Ease, attitude, and prevalence of lying amongst bankers,:
The role of psychopathic traits
Name:
Verele Vorstman
Student number:
0486221
Supervisor:
B.J. Verschuere
Institution:
University of Amsterdam
Department:
Klinische Psychologie
Abstract
Bankers are generally thought to lie more easily, more readily and more frequently than others, as well as to have more psychopathic traits that are allegedly linked to this perceived deceitful attitude. The goal of this study was to test this assumed popular stance towards deceit in bankers and its relation to levels of psychopathy. Ease, valence, and frequency of lying were assessed separately and correlated with psychopathy in a group of 63 bankers. Firstly, we examined response times (RTs) on a laptop with the Sheffield Lie test in a combined picture and text response task to assess ease and valence of lying. Frequency of lying was assessed with the Serota test. Secondly, we tested whether the bankers’ levels of psychopathy were related to the outcomes on these three indicators.
Psychopathy was measured with the Levenson Self-Report Psychopathy Scale (LSRP). Results indicate as expected that lies were slower than truths. However, counter expectation, a particular valence of lying remained undetermined. Secondly, no correlations between subjects’ psychopathy levels and their ease, valence, or frequency of lying were found. Implications are that RTs on a computer lie-detection task may not generalise to everyday life deceit in a banker population. Concluding, with our current instrument and set up it may not be viable to draw inferences about the levels of psychopathy amongst bankers.
Introduction
Currently, when searched for corporate scandals on Google for deviant and even criminal corporate behaviour, 4,120,000 results are found. Wikipedia (2013) lists 112 corporate scandals, of which banks and financial institutions represent 30% in increasing amounts over the years. The awareness of extensive corporate wrongdoing sparked a crisis of distrust in corporations and corporate management (Yu & Zhang, 2006). A plenitude of causes can be indicated to be at the root of this problem, such as a lack of governance, failing implementation of regulations, bad management and a lack of retribution. This paper will however focus on some personal factors within banks that may contribute to this situation. Some researchers have made attempts at describing possible characteristics that allow some individuals to adopt a self-enriching stance (Boddy, 2011; Hare, 2003; Kirkman, 2005), which may be detrimental to customers, the company, and even society. They suggest that varying degrees of psychopathic traits may be found in most individuals, higher levels of which make them prone to manipulative, deceitful and instrumental behaviour (Lilienfeld & Widows, 2005).
Psychopathy
Individuals high in psychopathic traits present with diminished empathy, conscience and care about anybody but themselves (Boddy, 2011). On varying levels, a lack of affect, superficial relationships, instantaneous and excessive outbursts of rage, and sometimes violence may be further characteristics of individuals high in psychopathic traits (Hildebrand, 2004). The Diagnostic and Statistical Manual of Mental Disorders (DSM-IVTR, American Psychiatric Association, 2007) offers no official diagnosis of psychopathy (Hildebrand & de Ruiter, 2004), though referring to a definition based on the leading psychopathy checklist designed by Hare (2003), a substantial overlap with antisocial personality disorder (APD) is present (Hildebrand, 2004). Nonetheless, psychopathy is a separable construct that places a greater emphasis on affective (e.g., lack of empathy) and interpersonal (e.g., manipulative) traits (Edens, Marcus, Lilienfeld & Poythress, 2006). Individuals presenting with psychopathy often meet criteria for APD, though vice versa this is generally not the case (Hildebrand, 2004).
Hare (2003) has developed an interview-based rating scale, the PCL-R (Psychopathy Checklist Revised) that is considered the gold standard for measuring psychopathy in a forensic context. Individuals scoring above the cut-off of 30 (out of 40) are considered to take up about 1% of the population (Hare, 2003). The scale measures two constructs. Factor 1 is a personality construct: "Aggressive narcissism", measuring glibness/superficial charm, pathological lying,
conning/manipulative attitude, and lack of remorse or guilt. Factor 2 describes the case history as "Socially deviant lifestyle", measuring need for stimulation/proneness to boredom, parasitic lifestyle, poor behavioural control, lack of realistic long-term goals, and impulsivity. Following the PCL-R, some self-report measures have been designed that are less time consuming and geared towards a non-forensic population, such as the Youth Psychopathic trait Inventory (YPI, Andershed, Kerr, Stattin &
Lavender, 2002) and the Psychopathic Personality Inventory-Revised (PPI-R; Lilienfeld & Widows, 2005).
In this study, the LSRP (Levenson's Self Report Psychopathy Scales: Levenson, Kiehl & Fitzpatrick, 1995) will be used, equally based on the PCL-R. The LSRP is geared towards and validated on measuring psychopathy, as well as the demeanour towards any anomaly found, in a non-clinical population. In contrast, earlier measures are mostly aimed at testing forensic settings. Self-report measures have been criticized for being less reliable due to demand characteristics (Holden, Wood & Tomashewski, 2001), especially when adopted in measuring behavioural patterns related to deceit (Cottler, Compton, Ridenour, Abdallah & Gallagher, 1998) of which salient characteristics are proneness to deceit and manipulation (Halevy, Shalvi, & Verschuere, 2013). However, several studies have validated self-report measures for psychopathy (Halevy et al., 2013; Porter, ten Brinke, Baker & Wallace, 2011; Zeier, & Newman, 2011) as presenting reliabilities and validities approximately in the same range as interviews.
