Psychopathy and hostile memory

Psychopathy and Hostile Memory

Abstract

Results of previous studies indicate that people with psychopathic traits have an intact Theory of Mind (ToM), which refers to the ability to attribute thoughts and intentions to others. However, little is known about the influence of hostility biases on ToM performance in psychopathy. This study investigated the relationship between psychopathic traits and hostile attributions, alongside (false) memory for hostile stimuli. Participants completed a measure for psychopathic symptoms, a task that measures hostile attributions and ToM abilities, and a task that measures hostile memory. It was expected that psychopathic traits are associated with a superior identification of hostile intentions, but only when stimuli are presented for an unlimited amount of time. Moreover, it was expected that individuals with psychopathic traits remember more hostile (false) than neutral information. Contrary to the expectations, results indicated that psychopathic traits are not predictive for performance on the ToM task. However, results did reveal that when stimuli are processed for a longer period of time, individuals (independently from psychopathy), are better at identifying real hostility, but also seem to identify hostility that is not actually there. Furthermore, results indicated, as expected, that individuals with psychopathic traits remember more hostile false information than neutral or negative information. Therefore, this study provides a deeper understanding in the hostile perception of psychopathic individuals and might provide an explanation for grudge feelings that they tend to hold against other people.

Introduction

Psychopathy is a developmental disorder characterized by a constellation of affective, interpersonal and behavioral features that include a tendency to exhibit antisocial and emotional dysfunctional behavior (Bolt, Hare, Vitale, & Newman, 2004). A frequently used measure to assess psychopathy is the Psychopathy Checklist-Revised (PCL-R) (Hare, 1991), that distinguishes two factors of psychopathy; the first factor includes affective and interpersonal traits (e.g. manipulate behavior, superficial charm and lack of remorse) and the second factor includes antisocial behavior (e.g. impulsivity, criminal activity and violence) (Harpur, Hakstian, & Hare, 1988). A very salient deficit in psychopathic individuals is a lack of empathy, which can be described as an affective reaction to the emotional state of another person. Empathy is thought to be an essential component of communication and pro-social behavior (Dolan & Fullam, 2004). A distinction can be made between emotional and cognitive empathy. Emotional empathy refers to the ability to share the emotional state of another person, whereas cognitive empathy, also referred to as Theory of Mind (ToM), refers to the ability to attribute feelings, thoughts and intentions to self and others (Blair, 2005).

It has been found that psychopathic individuals show selective dysfunctions in emotional empathy. For instance, psychopathy has been associated with impaired processing of fearful and sad facial expressions (Blair, 2005). Furthermore, it has been suggested that psychopathic individuals display impairments in ToM ability. However, research findings have consistently demonstrated that, compared with non-psychopathic individuals, psychopathic individuals do not show impairments in attributing mental states of another person from short stories (Blair et al., 1996, Dolan & Fullam, 2004) or from photographs of the eye region (Richell et al., 2003; Dolan & Fullam, 2004; Nentjes, Bernstein, Arntz, Van Breukelen & Slaats, in press). However, it should be noted that tasks that measure ToM abilities do not differentiate between separate emotions or mental states. For instance, the ‘Reading the Mind in The Eyes’ task (RMET) (Baren-Cohen, Wheelwright, Hill, Raste & Plumb, 2001) is a task that measures ToM abilities by requiring subjects to identify the mental state of a person by showing photographs of the eye region only. ToM performance is obtained by summing all the correct responses, without differentiating between separate mental states or emotions (Baren-Cohen et al., 2001). Nevertheless, it might be the case that some mental states or emotions are better recognized than others, which would indicate an influence of cognitive processing style on ToM performance.

Psychopaths’ ToM performance could, for instance, be influenced by the Hostile Attribution Bias (HAB), the latter implying that ambiguous behavior is being interpreted as hostile (Crick & Dodge, 1994; Orobio de Castro, Veerman, Koops, Bosch & Monshouwer, 2002). Research indicates that psychopathic individuals tend to exhibit a hostile attribution bias (Dodge, 1980; Vitale et al., 2005). However, findings are inconsistent. Miller and Lynam (2003) did not find an association between psychopathy and the HAB in a vignettes social information processing task, which would suggest that the information processing in psychopathic individuals is relatively intact. Furthermore, Nentjes et al., (in press) did not find a cognitive bias towards hostility in psychopathic offenders on the RMET. However, when the RMET stimuli were presented for an unlimited amount of time, psychopathic offenders were better at identifying hostility in the eyes than non-offenders. This effect might have been found only in the long stimulus duration because psychopathic individuals might felt like being stared at, which serves as signal provocation. Therefore, the longer stimulus presentation could have led psychopathic individuals to process the eye stimuli in a more focused and elaborate way, which increases the accessibility of aggressive thoughts (Nentjes et al., in press). These findings indicate that psychopathic individuals do not show a bias for hostile information, but are better at recognizing hostile information when it is actually present. However, since research findings are inconsistent about HAB deficits in psychopathic individuals, it should be further investigated.

