermann & Arkin, 2013; Leary & Kowalski, 1990; Martinez-Gonzalez et al., 2016; McGowan et al., 2008; Mijovic- Prelec & Prelec, 2010; Moomal & Henzi, 2000; Paulhus, 1988; Visu-Petra et al., 2014; von Hippel & Trivers, 2011), people who engage more frequently in social settings may have more need for social forms of deception. As a result of this, these people might use deception more regularly and become more practiced at it, to the point of the formation of a habit to be deceptive when necessary. Kashy and

DePaulo (1996) found that extroverted people tend to lie more than introverts. They also showed that it is not simply that extroverts have more opportunities for deception, but that their rate of deception is higher. Thus, given the same number of opportunities, extroverts will lie more than introverts. However, the inverse was found to be true for people who have a more thorough understanding of and association with the social knowledge of their society.

2.3.3.4 Socialization and responsibility. Since lying and deception are viewed as immoral in most societies and honesty is perceived as a virtue (Kashy & DePaulo, 1996; Nyberg, 1993; Saarni & Lewis, 1993; Saxe, 1994; Walczyk et al., 2003), people who are highly socialized into the cultural norms of their society would be less likely to engage in lying and deception. These people pride themselves on integrity and morality, and these values become inherently part of their identity. As such, they would perceive deception as fundamentally wrong and would therefore avoid engaging in such activities (Kashy & DePaulo, 1996).

Kashy and DePaulo (1996) used the Responsibility scale, which measures a person’s level of socialization (Jackson, 1976, 1978), to identify people who abide by and defend conventional morality. These would be people who are described as responsible, truthful, moral, ethical, principled, honorable, conscientious, reliable, unwavering and forthright (Kashy & DePaulo, 1996; Jackson, 1976). It was found that more responsible people tend to lie less than their irresponsible counterparts. Furthermore, they discovered that older people tend to score higher on the responsibility scale than younger people (Kashy & DePaulo, 1996), which may aid in explaining the correlation between age and propensity for deception, as reported on earlier (DePaulo et al., 1996; Serota et al., 2010; Serota & Levine, 2015).

2.3.3.5 Relationship quality. A further factor that has an influence on rate of lying is the quality of relationships (DePaulo et al., 1996; Kashy & DePaulo, 1996). DePaulo et al. (1996) found that people lied more often in less intimate and pleasant relationships, whereas they were generally more honest in closer and more

23 rewarding relationships. As a result, Kashy and DePaulo (1996) predicted that people who typically perceive their relationships as particularly meaningful would also tell fewer lies overall. However, their findings refuted this where opposite-sex relationships were concerned. Nevertheless, the most reliable predictor of lying was the quality of same-sex relationships, as people with more satisfying same-sex relationships were found to tell fewer lies than those with less fulfilling ones. This was especially true of self-centered lies (Kashy & DePaulo, 1996).

2.4 Prosocial Deception

Although there are variations in people’s beliefs about the acceptability of deception (Kashy & DePaulo, 1996; Nyberg, 1993; Saarni & Lewis, 1993; Saxe, 1994; Walczyk et al., 2003), DePaulo et al. (1996) suggested that deception is not usually used to achieve goals such as material advantage or financial gain, but rather for less physical rewards such as affection, admiration and respect. Some forms of deception can be classified as anti-social, while others are considered to be prosocial (Abe, 2011; Bryant, 2008; DePaulo & Kashy, 1998; DePaulo et al., 1996; Dunbar et al., 2016; Guthrie & Kunkel, 2013; Hayashi et al., 2014; K. Lee, 2013; Lindskold & Han, 1986; Lindskold & Walters, 1983; Talwar & Crossman, 2011; Vrij, 2000). Anti-social deception is thought to be immoral and is usually used for personal gain. This type of self-serving deception is generally judged more seriously and is more detrimental to interpersonal relationships (Abe, 2011; DePaulo & Kashy, 1998; Dunbar et al., 2016; Guthrie & Kunkel, 2013; Hayashi et al., 2014; Knapp, 2006; Lindskold & Han, 1986; Lindskold & Walters, 1983; Talwar & Crossman, 2011).

On the other hand, prosocial deception is considered crucial for the facilitation of appropriate social interactions and social relationships. It is believed to be altruistic or to be aimed at benefitting someone other than the deceiver or protecting someone from a hurtful truth (Abe, 2011; DePaulo & Kashy, 1998; Dunbar et al., 2016; Ennis et al., 2008; Guthrie & Kunkel, 2013; Hayashi et al., 2014; Lindskold & Han, 1986; Lindskold & Walters, 1983; Ning & Cross, 2007; Seiter, Bruschke, & Bai, 2002; Serota & Levine, 2015; Talwar & Crossman, 2011). For example, a person might

24 agree with someone so as not to create conflict, or give them a compliment to enhance their self-confidence, even if they do not necessarily believe what they are saying. Prosocial deception is also received more favourably than anti-social deception, as the intentions of the deceiver are not viewed to be as negative as those of antisocial deception (Dunbar et al., 2016; Ning & Cross, 2007; Seiter et al., 2002). The seriousness of deception can also vary based on cultural beliefs and the relational closeness of the people involved (Backbier, Hoogstraten, & Terwogt- Kouwenhoven, 1997; Seiter et al., 2002).

There are many types of prosocial deception that serve to enhance social acceptance and to facilitate relationships with others. These often entail presenting oneself, either consciously or unconsciously, as better, stronger, more accomplished, or more moral than one is in reality (Cervellione et al., 2009; deVries et al., 2014; Hermann & Arkin, 2013; Leary & Kowalski, 1990; Martinez-Gonzalez et al., 2016; McGowan et al., 2008; Mijovic-Prelec & Prelec, 2010; Moomal & Henzi, 2000; Paulhus, 1988; Visu-Petra et al., 2014; von Hippel & Trivers, 2011). These self-enhancing phenomena can be found among a variety of different cultures and in diverse settings, likely because of the social benefits thereof (Alicke & Sedikides, 2009; von Hippel & Trivers, 2011). Throughout almost all cultures, people have an intrinsic interest in how they are perceived by others, as this affects how they are evaluated and treated (Cole & Rozell, 2011; Leary & Kowalski, 1990). The classifications of prosocial deception that are relevant to this study are impression management and self-deception.

2.5 Impression Management

Also referred to as self-presentation or socially desirable responding, impression management involves one’s efforts at manipulating other people’s impressions of them and ensuring that they are viewed in a positive light by others (Bozeman & Kacmar, 1997; Cervellione et al., 2009; Cheng, Huang, Chuang, & Ju, 2015; Cole & Rozell, 2011; DePaulo et al., 1996; deVries et al., 2014; Farrow et al., 2015; Hermann & Arkin, 2013; G. Johnson, Griffith, & Buckley, 2016; Lambert, Arbuckle, & Holden, 2016; Leary & Kowalski, 1990; McGowan et al., 2008; Nagy, Kacmar, &

Harris, 2011; Schlenker, 1980; Visu-Petra et al., 2014). Some theorists view impression management as a conscious and intentional attempt to manipulate other people’s impressions of them by overemphasizing positive traits while underplaying negative ones (Farrow et al., 2015; Gaes, Kalle & Tedeschi, 1978; Gardner & Martinko, 1988; Paulhus, 1991; Rosenfeld, Booth-Kelley, Edwards & Alderton, 1994; Zerbe & Paulhus, 1987). Others argue that although self-presentation can be intentionally used for the purpose of deceit, it can also be an involuntary behavior that can be ascribed to unconscious habits (Cole & Rozell, 2011; Rosenfeld, Giacalone, & Riodan, 1995). Alternatively, it can be viewed as a conscious, natural behavior that forms an important part of social interactions (Cole & Rozell, 2011; Cheng et al., 2015; Goffman, 1959; Leary & Kowalsky, 1990; Schlenker & Pontari, 2000).

Impression management is a natural part of daily life and is closely linked with social conformity. It assists in defining the individual’s place in the social context, as well as characterising the manner of an interaction, facilitating role-governed behavior and ensuring that one’s behavior is in line with social norms (Cheng et al., 2015; Farrow et al., 2015; Goffman, 1959; Leary & Kowalsky, 1990; Schlenker & Pontari, 2000). The idea behind impression management was originally propagated by Goffman (1959), who introduced a dramaturgical framework describing the way a person portrays themselves and how they might be perceived by others. Since then, much research has been done on the topic and many varying theories and frameworks have been developed (Baumeister, 1989; Jones & Pittman, 1982; Leary & Kowalski, 1990; Schlenker, 1980; Schneider, 1981).

Gardner and Martinko (1988) suggested that a person consciously decides on a behavior to portray to others in order to elicit a desired consequence. If this action prompts the anticipated response, the individual will continue to implement that particular strategy (Cole & Rozell, 2011; Gardner & Martinko, 1988). The critical factors within this process include a thorough comprehension of the strategy being applied, the reason behind the use of that specific strategy, the target audience, and the circumstances surrounding the environment where the self-presentation takes

26 place (Cole & Rozell, 2011; Farrow et al., 2015; Gardner and Martinko, 1988; Roa, Schmidt & Murray, 1995).

2.5.1 Motives of impression management. There are a number of theories as to the specific motives or goals of impression management (Arkin, 1981; Baumeister, 1989; Cheng et al., 2015; Cole & Rozell, 2011; Giacalone & Rosenfield, 1989; Jones & Pittman, 1982; Leary & Kowalski, 1990; Nagy et al., 2011; Schlenker, 1980; Schneider, 1981). Many theorists have suggested that self-presentation could have any number of motives, depending on the situation (Cole & Rozell, 2011; Gardner & Matinko, 1988; Schlenker, 1980; Schneider, 1981), while other theories point towards more specific motives. One such theory is that the purpose of self- presentation is to appear attractive or liked (Cole & Rozell, 2011; Giacalone & Rosenfield, 1989; Jones, Gergen, Gumpert, & Thibaut, 1965; Liden & Mitchell, 1988; Roa, et al., 1995; Rosenfeld et al., 1995). Alternatively, Jones and Pittman (1982) proposed that the motivation behind the strategies used in impression management involves securing and maintaining power. This power is then used for the purpose of gaining control within an individual’s social environment (Cole & Rozell, 2011; Jones & Pittman, 1982).

Yet another theory, put forward by Cheng et al. (2015), is that the goals of self- presentation could be divided into two categories, namely defensive impression management and assertive impression management. They argued that defensive impression management is applied in order to safeguard a person’s established public image, while assertive impression management is implemented to enhance the social image. Defensive impression management is prompted by negative emotions that arise as a result of perceived threats to a person’s public image. On the other hand, assertive impression management is motivated by self-enhancing motives, which are activated at the prospect of generating favourable impressions on others (Arkin, 1981; Cheng et al., 2015; Schlenker, 1980).

Baumeister (1989) suggested a different approach, also comprising two types of goals to impression management – satisfying the audience and self-construction. The first involves the desire to look good to other people and the central theme would be approval from others. The second encompasses the formation and presentation of one’s own identity, by allowing the individual to create an identity that is in line with their personal goals and values. By presenting one’s ideal self, they may then receive the esteem of others that they desire (Baumeister, 1989; Cole & Rozell, 2011).

Leary and Kowalski (1990) named similar goals in their theory pertaining to the motives of impression management. They postulated that there are three fundamental interrelated motives that ultimately culminate in the enhancement of subjective well-being. These are social and material outcomes, self-esteem maintenance and development of identity. Firstly, self-presentation assists individuals to maximize their reward-cost ratio in their interactions with others (Leary & Kowalski, 1990; Schlenker, 1980). Creating the correct impression could increase the likelihood of obtaining the desired social or material outcomes, while avoiding undesired consequences.

The second motive to impression management, according to Leary and Kowalski (1990), is to maintain and enhance self-esteem, which can be accomplished in one of two ways. The first is that individuals may try to create impressions that will provoke reactions that enhance their esteem, rather than reactions that might reduce the self-esteem (Leary & Kowalski, 1990; Schneider, 1969). The second way of enhancing or maintaining self-esteem is through one’s perception of the impression they instilled and the imagined reactions of other people to these impressions (Darley & Goethals, 1980; Filter & Gross, 1975; Leary & Kowalski, 1990; Reis & Gruzen, 1976).

The final motive for self-presentation in this theory is developing identity (Leary & Kowalski, 1990). This motive is based on the assertions that identity is ultimately

28 derived from society (Dunbar et al., 2016; Leary & Kowalski, 1990; Mead, 1934; Tajfel & Turner, 1979). Thus, people may want to create a specific impression that would reveal that they possess characteristics that are crucial to their self-identity (Leary & Kowalski, 1990). According to Leary and Kowalski (1990), once a person is motivated to elicit a certain impression, one must then decide on the type of impression to generate, and then determine how this might be achieved.

2.5.2 Impression construction. This is referred to as impression construction and it involves the act of altering one’s behavior to influence others’ opinions of them. (Cole & Rozell, 2011; Leary & Kowalski, 1990). This depends greatly on the context and the audience, as the same set of actions can be perceived differently depending on the situation (Cole & Rozell, 2011; Farrow et al., 2015; Jones & Pittman, 1982; Leary & Kowalski, 1990). Leary and Kowalski (1990) presented five variables that determine the manner in which impression management is conducted. These include intrapersonal elements (self-concept and desired identity), as well as interpersonal features (role constraints, target values and current or potential social image).

The impression that one wishes to project is significantly influenced by one’s self- concept (Baumeister, 1989; Cole & Rozell, 2011; Leary & Kowalski, 1990; Nagy et al., 2011). Most people value specific characteristics that they possess and they would want to make a conscious effort for other people to know that they exhibit these features (Goffman, 1959; Leary & Kowalski, 1990). People also hesitate to project impressions that are inconsistent with their self-beliefs because of the probability of being unconvincing (Leary & Kowalski, 1990; Schlenker, 1980). Furthermore, people often have an internalized belief in the immorality of deception (Abe, 2011; DePaulo & Kashy, 1998; Dunbar et al., 2016; Guthrie & Kunkel, 2013; Hayashi et al., 2014; Knapp, 2006; Lindskold & Han, 1986; Lindskold & Walters, 1983; Talwar & Crossman, 2011), which discourages them from putting forward an impression of themselves that is obviously inconsistent with their self-beliefs (Leary & Kowalski, 1990). Alternatively, Nagy et al. (2011) argued that individuals with a

29 positive self-concept would have less of a need to manipulate other people’s impressions of them.

Impression management is not only influenced by the way a person believes themselves to be, but also by how they would like to be. Thus, people tend to exhibit impressions that are more reflective of their desired identity, while still representing some aspect of reality (Baumeister, 1989; Cole & Rozell, 2011; Leary & Kowalski, 1990). People generally try to maintain a balance between presenting themselves in a completely honest manner and portraying the best possible images of themselves (Leary & Kowalski, 1990; Schlenker, 1985). However, the way a person presents themselves can also be restricted by the expectations that society imposes on social roles. Deviating from these roles and creating impressions of incompetency and impropriety can have negative consequences. As a result, people attempt to ensure that the image that they portray to the public conforms as closely as possible to prototypic characteristics of the role that they possess (Leary, 1989; Leary & Kowalski, 1990).

People also modify their impressions based on the perceived values and standards of significant others (Forsyth, Riess, & Schlenker, 1977; Gaes & Tedeschi, 1978; Leary & Kowalski, 1990; Reis & Gruzen, 1976; von Baeyer, Sherk, & Zanna, 1981). However, even when people portray themselves in line with the values of others, they often selectively convey an image that is consistent with the way they view themselves (Leary & Kowalski, 1990). The final aspect that influences the impressions that people try to generate is current or potential social image. People are unlikely to present an image of themselves that is inconsistent with the information that is available to other people about them. This is likely associated with the low probability of the success of such an impression (Leary & Kowalski, 1990; Schlenker, 1980). Alternatively, a person’s current public image can also induce specific self-presentations (Leary & Kowalski, 1990). For example, if a person believes that their public image is different to the way they would want it, this could prompt face-saving approaches (Baumeister, 1982a; Baumeister & Jones, 1978; Leary & Schlenker, 1980).