Psychopathy in bankers
Scientists have recently suggested approaching psychopathy as a dimensional construct, instead of taking the historically applied dichotomous approach (e.g. Edens et al., 2006). This implies that psychopathy may be found throughout the entire population (Lilienfeld & Widows, 2005), with varying levels of its traits (Uzieblo, Verschuere & Crombez, 2007). A number of authors have
suggested that psychopathy can occasionally manifest itself in successful individuals that show at least subclinical presentations (Smith & Lilienfeld, 2013). In line with this, significant characteristics of personality disorders - mainly in the psychopathic realm - have been found amongst normally functioning managers, though not specifically bankers (Board & Fritzon, 2005).
Several researchers have suggested that companies begetting high financial yields attract and accommodate relatively more high-trait psychopathy individuals than businesses that generate less revenue (Boddy, 2006; Kirkman, 2005; Noll et al., 2012). Likewise, commercial university courses have been found to attract a significantly higher level of students who score high on the non-aggressive psychopathy dimension (Factor 1: Smith & Lilienfeld, 2013). In their study, Noll et al. (2012) compared bankers with high-trait psychopathy individuals and controls using a prisoner’s dilemma set-up. The results suggest bankers and high-trait psychopathy individuals have at least some traits in common, though bankers had an overall lower score on psychopathy than high-trait
psychopathy individuals. In contrast, they had a 2.3 times higher potential relative gain. Compared to controls they had a 53 times higher potential gain. In addition, bankers seem to be targeted towards selfish gain more than high-trait psychopathy individuals and controls, be it material or social (Noll et al., 2012).
Lying
This study defines a lie as: ‘A message that one gives to another in which one is deliberately deceiving the other’. It has been established that individuals take longer to lie than to tell the truth (Fullam, McKie & Dolam, 2009; Verschuere, Spruyt, Meijer & Otgaar, 2011; Vrij, Fisher, Mann & Leal, 2008). Individuals present with an increased cognitive load when lying, as they firstly need to suppress the truth and subsequently have to formulate a - believable and consistent - lie (Vendemia, Buzan and Simon-Dack, 2005). This generates bigger response latencies in subjects when lying than when telling the truth (Vrij et al., 2008), as truth telling in most individuals is the default reaction and thus cognitively more readily available.
Lying in high-trait psychopathy individuals
High-trait psychopathy individuals are suggested to tend more towards prolific lying (Halevy et al., 2013), towards willingly falsifying data or results, committing fraud (Kirkman, 2005), and being fairly insatiable in their hunt for more power and resources (Hare, 2003). They are said to show varying levels of decreased remorse about their lies and to tell contradictions without apparent shame (Hare, 2003). In addition, they are found to lie more frequently (Hare, 2003) and easily than individuals with fewer psychopathic traits (Kirkman, 2005). Furthermore, research has suggested that regular deceit facilitates the ease of lying (Verschuere et al., 2011). Corroborating this, Fullam et al., (2009) found correlations between some, but not all, psychopathic personality trait scores and brain responses on fMRI scans, during deception in a number of brain areas of interest.
Lying in bankers
Most bankers can be regarded as high-end salespeople, selling products with extremely high monetary margins. As there is a very limited research body on deceit in bankers, references have to be drawn from research on salespeople in general. About 50% of salespeople have been found to lie to their customers about products, especially when the client has less information than the salesperson (Mathieu & Pousa, 2011), as hypothesised by the so-called agency theory (Grover, 1993). In a different poll 55% of respondents indicated this practice has increased greatly in the past 10 years (Schwepker, & Good, 2010). Niemeijer (2006) describes how salespeople get a ‘kick’ out of misleading customers when this leads to higher revenue. This so-called ‘duping delight’ (Eckman, 1985, in: Niemeijer, 2006) influences customers in their decisions to buy. Up to 70% of customers decide to purchase the advertised product when a salesperson clearly enjoys his sales tricks, whereas a salesperson that feels guilty presents with a success rate of only 30% (Niemeijer, 2006).
Frequency
Intentional lying is generally considered as something objectionable, especially informed by Judeo-Christian ethics (Grover, 1993) and other religions (Shalvi & Leiser, 2013). Nonetheless, most people will confess to lying on average once or twice a day (Debey, De Schryver, Logan, Suchotzki & Verschuere (2015); Halevy et al, (2013); Serota, Levine & Boster, 2010). More precisely, the distribution is skewed, as Serota et al. (2010) found that most people hardly tell any lies and nearly 50% of lies are being told by only 5% of the population.