As stated above, psychopathy has been associated with deficits in emotional processing (Blair, 2005; Vitale et al., 2005). These deficits in emotional processing might also emerge in emotional memory. However, only a few studies have investigated the relationship between psychopathy and emotional memory. Christianson et al., (1996) found that psychopathic individuals do not show the narrowing of attention for negative stimuli as non-psychopathic individuals do, which implies a lack of differential processing and recall of emotional information. However, Glass and Newman (2009) found no impairments in psychopathic individuals when they recalled emotional words. Furthermore, Wilson, Demetrioff and Porter (2008) investigated the association between psychopathic traits and recall of biographical details of characters that differed in career success and vulnerability. Individuals with psychopathic traits had an accurate memory for sad, unsuccessful female characters, but impaired memory for other characters. These findings suggest that individuals with psychopathic traits have an enhanced memory for predatory stimuli.

unambiguous violent information that was never actually presented. This suggests that there is an associative process that underlies the HAB and predisposes aggressive individuals to falsely remember hostile information (Takarangi, Polaschek, Hignett & Garry, 2008). These findings are extended by research that indicated an association between hostile memory distortion and cyber-bullying behavior (Vannucci, Nocentini, Mazzoni & Menesini, 2012). Since psychopathy has consistently been linked to antisocial and aggressive behavior (Staffort & Cornell, 2003; Miller & Lynam, 2003), there might be an association between psychopathy and distorted memory for hostile information. In this study, the Deese-Roediger-McDermott (DRM) paradigm (Deese, 1959) will be used to investigate whether hostile attributions predispose psychopathic individuals to falsely remember hostile information. In addition, it will be investigated whether psychopathic individuals show a superior memory for hostile stimuli.

Hypotheses

This study investigates hostile ToM, alongside (false) memory for hostile stimuli in a sample of individuals with psychopathic traits. Based on previous literature, it is firstly hypothesized that psychopathic traits predict the chance of choosing the right answering option on the RMET, but only when the stimulus is presented for an unlimited amount of time and when the eyes that are to be identified are relatively hostile (Dodge, 1980; Vitale et al., 2005, Nentjes et al., in press). Secondly, it is hypothesized that psychopathic traits do not predict the tendency to choose more hostile answering options on the RMET when a mistake has been made (Nentjes et al., in press). This indicates that individuals with psychopathic traits do not show a hostility bias, but are better at identifying hostility when it is actually present. Thirdly, in line with previous research, it is hypothesized that individuals with psychopathic traits show a tendency to remember more (false) information with a hostile content compared to a neutral or a negative content, as will be assessed using the DRM. Furthermore, it is expected that the effect of psychopathic traits on the DRM will be mediated by the relative ease with which hostile eyes on the RMET are identified (Takarangi et al., 2008; Vannucci et al., 2012) (figure 1).

Figure 1. Mediation model of psychopathic traits, hostile ToM and hostile memory. Methods

Participants

Fifty-six male participants that were between 18 and 57 years old (mean age = 24.94) were tested. Participants consisted of (under)graduate students, employed and unemployed males. Participants received 25 euros or 2.5 credits to meet research participation requirements as part of their study.

Procedure

Participants were recruited by handing out flyers at the university area (university of Amsterdam) and by online advertisement. Participants were also approached face-to-face to enhance the likelihood of participation. Appointments were scheduled by e-mail. Prior to the experiment, participants were handed out the information brochure. Subjects had the opportunity to ask questions and were then asked to sign an informed consent. Subsequently, demographic variables were collected, which included age, marital status, education, education of both parents, current study or work situation, nationality and native language.

Participants were subjected to the Stroop task, RMET, DRM and the Psychopathic Personality Inventory Revised (PPI-R; Lilienfeld & Widows, 2005), respectively (for details about these measures, see below). In order to administer the RMET, participants were seated in front of a computer about 35 cm from the screen. A mouse was used for selecting the preferred answering option during the task. Subsequently, participants were subjected to the DRM. Participants were wearing headphones in order to hear the selected word lists from the computer. After completing the DRM, a measure of psychopathy (PPI-R) was presented through Inquisit (Inquisit, 2014), which took about 25 minutes to administer. Since this research is part of an overarching research project, a variety of other tests (measuring lying behavior and

Hostile Theory of Mind Hostile memory Psychopathy

aggression) were administered as well, which are described in different thesis research reports. All tasks and questionnaires were administered in a quiet, closed testing room.