2.5.3 Strategies of impression management. Once an individual has decided the type of perception they would like to elicit, certain strategies are put into place in order to implement them (Cole & Rozell, 2011; Jones & Pittman, 1982). The five most commonly used tactics are ingratiation, self-promotion, exemplification, intimidation and supplication (Bolino, Kacmar, Turnley, & Gilstrap, 2008; Bolino & Turnley, 1999; Cole & Rozell, 2011; Jones & Pittman, 1982; Nagy et al., 2011; Turnley & Bolino, 2001). Ingratiation involves any number of tactics including conforming, self-enhancement, the use of flattery, or performing favours. This is usually implemented in order to pursue and establish social acceptance and likeability (Cole & Rozell, 2011; Gardner, 1992; Jones, 1964; Jones & Pittman, 1982; Nagy et al., 2011; Schneider, 1981; Rosenfeld et al., 1995).

On the other hand, self-promotion aims at portraying competence in a certain ability or skill (Cole & Rozell, 2011; Jones & Pittman, 1982; Nagy et al., 2011). A concept similar to this is exemplification, which involves going beyond what is expected in order to achieve admiration and respect (Cole & Rozell, 2011; Jones & Pittman, 1982; Nagy et al., 2011). However, unlike with self-promotion, which portrays competence in certain skills, exemplification is done by promoting one’s integrity and morality by exhibiting positive traits such as generosity, kindness, honesty and sincerity (Cole & Rozell, 2011; Jones & Pittman, 1982). The three strategies that have been mentioned thus far are all aimed at achieving a positive appraisal from others (Cole & Rozell, 2011; Jones & Pittman, 1982; Nagy et al., 2011). However, sometimes a person might have motive to appear to be helpless, weak or dependant (Cole & Rozell, 2011; Jones & Pittman, 1982; Nagy et al., 2011).

Such a strategy is known as supplication, which involves exploiting personal weaknesses (Cole & Rozell, 2011; Jones & Pittman, 1982; Nagy et al., 2011). This might be used in order to invoke pity, make the other person seem better in comparison or even to push others away. However, this could also result in negative consequences, as it can negatively influence one’s self-esteem (Cole & Rozell, 2011; Jones & Pittman, 1982). Another strategy which is also not meant to result in a positive appraisal, but rather the opposite is intimidation. This approach is used

31 when an individual purposefully wants to be disliked, by convincing others that they are dangerous and should be feared. As such, people often abide by the wishes of the intimidator in order to evade negative consequences (Cole & Rozell, 2011; Jones & Pittman, 1982). In the case of all of the above-mentioned tactics of impression management, it is sometimes difficult to determine whether the individual is solely deceiving others by presenting this image of themselves, or whether they are deceiving themselves by thinking that they actually possess the characteristics that they are portraying (Farrow et al., 2015).

2.5.4 Distinguishing between impression management and self- deception. It should be recognized that impression management, or self- presentation, refers only to how one portrays themselves to others, and not how one actually regards oneself as part of their self-image (Arkin & Baumgardner, 1986;

Baumeister, 1982b; Jones & Pittman, 1982; Leary & Kowalsky, 1990; Schlenker, 1980; Schneider, 1981). Leary and Kowalski (1990) argued that the most important distinguishing factor is that the two processes are composed of entirely different psychological manifestations. Public self-presentation is explicitly behavioural, while self-perception, and thus also self-deception, is facilitated overtly by cognitive processes (Leary & Kowalski, 1990; Greenwald & Breckler, 1985). Another factor that differentiates between the two is the motivation behind it, as many of the social factors that affect an individual’s public image would have little or no consequence in one’s private self-image (Leary & Kowalski, 1990). Nevertheless, it is very difficult to distinguish whether a certain behavior is impression management or whether the person is also self-deceptive (Farrow et al., 2015).

2.6 Self-deception

Individuals can unconsciously project a more positive image of themselves through self-deception, thereby deceiving others in the process (Cervellione et al., 2009; deVries et al., 2014; Farrow et al., 2015; Martinez-Gonzalez et al., 2016; Mijovic- Prelec & Prelec, 2010; Moomal & Henzi, 2000; Paulhus, 1988; Visu-Petra et al., 2014; von Hippel & Trivers, 2011). Von Hippel and Trivers (2011) viewed this form of self-deception as information processing biases that give preference to positive

32 information rather than that which is unwelcoming or uncomfortable. Self-deceptive enhancement involves a person’s unconscious, idealistically positive evaluations of the self and the propensity to project a positive appearance thereof (Cervellione et al., 2009; deVries et al., 2014; Lambert et al., 2016; Martinez-Gonzalez et al., 2016; Mijovic-Prelec & Prelec, 2010; Moomal & Henzi, 2000; Paulhus, 1988; Visu-Petra et al., 2014; von Hippel & Trivers, 2011). If a person possesses a positive opinion of themselves, this would enhance their self-confidence, which would in turn influence their outward expression of themselves. By doing so, they are able to influence how others perceive them and thereby enhance their social circumstances (von Hippel & Trivers, 2011).

2.6.1 Types of self-deception. Self-deception can occur in many different forms, through various biases at different stages of information processing. These can be categorized as biased information search, biased interpretation, misremembering, rationalization, and convincing the self that a lie is the truth (Ceci et al., 1994; Conway & Ross, 1984; Croyle et al., 2006; D’Argembeau & Van der Linden, 2008; Dawson, Gilovich, & Regan, 2002; Green, Sedikides, & Gregg, 2008; Kay et al., 2008; Lord, Ross, & Lepper, 1979; Norris & Inglehart, 2004; Saucier, Miller, & Doucet, 2005; Snyder, Kleck, Strenta, & Mentzer, 1979; Valdesolo & DeSteno, 2008; Vohs & Schooler, 2007; von Hippel & Trivers, 2011; Westen, Blagov, Harenski, Kilts, & Hamann, 2006; Whitson & Galinsky, 2008; Zaragoza & Mitchell, 1996).

2.6.1.1 Biased information search. Self-deception can take place in the form of manipulating the information that one processes through specific biases. These include selective searching, amount of searching and selective attention (von Hippel & Trivers, 2011). Selective searching involves the tendency for some people to search for information that is consistent with their beliefs, desires and goals, and to search in places where they believe that such information would be most likely to be uncovered (Armitage, Harris, Hepton, & Napper, 2008; Frey, 1986; Harris, Mayle, Mabbott, & Napper, 2007; von Hippel & Trivers, 2011). Therefore, people engage in

33 self-deception by entirely avoiding the truth in the form of solely looking for information that encourages their own views (von Hippel & Trivers, 2011).

Amount of searching refers to limiting the amount of information received by restricting the amount of searching done when looking for information (von Hippel & Trivers, 2011). People often avoid searching further if there is a possibility that the information uncovered would be unsuited to their desires and goals (Dawson, Savitsky, & Dunning, 2006; Ditto & Lopez, 1992; Ditto, Munro, Apanovitch, Scepansky, & Lockhart, 2003; Lerman, Croyle, Tercyak, & Hamann, 2002; Olson & Zanna, 1979; von Hippel & Trivers, 2011). Therefore, people are sometimes content with a partial truth if the entire truth is not as pleasant (von Hippel & Trivers, 2011).

When information is available to a person and it does not have to be actively searched for, biases can still occur in the encoding of the information by selectively applying attention to features of the information that appear more agreeable (Isaacowitz, Toner, Goren, & Wilson, 2008; von Hippel & Trivers, 2011; Wilson, Wheatley, Kurtz, Dunn, & Gilbert, 2004). For example, if there are multiple sources of information being presented simultaneously, people often choose to apply attention to the one that bears out their beliefs, thus ignoring those that are contradictory to their views. Therefore, selective attention can be used as another method of self-deception (von Hippel & Trivers, 2011).

2.6.1.2 Biased interpretation. Despite the various methods for evading undesirable information described above, there are times when such information is successfully processed and encoded. When this occurs the information can be dismissed through biases in the interpretation, which is based on whether the information is consistent or inconsistent with one’s attitudes. In other words, people tend to accept information that supports their beliefs and reject that which opposes them as flawed or inaccurate (Dawson et al., 2002; Lord et al., 1979; von Hippel & Trivers, 2011). During this selective skepticism, people have a potential awareness of the unbiased judgement, but they appear to rely on their motivational and mental

34 resources in order to positively interpret only the desirable information. Therefore, this process would be regarded as a form of self-deception, as the person is not objectively evaluating new information that is inconsistent with the person’s aims (von Hippel & Trivers, 2011; Westen et al., 2006).

2.6.1.3 Misremembering. Even if the two above-mentioned processes of self- deception do not take place and the adequate attention is applied, with the information being encoded without selectively skeptical interpretations, another self- deceptive bias could still affect the correct retrieval of the information (von Hippel & Trivers, 2011). Undesirable information can merely be forgotten or misremembered as neutral or consistent with one’s preferences (Conway & Ross, 1984; Croyle et al., 2006; D’Argembeau & Van der Linden, 2008; Green et al., 2008; von Hippel & Trivers, 2011). One such example is when individuals apply effort for the purpose of self-improvement which is not successful; they can then fabricate positive results by misremembering how they had been at the beginning of the process (Conway & Ross, 1984; von Hippel & Trivers, 2011).

This type of memory bias also occurs in the recall of daily experiences, as individuals usually have an improved recollection of their positive behavior as compared to the negative. However, this same bias does not apply to the behavior of others (D’Argembeau & Van der Linden, 2008; von Hippel & Trivers, 2011). Nevertheless, it is apparent that people do possess potential awareness of the negative information about themselves, although they are biased to misremember it. Therefore, people’s memories appear to be susceptible to this self-enhancing bias, as the memories themselves are sometimes comprised of information that is inclined to be consistent with one’s beliefs, attitudes and goals, and sometimes simply omits parts of the truth (Conway & Ross, 1984; Croyle et al., 2006; D’Argembeau & Van der Linden, 2008; Green et al., 2008; von Hippel & Trivers, 2011).

2.6.1.4 Rationalization. Even if one possessed accurate recollections of events, it is still possible to avoid acknowledging the entire truth. This can be done

35 by means of rationalizing or recreating the motives behind one’s behavior in such a way that it appears to be more socially acceptable (Saucier et al., 2005; Snyder et al., 1979; Valdesolo & DeSteno, 2008; Vohs & Schooler, 2007; von Hippel & Trivers, 2011; von Hippel, Lakin, & Shakarchi, 2005). For example, people might choose to exhibit the less desirable behavior if they believe that it can be explained as being caused by external factors rather than by socially undesirable personal characteristics (Saucier et al., 2005; Snyder et al., 1979; von Hippel & Trivers, 2011). This was demonstrated in a study by Saucier and colleagues (2005) that showed that white Americans were less likely to assist African Americans than those of their own race, but only when tangible situational obstacles existed, such as personal risk or distance.

Furthermore, people are more likely to cheat at activities if it could appear that it was unintentional rather than if it were clearly deliberate (von Hippel & Trivers, 2011; von Hippel et al., 2005). In such cases, people do not ignore, deny or misremember their behavior, but rather deny the socially undesirable reasons behind such behavior. They do so by rationalizing that their actions can be ascribed to external factors (Saucier et al., 2005; Snyder et al., 1979; Valdesolo & DeSteno, 2008; Vohs & Schooler, 2007; von Hippel & Trivers, 2011; von Hippel et al., 2005).

2.6.1.5 Convincing the self that the deception is the truth. In situations where all the above methods of self-deception are not implemented, people might ultimately convince themselves that the deception is in fact the truth (Ceci et al., 1994; Kay et al., 2008; Norris & Inglehart, 2004; von Hippel & Trivers, 2011; Whitson & Galinsky, 2008; Zaragoza & Mitchell, 1996). Since self-deception usually occurs in combination with the deception of others, it can be difficult to discern whether the person truly believes in the truthfulness of their deception (von Hippel & Trivers, 2011). Nevertheless, research exists that confirms the existence of this phenomenon (Epley & Whitchurch, 2008; Ceci et al., 1994; von Hippel & Trivers, 2011; Zaragoza & Mitchell, 1996). For example, people tend to perceive themselves to be more attractive than they actually are (Epley & Whitchurch, 2008; von Hippel & Trivers, 2011). Research in cognitive dissociation has also shown that the deception of

36 others often inadvertently results in the individual believing their own dishonesty (Ceci et al., 1994; von Hippel & Trivers, 2011; Zaragoza & Mitchell, 1996).

Another example of how people deceive themselves is that if an individual believes their level of personal control to be low, they might perceive imagined patterns in arbitrary events (Kay et al., 2008; Norris & Inglehart, 2004; von Hippel & Trivers, 2011; Whitson & Galinsky, 2008), and more readily endorse conspiracy theories as an explanation of such occurrences (Whitson & Galinsky, 2008). Thus, people might deceive themselves into achieving a sense of control (Kay et al., 2008; Norris & Inglehart, 2004; von Hippel & Trivers, 2011; Whitson & Galinsky, 2008). With all these types of self-deception, a number psychological and cognitive processes must take place in order for an individual to truly be able to deceive themselves (Bargh, 1994; Chartrand, Huber, Shiv, & Tanner, 2008; Coates, Butler, & Berry, 2006; Fazio & Olson, 2003; Hofmann, Gawronski, Gshwendner, Le, & Schmitt, 2005; Kolers, 1976; A.Y. Lee, 2002; Seamon et al., 1995; von Hippel & Trivers, 2011; Wilson, Lindsey, & Schooler, 2000).

2.6.2 Psychological and cognitive processes of self-deception. Farrow et al. (2015) proposed that self-deception comprises selected attention to information that affirms a person’s goals and beliefs, as well as self-induced ignorance and neglecting to process information that fails to do so. von Hippel and Trivers (2011), however, proposed that other cognitive aspects come into play for an individual to be deceptive to themselves when all the processes involved occur within the same brain. They explained that there are dissociations between different aspects of the mind, thereby ensuring that the mental processes that are being deceived have limited conscious access to the content of the processes that are doing the deceiving (Bargh, 1994; Chartrand et al., 2008; Coates et al., 2006; Fazio & Olson, 2003; Hofmann et al., 2005; Kolers, 1976; A.Y. Lee, 2002; Seamon et al., 1995; von Hippel & Trivers, 2011; Wilson et al., 2000). These dissociations refer to different forms of memory, attitudes and processes (von Hippel & Trivers, 2011).

2.6.2.1 Implicit and explicit memory. Memory can be broken down into two systems that involve the storage and retrieval of information in the long term, namely explicit memory and implicit memory (Lezak, Howieson, Bigler, & Tranel, 2012; Milner, Squire, & Kandel, 1998; Squire & Knowlton, 2000; von Hippel & Trivers, 2011). Explicit memory refers to facts and events that can be consciously and intentionally recollected (Lezak et al., 2012; Milner et al., 1998; Squire & Knowlton, 2000; Tranel & Damasio, 2002; von Hippel & Trivers, 2011). In contrast to this, implicit memory is comprised of the information that a person retains without conscious awareness of its existence (Lezak et al., 2012; Milner et al., 1998; Schacter, McAndrews, & Moscovitch, 1988; Squire & Knowlton, 2000; von Hippel & Trivers, 2011). A dissociation between these two types of memory can serve as the foundation of self-deception (von Hippel & Trivers, 2011).

The explicit memory could encompass the deceptive information that the person wishes to portray, while the implicit memory could entail the facts as they truthfully present themselves. There are a number of possible explanations as to how memories might selectively be excluded from accessing consciousness in order to assist self-deception (Ceci et al., 1994; Chrobak & Zaragoza 2008; Cuc, Koppel, & Hirst, 2007; Drivdahl, Zaragoza, & Learned, 2009; Gonsalves et al. 2004; McCloskey & Zaragoza 1985; Slusher & Anderson, 1987; von Hippel & Trivers, 2011; Zaragoza & Mitchell, 1996; Zaragoza, Payment, Ackil, Drivdahl, & Beck, 2001). One such possibility is that the truth might be substituted by deception within conscious memory through repeatedly reporting the misrepresentation (von Hippel & Trivers, 2011). As previously noted, people can come to believe their own deception through the deception of others. In other words, rehearsal of untruthful information can make it difficult to ascertain its source, which results in people believing their own deception to be true (Ceci et al., 1994; von Hippel & Trivers, 2011; Zaragoza & Mitchell, 1996).