Most studies conducted in businesses, however, have aimed at lying as a factor dependent on the situation as opposed to personality (Farrell & Franco, 1999). They found that greater social distance between parties and asymmetry of information, that is when one party has more information than the other and knows it, enhance the occurrence of lying (Ackert, Church, Kuang & Qi, 2011).
Nonetheless, when individuals are concerned about what others think of them, they may engage in impression management (i.e., deceit) more when social distance is smaller (Ackert et al., 2011). Smaller businesses suffer from lying employees more, as they have fewer means to control for manipulation (Farrell & Franco, 1999). In addition, a business culture that supports or even promotes lying, greatly enhances the intention (Paternoster & Simpson, 1986) and occurrence of deceit (Farrell & Franco, 1999). To summarize, frequency of lying is partly dependent on an individual’s character and moral development, and partly on the possibility to act on one’s proneness to lie (Paternoster & Simpson, 1986). These researchers furthermore found, that individuals’ proneness to commit deceit was consistent throughout different suggested scenarios.
Attitude towards lying
It has been hypothesized that frequent liars tend to care less about their deceit (Grubin, 2005; Halevy et al., 2013). In a large university sample, the latter researchers found a non-significant trend between lying frequency and explicit attitude towards deceit. To our knowledge however, implicit attitude towards lying, has not been tested so far.
Goal of the present study
In the present study, we investigate 1) bankers’ propensity to lie, as indicated by the speed (ease), attitude towards (valence), and frequency of lying, related to 2) their levels of psychopathy. Based on the relationship between deceit and psychopathy suggested by Board and Fritzon (2005); Boddy (2006); Edens et al., (2006); Hare (2003); Kirkman (2005); Lilienfeld and Widows, (2005); and Noll et al. (2012), we expect that greater ease of lying, a less negative attitude towards lying, and more frequent lying are associated with higher psychopathic levels.
Procedure
Data were collected in the bankers’ working environment, as research has suggested that implicit attitudes of subjects can adapt to the context in which they find themselves (Barden, Maddux, Petty, & Brewer, 2004), allowing for priming. Subjects took the test in a conference room on a one-on-one basis, where the project leader instructed them regarding the questionnaires and the laptop running the Sheffield test. Firstly, written informed consent was obtained from all participants. Then, subjects were asked to fill in a demographics questionnaire. Subsequently, subjects were asked to fill in the LSRP (Levenson et al., 1995) and the Serota task (Serota et al., 2010). Lastly, subjects took the combined Spence/valence-of-lying computer test, for which latter subjects firstly got a practice opportunity of 6 x 2 questions. At the end of the test, subjects were asked to rate the pictures from 1-10, where 1 was very unpleasant and 10 very pleasant, as a manipulation check. The total time of the tasks comprised about 25 minutes.
Measures
The demographic questionnaire consisted of 16 questions addressing subjects’ personal circumstances as well as work environment, such as: How many people are ranked above you?
The Sheffield task (Spence et al., 2001) was administered on a windows laptop running Inquisit 3.0.6, measuring response times (RTs) of subjects to 20 yes/no questions. Ten questions were
presented e.g.: ‘Is London in England?’ and ‘Is a computer an animal?’, equally rightly and wrongly formulated in blocks of 40: 2 (Right vs. Wrong) x 10 (number of questions) x 2, randomly presented. Firstly, a screen colour prompted subjects to either lie (blue) or tell the truth (yellow) for 1000 ms. Then a picture was shown for 1000 ms., which was to be truthfully valued as positive or negative by pressing the a-key for positive and the s-key for negative with the left hand. Lastly, a question was shown for 1000 ms., which had to be answered according to the screen colour, by pressing the k-key for no and the l-key for yes with the right hand. Subjects were instructed to keep their fingers on the keys to facilitate optimum RTs. Pre and post-trial pauses were 500, 1000 or 1500 ms., randomly distributed. The test consisted of 40 lies and 40 truths and 40 (4 x 10) positive and 40 (4 x 10) negative pictures. The pictures were taken from the IAPS (International Affective Picture System: Lang, Bradley & Cuthbert, 1997), and were paired according to arousal, to balance the intended emotional priming effect. These probes have been found to have an exacerbating effect on the RTs when congruent with the stimulus and the attitude of the subject towards lying (Vendemia, Buzan & Green, 2005). This means, when for example a subject has a positive attitude towards lying and a positive picture is shown before a lie is shown, the RT will be significantly shorter. When incongruent, however, the probes may slow down response times significantly (Kerkhof et al., 2008). Firstly, subjects were being offered a practice session of 6 x 2 (Right vs. Wrong) questions, followed by
another 6 x 2 questions that were preceded by the pictures, after which the real test started. At the end of the test, subjects were asked to rate the pictures from 1-10, where 1 was very unpleasant and 10
very pleasant, as a manipulation check.
The explicit Serota questionnaire was administered on paper to determine frequency of lying over the past 24 hours. Sixteen questions addressed frequency (e.g. How often have you lied to a family
member in a face-to-face communication?), divided by means (face-to-face or indirect e.g., email) and
closeness (strangers or family/friends) (Serota et al., 2010). The sum score was calculated as a measure for frequency of lying. For efficiency reasons, only three questions were used in this study: total lie, difficulty, and emotionality of telling the lie.