This process of convincing oneself of the truth of false memories can then be exacerbated by other features that are usually involved in the deception of others (von Hippel & Trivers, 2011). For example, people usually create an intricate, vivid

38 and tangible image of the deception, thereby making it more difficult to differentiate between false memories and truthful ones (Gonsalves et al. 2004; Slusher & Anderson, 1987; von Hippel & Trivers, 2011). Furthermore, socially discussing the misinformation can result in selectively forgetting information which has not been mentioned (Cuc et al., 2007; von Hippel & Trivers, 2011), and social validation of incorrect information can exaggerate the phenomena of the false memory (von Hippel & Trivers, 2011; Zaragoza et al., 2001). Therefore, one consequence of the rehearsal and retrieval of deceptive information from memory is that one may eventually recollect the false information as though it is the truth, while still preserving the accurate events in the implicit memory, which is not as easy to access consciously (Chrobak & Zaragoza 2008; Drivdahl et al., 2009; McCloskey & Zaragoza 1985; von Hippel & Trivers, 2011).

2.6.2.2 Implicit and explicit attitudes. The same concept that applies to memory in terms of being explicit or implicit can also be applied to one’s attitudes, and evidence suggests that people retain two varying kinds of attitudinal information (Fazio & Olson, 2003; von Hippel & Trivers, 2011; Wilson et al., 2000). Furthermore, just as unconscious memories can have an effect on behaviour, so can the attitudes that people possess that they are not explicitly aware of (Greenwald, Poehlman, Uhlmann, & Banaji, 2009; Nock et al., 2010; von Hippel & Trivers, 2011). Dissociations between conscious and unconscious attitudes arise across a number of diverse domains, although they occur most commonly when implicit attitudes are not socially desirable (Hofmann et al., 2005; von Hippel & Trivers, 2011). As is the case with memory, von Hippel and Trivers (2011) proposed that the co-existence of these dual attitudes lends itself to self-deception. They stated that self-deception is exacerbated by the dissociation between conscious and unconscious attitudes because they allow individuals to express socially desirable attitudes and also exhibit socially undesirable attitudes that are somewhat inaccessible when they can retain reasonable deniability.

2.6.2.3 Automatic and controlled processes. Similarly, social deception is facilitated by the dissociation between controlled and automatic processes.

Controlled processes entail awareness, intention and conscious effort, and can be stopped at any time. On the other hand, automatic processes involve unconscious, effortless and unintentional developments that usually continue until their completion (Bargh, 1994; von Hippel & Trivers, 2011). However, some goal-directed behaviours can appear to be consciously driven, but actually occur automatically, with the person often being unaware of the goal itself (Chartrand et al., 2008; von Hippel & Trivers, 2011).

Unconscious processes can even be contradictory to consciously identified goals. Therefore, the dissociation between these processes can aid in self-deception by making it possible to have consciously constructed goals that are endorsed by one’s peers and are therefore socially desirable, while simultaneously performing automatic processes that would be deemed unacceptable by peers and are socially undesirable (Chartrand, Dalton, & Fitzsimons, 2007; von Hippel & Trivers, 2011). Just as self-deception entails very specific cognitive functions, deception as a whole is cognitively demanding and requires the activation and integration of a number of cognitive mechanisms (Carter et al., 1998; Carrion et al., 2010; Debey et al., 2015; Gehring & Knight, 2000; Gombos, 2006; Johnson Jr. et al., 2004; Mohamed et al., 2006; Moomal & Henzi, 2000; Talwar & Crossman, 2011; Turken & Swick, 1999; Vrij et al., 2010; Walczyk et al., 2003; Zuckerman et al., 1981).

2.7 Cognition of Deception

Neurocognitive studies have shown that certain areas of the brain show higher levels of activity during deception than during truthfulness (Abe, 2011; Gombos, 2006; Johnson Jr. et al., 2004; Mohamed et al., 2006; Spence et al., 2001; Vartanian et al., 2013; Wu, Loke, Xu, & Lee, 2011). These include the areas responsible for response inhibition, memory, attention and planning (Gombos, 2006; Johnson Jr. et al., 2004; Kozel, Padgett, & George, 2004; Langleben et al., 2002; T.M.C. Lee et al., 2002; Mohamed et al., 2006). Various theories of deception predict that the limitation of these cognitive resources would significantly increase the difficulty of successfully deceiving another individual (Buller & Burgoon, 1996; Gombos, 2006; Lane & Wegner, 1995; Mohamed et al., 2006; Vrij et al., 2010; Walczyk et al., 2003;

Zuckerman et al., 1981). Moreover, there are a number of theorists that suggest that deception is more cognitively demanding than being truthful (Carrion et al., 2010; Debey, et al., 2015; Gombos, 2006; Johnson Jr. et al., 2004; McCornack, 1997; Visu-Petra et al., 2014; Vrij, 2000; Vrij & Granhag, 2012; Vrij et al., 2008; Walczyk et al., 2014).

2.7.1 Cognitive load. When an individual has to maintain two types of information simultaneously in working memory, cognitive load occurs (von Hippel & Triver, 2011; Vrij, 2004). In the case of deception, this arises because both the truth and deception must be maintained in working memory simultaneously in order to suppress the truth and maintain the deception (Gombos, 2006; von Hippel & Triver, 2011; Vrij, 2004; Vrij & Mann, 2001). Thus, the argument of this theory states that being deceitful involves greater cognitive load than being honest, as the truth requires only one set of information to be maintained (Buller & Burgoon, 1996; Gombos, 2006; von Hippel & Triver, 2011; Vrij, 2004, 2011; Vrij & Mann, 2001).

Based on this theory, Vrij et al. (2010) speculated that very good liars would experience less cognitive load, would exhibit quick thinking and possess high intelligence and good memory. They further indicated that cognitive load can be reduced by being well-prepared, which is characteristic of good liars. However, despite being prepared, unexpected situations can arise, in which case original thinking, eloquence and fast mental processing would facilitate the fabrication of a believable deceptive response. Vrij and colleagues further indicated that good liars require a good memory, as they should be able to repeat their lies or provide further information without contradicting what has already been said. Moreover, it would appear that more intelligent people find it easier to lie (Ekman & Frank, 1993; Vrij & Mann, 2001), leading to the belief that good liars tend to be more intelligent than bad liars (Vrij et al., 2010).

Contradictory views exist with regards to deception inducing greater cognitive load than honesty, as other researchers argue that there are contextual circumstances

41 under which the truth evokes greater cognitive load than deception (Gombos, 2006; Levine and McCornack, 2014; McCornack, 1997; Vrij, 2000). This occurs when the truth requires more explanation than deception, when false information is more easily retrievable from working memory or if the truth is difficult to retrieve from long- term memory. For example, if an individual were placed under pressure to state what they were doing at a specific time on a specified date in the distant past, the truth would be much more difficult to obtain than what deception would be to conceive (Gombos, 2006; Levine and McCornack, 2014).

DePaulo et al. (2003) also found that the opportunity to generate a deceptive response and the duration during which a person is required to be deceptive may influence cognitive load. For example, less time in which to construct a deceptive response and a longer duration of deception are linked to greater cognitive load. Despite the varying views with regards to cognitive load, there is a general consensus among the literature that deception is a cognitively demanding activity and involves active executive processes (Carter et al., 1998; Carrion et al., 2010; Debey et al., 2015; Gehring & Knight, 2000; Gombos, 2006; Johnson Jr. et al., 2004; Moomal & Henzi, 2000; Talwar & Crossman, 2011; Turken & Swick, 1999).

2.7.2 Executive functions. Deception is associated with higher levels of activity in the prefrontal cortex, which is the area of the brain associated with cognitive control and executive functioning. Therefore, research has shown that executive processes are crucial for deception (Abe, 2011; Debey et al., 2015; Gombos, 2006). Executive functions refer to cognitive activities that manage information, including attention, planning, problem-solving, response inhibition, and working memory (Baddeley, 2000; Botvinick et al., 2001; Carter et al., 1998; Garcia, Plasencia, & Benito, 2015; Gehring & Knight, 2000; Gombos, 2006; Mohamed et al., 2006; Talwar & Crossman, 2011; Turken & Swick, 1999; Visu-Petra et al., 2014). There are a number of theories that attempt to explain the cognitive aspects of deception (Buller & Burgoon, 1996; Lane & Wegner, 1995; Levine & McCornack, 2014; Mohamed et al., 2006; Walczyk et al., 2003; Zuckerman et al., 1981).

2.8 Cognitive Theories of Deception

2.8.1 Four-Factor theory of deception. The first cohesive theory that endeavored to explain the processes involved in deception was developed by Zuckerman and colleagues (1981). Their Four-Factor theory of deception proposed four characteristics that differentiate people who are engaging in deception and those who are being truthful. These include heightened levels of arousal during lying or deception, emotions that are associated with guilt, more complex cognitive aspects associated with lying, and the propensity for deceivers to attempt to control verbal and non-verbal factors to avoid detection (Gombos, 2006; Zuckerman et al., 1981). A number of theorists expanded on this theory and used it as a basis for research into similar concepts (Buller & Burgoon, 1996; Gombos, 2006; Lane & Wegner, 1995; Mohamed et al., 2006; Walczyk et al., 2003).

2.8.2 Interpersonal Deception Theory. One such example is Buller and Burgoon’s (1996) Interpersonal Deception Theory, which postulates that deception is a process that entails interactive, reciprocal communication, which involves many simultaneous tasks. The deceiver must fabricate the deceptive response while constantly monitoring the person being deceived for signs of disbelief, and adjusting one’s behavior accordingly (Buller & Burgoon, 1996; Debey et al., 2015; Ekman, 2001; Gombos, 2006; von Hippel & Trivers, 2011; Vrij & Mann, 2001; Walczyk et al., 2003). In the meantime, the person being deceived anticipates evidence of deception through behavioural and verbal cues (Buller & Burgoon, 1996; Gombos, 2006).

Within this theory, monitoring one’s behavior and verbal cues, as well as that of the target of the deception, constitutes executive attention and metacognitive regulation (Fernandez-Duque, Baird, & Posner, 2000; Gombos, 2006). Furthermore, this theory implies that the afore-mentioned cues must be suppressed, which involves behavioural and cognitive inhibition (Carlson, Moses, & Hix, 1998; Debey et al., 2015; Gombos, 2006; Hala & Russell, 2001; Spence et al., 2004; Vendemia,

Schillaci, Buzan, Green, & Meek, 2009; Walczyk et al., 2003, 2014). Ultimately the internal and external information being received must be processed as well as continually being facilitated and organized, which necessitates executive cognition (Gombos, 2006).

2.8.3 Neural-cognitive theory of deception. Mohamed et al. (2006) introduced a theoretical model of deception that emphasizes the neural-cognitive interactions during deception. According to their proposition, the process of deception involves seven stages. Some of these stages can take place simultaneously, but each involves different areas of the brain. They are described as follows: hearing a question presented by another individual, understanding the question, retrieval of memories associated with the question, judgement and planning a response (which involves inhibition), the experience of emotions associated with the deception, the verbal response, and finally, the stimulation of the sympathetic nervous system. However, according to Gombos (2006), only one of the stages of Mohamed et al.’s (2006) theory differentiates the process of being truthful from that of being deceptive – the phase involving judgement, planning and inhibition.

Gombos (2006) argued that the remainder of the processes occur in much the same way during truth-telling as in deception. In contrast, the cognitive processes of judgement, planning and inhibition have been implicated in the process of deception in a number of imaging studies (Johnson Jr. et al., 2004; Kozel et al., 2004; Langleben et al., 2002; T.M.C. Lee et al., 2002). Mohamed et al. (2006) further confirmed increased activation in the areas of the brain associated with effortful executive functions.

2.8.4 Preoccupation Model of Secrecy. The Preoccupation Model of Secrecy (Lane & Wegner, 1995), although not a complete explanation of deception, highlights the importance of suppressing one’s thoughts during secrecy or omission. The underlying construct which allows suppression to take place, as previously

44 noted, is inhibitory control (Carlson et al., 1998; Debey et al., 2015; Gombos, 2006; Hala & Russell, 2001; Spence et al., 2004; Vendemia et al., 2009; Walczyk et al., 2003, 2014). Another model, established by Walczyk et al. (2003), goes on to explain not only how the truth is supressed, but also how deceptive responses are generated.

2.8.5 Activation-Decision-Construction Model. Walczyk et al. (2003) conducted research based on their model which ultimately showed that a number of executive processes must be activated and managed in order to produce deceptive responses, which is supported by a large mass of the literature on the subject (Carter et al., 1998; Carrion et al., 2010; Debey et al., 2015; Gehring & Knight, 2000; Gombos, 2006; Johnson Jr. et al., 2004; Moomal & Henzi, 2000; Talwar & Crossman, 2011; Turken & Swick, 1999; Vrij et al., 2010). The Activation-Deception- Construction Model (ADCM) of deception is comprised of three crucial cognitive processes – the activation of the truth in memory, the decision of whether to be deceptive or truthful, and the construction of the deceptive response (Gombos, 2006; Walczyk et al., 2003).

This model is based on four assumptions: (1) Semantic memory is comprised of common knowledge, including social concepts and theory of mind, and is organised based on meaning (Fiske & Taylor, 1991; Spence et al., 2001; Walczyk et al., 2003). Episodic memory contains biographical information and is organised based on perceived similarity and the chronological order of events (Anderson, 1993; Tulving & Thomas, 1973). (2) When long-term nodes are activated, adjacent nodes within their respective networks are primed by means of a process of spreading activation that decays at a rapid pace (Anderson, 1993). (3) Semantic and episodic memory form part of the long-term working memory and are linked to the truth that is rapidly accessible by the retrieval structure of the working memory. Furthermore, most people are proficient in the processing of speech and discourse (Kintsch, 1998; Perfetti, 1985, 1988). (4) Although it describes lying and deception in general, the ADCM is most pertinent to situations wherein the individual does not have previous knowledge of the questions that would be asked (Walczyk et al., 2003).

2.8.5.1 Activation. The first component of the model is that of activation. Information is stimulated within the semantic or episodic memory so that knowledge of the truth is held in the working memory (Gombos, 2006; Walczyk et al., 2003). While a question or alternatively stimuli from the environment is being encoded, relevant information is simultaneously being activated in semantic and episodic memory (Kintsch, 1998). In the case of a question, it would occupy the articulatory loop of the working memory (Baddeley, 2003; Cabeza & Nyberg, 1997). The truth is transferred from the long-term memory to working memory and it receives the greatest amount of activation (Ericsson & Kintsch, 1995).

This activation may occur automatically. However, the allocation of attention may be required if the target semantic or episodic memories have been inactive for a prolonged period (Conway, 2002; Menon, Boyett-Anderson, Schatzberg, & Reiss, 2002). After the truth is active, any information that is semantically or episodically associated with it will be readily accessible if needed in order to construct a deceptive response (Ericsson & Kintsch, 1995). While the truth can be activated automatically (Kintsch, 1998), the decisions and construction processes are intentional (Walczyk et al., 2003).

2.8.5.2 Decision. The decision-making process governs whether an individual will choose to be deceptive or tell the truth (Gombos, 2006; Walczyk et al., 2003). Potential deceivers will decide whether it is in their best interest to be truthful or not depending on the semantic and episodic data that is activated and the social context in which they find themselves (Walczyk et al., 2003). Stimulated episodic nodes that are linked with negative emotions, such as anxiety or guilt, will be particularly prominent (Cabeza & Nyberg, 1997; Lykken, 1998). If the truth is anticipated to cause severe negative outcomes, then the decision will be made to be deceptive (Walczyk et al., 2003).

This is consistent with the views held by Levine and McCornack (2014), who stated that the factors that most influence whether an individual will be truthful or choose to

46 engage in deception is the nature of the information that is available in working memory and long-term memory, as well as the specific contextual constraints that present themselves on divulging the truth. K. Lee (2013) further indicated that an individual must determine the social context in which they find themselves and the socials norms that apply in order to make a decision on whether or not to tell a lie. If the costs of being truthful are low, in terms of personal, relational and professional significance, individuals will usually be truthful.