The LSRP was used to measure psychopathy. It consists of 26 self-report items and its reliability is moderate (LSRP I .82 and LSRP II .63: Levenson et al., 1995). It measures antisocial behaviours and the attitude towards such deviance, which is more prevalent in non-clinical community life than forensic settings. Using a Likert-style format, item responses range from 1 (‘strongly disagree’) to 4 (‘strongly agree’). Factor analyses have generated two correlated subscales, that have been
demonstrated a resemblance to Factor 1 and Factor 2, respectively, of the PCL-R (Levenson et al., 1995). Primary psychopathy (LSRP 1) assesses a callous and unemotional personality style and a propensity to manipulate others (e.g., ‘For me, what’s right is whatever I can get away with’ and ‘I tell
other people what they want to hear so that they will do what I want them to do’). Secondary
psychopathy (LSRP II) measures impulsive antisociality (e.g., “When I get in trouble, I often let off
steam by blowing my top’). In validation studies, LSRP 1 has shown to be somewhat more reliable (α
= .82) than LSRP II (α = .63). Lastly, the LSRP was found to measure psychopathy as a dimensional construct (Walters, Brinkley, Magaletta & Diamond, 2008).
The hypotheses that were generated to guide this research are the following: 1 Regarding the stance towards lying
1. Subjects present with an increased cognitive load when lying, as expressed in more rapid responses on questions asking them to tell a truth vs. a lie
2. Subjects show more rapid responses on valuing positive pictures vs. negative pictures 3. Subjects present with a negative valence of lying, meaning that the incongruent condition
(positive picture + lie, negative picture + truth, added up) will generate longer RTs than the congruent condition (positive picture + truth, negative picture + lie, added up).
2 Regarding levels of psychopathy
5. Subjects presenting with higher valence of lying also present with higher psychopathic levels 6. Subjects presenting with a greater frequency of lying also present with higher psychopathic
levels
Participants
Bankers, all working in sales and sales management, were recruited from a number of international banks. A total of 65 subjects were tested (51 male, 14 female, age range: 25 - 58 (Mage = 42 years), 42 Caucasians (55.4 %), 20 Asians (28.4 %), and one mixed Asian-European (1.4 %); wages range: =< £ 80.000 - >=£ 200.00 (Mwages = £ 150.000), of which 40% >= £ 200.000; 26 no religion (41.3 %), 31
Christians (49.2 %), three Hindus (4.1 %), two Buddhists (2.7 %), and one Sikh (1.4 %); range of people reporting to subjects: 0 – 40 (Mreportees = 3.37). Two male subjects were excluded from the results, as one appeared to be drunk and the other walked away halfway through the procedure, leaving 63 subjects with testable data.
Results
Preliminary analyses
Power: with a power of .80, and α of 0.05 (one-tailed) a number of 63 subjects was needed to enable an effect in this study of at least moderate size of 0.3 in a correlational analysis (Faul, Erdfelder, Buchner & Lang, 2009).
Religion
To control for religion, two groups were created: religious (comprising Christian, Sikh, Buddhist, and Hindu) and non-religious. Results show, that no significant differences were found between religious and non-religious for ease of lying (lie – truth), ease of lying (error lie – error truth), valence of lying (congruent – incongruent), valence of lying (error negative picture – error positive picture), frequency of lying and rating pictures. Hence, data were subsequently collapsed between the religious and non-religious groups.
Scores on the LSRP scales yielded a mean of 51.62 for LSRP total (SD = 8.54), 32.72 for LSRP I (SD = 6.43), and 18.89 for LSRP II (SD = 3.92). Cronbach’s α was for LSRP total: .79, for LSRP I α = .79 and for LSRP II α = .62. Pearson’s r between LSRP I and LSRP II: r = .32, p < .01; between LSRP I and LSRP total: r = .90, p < .00 and between LSRP II and LSRP total: r = .70, p < .00.
Bivariate correlations (Pearson’s r) were subsequently carried out between subjects’ answers on the demographics questionnaire and the scales of the LSRP. Results show no significant correlations between the scales of the LSRP and subjects’ age, number of people at the desk or in the company,
number of people reporting to them, number of people they report to themselves, the number of people that are ranked above subjects, the amount of power they perceived themselves to have in the
company regarding policy and decisions, and loyalty to customers, their own family and the company, or the values they ascribed to themselves being higher than or equal to the company’s values. In contrast, loyalty to the company correlated significantly and negatively with LSRP II, r = -.26, p < .05. A Spearman’s rank order correlation was carried out between the bankers’ wages and their
psychopathy scores, however, no correlation was found.
Main analyses
Outliers, defined as RTs less than 300 ms. and greater than 3000 ms. (4.3 %) (Greenwald, Nosek, & Banaji, 2003), Verschuere et al., 2011), were excluded from the analyses. In addition, behavioural errors (10.6%) were excluded from RT analyses.