This leads to the conclusion that most people will usually be honest, as most of daily discourse does not involve high stakes on important matters (Levine & McCornack, 2014; Serota & Levine, 2015; Serota et al., 2010). Furthermore, in situations where a person is placed under pressure to reveal unpleasant truths and there is no appropriate false information obtainable from the working memory or long-term memory, the individual will likely admit the truth. However, when individuals possess information that would be too problematic to reveal and the relevant false information is easily attainable from memory, they will usually choose to be deceptive (Levine, Kim, & Hamel, 2010; Levine & McCornack, 2014).

In addition to memory, inhibition is also necessary during this stage in order to suppress crucial details about the truth. This process of deciding whether to be deceptive subsequently increases the individual’s response time (Carlson et al., 1998; Debey et al., 2015; Gombos, 2006; Hala & Russell, 2001; Spence et al., 2004; Vendemia et al., 2009; Walczyk et al., 2003, 2014). Research conducted by Walczyk et al. (2003) showed that response time was significantly longer when an individual was faced with the decision of whether to be deceptive, compared to when they were specifically instructed to be truthful or to tell a lie. This additional time is ascribed to the process of decision-making.

2.8.5.3 Construction. Another aspect that increases response time when being deceptive is the construction of the deceptive response (Debey et al., 2015; Hu et al., 2011; Johnson Jr. et al., 2004; Seymour, Seifert, Shafto, & Mosmann,

2000; Spence et al., 2001; Verschuere & DeHouwer, 2011; Walczyk et al., 2003). The activation of the truth poses as a retrieval cue to an array of semantic and episodic information which could be used to construct a plausible alternative to the truth, which is the final stage of this model of deception (Walczyk et al., 2003). The possibilities in terms of feasible deceptive responses are limited by social context (Cole & Rozell, 2011; Farrow et al., 2015; Fiske & Taylor, 1991; Jones & Pittman, 1982; Leary & Kowalski, 1990), including knowledge about the people being deceived, and interpretations about their levels of suspicion (Fiske & Taylor, 1991).

Impermissible options are briskly inhibited by social cognitive nodes. They might be deemed inappropriate because they are unconvincing, could be verified as incorrect, contradict other statements, or they do not successfully protect the deceiver (DePaulo et al., 1996). After this processes of inhibition has taken place, the long- term working memory node that is most active would become completely active in working memory and would be the deceptive response that is chosen (Kintsch, 1998; Walczyk et al., 2003).

A study by Walczyk and colleagues (2003) showed that response time was longer when an individual was instructed to construct a lie as opposed to answering deceptively with a yes/no answer, which is similar to findings by Spencer et al. (2001). This latency is ascribed to the construction of the deceptive response (Debey et al., 2015; Hu et al., 2011; Johnson Jr. et al., 2004; Seymour et al., 2000; Spence et al., 2001; Verschuere & DeHouwer, 2011; Walczyk et al., 2003). A critical component of this phase of deception is attention, which facilitates knowledge about the social framework and features in memory to generate a deceptive response that is conceivable (Gombos, 2006; Walczyk et al., 2003).

2.9 Cognitive Functions involved in Deception

Each of the above-mentioned theories make reference to a number of cognitive functions which enable deception to take place. These include working memory, long-term memory, response inhibition, self-monitoring, and attention (Buller &

Burgoon, 1996; Gombos, 2006; Johnson Jr. et al., 2004; Lane & Wegner, 1995; Mohamed et al., 2006; Walczyk et al., 2003; Zuckerman et al., 1981). For the purpose of this study, it is imperative to highlight each of these constructs and review how they relate to deception.

2.9.1 Memory. One of the critical cognitive aspects of deception that emerged in the literature is memory, as it is necessary to remember ones transgressions, the reaction that the deception received as well as the strategy that should be used thereafter (Gombos, 2006; Hala & Russell, 2001; Johnson Jr. et al., 2004; Vrij et al., 2010; Walczyk et al., 2003). In a situation wherein deception is necessary, information regarding the truth is activated and conveyed from the long-term memory to working memory (Gombos, 2006; Ericsson & Kintsch, 1995; Walczyk et al., 2003). The information that is activated in memory then assists in determining whether an individual will choose to be deceptive or truthful (Levine & McCornack, 2014; Walczyk et al., 2003).

Working memory allows the manipulation of information within temporary storage for the purpose of complex cognitive functions (Lezak et al., 2012). Thus, the information available in the working memory is then manipulated in order to construct the deceptive response (Walczyk et al., 2003). The individual would then need to store their deceptive responses in memory and mentally keep track of them in order to be able to maintain their deception (Vrij et al., 2010). During this process, the truth must be suppressed by implementing response inhibition (Carlson et al., 1998; Debey et al., 2015; Gombos, 2006; Hala & Russell, 2001; Hu, Wu, & Fu, 2011; Spence et al., 2004; Vendemia et al., 2009; Walczyk et al., 2003; Walczyk et al., 2014).

2.9.2 Response inhibition. As previously mentioned, response inhibition, or inhibitory control, is one of the crucial executive functions of deception, as effortful control must be implemented in order to suppress the truthful response as the physical indicators of deception (Buller & Burgoo, 1996; Carlson et al., 1998; Debey

49 et al., 2015; Gombos, 2006; Hala & Russell, 2001; Hu et al., 2011; Lane & Wegner, 1995; Mohamed et al., 2006; Spence et al., 2004; Vendemia et al., 2009; Walczyk et al., 2003; Walczyk et al., 2014). Response inhibition refers to the executive function that allows an individual to intentionally inhibit an automatic or dominant response. It is most commonly measured by response time - the longer the response time, the higher the response inhibition is said to be (Debey et al., 2015; Miyake et al., 2000; Weinbach, Kalanthroff, Avnit, & Henik, 2015).

Research has shown that response time is longer when individuals are deceptive, as compared to when they are truthful (Debey et al., 2015; Goldstein, 1923; Hu et al., 2011; Johnson Jr. et al., 2004; Lykken, 1998; Seymour et al., 2000; Spence et al., 2001; Sporer, 1997; Verschuere & DeHouwer, 2011; Walczyk et al., 2003). This is likely associated with the construction of the deception and the process of inhibiting the truth (Debey et al., 2015; Hu et al., 2011; Johnson Jr. et al., 2004; Seymour et al., 2000; Verschuere & DeHouwer, 2011; Walczyk et al., 2003). The truth is generally a more dominant response than deception and is therefore the first to be activated when being deceptive. This results in response conflict, which is subsequently resolved by actively inhibiting the truth (Debey et al., 2015; Duran, Dale, & McNamara, 2010; Hadar, Makris, & Yarrow, 2012; Johnson Jr. et al., 2004; Seymour & Schumacher, 2009; Spence et al., 2001; Walczyk et al., 2003). This theory is supported by brain imaging studies which reveal that deception results in increased levels of activation in the areas of the brain that are involved in response inhibition activation, such as the inferior frontal gyrus (Abe, 2011; Vartanian et al., 2013), and the bilateral and ventrolateral prefrontal cortices (Spence et al., 2001).

Walczyk et al. (2003) confirmed the occurrence of reticence effect, which entails longer response times for questions that entail episodic memories that are linked to negative emotions or information that is not in the person’s best interest. Consistent with the findings of other studies (Borod, 2000; DePaulo et al., 1996; Seymour et al., 2000), this effect occurred whether the person intended to be truthful or deceptive, so long as the information they were required to share was disagreeable. Response inhibition consists of two cognitive aspects – attention to stimuli and prevention of

50 automatic responses (Lezak et al., 2012). As such, attention is frequently necessary in order to inhibit the truth (Spence et al., 2001; Walczyk et al., 2003).

2.9.3 Attention. Attention is an intricate cognitive function that enhances certain information while inhibiting other stimuli at any given point in time (Gogtay et al., 2004; Kosslyn & Smith, 2006). The enhancement allows specific information to be prioritized and designated for further processing, while the inhibition facilitates the exclusion of other information from this process (Kosslyn & Smith, 2006; Raz & Buhle, 2006). Attention is a restricted cognitive resource, whereby it allocates limited brain resources selectively to one source of stimuli while excluding other information or distractions, thereby forfeiting the attention of other stimuli (Duncan, 1999). The role of attention within deception is that of facilitating the construction of a deceptive response (Gombos, 2006; Walczyk et al., 2003).

By allocating attention to the social context and relevant information in memory, one is able to construct an appropriate deceptive response (Gombos, 2006; Walczyk et al., 2003). The individual must also assign attention to the person being deceived in order to detect cues of disbelief and be able to regulate one’s behaviour based on these cues (Buller & Burgoon, 1996; Debey et al., 2015; Ekman, 2001; Gombos, 2006; von Hippel & Trivers, 2011; Vrij & Mann, 2001; Walczyk et al., 2003). One must likewise focus attention to one’s own responses in the form of self-monitoring, so as not to externally display any cues to their deception (Buller & Burgoon, 1996; Fernandez-Duque et al., 2000; Gombos, 2006). Furthermore, attention is fundamental to the processes of problem-solving, planning, decision-making and reasoning (Herrmann, Yoder, Gruneberg, & Payne, 2006; Lezak et al., 2012).

2.9.4 Planning and judgement. Vrij et al. (2010) pointed out that good liars are those who are well-prepared. This would involve planning possible scenarios and conceivable responses. Mohamed et al.’s (2006) neuro-cognitive theory of deception similarly emphasizes the role of planning and judgement, which have also been linked to deception in other imaging studies (Johnson Jr. et al., 2004; Kozel et al.,

2004; Langleben et al., 2002; T.M.C. Lee et al., 2002). Planning constitutes identifying and organizing the essential steps that are necessary in order to achieve an intended goal (Lezak et al., 2012). “In order to plan, one must be able to conceptualize changes from present circumstances (i.e., look ahead), deal objectively with oneself in relation to the environment, and view the environment objectively.” (Lezak et al., 2012, p. 671). Planning also involves conceiving alternatives, weighing various options, and making choices. Thus, these are some of the processes that ensure successful deception (Gombos, 2006; Johnson Jr. et al., 2004; Kozel et al., 2004; Langleben et al., 2002; T.M.C. Lee et al., 2002; Mohamed et al., 2006; Vrij et al., 2010).

2.9.5 Verbal efficiency. Walczyk et al (2003) found that verbal efficiency may be a factor that plays a role in lying. Their research showed that lying to a question appears to be dependent on a person’s aptitude for accessing and manipulating linguistic codes in working memory, which is not the case for retrieval of the truth. Verbal efficiency may be a useful factor in understanding individual differences among people who are susceptible to lying. Vrij et al. (2010) further emphasised the importance of eloquent speech in the fabrication of believable lies. However, this association in the literature pertains to lying (and not deception as a whole) as it specifically entails false statements (Bok, 1999; Dunbar et al., 2016; Gert, 2004; Levine, 2014; Mahon, 2007; 2008; Metts, 1989; Williams, 2002), in which verbal abilities are necessary (Vrij et al., 2010; Walczyk et al., 2003). Therefore, it is unclear whether verbal efficiency could also be linked to deception as a whole.

2.10 Conclusion

The above literature review provides a thorough explanation of deception, with specific focus on the forms of prosocial deception that are relevant to this study. It further delivers evidence of the importance of cognitive functioning in deception. It shows that memory, response inhibition, attention, planning and possibly verbal fluency are essential aspects that enable people to conjure and successfully produce deception. As these functions are so crucial in this process, it is possible that individuals who exhibit greater abilities in these cognitive skills may be more prone to

52 deception, as they find it easier. Inversely, people who have difficulty in these cognitive functions may be more inept at deception and may therefore not engage in it as readily. The following chapter explains the methodological procedures that were implemented in order to establish whether there is a correlation between cognitive abilities and proneness to deception.

Chapter 3:

RESEARCH METHODOLOGY

3.1 Introduction

The research problem being investigated in this study is whether there is a correlation between an individual’s proneness for deception and their cognitive ability. The aim of this study was to compare the results of various cognitive tests between those who scored high in deception and those who scored low in deception. This chapter will discuss the research design, the participants in this study and the sampling techniques used, the measuring instruments that were implemented, the procedure applied for the collection of data, the details of data analysis, and the ethical considerations pertinent to this study.

3.2 Research Design

A quantitative research design, rooted in the positivist paradigm, was used in order to most efficiently resolve the research problem. Quantitative research involves quantifying the relationship between variables (Heddle, 2002; Hopkins, 2000). The positivist paradigm views social science as an objective means of merging empirical observations of individual behaviour with deductive reasoning for the purpose of ascertaining and confirming causal laws that may assist in predicting universal patterns within human life (Neuman, 2003; Tuli, 2010). This study would be characterised as a descriptive study, as it entails the investigation of variables as they occur naturally, with no manipulation from the examiner, and aims to establish whether a relationship exists between said variables (Heddle, 2002; Hopkins, 2000). It implements a cross-sectional method of investigating variables within a sample at one specific point in time (Hopkins, 2000).

3.3 Participants and Sampling

For the purpose of this study, the population was defined as third year Psychology students at the University of Johannesburg, in the faculties of Humanities. 143

54 participants were recruited using Gravetter and Forzano’s (2009) described method of convenience sampling, which entails selecting participants on the basis of their availability and willingness to participate (Gelo, Braakmann, & Benetka, 2008; Wilkinson, 1999). The researcher and the supervisor on this study addressed the students at a psychology lecture to inform them about the research that would be done and to appeal for their involvement as participants. Participation was voluntary and no incentives were offered for their involvement, nor did any form of coercion take place, with the supervisor serving as a mediator in the first stage of research. There were no including criteria for the sample, although participants were excluded if they presented with any known neurological or neurocognitive disorders that would have a bearing on the results (e.g. epilepsy, ADHD). Of the 143 participants who completed the questionnaires online, 26 participants were selected based on their scores on the questionnaire (see below for procedure).

3.4 Measuring Instruments

3.4.1 Biographical Questionnaire. The biographical questionnaire (see Appenidx A) was used with the aim of obtaining biographical information from the participants, which specifically included the participants’ age, gender, ethnicity and first language.

3.4.2 Balanced Inventory of Desirable Responding (BIDR). The BIDR (see Appendix B) is commonly known as a measure of deceptiveness. It is a self-report measure used to quantify socially desirable responding, which can be broken down into impression management and self-deception (Cervellione et al., 2009; deVries et al., 2014; Djikic, Chan, & Peterson, 2007; Djikic, Peterson, & Zelazo, 2005; Farrow et al., 2015; Lambert et al., 2016; Stober, Dette, & Musch, 2002; Visu-Petra et al., 2014). Impression management refers to an individuals attempt to manipulate other people’s impressions of them by under-reporting negative attributes and over- reporting positive ones, while self-deception, or self-deceptive enhancement, is one’s unconscious unrealistically positive self-evaluations and tendency to project a

55 positive image (Cervellione et al., 2009; deVries et al., 2014; Hermann & Arkin, 2013; Lambert et al., 2016; Leary & Kowalski, 1990; Visu-Petra et al., 2014).

The BIDR is comprised of 40 statements, which the participants respond to using a 7-point answer scale (Cervellione et al., 2009; deVries et al., 2014; Djikic et al., 2007; Lambert et al., 2016; Stober et al., 2002). There are two methods of scoring the BIDR. The continuous method combines the numerical ratings of the answers for each sub-scale. The dichotomous method, on the other hand, takes into consideration only the extreme measures so that two groups are formed – those with high scores and those with low scores (Cervellione et al., 2009; Djikic et al., 2007; Lambert et al., 2016; Stober et al., 2002). The continuous method was used for the purpose of this study. It was implemented in order to place the results on a scale of lowest to highest.