The ease of lying RTs
To assess the ease of lying, a repeated measures 2 (Emotion: Positive vs. Negative Picture) x 2 (Deception: Truth vs. Lie) ANOVA was carried out as to establish differences between RTs on the deception task. There was a main effect for deception: F (1,62) = 89.09, p < .01. However, there was no main effect for emotion: F (1,62) = 1.41, p > .05. No interaction effect was found. Results indicate that subjects were significantly quicker at responding to truths than to lies.
Table 1: Ease of Lying; Means (Standard Deviations) of Deception when preceded by a Positive or a Negative Picture
Deception Lie (ms) Truth (ms) Emotion M (SD) M (SD) Negative Picture 1961 (543) 1556 (352) Positive Picture 1896 (497) 1551 (416) Errors
Subjects made a mean total of 8.48 errors on the deception task (SD = 5.86), of which 5.15
(SD = 3.85) in the lie and 3.30 (SD = 2.70) in the truth condition. To assess if there was a difference in errors between the lie and the truth conditions, a paired t-test was performed. Results indicated that significantly more errors were made in the lie than in the truth condition t (62) = 4.74, p < .01, see table 3 below.
Correlations
the LSRP and the difference between lie and truth on the deception RTs. No significant correlations were found for RT lie - RT truth with LSRP total: r = -.15, p > .05; with LSRP I: r = -.09, p > .05; and LSRP II: r = -.18, p > .05. Error percentage lie - error percentage truth with LSRPtotal: r = -.02, p > .05; with LSRP I: r = .01, p > .05 and LSRP II: r = -.04, p > .05, see table 3 below.
The valence of lying RTs
To assess if the bankers presented with a positive valence of lying, the RTs to the pictures were subjected to a repeated measures 2 (Emotion: Positive vs. Negative Picture) x 2 (Deception: Truth vs. Lie) ANOVA. This ANOVA showed a main effect for emotion: F (1,62) = 9.29, p < .05 and for deception: F (1, 62) = 17.2, p < .01. No interaction effect was found. Results imply that subjects were significantly quicker at responding to negative pictures than to positive pictures. In addition, when a lie was anticipated, responses to the pictures were quicker than when a truth was to come, regardless if a positive or a negative picture was shown. However, the anticipation of a lie or a truth yielded no speedier response to the respective negative or positive pictures as per the conditions.
Table 2: Valence of Lying; Means (Standard Deviations) of RTs of Emotion when preceded by an Expectation to Lie or to Tell the Truth
Emotion Negative Picture (ms) Positive Picture (ms) Deception M (SD) M (SD) Lie 1178 (340) 1261 (378) Truth 1069 (270) 1198 (483) Correlations
RTs were added up for the congruent condition: truth + positive picture and lie + negative picture, and vice versa, lie + positive picture and truth + negative picture for the incongruent condition. A bivariate correlation (Pearson’s r) was carried out to determine if there was a significant correlation between the scales of the LSRP and the difference between the congruent and the incongruent condition. No significant results were found. As a manipulation check, a paired samples t-test was carried out. Results indicated there was no significant difference between the congruent and the incongruent condition: t (62) = 1.10, p > .05, indicating that no valence for either lying or truth telling could be determined. Moreover, error percentagepositive picture - error percentagenegative picture, as shown in table 3, yielded no significant correlations with the scales of the LSRP.
Table 3: Pearson’s Correlations between the Scales of the LSRP and the Difference in RTs between Lie and Truth for the Deception Condition, between Error Percentages for the Deception and Emotion Condition, and between the Congruent and the Incongruent Conditions
LSRPtotal LSRP I LSRP II
Ease of lying
(RT lie- RT truth) -.15 -.09 -.18
Ease of lying
Percentage Error lie – Error truth -.02 .01 -.04 Valence of lying
(Incongruent – congruent) -.13 -.17 .00
Rating pictures
A one-way t-test was performed to determine the difference in ratings of the pictures between subjects and the reference group of the IAPS (Lang et al., 1997). Results indicate that subjects rated the negative pictures significantly higher than the IAPS norm group: t (62) = 9.86, p < .01. However, the positive pictures too were rated significantly higher: t (62) = 13.15, p < .01. As the results were not valence specific, a paired sample t-test was carried out as a manipulation check. Results show that the difference between the ratings on the positive and the negative pictures was significant: t (62) = 41.58,
p < .01, indicating that the bankers rated the negative pictures much lower than the positive pictures,
as expected. See table 4.