A number of studies have been conducted using the BIDR (Cervellione et al., 2009; Djikic et al., 2005; Djikic et al., 2007; Farrow et al., 2015; Lanyon & Carle, 2007; Paulhus, 1991; Uziel, 2014; Visu-Petra et al., 2014), which have found the measure to show considerable internal consistency, as well as satisfactory test-retest reliability. Although it is difficult to identify a certain behaviour as either impression management or self-deception, the BIDR shows discriminant validity in establishing separate factors in factor analysis (Farrow et al., 2015). Furthermore, the subscales have shown substantial validity, when compared with other tests that measure the same scales (Djikic et al., 2005; Lambert et al., 2016; Lanyon & Carle, 2007; Leite & Beretvas, 2005; Paulhus, 1991; Stober et al., 2002).

3.4.3 Rey-Osterrieth Complex Figure Test (RCFT). The Rey-Osterrieth Complex Figure Test (RCFT) is a widely used neuropsychological test of visuospatial memory and visuo-constructional skills in the clinical setting (Lezak et al., 2012; Luzzi et al., 2011; Senese, De Lucia, & Conson, 2015). It is a detailed figure comprised of basic non-meaningful geometric shapes and elements, which elude the use of verbal strategies for retrieving and encoding information (Grieve, 2001; Lezak

56 et al., 2012; Luzzi et al., 2011; Martens, Hurks, & Jolles, 2014; Senese et al., 2015; Tremblay et al., 2015).

The first part of this test requires participants to copy the figure as precisely and accurately as possible (Anderson, 2000; Casarotti, Papagno, & Zarino, 2014; Grieve, 2001; Lezak et al., 2012; Luzzi et al., 2011; Senese et al., 2015; Tremblay et al., 2015). This phase serves as a measure of planning and organisational skills (Grieve, 2001; Senese et al., 2015). Following a three minute period, and without prior notice, he or she is asked to replicate the figure from memory (Casarotti et al., 2014; Grieve, 2001; Lezak et al., 2012; Luzzi et al., 2011; Senese et al., 2015; Tremblay et al., 2015). This is known as the immediate recall condition, which measures visual episodic memory (Blaskewitz, Marten, & Brockhaus, 2009; Lezak et al., 2012; Senese et al., 2015). A delayed recall is sometimes included, which requires the participant to draw the figure again after a period of 30 minutes, which gives an indication of the participants’ long-term visual memory (Anderson, 2000; Blaskewitz et al., 2009; Grieve, 2001; Lezak et al., 2012; Tremblay et al., 2015).

In addition to visuospatial memory, the RCF tests a number of cognitive processes, such as perceptual abilities, perceptual organisation, visual episodic memory, planning, constructional praxis, visuoconstructional and visuospatial abilities (Blaskewitz et al., 2009; Casarotti et al., 2014; Lezak, 2012; Martens et al., 2014; Senese et al., 2015; Tremblay et al., 2015), some of which have been linked to the process of deception (Johnson Jr. et al., 2004; Gombos, 2006; Mohamed et al., 2006).

There are a number of methods of scoring used for the RCFT, which include either quantitative or qualitative ratings of performance, or both (Anderson, 2000; Grieve, 2001; Lezak et al., 2012; Martens et al., 2014; Spreen & Strauss, 1998; von Rhein et al., 2015). For the purpose of this study, the quantitative method will be used, which differentiates 18 distinctive elements and scores them according to their accuracy and placement. Each element can receive 0 or 1 for placement, and 0, 0.5, or 1 point

57 for accuracy. These scores are then added up to produce a total score, ranging from 0 to 36 points (Anderson, 2000; Martens et al., 2014; Spreen & Strauss, 1998; von Rhein et al., 2015). Spreen & Strauss (1998) provide norms for different age groups against which the participants’ results were compared to interpret the relevance of their scores.

There is contradicting information in the body of research based on the RCFT as to whether sociodemographic factors have an effect on performance of the neuropsychological test (Casarotti et al., 2014; Lezak et al., 2012; Tremblay et al., 2015). Age, level of education, gender, intellectual ability and culture are amongst these factors (Berry, Allen, & Schmitt, 1991; Caffarra, Vezzadini, Diece, Zonato, & Venneri, 2002; Grieve, 2001; Lezak et al., 2012; Hubley, 2010; Tremblay et al., 2015). Nevertheless, results on the RCFT have consistently been linked with general cognitive function, as well as visuo-constructional abilities, spatial reasoning and processing (Lezak et al., 2012; Senese et al., 2015). A number of studies have been conducted using the RCFT (Anderson, 2000; Blaskewitz et al., 2009; Casarotti et al., 2014; Grieve, 2001; Luzzi et al., 2011; Martens et al., 2014; Senese et al., 2015; Tremblay et al., 2015), which have found the measure to show sensitivity, internal consistency and reliability.

3.4.4 Rey Auditory Verbal Learning Test (RAVLT). The Rey Auditory Verbal Learning Test (RAVLT) is a commonly used neuropsychological test that simultaneously measures immediate verbal memory span, working memory, learning potential and the long term storage and recall of verbal information (Anderson, 2000; Blumenau & Broom, 2011; Carstairs, Shores, & Myors, 2012; Davis, Millis, & Axelrod, 2012; Grieve, 2001; Lezak et al., 2012; Messinis, Tsakona, Malefaki, & Papathanasopoulos, 2007; Rabin, Barr, & Burton, 2005; Spreen & Strauss, 1998; Vakil & Bachstein, 1993). Many of these constructs are necessary during deception, particularly working memory and the long-term retrieval of verbal data (Gombos, 2006; Hala & Russell, 2001; Johnson Jr. et al., 2004).

The test consists of a list of 15 words, which are read to the participant, who is required to recall as many words as possible. This process is repeated five times with the same list, after which a second list is presented for the participant to recall. Without prior notice, the participant is then asked to recall as many words as he/she can from the original list. This is followed by a delayed recall trial, after approximately 20 to 30 minutes (Anderson, 2000; Blumenau & Broom, 2011; Grieve, 2001; Lezak, Howieson, & Loring, 2004; Lezak et al., 2012; Messinis et al., 2007).

The initial presentation of the first list measures immediate recall abilities or working memory, by the number of words that are recalled (Anderson, 2000; Blumenau & Broom, 2011; Grieve, 2001; Lezak et al., 2012). The repetition of the first list serves as an indication of learning potential, by ascertaining whether the individual was able to recall more words in each successive attempt. The second list is introduced in order to assess whether the participant is adequately able to shift attention and memory functions, whereas the last two trials of the test measure the ability to retain information after distraction and long-term memory abilities, respectively (Anderson, 2000; Grieve, 2001; Lezak et al., 2012). This test therefore requires data to be processed in working memory and then transferred into long-term memory through repetition (Blumenau & Broom, 2011; Mansbach, Mace, & Clark, 2014). In addition, as the list is made up of mostly unrelated words, it requires participants to generate self-organizational strategies with which they recall the words (Mansbach et al., 2014).

Performance on this test is scored based on the number of words recalled on each trial (Anderson, 2000; Grieve, 2001; Lezak et al., 2012). The scores for each of the trials were interpreted using norms provided by Spreen and Strauss (1998) for the specific age group of the participant. An overall score can be obtained for trials 1 to 5 by adding the scores for these trials together (Anderson, 2000; Grieve, 2001; Lezak et al., 2012). Lezak et al. (2012) indicated that it is important to make note of any words that are repeated throughout the task, as numerous repetitions usually reflect self-monitoring and tracking difficulties, as well as learning deficits.

A number of variables of the RAVLT have been examined in studies, including age, gender, and level of education, with better performance being found in females, younger adult groups, and higher levels of education (Carstairs et al., 2012; Davis et al., 2012; Messinis et al., 2007; Vakil & Blachstein, 1993, 1997). Nevertheless, Tripathi, Kumar, & Bharath (2015) argue that word list tests are sensitive to identifying memory impairment in heterogeneous educational backgrounds. Another variable that should be considered is language experience. Although the RAVLT tests predominantly learning and recall of verbal data, the task involves comprehension of language (Blumenau & Broom, 2011). Furthermore, cultural differences have been found to affect the memory for verbal information, as people have been found to more readily recall words that are culturally significant (Blumenau & Broom, 2011; Tripathi et al., 2015). As a result of the numerous variables, many studies have been published providing normative data for the different variables, as well as a variety of different populations, indicating its acceptance as a diagnostic tool (Carstairs et al., 2012; Messinis et al., 2007; Vakil & Blachstein, 1997).

Some studies have noted that the RAVLT has poor test-retest reliability, which could be ascribed to a knowledge of the test and what is expected (Carstairs et al., 2012; Geffen, Butterworth, & Geffen, 1994). Nonetheless, certain measures on the RAVLT were found to show adequate test-retest reliability. These include the total number of words recalled over the first five trials and performance on the trial directly following the interference trial (Geffen et al., 1994). However, as the participants in this study were only tested once, this potential flaw of this test would not apply to this study.

Results on the RAVLT have consistently been linked to immediate verbal memory span, working memory, learning potential and long term verbal auditory recall (Anderson, 2000; Blumenau & Broom, 2011; Carstairs et al., 2012; Davis et al., 2012; Grieve, 2001; Lezak et al., 2004; Messinis et al., 2007; Rabin et al., 2005; Spreen & Strauss, 1998; Vakil & Bachstein, 1993). The RAVLT has further been shown to be sensitive to memory deficits and neurological impairment (Anderson, 2000; Grieve, 2001; Messinis et al., 2007; Ricci, Graef, Blundo, & Miller, 2012).

From a clinical perspective, it has been put forward that it might be beneficial to include both story recall and word lists in assessing cognition (Mansbach et al., 2014; Zahodne et al., 2011). Combining both metric types may improve overall diagnostic sensitivity, as individuals with varying cognitive, educational, and functional skills may differentially perform on word list and story recall metrics (Grieve, 2001; Mansbach et al., 2014; Rabin et al., 2009; Zahodne et al., 2011).

3.4.5 Babcock Story Recall Test. The Babcock Story Recall Test is a measure of verbal memory (Foldi, 2011; Horner, Teichner, Kortte, & Harvey, 2002; Tripathi et al., 2015). In the first phase of this test, the immediate recall trial, the participant is read a short story and then asked to repeat the story back immediately thereafter. The story is then repeated by the examiner, and following a 30 minute delay, the participant is asked to recite it again, which is known as the delayed recall trial (Horner et al., 2002; Lezak et al., 2012). This test requires the processing of auditory verbal information and engagement of working memory to enable encoding and consolidation of the information into both short-term and long-term memory (Mansbach et al., 2014).

While the immediate recall trial is a measure of working memory and immediate verbal auditory memory, the delayed recall trial indicates learning ability and episodic memory capacity (Foldi, 2011; Horner et al., 2002). Unlike word-list recall that necessitates exact recall of target words, story narratives involve semantically meaningful material and a number of associated ideas (Foldi, 2011; Lezak et al., 2012; Mansbach et al., 2014). Therefore, story recall tests resemble the memory required for everyday processing of information, as it places emphasis on the influence of a meaningful context to our memory capability (Lezak et al., 2012). This is a necessary process in deception, as deception occurs in the form of a story, or sequence of related events, which must be retained both in short-term and long-term memory.

The Babcock Story Recall Test is scored based on the number of units of the story that are recalled (Grieve, 2001; Lezak et al., 2012). Lezak et al. (2012) identified a problem which presents itself in the scoring of story recall tests, in that most people do not repeat the story exactly. Therefore, specific rules should be applied to alterations in order to ensure succinct and objective standards. Nevertheless, according to Lezak et al., (2012) this small margin of error is found to be of small consequence in most cases. Grieve (2001) indicated that participants should be able to recall at least half the content of the story. Research shows that there is usually an improvement in the score of approximately 4 points on the second recall (Lezak et al., 2012; Rapaport, Gill, & Schafer, 1968). For the purpose of this study, norms from Rapaport et al. (1968) were used, with which the performance of the participants was compared.

Variables which have been found to influence performance on story recall tests include age and level of education (Freides, Engen, Miller, & Londa, 1996; Lezak et al., 2012; Tripathi et al, 2015). Nevertheless, story recall is one of the most reliable neuropsychological tests for assessing verbal memory function with the intention of detecting memory and cognitive impairment and differentiating between persons with normal aging, mild cognitive impairment (MCI), dementia and Alzheimer's disease (Baek et al., 2011; Foldi, 2011; Lezak et al., 2012; Tripathi, 2015). As a measure of verbal memory, the delayed phase of the Babcock Story Recall Test has both convergent and divergent validity, which suggests that it is an appropriate measure of verbal memory of structured information (Horner et al, 2002). Furthermore, when scores from this test are compared with the Categories Completed score from the Wisconsin Card Sorting Test and a measure of remote memory, there is a sensitivity of 96.6% in accurate diagnosis classification (Lezak et al., 2012).

3.4.6 Controlled Oral Word Association Test (COWAT). The Controlled Oral Word Association Test (COWAT) is a commonly used test of verbal fluency and phonemic retrieval (Anderson, 2000; Garcia et al., 2015; Grieve, 2001; S.C. Johnson, Silverberg, Millis, & Hanks, 2012; Lezak et al., 2012; Rodriguez-Aranda & Martinussen, 2006). The participant is asked to list as many words as possible

62 starting with the letters “F”, “A”, and “S” within a time limit of 60 seconds per letter (Anderson, 2000; Grieve, 2001; S.C. Johnson et al., 2012; Lezak et al., 2012; Loonstra, Alison, & Sellers, 2001; Rodriguez-Aranda & Martinussen, 2006; Sugarman & Axelrod, 2015). In addition to this, a Category Naming Test is sometimes used as a supplementary measure of semantic fluency and cognitive flexibility (Anderson, 2000; Garcia et al., 2015; Grieve, 2001; Lezak et al., 2012; Sugarman & Axelrod, 2015).

The average adult produces between 36 and 42 words on the COWAT (Grieve, 2001; Lezak et al., 2012). In addition, Loonstra et al. (2001) combined statistics from a number of studies with a total of 17 625 participants, which gave an average aggregate score of 34.78 with a standard deviation of 12.83. For the purpose of this study, 36 to 42 words was used as the norm, against which the scores of the participants was measured.

Variables which may have an effect on results on this test include age, gender, cultural background, intelligence, and level of education (Anderson, 2000; Cockcroft, Alloway, Copello, & Milligan, 2015; Grieve, 2001; Lezak et al., 2012; Loonstra et al., 2001; Rodriguez-Aranda & Martinussen, 2006). The COWAT and the Category Naming Test have been found to be sensitive to brain lesions, brain dysfunction, frontal lobe disorders, and all dementing progressions, such as Alzheimer’s disease, as well as problems with language development in children (Anderson, 2000; Lezak et al., 2012; Loonstra et al., 2001; Rodriguez-Aranda & Martinussen, 2006).

3.4.7 Comprehension Test. The Comprehension Test, which was used as a subtest of the Wechsler Adult Intelligence Scale-III (WAIS-III), is a test of social reasoning and judgement, in addition to verbal conceptualization and comprehension (Beebe, Pfiffner, & McBurnett, 2000; Garcia et al., 2015; Krippner, 1964; Lezak et al., 2012; Nestor et al., 2013). It entails 18 open-ended questions involving either practical judgement or abstract reasoning. A score of 0, 1 or 2 is awarded for each item, depending on the relevance of the answer. This score is then converted to a

63 scaled score, for which 10 is considered average (Lezak et al., 2012; Linger, Ray, & Zachar, 2007).

The questions on this test deal with a variety of situations and activities that are largely social in nature, and involve knowledge of daily realities and comprehension of social norms, as well as verbal comprehension (Cockcroft et al., 2015; Grieve, 2001; Lezak et al., 2012; Krippner, 1964; Nestor et al., 2013). Although Lezak et al., (2012) argue that individuals with high scores on this test do not necessarily possess social competence, they would show a better understanding of social norms than their lower-scored counterparts. This understanding is vital in the process of social deception, which involves the perception of what is considered acceptable in social interactions (Abe, 2011; Carrion et al., 2010; DePaulo & Kashy, 1998; Hayashi et al., 2014; Saxe, 1991).