Table 4: Means (Standard Deviations) of the Ratings of the Positive and Negative Pictures
Current study IAPS Reference group M (SD) M (SD) Positive pictures 8.72* (.63) 7.68 (.42) Negative pictures 3.06* (.77) 2.10 (.28) *significant at a level of .01 Frequency of lying
To assess the number of lies subjects had told in the past 24 hours, the results on the Serota test were added up for total amount, and for emotionality and difficulty. Subjects presented with a mean of 2.73 lies in the past 24 hours (SD = 3.25). A distinction was then made between frequent and non-frequent liars. Eight subjects (12.5%) confessed to having lied five times or more in the past 24 hours, accounting for 43% of all the lies told between all subjects (M = 9.38, SD = 4.98). Results on a repeated measures 2 (Deception: Lie vs. Truth) x 2 (Frequency: Frequent vs. Infrequent) ANOVA showed no difference between frequent and infrequent liars on the speed of lying; F (1, 61) = .38,
p > .05; on RTs for the pictures with a 2 (Emotion: Positive vs. Negative Picture) x 2 (Frequency:
Frequent vs. Infrequent) ANOVA: F (1, 61) = .341, p > .05, or on number of errors with a 2
(Deception: Lie vs. Truth) x 2 (Frequency: Frequent vs. Infrequent) ANOVA: F (1, 61) = 01, p > .05. A one-way ANOVA was carried out to determine if there was a difference between frequent and
infrequent liars on valence of lying (incongruent - congruent). No significant difference was found:
F (1, 61) = .09, p > .05. These results indicate frequent liars’ lies were not quicker, they did not value
deceit more, nor did they make fewer errors than the infrequent liars. As a result, data on frequency of lying were collapsed between frequent and infrequent liars.
Correlations
A bivariate (Spearman’s rho) correlation yielded no significant results between the amount of confessed lies and the scales of the LSRP: LSRP total: ρ = -.05, p > .05; LSRP I: ρ = -.03, p > .05; and LSRP II: ρ = -.01, p > .05.
A bivariate (Spearman’s rho) correlation between subjects’ total number of lies and the demographics questionnaire, resulted in one significant but weak and negative result: ‘number of
people you report to’: ρ = -.27, p < .05, implying the more people subjects reported to, the less lies
they told.
A bivariate (Spearman’s rho) correlation between subjects’ perceived difficulty and emotionality of lying and their total amount of lies showed that emotionality and difficulty were highly correlated:
ρ = .75, p < .01. The total amount of lies was not significantly (negatively) correlated with difficulty: ρ = -.04, p > .05, or emotionality: ρ = -.14, p > .05, implying, explicit negative valence of lying did not
result in subjects telling less lies.
Discussion
Fueled by the global financial crisis, public opinion has presumed connections between the suspected deceitful nature of bankers, their suspected levels of psychopathy, and the worldwide devastating effects of bankers’ sales behaviour. This study aimed to assess bankers attitude towards lying, as expressed in their ease, valence, and frequency of lying. Correlations were then sought between these three expressions of deceit and the LSRP (Levenson et al., 1995).
Findings
Our first hypothesis was confirmed, predicting subjects presented with slower lies than truths. All other hypotheses, however, were disproved. In addition, subjects responded quicker to negative than to positive pictures, as opposed to the reverse. When a lie was anticipated, pictures generated quicker responses than when a truth was to come. A mere positive or negative attitude towards lying remained undetermined. Moreover, frequent liars did not generate quicker lies than less frequent liars, or a higher valence of lying. Lastly, correlations between these findings reflecting subjects’ attitude towards lying and subjects’ levels of psychopathy, remained unproven.
Ease of lying
Subjects’ quicker answers on truthful questions over lies in this study corroborate earlier findings of increased cognitive load when lying (Verschuere et al., 2011), as did their increased error rate when lying (Verschuere & in ‘t Hout, 2015; Verschuere et al., 2010). This implies that the cognitive burden of deceit, as found in student (Verschuere, Suchotzki, & Debey, 2015), and forensic samples
(Verschuere & in ‘t Hout, 2015) generalises to bankers.
Valence of lying
Our study showed no differences between the congruent and the incongruent conditions, in contrast with earlier research (Vendemia et al., 2005). The quicker responses on the negative than the positive pictures are remarkable and may account for the absence of an interaction effect between the emotion and deception condition. If negative pictures were processed more rapidly, their cognitive burden may have been less and therefore exerting less than expected priming on the deception task. Moreover, the higher explicit rating of the negative pictures by subjects than the IAPS norm group may have diminished the negative priming the pictures were intended to cause, which then may have mitigated the slowing of the RTs. This would suggest that conclusions regarding (an absence of) valence of lying in our study might be less substantiated. With adequate priming using more impactful negative pictures, a difference between congruent and incongruent may have been found, generating a more pronounced valence of lying. On the other hand, Grubin (2005) suggested that pathological liars do not link negative affect to lying, offering an alternative explanation for an absence of valence. It remains to be determined what is precisely the difference between pathological and frequent liars. Nonetheless, as frequent liars have been shown to admit to their prolific deceit (Halevy et al., 2013), our slightly higher frequency ratings may not warrant labelling subjects as pathological liars. Involving a control group in future research may clarify differences between ratings and valence. Next, when anticipating a lie, subjects responded to all pictures slower than when a truth was to follow. In line with this, Estes and Verges (2008) showed that attentional disengagement for negative stimuli (in our study the blue screen instructing to lie) takes longer than for positive ones, slowing subsequent tasks. Supporting this, Smith, Cacioppo, Larsen and Chartrand (2003) found bigger ERP (Event Related Potentials) associated with anticipation for negative than for positive stimuli. Possibly the mere anticipation of having to lie - a difficult task- increased subjects’ cognitive load (Suchotzki et al., 2015) and slowed down their RTs on the pictures.
Lastly, we found contrasting results on valence of lying between the RT test and the explicit Serota test (2010). In the former we found an implicit absence of valence. In the latter, subjects reported an explicit negative valence of lying, according to high emotionality and difficulty. Jung and Lee (2009) reported a difference in implicit and explicit valence of lying, which former being more indicative of
subjects’ proneness to lie. It seems that subjects reported socially desirable explicit answers regarding valence.
Frequency of lying
Subjects reported a slightly higher number of lies than the mean reported in earlier research (Serota et al., 2010; Debey et al., 2015). It is unknown if this observed difference is significant, and therefore meaningful. In future research a control group may clarify any differences between groups.
The skewed results our study found regarding frequency of lying replicate earlier research findings (Serota et al., 2010) and generalises these findings to bankers. However, more frequent lying did not reflect in quicker lies, or less errors. This goes counter earlier research, which found a moderate correlation between frequency and speed of deceit (Debey et al., 2015, Verschuere et al., 2010). Possibly our bankers have been imprecise in their reports, intentionally or not. In future tests a control group may allow for comparisons.
Another possibility for the absence of quicker lies amongst the frequent liars may be that the Sheffield test was a lab test, making a resemblance between the experimental lies and the confessed lies less than ideal. The cognitive load that causes RTs on a lie to be longer may reduce with practice (Verschuere et al., 2010). However, practice in every day life may not generalise to a RT test (Sip, Roepstorff, McGregor & Frith, 2008). In addition, (Suchotzki et al., 2015) make a point of the difference between an instructed lie, as in our research, and a voluntary lie, generating at least
different brain patterns. Sip et al. (2008) suggest an RT test modelled after daily life situations as more suitable to assess actual lie detection.
How do these abovementioned findings relate to the findings regarding levels of psychopathy?
Ease of lying related to psychopathy
The absence of correlations between higher levels of psychopathy and quicker lies prompts further exploration. Three explanations are possible is this regard:
1 Possibly the LSRP generated less adequate results. Kelsey, Rogers and Robinson (2015) found in a forensic setting that subjects high in psychopathy, as measured with the PCL-R, were very able to hide their malevolent traits on the LSRP, resulting in an average non-clinical score. Though not being a forensic setting, it has been hypothesised that financial institutions attract significantly more high-trait psychopathy individuals than can be found elsewhere (Hare, 2003). Future research may want to correlate RTs with different psychopathy measures.
2 Our subjects may have been imprecise filling in the measures. Though our study was kept as short as possible, some subjects displayed clear impatience. Subjects have been found to fill in questionnaires wrongly when they find them too long and annoying (Merkelbach, Giesbrecht, Jelicic, Smeets, 2010). In addition, in our study, some showed relative eagerness to prove their good
intentions to counter current popular judgment. MacNeil and Holden (2006) found in an undergraduate sample that successfully faking good on self-report measures is related to sub scales of psychopathy. They advocate the use of a validity index when administering self-report measures.
3 Subjects may not have been so highly psychopathic. In line with this, Noll et al. (2012) found only part similarities between bankers and individuals with high-trait psychopathy in a prisoners-dilemma set up. Bankers presented with lower levels of psychopathy but higher self-serving
behaviour. No deceit was tested however. High-trait psychopathy individuals are suggested to engage in deceit for self-advancement and material gain (Hare, 2003). The absence of these incentives may have confounded a) the kind of subject that was willing to participate or b) the drive to fully engage in the task (Sip et al., 2008).
Moreover, restriction of range in our sample may seem plausible. Psychopathy scores did not vary much between subjects (e.g., LSRPtotal scores ranged from 33 - 72, (M = 52), where the obtainable ranged from 26 -104). Due to lack of a cut-off point or reference group for the LSRP, comparisons were not applicable. Including a control group in future research may allow for contrasting results.
Valence of lying related to psychopathy
No particular valence of lying was found, thus making correlations with psychopathy impossible. This absence may still be of interest, as to how it compares with a generally found negative valence of lying (Vendemia et al., 2005). It remains to be investigated by means of implicit tests, if this is a typical characteristic of bankers or frequent liars.
Frequency of lying related to psychopathy
The reliability of the answers on the Serota self-report measure was weak. Possibly, if only partly, this may explain the absence of correlations with the psychopathy outcomes, where others did find modest correlations, be it with other measures (Halevy et al., 2013, 2015, Debey et al., 2013).