Variables which may have an impact on the results obtained on this test include age, level of education, cultural differences and understanding of the language (Lezak et al., 2012). The Comprehension Test is sensitive to traumatic brain damage and neuropsychological impairment as the result of a number of conditions, including multiple sclerosis and Alzheimer’s disease (Beebe et al., 2000; Lezak et al., 2012). The reliability of this test has been questioned, as it is dependant to some degree on the examiner’s perception of whether the answer given is correct (Linger et al., 2007), as has its validity as a measure of social intelligence (Beebe et al., 2000). Nevertheless, Lezak et al., (2012) argued that it has sound internal consistency and test-retest reliability. Further evidence indicates that the Comprehension Test is a valid measure of social comprehension, as research has been performed wherein the Comprehension Test was found to confirm two subtypes of mentally disordered murderers, and to predict mentally ill defendants that were incompetent to stand trial (Nestor, Daggett, Haycock, & Price, 1999; Nestor, Kimble, Berman, & Haycock, 2002; Nestor et al., 2013).

3.4.8 Digit Span Test. Another subtest of the Wechsler Adult Intelligence Scale-III (WAIS-III) that was used in this study was the Digit Span Test. It is a measure of attention and concentration, as well as working memory and mental tracking (Cockcroft et al., 2015; Lezak et al., 2012). It can be divided into two subtests, namely the Digits Forwards Test and the Digits Backwards Test, each of which assesses different mental abilities (Anderson, 2000; Lezak et al., 2012). The Digits Forwards Test requires participants to recite increasingly longer sequences of arbitrary numbers in the order in which they are read to them. The Digits Backwards Test then requires that participants recite different sequences of numbers in reverse order (Anderson, 2000; Cockcroft et al., 2015; Lezak et al., 2012).

The Digits Forwards Test measures auditory attention, concentration and incidental memory for auditory information (Anderson, 2000; Lezak et al., 2012), which are necessary cognitive processes for successful deception (Johnson Jr. et al., 2004; Gombos, 2006; Hala & Russell, 2001; Mohamed et al., 2006). The Digits Backwards Test is significantly more complex, as it involves not only sustained attention, but also working memory and mental double-tracking as it necessitates storing the data briefly and manipulating it (Anderson, 2000; Lezak et al., 2012), which is also crucial in the process of deception (Gombos, 2006; Hala & Russell, 2001; Johnson Jr. et al., 2004).

Lezak et al., (2012) suggested norms of 6 digits forwards, where 4 digits is considered borderline and 3 is impaired. On the digits backwards, 4 to 5 digits is considered to be an average result, while 3 is viewed as borderline to impaired. However, Anderson (2000) indicated that such norms are impractical in a South African context, and he has therefore developed norms based on local research with Zulu-speaking factory workers, which would be in line with their educational level. For the purpose of this study, the norms developed by Lezak et al (2012) were used as the sample in this case is comprised of individuals with a minimum of 12 years of education, and their performance should therefore be comparable to Western norms.

Performance on the Digit Span Test can vary depending on factors such as the participants’ level of education, culture, age, fatigue and even level of stress at the time of the test taking (Anderson, 2000; Cockcroft et al., 2015; Lezak et al., 2012). Nevertheless, it is considered to have high test-retest reliability (Lezak et al., 2012). The Digits Span Test is sensitive to head injuries, as well as a number of brain disorders and dementing processes (Anderson, 2000; Lezak et al., 2012).

3.4.9 Trail Making Test (TMT). The Trail Making Test (TMT) is frequently used to evaluate executive function. It is a measure of sustained attention, complex visual scanning, mental tracking and cognitive flexibility (Andrews, Shuttleworth, & Radloff, 2012; Garcia et al., 2015; Grieve, 2001; Lezak et al., 2012). This test is comprised of two sections. Part A requires participants to draw lines connecting a number of points in numerical order, as quickly as possible. Part B of the test entails alternating between numbers and letters in successive order, also within the shortest possible period of time (Anderson, 2000; Andrews et al., 2012; Grieve, 2001; Lezak et al., 2012). For each task, the individual is timed, and they are scored based on the amount of time taken to complete each task. Thus, TMT serves as a further measure of psychomotor speed (Anderson, 2000; Andrews et al., 2012; Grieve, 2001). It also requires participants to selectively screen out interfering stimuli, and relies on the working memory (Anderson, 2000; Andrews et al., 2012).

Spreen and Strauss (1998) have developed norms, based on age category against which the time can be compared. In addition, Anderson (2000) and Andrews et al (2012) have developed norms that could be applied to specific demographic groups of South Africans, based on specific demographic factors. However, for the purpose of this study, the norms developed by Spreen and Strauss (1998) will be used as a comparative measure, due to the varying demographics of the participants and the fact that they are all university students.

Variables influencing results on the TMT include age and level of education, although the literature varies on whether gender differences occur (Andrews et al.,

2012; Bornstein & Suga, 1988; Lezak et al., 2012; Mitrushina, Boone, & D’Elia, 2005). Furthermore, cross-cultural differences in TMT performance exist due to the importance of speed within different cultures, perceived task importance, and the quality of education (Andrews et al., 2012; Mitrushina et al., 2005; Strauss et al., 2006). Scores on the Trail Making Test have been found to correlate with other tests measuring similar constructs (Lezak et al., 2012). Furthermore, interpretations made from this test can be seen as a reliable indication of lesions or other damage to the brain, as well as dementia (Andrews et al., 2012; Anderson, 2000; Lezak et al., 2012; Stuss et al., 2001). Poor performance may also be found in individuals with cerebral dysfunction, depression with psychomotor retardation, or slow cognitive processing speed (Andrews et al., 2012; Grieve, 2001; Lezak et al., 2012).

3.4.10 Stroop Colour Word Test. The Stroop Colour Word Test serves as a measure of a number of psychological functions including cognitive control, selective attention and concentration, response inhibition, cognitive flexibility, and the ability to shift attention to adapt to varying demands (Anderson, 2000; Andrews et al., 2012;

Chang, Yusoff, & Begum, 2015; Garcia et al., 2015; Grieve, 2001; Lezak et al., 2004;

Lezak et al., 2012; Spreen & Strauss, 1998; Young, Bramham, Tyson, & Morris, 2006; Zalonis et al., 2009). The test is comprised of two pages which include between 100 and 112 colour words (blue, green, red, etc) arranged in four columns, printed in coloured ink that generally does not correspond with the word. The difference between the two forms is that the words are arranged in a different order (Grieve, 2011; Chang et al., 2015; Trenerry, Crosson, DeBoe, & Leber, 1989; Young et al., 2006; Zalonis et al., 2009).

The participant is first asked to read the words, while ignoring the colour of the ink, as fast as possible. On the second phase, they are requested to name the colour in which the word is printed, also within the shortest possible time (Grieve, 2001; Trenerry et al., 1989; Young et al., 2006; Zalonis et al., 2009). The second trial produces higher levels of interference because the individual has to inhibit the preferential response to process the verbal material (Mitrushina, Boone, Razani, & D’Elia, 1999; Spreen & Strauss, 1998; Young et al., 2006; Zalonis et al., 2009).

There are various ways of scoring the Stroop Test (Dodrill, 1978; Golden, 1978; Trenerry et al., 1989). One of these methods is based on the total number of correct responses within a 2 minute period for each of the phases (Anderson, 2000; Grieve, 2001), or alternative within a time frame of 45 seconds (Golden, 1978; Norman et al., 2011). Trenerry and colleagues (1989) have developed normative data for this type of scoring, for individuals between the ages of 18 and 49, and those over the age of 50 (Anderson, 2000; Grieve, 2001). For the purpose of this study, the 2 minute time period was used, and the norms from Trenerry et al (1989) were used as a means to score the results.

Factors influencing performance on the Stroop Test include age (Andrews et al., 2012; Hameleers et al., 2000; Ivnik, Malec, Smith, Tangalos, & Petersen, 1996; Klein, Ponds, Houx, & Jolles, 1997; Trenerry et al., 1989; Van Boxtel, Ten Tusscher, Metsemakers, Willems, & Jolles, 2001; Zalonis et al., 2009) and level of education (Andrews et al., 2012; Hameleers et al., 2000; Moering, Schinka, Mortimer, & Graves, 2004; Van Boxtel et al., 2001; Zalonis et al., 2009) and quality of education (Andrews et al., 2012; Manly, Byrd, Touradji, Sanches, & Stern, 2004; Nell, 1999; Shuttleworth-Edwards et al., 2004). Factors that present with variable data on whether there is a significant impact on test scores are gender differences (Andrews et al., 2012; Hameleers et al., 2000; Houx, Vreeling, & Jolles, 1993; Ivnik et al.,

1996; Klein et al., 1997; Moering et al., 2004; Trenerry et al., 1989; Van Boxtel et al., 2001) and cross-cultural differences (Andrews et al., 2012; Doan & Swerdlow, 1999; Mitrushina et al., 2005; Moering et al., 2004).

The Stroop Test has shown to be reliable, although there is variation in the findings as to its test-retest reliability (Lezak et al., 2012). Furthermore, the reliability of the scores obtained on the Stroop Test is highly consistent throughout the various versions of the test (Chang et al., 2015; Zalonis et al., 2009). It is sensitive to left hemisphere lesions, frontal lobe dysfunction, memory impairment associated with age, attention-deficit hyperactivity disorder, and head injury (Andrews et al., 2012; Lezak et al., 2012).

3.5 Procedure

Students were invited to participate in the research and 143 students volunteered. The 143 the voluntary participants were required to complete the biographical questionnaire and the BIDR, which was posted online by means of Survey Monkey. The BIDR was scored using the continuous method, by calculating the total scores for each dimension. A secondary party (the supervisor) scored the questionnaire and selected 26 students based on their results. 14 of the participants were selected from amongst the lowest scores and 12 were chosen from amongst the highest scores. These participants were then subjected to the neuropsychological tests, conducted by the researcher. These tests included the Rey-Osterrieth Complex Figure Test (RCFT), the Rey Auditory Verbal Learning Test (RAVLT), Babcock Story Recall Test, Controlled Oral Word Association Test (COWAT), Comprehension Test, Digit Span Test, Trail Making Test (TMT) and Stroop Colour Word Test. Given the fact that the scores of the BIDR were not known to the researcher at the time that the testing was done, this counteracted the researcher’s bias.

3.6 Data analysis

Data was analysed by dividing the sample into two groups according to the results of the BIDR. One group consisted of the participants with high scores of desirable responding and the other included low scores. The results of the cognitive tests were categorised as either superior, above average, average, below average, borderline or impaired, based on norms discussed above. This was done in order to give an indication of the individuals’ functioning when compared to expectations of the normal population. Furthermore, as some of the tests were time based, a higher score would suggest poorer performance. Thus, this method was used in order to provide distinct and comprehensive results.

The results of each of the participants on both the BIDR and the various cognitive tests were displayed on a Microsoft Excel spreadsheet. Thereafter, statistical analyses were conducted using SPSS. Frequency analysis was performed for demographic purposes. As the data for both instruments is on an interval / ratio level

69 of measurement, the Mann-Whitney U Test was applied in order to determine whether there are any between-group differences on the various tests of cognitive functions. Furthermore, the Chi-square and Fisher’s Exact Test were conducted.

3.7 Ethical Considerations

Ethics approval was granted by the Faculty of Humanities’ Ethical Committee before the research commenced (ethics approval number: 02-024-2016). Furthermore, the sample consists of participants who are of consenting age. Moreover, participation was voluntary and participants could choose to withdraw from the study at any stage. Anonymity was guaranteed to preserve the right to privacy of the participants. In addition, the volunteers were only included in the study once they gave written consent. The participants were debriefed in order to get a clear understanding of the procedure and aims of the study (Broadhead, 1984; Crano & Brewer, 2002) and upon request, feedback was provided regarding their results. Great care was taken not to let the participants identified as having “low cognitive ability” be openly referred to as such, since this could lead to emotional harm. Furthermore, the research itself did not cause any physical or psychological harm to the participants (Meltzoff, 2005).

Chapter 4:

Results

4.1 Introduction

This chapter demonstrates the results of the study conducted to investigate the relationship between cognitive ability and deception in university students. The first section contains the descriptive statistics for biographical questions posed in the survey for demographic purposes. These factors include age, gender and race. Subsequent to this, the inferential statistics are presented, implementing the method described in Chapter 3. This is comprised of the tables depicting the results from the Mann-Whitney U Test, as well as the Chi-Square and Fisher’s Exact Test. It should be noted that Group 1 was comprised of participants with high scores on the BIDR, while Group 2 contained those with low scores. The results of the neurocognitive tests were rated as either impaired, borderline, below average, average, above average and superior. Each of these categories was ascribed to a number ranging from 0 to 5 in ascending order. Therefore, an impaired score was assigned the number 0, while a borderline score was assigned number 1, a below average score was allocated the number 2, average was allocated number 3, above average was 4, and superior was 5.

4.2 Descriptive Statistics

The participants’ details were requested in the initial survey as part of the biographical questionnaire, as well as at the time of the testing. The below descriptive statistics pertain to the age, gender and race of the participants involved in this study.

4.2.1 Age.

Table 1

Age of participants

Age

Group 1 Group 2 Total Sample

Valid Cumulative Valid Cumulative Valid Cumulative N % % % N % % % N % % %

Valid 19 2 7.7 7.7 7.7 1 8.3 8.3 8.3 1 7.1 7.1 7.1

20 5 19.2 19.2 26.9 1 8.3 8.3 16.7 4 28.6 28.6 35.7

21 9 34.6 34.6 61.5 5 41.7 41.7 58.3 4 28.6 28.6 64.3

22 6 23.1 23.1 84.6 3 25.0 25.0 83.3 3 21.4 21.4 85.7

23 3 11.5 11.5 96.2 2 16.7 16.7 100.0 1 7.1 7.1 92.9

26 1 3.8 3.8 100.0 1 7.1 7.1 100.0

Total 26 100.0 100.0 12 100.0 100.0 14 100.0 100.0

The sample’s age ranged between 19 and 26 years old, with 21 years being the most prominent age (34.6%). This is considered to be in line with the population, which was comprised of third year Psychology students at the University of Johannesburg.

Within the different age groups, ages 19 years and 22 years were divided evenly between Group 1 and Group 2. The age categories 21 years, 23 years and 26 years were slightly slanted towards Group 1, with the difference of one student more in this group for each category. This was likely the result of each of these categories being comprised of an odd number of students. Thus, it would be impossible for these categories to be evenly distributed. The most noteworthy of the age categories, was 20 years, as it was comprised of one participant in Group 1 and four participants in

Group 2, suggesting that a large portion of the 20 year old participants scored low on the deceptive scale. It should be noted that this study was comprised of a small sample, with a small number of participants comprising each age group. Therefore, no generalizations can be made regarding difference in age and propensity for deception.

4.2.2 Gender.

Table 2

Gender of participants

Gender

Total Sample Group 1 Group 2

Valid Cumulative Valid Cumulative Valid Cumulative N % % % N % % % N % % %

Valid 0 6 23.1 23.1 23.1 2 16.7 16.7 16.7 4 28.6 28.6 28.6

1 20 76.9 76.9 100.0 10 83.3 83.3 100.0 10 71.4 71.4 100.0

Total 26 100.0 100.0 12 100.0 100.0 14 100.0 100.0

The sample consisted of 20 females (76.9% of the sample) and six males (23.1%). This slanted sample is likely associated with the skewed ratio of male to female students within the department of psychology. Thus, this is consistent with expectations of the population. The females within the sample were evenly spread throughout Group 1 and Group 2. However, of the six males in the sample, four of them obtained low scores on the BIDR and only two obtained high scores. As with the age categories, the small sample size once again makes it impossible to make generalisations based on gender.