In our study, less manipulative subjects admitted to more lies, contrasting earlier research (Kashy & Depaulo, 1996; Halevy et al., 2013). Indeed, frequency of lying may in some areas be unrelated to levels of psychopathy. For example, white lies to flatter someone are told by both agreeable people and manipulators (Hare, 2003). Possibly our study registered more of these undifferentiated kind of lies and as such has increased the amount of confessed lies of less manipulative subjects. In addition, less manipulative subjects may have admitted to more lies to aid the research by giving socially desirable answers. Second order beliefs (peoples’ expectations of other peoples’ expectations) are context specific (Erat & Gneezy, 2012) and may hence be a driver in research settings, generating less reliable results. This suggested pleasing behaviour of our subjects would contrast with suspected high trait psychopathic behaviour, possibly relating to the absent relations with the LSRP.
Farrell & Franco, 1999). No validated questionnaire was used, but rather an exploratory compilation of questions, possibly rendering the demographics questionnaire less valid and reliable.
Limitations
The α’s on all LSRP scales were (slightly) lower than found in validation studies (Levenson et al., 1995; Lynam et al., 1999) and moderate, however still acceptable (Clark & Watson, 1995). In
addition, the LSRP has been validated in student (Lynam et al., 1999) and forensic samples (Walters et al., 2008) only, but not in a banker population, to our knowledge. Moreover, some research has
suggested the construct of psychopathy better fitting a three-factor structure of the LSRP (Brinkley, Diamond, Magaletta & Heigel, 2008), possibly making our two-factors generate fewer correlations. Sip et al. (2008) have argued that experimental settings are not exactly measuring deceit, but rather the executive functions indirectly involved in deceit, of which delayed responses is only one. Taken into account that lies are generally told in social situations and on a voluntary basis, outcomes in our study may be less related to actual frequency of lying (Sip et al., 2008).
Subjects were mostly recruited from middle management as well as senior executives groups and lacking members of senior and top management, possibly restricting the range of psychopathy levels. It was hypothesised that a more senior position in the bank would reflect in higher psychopathy scores, derived from the notion that more power is the aim of the individual high in psychopathic traits
(Boddy, 2006).
Moreover, the administering of the test was not entirely standardised, as subjects were visited in their own work environment for taking the test, to generate as much work-related priming as possible (Barden et al., 2004), and to guarantee maximum cooperation.
Furthermore, the assessed group was relatively heterogeneous. It has been found that women’s psychopathy scores are lower (Levenson et al., 1995; Lilienfeld & Andrews, 1996) and different (Marion & Sellblom, 2011) from men’s, the latter mainly through lower scores on the LSRP II (Forth, Brown, Hart, & Hare, 1996). This has been hypothesised as stemming from different construct validity for the LSRP between men and women (Marion & Sellblom, 2011). Lastly, Serota found frequency of lying biased by gender (2010). As female participation comprised a mere 11%, this may well have had a confounding effect on LSRP scores and correlations.
Regarding ethnicity, results are limited. Serota et al. (2010) reported Caucasians confessing to more lies than ‘other’ race. More results were not found.
Our study did not control for age. Age has been found to play a role in deceit proficiency, peaking in early adulthood and declining after that (Debey et al, 2015), with error rates following the inverse pattern. Moreover, Serota et al. found age to be negatively related to frequency of lying (2010), as did Debey et al (2015). Levenson et al., (1995) found age to be reversely related to LSRP scores, possibly due to a lower impulse control component, as opposed to a structural character change (Debey et al.,
2015; Harpur & Hare, 1994, Hare, 2003).
Considering the above limitations, in future research it may be of interest to assess RTs and levels of psychopathy between gender, age, ethnicity, and seniority, related to or in combination with a different psychopathy measure than the LSRP. Adding a validity index may sieve out invalid (fake good) responses. A more lifelike design may generate more generalisable results regarding deceit. Lies may need to be specified and lastly, a control group may allow for comparisons and inferences.
Conclusion
Following increasing focus of society on the role bankers and their conduct, we tried to establish a relationship between deceit and psychopathy within the banker population. This study investigated 1) bankers’ propensity to lie, as indicated by the speed (ease), attitude towards (valence), and frequency of lying, related to 2) their levels of psychopathy. Our study proved only one hypothesis, showing that the higher cognitive cost for lying can be generalised to bankers. All our other hypotheses were rejected, resulting in neither propensity to lie nor relations with psychopathy being established. However, we found some other interesting outcomes, which might be the basis for future research. The most important of which were: 1) bankers’ neutral implicit valence of lying, as opposed to the positive one that we predicted; 2) an inverse relation between manipulative attitude and frequency of lying; 3) the significant higher ratings by the bankers of the emotional stimuli. Lack of correlations with levels of psychopathy has been hypothesised due to a less suitable psychopathy measure and a heterogenous group. Results imply, that no generalisations can be made to bankers regarding deceit and psychopathy. Changing measure, adding a control group as well as a validity index may allow future research to draw substantial inferences. Controlling for age, gender, ethnicity, and seniority is recommended. Expanding research to more lifelike situations may generate more detailed results regarding deception.
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