4.2.3 Race.

Table 3

Race of participants

Race

Group 1 Group 2 Total Sample

Valid Cumulative Valid Cumulative Valid Cumulative N % % % N % % % N % % %

Valid 0 1 3.8 3.8 3.8 1 8.3 8.3 8.3

1 20 76.9 76.9 80.8 10 83.3 83.3 91.7 10 71.4 71.4 71.4

2 3 11.5 11.5 92.3 3 21.4 21.4 92.9

3 2 7.7 7.7 100.0 1 8.3 8.3 100.0 1 7.1 7.1 100.0

Total 26 100.0 100.0 12 100.0 100.0 14 100.0 100.0

The sample comprised of 20 black students (76.95%), three coloured students (11.5%), two indian students (7.7%) and one white student (3.8%). This is considered to be representative of the population of university students. The black students and the indian participants were divided equally between the two Groups. However, all three of the coloured participants scored low on the deceptive scale. Furthermore, the singular white participant scored high on the scale of social deception. However, this is not a sufficiently large group in order to make any generalizations.

4.3 Inferential Statistics

4.3.1 Mann-Whitney Test.

Table 4

Mann-Whitney Test ranks results

Ranks

Group N Mean Rank Sum of Ranks

BIDR 1 12 20.50 246.00

2 14 7.50 105.00

Total 26

RAVLT Immediate 1 12 14.25 171.00

2 14 12.86 180.00

Total 26

RAVLT T1-T5 1 12 15.00 180.00

2 14 12.21 171.00

Total 26

RAVLT Distractor 1 12 14.92 179.00

2 14 12.29 172.00

Total 26

RAVLT 6 1 12 16.13 193.50

2 14 11.25 157.50

Total 26

RAVLT delayed 1 12 16.04 192.50

2 14 11.32 158.50

Total 26

RAVLT repetition 1 12 12.25 147.00

2 14 14.57 204.00

Total 26

Babcock immediate 1 12 13.92 167.00

2 14 13.14 184.00

Total 26

Babcock delayed 1 12 14.67 176.00

2 14 12.50 175.00

Total 26

RCFT Copy 1 12 13.33 160.00

2 14 13.64 191.00

Total 26

RCFT Immediate 1 12 14.96 179.50

2 14 12.25 171.50

Total 26

RCFT delayed 1 12 14.33 172.00

2 14 12.79 179.00

Total 26

Stroop 1 12 12.96 155.50

2 14 13.96 195.50

Total 26

Digits forward 1 12 14.92 179.00

2 14 12.29 172.00

Total 26

Digits backward 1 12 15.63 187.50

2 14 11.68 163.50

Total 26

TMT - A 1 12 10.17 122.00

2 14 16.36 229.00

Total 26

TMT - B 1 12 12.21 146.50

2 14 14.61 204.50

Total 26

Comprehension 1 12 12.42 149.00

2 14 14.43 202.00

Total 26

COWAT 1 12 12.33 148.00

2 14 14.50 203.00

Total 26

Table 5

Summary of findings of the Mann-Whitney Test

Mann- Wilcox W Z Asymp. Sig. Exact Sig. Whitney U (2-tailed) [2*91-tailed Sig.)]

BIDR 0.00 105.000 -43.32 0.00 0.00

RAVLT 75.000 180.000 -.503 .615 .667 immediate

RAVLT T1-T5 66.000 171.000 -.985 .325 .374

RAVLT 67.000 172.000 -.949 .343 .403

77 distractor

RAVLT T6 52.500 157.500 -18.36 .066 .106

RAVLT delayed 53.500 158.500 -1.923 .055 .118

RAVLT 69.000 147.000 -.936 .349 .462 repetition

Babcock 79.000 184.000 -.267 .790 .820 immediate

Babcock 70.000 175.000 -.734 .463 .494 delayed

RCFT copy 82.000 160.000 -.106 .915 .940

RCFT 66.500 171.500 -1.313 .189 .374 immediate

RCFT delayed 74.000 179.000 -.704 .481 .631

Stroop 77.500 155.500 -.384 .701 .742

Digits forward 67.000 172.000 -.926 .355 .403

Digits 58.500 163.500 -1.400 .162 .193 Backward

TMT – A 44.000 122.000 -2.296 .022 .041

TMT - B 68.500 146.500 -.856 .392 .432

Comprehension 71.000 149.000 -.711 .477 .527

COWAT 70.000 148.000 -.744 .457 .494

The Mann-Whitney U Test was administered in order to determine whether any between-group differences exist on the various tests of cognitive functions. Only the results of the Trail Making Test (Part A) were found to vary significantly, with Group 2 performing better than Group 1.

4.3.2 Chi-Square.

Table 6

Results on the RAVLT Immediate Recall Trial

RAVLT Immediate

0 1 2 3 5 Total

Group 1 1 1 5 4 1 12

2 0 2 8 4 0 14

Total 1 3 13 8 1 26

Table 7

Calculation of Chi-Square Test for the RAVLT Immediate Recall Phase

Chi-Square Tests

Asymptotic Significance Value df (2-sided)

Pearson Chi-Square 2.889a 4 .577

Likelihood Ratio 3.657 4 .454

Linear-by-Linear .259 1 .611 Association

N of Valid Cases 26

a. 8 cells (80.0%) have expected count less than 5. The minimum expected count is .46.

There was no significant difference between the two groups on the RAVLT immediate recall phase.

Table 8

Results on the RAVLT T1-T5

RAVLT T1-T5

1 2 3 4 Total

Group 1 0 6 5 1 12

2 4 4 5 1 14

Total 4 10 10 2 26

Table 9

Calculation of Chi-Square Test on the RAVLT T1-T5

Chi-Square Tests

Asymptotic Significance Value df (2-sided)

Pearson Chi-Square 4.271a 3 .234

Likelihood Ratio 5.794 3 .122

Linear-by-Linear 1.212 1 .271 Association

N of Valid Cases 26

a. 6 cells (75.0%) have expected count less than 5. The minimum expected count is .92.

There was no substantial deviation between the two groups in the total number of words recalled on trials one to five.

Table 10

Results on the RAVLT Distractor Trial

RAVLT Distractor

1 2 3 4 Total

Group 1 1 4 6 1 12

2 4 3 7 0 14

Total 5 7 13 1 26

Table 11

Calculation of Chi-Square on the RAVLT Distractor Trial

Chi-Square Tests

Asymptotic Significance Value df (2-sided)

Pearson Chi-Square 2.883a 3 .410

Likelihood Ratio 3.380 3 .337

Linear-by-Linear 1.212 1 .271 Association

N of Valid Cases 26

a. 6 cells (75.0%) have expected count less than 5. The minimum expected count is .46.

No significant difference was found between the two groups on the Distractor Trial of the RAVLT.

Table 12

Results on the RAVLT Trial 6

RAVLT 6

1 2 3 Total

Group 1 0 3 9 12

2 3 5 6 14

Total 3 8 15 26

Table 13

Calculation of the Chi-Square Test on the RAVLT Trial 6

Chi-Square Tests

Asymptotic Significance Value df (2-sided)

Pearson Chi-Square 3.970a 2 .137

Likelihood Ratio 5.114 2 .078

Linear-by-Linear 3.720 1 .054 Association

N of Valid Cases 26

a. 4 cells (66.7%) have expected count less than 5. The minimum expected count is 1.38.

There was no significant deviation between the two groups on Trial 6 of the RAVLT.

Table 14

Results on the RAVLT Delayed Recall Trial

RAVLT delayed

1 2 3 4 Total

Group 1 1 0 9 2 12

2 2 3 9 0 14

Total 3 3 18 2 26

Table 15

Calculation of the Chi-Square Test on the RAVLT Delayed Recall Trial

Chi-Square Tests

Asymptotic Significance Value df (2-sided)

Pearson Chi-Square 5.210a 3 .157

Likelihood Ratio 7.117 3 .068

Linear-by-Linear 2.672 1 .102 Association

N of Valid Cases 26

a. 6 cells (75.0%) have expected count less than 5. The minimum expected count is .92.

No significant difference was observed between the two groups of the delayed recall trial of the RAVLT.

Table 16

Results on the RAVLT Repetition Condition

RAVLT repetition

0 1 Total

Group 1 9 3 12

2 8 6 14

Total 17 9 26

Table 17

Calculation of the Chi-Square Test on the RAVLT Repetition Condition

Asymptotic Significance Exact Sig. (2-Exact Sig. Value df (2-sided) sided) (1-sided)

Pearson Chi-Square .910a 1 .340

Continuity Correctionb .292 1 .589

Likelihood Ratio .924 1 .336

Fisher's Exact Test .429 .296

Linear-by-Linear .875 1 .349 Association

N of Valid Cases 26

a. 2 cells (50.0%) have expected count less than 5. The minimum expected count is 4.15. b. Computed only for a 2x2 table

Group 2 performed significantly better on the repetition condition of the RAVLT than Group 1

Table 18

Results on the Babcock Immediate Recall Trial

Babcock immediate

0 1 2 3 Total

Group 1 2 5 1 4 12

2 3 3 7 1 14

Total 5 8 8 5 26

Table 19

Calculation of the Chi-Square Test on the Babcock Immediate Recall Trial

Chi-Square Tests

Asymptotic Significance Value df (2-sided)

Pearson Chi-Square 6.887a 3 .076

Likelihood Ratio 7.542 3 .056

Linear-by-Linear .146 1 .702 Association

N of Valid Cases 26

a. 8 cells (100.0%) have expected count less than 5. The minimum expected count is 2.31.

No significant difference was noted on the Babcock immediate recall trial.

Table 20

Results on the Babcock Delayed Recall Trial

Babcock delayed

0 1 2 3 4 5 Total

Group 1 2 2 3 2 1 2 12

2 3 3 3 4 1 0 14

Total 5 5 6 6 2 2 26

Table 21

Calculation of the Chi-Square Test on the Babcock Delayed Recall Trial

Chi-Square Tests

Asymptotic Significance Value df (2-sided)

Pearson Chi-Square 2.930a 5 .711

Likelihood Ratio 3.701 5 .593

Linear-by-Linear .850 1 .356 Association

N of Valid Cases 26

a. 12 cells (100.0%) have expected count less than 5. The minimum expected count is .92.

There was no noteworthy difference between the two groups on the delayed recall trial of the Babcock Test.

Table 22

Results on the RCFT Copy Phase

RCFT Copy

0 1 2 3 Total

Group 1 4 2 2 4 12

2 2 4 6 2 14

Total 6 6 8 6 26

Table 23

Calculation of the Chi-Square Test on the RCFT Copy Phase

Chi-Square Tests

Asymptotic Significance Value df (2-sided)

Pearson Chi-Square 3.869a 3 .276

Likelihood Ratio 3.978 3 .264

Linear-by-Linear .027 1 .869 Association

N of Valid Cases 26

a. 8 cells (100.0%) have expected count less than 5. The minimum expected count is 2.77.

No significant difference was indicated on the copy phase of the RCFT.

Table 24

Results on the RCFT Immediate Recall Phase

RCFT Immediate

1 2 3 Total

Group 1 0 1 11 12

2 1 3 10 14

Total 1 4 21 26

Table 25

Calculation of the Chi-Square Test on the RCFT Immediate Recall Phase

Chi-Square Tests

Asymptotic Significance Value df (2-sided)

Pearson Chi-Square 1.905a 2 .386

Likelihood Ratio 2.326 2 .312

Linear-by-Linear 1.831 1 .176 Association

N of Valid Cases 26

a. 4 cells (66.7%) have expected count less than 5. The minimum expected count is .46.

No significant difference was indicated on the RCFT immediate recall trial.

Table 26

Results on the RCFT Delayed Recall Phase

RCFT delayed

2 3 Total

Group 1 2 10 12

2 4 10 14

Total 6 20 26

Table 27

Calculation of the Chi-Square Test on the RCFT Delayed Recall Phase

Chi-Square Tests

Asymptotic Significance Exact Sig. (2-Exact Sig. Value df (2-sided) sided) (1-sided) Pearson Chi-Square .516a 1 .473 Continuity Correctionb .063 1 .802 Likelihood Ratio .526 1 .468 Fisher's Exact Test .652 .404 Linear-by-Linear .496 1 .481 Association N of Valid Cases 26

a. 2 cells (50.0%) have expected count less than 5. The minimum expected count is 2.77. b. Computed only for a 2x2 table

There was no indication of a significant difference between the two groups on the delayed recall trial of the RCFT.

Table 28

Results on the Stroop Test

Stroop

0 1 2 3 Total

Group 1 2 3 0 7 12

2 2 2 1 9 14

Total 4 5 1 16 26

Table 29

Calculation of the Chi-Square Test on the Stroop Test

Chi-Square Tests

Asymptotic Significance Value df (2-sided)

Pearson Chi-Square 1.304a 3 .728

Likelihood Ratio 1.684 3 .640

Linear-by-Linear .202 1 .653 Association

N of Valid Cases 26

a. 6 cells (75.0%) have expected count less than 5. The minimum expected count is .46.

There was no significant difference on the Stroop Test.

Table 30

Results on the Digits Forward Test

Digits forward

0 1 2 3 4 Total

Group 1 0 2 4 5 1 12

2 1 2 7 3 1 14

Total 1 4 11 8 2 26

Table 31

Calculation of the Chi-Square Test on the Digits Forward Test

Chi-Square Tests

Asymptotic Significance Value df (2-sided)

Pearson Chi-Square 2.177a 4 .703

Likelihood Ratio 2.566 4 .633

Linear-by-Linear .851 1 .356 Association

N of Valid Cases 26

a. 8 cells (80.0%) have expected count less than 5. The minimum expected count is .46.

No significant difference was noted on the Digits Forward task.

Table 32

Results on the Digits Backwards Test

Digits backward

0 1 2 3 Total

Group 1 0 2 3 7 12

2 3 2 4 5 14

Total 3 4 7 12 26

Table 33

Calculation of the Chi-Square Test on the Digits Backwards Test

Chi-Square Tests

Asymptotic Significance Value df (2-sided)

Pearson Chi-Square 3.342a 3 .342

Likelihood Ratio 4.483 3 .214

Linear-by-Linear 2.309 1 .129 Association

N of Valid Cases 26

a. 6 cells (75.0%) have expected count less than 5. The minimum expected count is 1.38.

There was no significant difference between the two groups on the Digits Backwards Task.

Table 34

Results on the TMT – Part A

TMT - A

0 1 2 3 4 Total

Group 1 2 1 4 5 0 12

2 0 2 0 10 2 14

Total 2 3 4 15 2 26

Table 35

Calculation of the Chi-Square Test on the TMT – Part A

Chi-Square Tests

Asymptotic Significance Value df (2-sided)

Pearson Chi-Square 9.905a 4 .042

Likelihood Ratio 12.975 4 .011

Linear-by-Linear 4.170 1 .041 Association

N of Valid Cases 26

a. 8 cells (80.0%) have expected count less than 5. The minimum expected count is .92.

Group 2 performed significantly better on the TMT, Part A, than Group 1.

Table 36

Results on the TMT – Part B

TMT - B

0 1 2 3 4

Group 1 2 1 2 7 0

2 2 1 2 6 3

Total 4 2 4 13 3

Table 37

Calculation of the Chi-Square Test on the TMT – Part B

Chi-Square Tests

Asymptotic Significance Value df (2-sided)

Pearson Chi-Square 2.940a 4 .568

Likelihood Ratio 4.082 4 .395

Linear-by-Linear .450 1 .502 Association

N of Valid Cases 26

a. 8 cells (80.0%) have expected count less than 5. The minimum expected count is .92.

There was no significant difference on the Trail Making Test – Part B.

Table 38

Results on the Comprehension Test

Comprehension

0 1 2 3 5 Total

Group 1 2 3 2 5 0 12

2 2 3 1 7 1 14

Total 4 6 3 12 1 26

Table 39

Calculation of the Chi-Square Test on the Comprehension Test

Chi-Square Tests

Asymptotic Significance Value df (2-sided)

Pearson Chi-Square 1.522a 4 .823

Likelihood Ratio 1.907 4 .753

Linear-by-Linear .546 1 .460 Association

N of Valid Cases 26

a. 8 cells (80.0%) have expected count less than 5. The minimum expected count is .46.

No significant difference was indicated on the Category Naming Test.

Table 40

Results on the COWAT

COWAT

1 2 3 4 5 Total

Group 1 4 3 3 1 1 12

2 2 6 2 2 2 14

Total 6 9 5 3 3 26

Table 41

Calculation of the Chi-Square Test on the COWAT

Chi-Square Tests

Asymptotic Significance Value df (2-sided)

Pearson Chi-Square 2.394a 4 .664

Likelihood Ratio 2.426 4 .658

Linear-by-Linear .552 1 .457 Association

N of Valid Cases 26

a. 10 cells (100.0%) have expected count less than 5. The minimum expected count is 1.38.

There was no significant difference between the two groups on the COWAT.

4.4 Conclusion

The above results suggested that although there was a general trend in the expected direction, most of the tests did not have a significant association with the results of the BIDR. The Mann-Whitney Test showed that Group 2 performed significantly better on the TMT, Part A. The Chi-Square Test confirmed this finding and further noted that individuals from Group 2 also performed better on the Repetition condition of the RAVLT. Due to the limited significant findings based on the scaled scores and categorization of the results, the raw scores of the tests were subjected to parametric statistical techniques. This yielded only one significant difference, on the RAVLT T6, thus confirming the above findings of no significant difference for majority of the tests.

Chapter 5:

Discussion and Conclusion

5.1 Introduction

In order to explore whether there is a relationship between cognitive ability and proneness for deception, a comparative study was conducted between two groups. These two groups were comprised of individuals who scored high on deception and those that received low scores. The results of the cognitive tests of the two groups were compared in order to establish whether there is any significant difference between low deceivers and high deceivers on the various cognitive functions. The findings, which are presented in the chapter above, showed no significant correlation between cognitive ability and propensity for deception, as only two of the test conditions revealed significant findings. In this chapter, observations are made pertaining to the demographic frequencies on the BIDR, the comparative results are discussed in relation to previous research within the field, and the possible implications are noted. Furthermore, limitations of this study are discussed, as well as recommendations for future research. This is followed by concluding remarks regarding the research study.

5.2 Demographic Frequency

It is difficult to make demographic assumptions based on the results of the current study due to the small number of participants that are contained within each category of demographic factors when the participants are divided amongst them. One of the few noteworthy findings in this regard is that a large portion of the 20 year old participants obtained low scores on the BIDR. Furthermore, while females were evenly spread between high and low deceivers, a large portion of the males obtained low scores on the BIDR, showing low social deception. The only notable result to be reported with regards to the different races was that all the coloured participants scored low on the deceptive scale. However, as previously noted, it would not be correct to state that any specific age, gender or race is highly deceptive or less deceptive based on the few participants that would fall within that category.

5.3 Trends

Although most of the tests did not yield a significant difference between the two groups, a general trend was seen in 11 of the 18 test conditions, whereby Group 1 (high scores on the BIDR) performed generally better than Group 2 (low scores on the BIDR). Thus, it would appear that people who are more prone to social deception performed slightly better than those less prone to deception on most of the cognitive tasks. However, the difference in the scores was not significant.

The test conditions that showed better performance among high deceivers, although not to a significant degree, include a number of the conditions of the RAVLT, including Trial 1, the sum of Trial 1 to 5, the distractor trial, Trial 6 and Trial 7. A similar trend was noted on the Babcock Story Recall Test (both the immediate and delayed recall trials), the recall trials of the RCFT, and the Digit Span Test (both forward and backwards). The common thread amongst these tasks is that they predominantly measure memory, be it short-term memory, working memory or long- term memory (Anderson, 2000; Blaskewitz et al., 2009; Blumenau & Broom, 2011; Carstairs et al., 2012; Davis et al., 2012; Foldi, 2011; Grieve, 2001; Horner et al., 2002; Lezak et al., 2012; Mansbach et al., 2014; Messinis et al., 2007; Rabin et al., 2005; Senese et al., 2015; Spreen & Strauss, 1998; Tremblay et al., 2015; Vakil & Bachstein, 1993). Thus, according to the above results, individuals who are more prone to deception possess marginally better memory than those who are less prone to deception, although not to a significant degree.

There were also tests wherein low deceivers performed better than high deceivers. However, of these, only Part A of the TMT and the repetition condition of the RAVLT showed a significant difference between the two groups. The TMT, Part A, serves primarily as a measure of simple mental tracking and concentration (Andrews et al., 2012; Garcia et al., 2015; Grieve, 2001; Lezak et al., 2012). On the other hand the repetition condition of the RAVLT measures self-monitoring ability. Numerous repetitions throughout the RAVLT are often indicative of difficulties with self- monitoring and mental tracking. The absence of repetitions therefore suggests that the individual was able to adequately monitor their responses and mentally keep

99 track of their answers (Lezak et al., 2012). Therefore, the results of this study suggest that low deceivers exhibit significantly better mental tracking abilities and self-monitoring than high deceivers. Alternatively perceived, individuals with better mental tracking and self-monitoring abilities appear to be less prone to social deception.

The other tasks that showed better performance among non-deceivers as compared with deceivers include the TMT (Part B), the Stroop Test, RCFT copy trail, Comprehension Test and the COWAT. These tests measure an array of cognitive functions including complex conceptual tracking, selective attention, response inhibition, visuospatial abilities, perceptual organization, planning, social reasoning and verbal fluency (Anderson, 2000; Andrews et al., 2012; Beebe et al., 2000; Casarotti et al., 2014; Chang et al., 2015; Garcia et al., 2015; Grieve, 2001; S.C. Johnson et al., 2012; Krippner, 1964; Lezak et al., 2004; Lezak et al., 2012; Luzzi et al., 2011; Nestor et al., 2013; Rodriguez-Aranda & Martinussen, 2006; Senese et al., 2015; Spreen & Strauss, 1998; Tremblay et al., 2015; Young et al., 2006; Zalonis et al., 2009). The results therefore imply that people with a lower tendency toward deception possess these cognitive functions to higher degree, although not significantly.

5.4 Explanation

Despite the slight trends that were observed, most of the findings were not significant. Therefore, this research suggests that individuals that are prone to deception do not possess significantly superior cognitive skills to those who are less prone to deception, or vice versa. It would appear that although these cognitive functions are involved in the process of deception (Buller & Burgoon, 1996; Carter et al., 1998; Gehring & Knight, 2000; Gombos, 2006; Johnson Jr. et al., 2004; Lane & Wegner, 1995; Mohamed et al., 2006; Talwar & Crossman, 2011; Turken & Swick, 1999; Visu-Petra et al., 2014; Vrij et al., 2010; Walczyk et al., 2003; Zuckerman et al., 1981), cognitive abilities have no significant correlation with an individual’s propensity for deception. This leads to the conclusion that whether an individual is prone to deception must be ascribed elsewhere. One possibility is that this is

100 associated more closely with personality traits than an individual’s cognitive strengths (DePaulo et al., 1996; Kashy & DePaulo, 1996; Vrij et al., 2010).

As noted in the literature review above, Kashy and DePaulo’s (1996) study found that manipulativeness, impression management, extroversion, level of responsibility and quality of same-sex relationships are all significantly linked to people’s predisposition for deception. Manipulative people use deception as a means to influence people and attain their personal goals. Furthermore, manipulative individuals are better liars (Vrij et al., 2010) and engage in deception more frequently (Kashy & DePaulo, 1996; Virj et al., 2010) than individuals who are not manipulative by nature.

Unlike manipulators, people high in impression management adjust their own behavior (as opposed to that of other people) in order to achieve their social goals (Cervellione et al., 2009; Cole & Rozell, 2011; DePaulo et al., 1996; deVries et al., 2014; Farrow et al., 2015; Kashy & DePaulo, 1996; Leary & Kowalski, 1990; McGowan et al., 2008; Schlenker, 1980; Visu-Petra et al., 2014). Kashy and DePaulo (1996) found that this motivation to appear in a positive light to others leads these individuals to be more deceptive than people who are less concerned with what other people think of them.

Their research further showed that people who are more sociable have a higher need for social deception and are consequently more prone to deception. Thus, extroverted people lie more frequently than introverts, given the same number of opportunities for deception (Kashy & DePaulo, 1996). Kashy and DePaulo’s (1996) study further indicated that people who have a thorough understanding of the cultural norms of their society would be less likely to engage in lying and deception because most societies view deception to be, at least to some extent, immoral (Nyberg, 1993; Saarni & Lewis, 1993; Saxe, 1994; Walczyk et al., 2003). This was reflected in the current study within the results of the Comprehension Test. Although the findings

101 were not significant, there was a trend towards better social understanding in individuals who are less socially deceptive.

The final factor, and the most reliable predictor of lying tendency according to Kashy and DePaulo (1996), is relationship quality. They found that individuals with more fulfilling same-sex relationships are less prone to deception than those with less rewarding ones. As the current study cannot provide a definitive link between cognitive ability and inclination toward deception, future research should possibly direct focus onto personality traits as a contributing factor to deceptive tendencies.

Furthermore, this study specifically investigated people’s predisposition for deception, as opposed to deceptive ability. Due to the intellectual nature of deception and the cognitive processes involved therein (Botvinick et al., 2001; Carter et al., 1998; Carrion et al., 2010; Debey et al., 2015; Gehring & Knight, 2000; Gombos, 2006; Johnson Jr. et al., 2004; Moomal & Henzi, 2000; Talwar & Crossman, 2011; Turken & Swick, 1999; Vrij et al., 2010; Walczyk et al., 2003), it is possible that cognitive ability is linked more closely with how well people can achieve deception (Vrij et al., 2010), as opposed to how often they engage in deception. Although there is not a great deal of literature on what makes some people better at deceiving others, it has been found that intelligence, good memory, astute planning abilities, quick thinking and verbal eloquence are characteristics of good liars (Ekman & Frank, 1993; Vrij et al., 2010; Vrij & Mann, 2001). Thus, the cognitive functions that determine better deceptive abilities is another possible course for future research.

5.5 Theoretical and Practical Implications

This study enhances the body of knowledge on the topic of deception and the cognitive functions involved therein. Although research has found that some people engage in deceptive behavior more frequently and readily than others (DePaulo et al., 1996; Kashy & DePaulo, 1996; Serota & Levine, 2015; Serota et al., 2010), an extensive investigation into the available literature found that little is known about the factors that influence individuals’ predisposition for deception. This study therefore

102 addresses this gap in literature. Although there were not sufficient significant findings to establish a correlation between cognitive abilities and proclivity for deception, this study narrows down the possibilities and highlights possible explanations that warrant future research.

As deception is an integral part of many aspects of human life and plays a role within many spheres of psychology (Abe, 2011; Carrion et al., 2010; DePaulo & Kashy, 1998; DePaulo et al., 1996; Dunbar et al., 2016; Ennis et al., 2008; Gombos et al., 2006; Hayashi et al., 2014; Kashy & DePaulo, 1996; Knapp, 2008; Levine & McCornack, 2014; Martinez-Gonzalez et al., 2016; Talwar & Crossman, 2011; Visu- Petra et al., 2014; Walczyk et al., 2003; Zagorin, 1996), this study further adds to the growth of knowledge within the fields of social psychology, developmental psychology, forensic psychology and clinical psychology (Farrow et al., 2015; Gombos, 2006; Troisi, 2011).

5.6 Limitations

A limitation of this study is the small sample size. It is possible that a greater sample size might have revealed more succinct results. However, due to the limitations of the Masters dissertation, time did not allow for the testing of a greater number of participants. Therefore, it would be imperative to view this study as accurate in light of the circumstances surrounding the study.

The research process further allowed for human error, as the testing was conducted by the researcher, as opposed to a computerized version of the tests. In such instances, human error can occur, as with any other study conducted by human researchers. However, every measure was taken to ensure a precise and candid analysis of the participants’ cognitive abilities. It should further be noted that the researcher has undergone extensive training in the content, examination, scoring and analysis of each of the tests. Furthermore, this study attempted to minimize examiner’s bias, as the researcher did not know at the time of the assessments which of the participants scored high or low on the BIDR. Thus, the findings could

103 not be skewed according to the researcher’s preconceptions of what the results should entail.

Another possible limitation of the present study is the tests themselves, which each possess their own restrictions, as previously noted in the methodology chapter. Nevertheless, each of the tests used in this study have been scrutinized by past researchers and have been found to be as valid and reliable as possible, and are therefore widely accepted as neuropsychological measures (Anderson, 2000; Baek et al., 2011; Blaskewitz et al., 2009; Casarotti et al., 2014; Cervellione et al., 2009; Djikic et al., 2005; Djikic et al., 2007; Farrow et al., 2015; Foldi, 2011; Horner et al, 2002; Lanyon & Carle, 2007; Lezak, 1995; Lezak et al., 2012; Loonstra et al., 2001; Luzzi et al., 2011; Martens et al., 2014; Messinis et al., 2007; Nestor et al., 1999; Nestor et al., 2002; Nestor et al., 2013; Paulhus, 1991; Rodriguez-Aranda & Martinussen, 2006; Senese et al., 2015; Tremblay et al., 2015; Tripathi, 2015; Uziel, 2014; Visu-Petra et al., 2014).

5.7 Concluding Remarks

With consideration to the limitations and implications, this study investigated and tested the relationship between cognitive capability and propensity for deception. However, no significant correlation was found. This research was presented in a precise and logical manner, so as to ensure the merit and validity of the findings. It found that although cognitive functions are a crucial aspect of deception, an individual’s level of cognitive ability has no bearing on their tendency to be deceptive. Instead, one of the possible alternative explanations could be that personality traits, more than cognitive functioning, have an impact on propensity for deception. Furthermore, cognitive functioning may be more closely linked to aptitude at deception, as opposed to inclination toward deception. Both these prospects exhibit potential for future research.

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Appendix A

Biographical Questionnaire

What is your age?

What is your gender?

Male Female Other (Please specify)

What is your ethnicity?

Other (please specify) Black Coloured Indian White

What is your first language?

Other (please specify) Afrikaans English Ndebele Northern Sotho Sotho Swati Tsonga Tswana Venda Xhosa Zulu

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Appenix B

Balanced Inventory of Desirable Responding (BIDR)

Using the scale below as a guide, write a number beside each statement to indicate how true it is.

+ + + + + + + 1 2 3 4 5 6 7 not true somewhat very true

____ 1. My first impressions of people usually turn out to be right.

____ 2. It would be hard for me to break any of my bad habits.

____ 3. I don't care to know what other people really think of me.

____ 4. I have not always been honest with myself.

____ 5. I always know why I like things.

____ 6. When my emotions are aroused, it biases my thinking.

____ 7. Once I've made up my mind, other people can seldom change my opinion.

____ 8. I am not a safe driver when I exceed the speed limit.

____ 9. I am fully in control of my own fate.

____ 10. It's hard for me to shut off a disturbing thought.

____ 11. I never regret my decisions.

____ 12. I sometimes lose out on things because I can't make up my mind soon enough.

____ 13. The reason I vote is because my vote can make a difference.

____ 14. My parents were not always fair when they punished me.

____ 15. I am a completely rational person.

____ 16. I rarely appreciate criticism.

____ 17. I am very confident of my judgments

____ 18. I have sometimes doubted my ability as a lover.

____ 19. It's all right with me if some people happen to dislike me.

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____ 20. I don't always know the reasons why I do the things I do.

Using the scale below as a guide, write a number beside each statement to indicate how true it is.

+ + + + + + + 1 2 3 4 5 6 7 not true somewhat very true

____ 21. I sometimes tell lies if I have to.

____ 22. I never cover up my mistakes.

____ 23. There have been occasions when I have taken advantage of someone.

____ 24. I never swear.

____ 25. I sometimes try to get even rather than forgive and forget.

____ 26. I always obey laws, even if I'm unlikely to get caught.

____ 27. I have said something bad about a friend behind his/her back.

____ 28. When I hear people talking privately, I avoid listening.

____ 29. I have received too much change from a salesperson without telling him or her.

____ 30. I always declare everything at customs.

____ 31. When I was young I sometimes stole things.

____ 32. I have never dropped litter on the street.

____ 33. I sometimes drive faster than the speed limit.

____ 34. I never read sexy books or magazines.

____ 35. I have done things that I don't tell other people about.

____ 36. I never take things that don't belong to me.

____ 37. I have taken sick-leave from work or school even though I wasn't really sick.

____ 38. I have never damaged a library book or store merchandise without reporting it.

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____ 39. I have some pretty awful habits.

____ 40. I don't gossip about other people's business.

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