Measures

The Psychopathic Personality Inventory Revised (PPI-R; Lilienfeld & Widows, 2005, translated in Dutch by Uzieblo et al., 2006) is a self-report measure of psychopathic traits that consists of 154 items that are rated on a 4-point Likert scale (1=false to 4=true), where higher scores indicate more psychopathic traits. The PPI-R yields scores on eight different components of psychopathic traits, that consist of two main factors; “Fearless Dominance”(FD) that measures interpersonal/affective traits and “Self-Centered Impulsivity”(SCI) that measures impulsive/antisocial traits. Because the PPI-R is designed to be used among non-institutionalized samples, it does not focus on criminal behavior. The eight different components make up for the total psychopathy score, but separate scores on the two factors FD and SCI can be obtained as well. The FD score consists of the sum of the Fearlessness [F], Social Influence [SOI] and Stress Immunity [STI]) scales, whereas the SCI score consists of the sum of the Machiavellian Egocentricity [ME], Rebellious Nonconformity [RN], Blame Externalization [BE] and Carefree Nonplanfulness [CN] scales. The eighth component, Coldheartedness (C) is examined separately. Additionally, the PPI-R includes measures of deviant responding, virtuous responding and inconsistency that can be used to identify individuals who did not respond truthfully (Lilienfeld & Widows, 2005). The PPI-R has good psychometric properties with good internal consistency for the total scale (Cronbach’s alpha = 0.89) and for each of the two main factors (SCI α = 0.94; FD α = 0.89) (Hughes, Stout & Dolan, 2013). Cronbach’s alpha for the Total PPI-R scale, Factor 1 (SCI) and Factor 2 (FD) in the current sample was 0.85, 0.86 and 0.83, respectively. The PPI-R has been validated in both institutionalized and general population samples (Patrick, Edens, Poythress, Lilienfeld & Benning, 2006).

The Reading the Mind in the Eyes task (RMET; Baron-Cohen et al., 2001) has been administered to assess ToM abilities. In this computerized task, participants are presented with 36 photographs (18 males, 18 females) of the eye region of a face that express a complex mental state (e.g. insecurity or hostility). After a fixation cross is presented (1000 ms), photographs are shown successively with four words as answering options. One of these four words (the target word) correctly identifies the mental state of the individual in the photograph, while the other three words are included as foils. Subjects are required to choose one out of four words that best represents what the individual in the photograph is feeling or thinking. Participants are

asked to answer as fast and correct as possible, because reaction time was recorded. In this study, the RMET was altered in accordance with Nentjes and colleagues (in press) to differentiate between trial duration and to create more diversity in the level of hostility in the RMET answering options. In the study of Nentjes et al., (in press), the hostility level of the RMET answering options (and foils) was rated by 33 students, ranging from 0 (not hostile at all) to 10 (very hostile). Subsequently, the average hostility level for each answering option (HS) was calculated. The modified RMET task has shown construct validity (r=0.36) with the Happé’s advanced test of ToM (Nentjes et al., in press).

The Deese-Roediger-McDermott paradigm (DRM; Deese, 1959) has been used to investigate whether subjects that are presented with unambiguous material, recall and recognize additional false information. Subsequently, the DRM task has been used to investigate recall and recognition of neutral, negative and hostile information. In the DRM task, participants heard 15 recorded lists of 10 words (with a rate of 2.0 seconds per word). Each list is associated with a non-shown but semantically related lure that is often falsely recalled. In this study, subjects were asked to recall five lists of neutral related words (e.g., table, sit, legs, seat, couch, desk, recliner, sofa, cushion, stool), five lists of negative (but not hostile) related words (e.g., ill, flu, nausea, virus, hospital, fever, disease, healthy, vomit, germ) and five lists of hostile related words (e.g., rage, hostility, fury, frustration, temper, tantrum, violent, fight, annoy, argument). The five neutral word lists (critical lures: chair, foot, fruit, mountain and king) were chosen from DRM lists of Dewhurst, Anderson and Knott (2012), and were used to determine whether subjects show the standard DRM effect. The five negative lists contain the following critical lures; smell (Howe, Threadgold, Norbury, Garner & Ball, 2013), danger, sick (Dewhurst et al., 2012), slave (Dehon, Larøi & Van der Linden, 2010) and dead (Otgaar & Smeets, 2010). These negative lists were used to differentiate between negative and hostile memory. The five hostile lists that were selected from previous studies had the following critical lures; anger (Dewhurst et al., 2012), fight (Howe & Derbish, 2010), kill (Watson, Balota & Roediger, 2003), hate (Dewhurst et al., 2012) and murder (Otgaar, Peters & Howe, 2012). These hostile word lists were used to investigate hostile memory.

The negative and hostile word lists have been chosen from 25 lists that were thought to have a hostile or negative content. Twenty-one students rated the critical lures of these 25 lists on hostility, negativity and arousal. Ratings were given on a scale from 0 to 100 (e.g. for hostility; 0=not hostile at all to 100=very hostile). From the 25 rated critical lures, five were

selected because they were rated low in hostility (i.e., having an average hostility rating < 50), but high in negativity (i.e. having an average hostility rating > 50). In addition, five critical lures were selected that were rated high in both hostility and negativity (i.e. being rated > 50 on both scales).

An independent-samples t-test was conducted to compare the hostile and negative word lists on hostility, negativity and arousal. The hostile (M=74.43, SD=15.82) and the negative word lists (M=32.64, SD=14.59) differed from each other in hostility (t(8)=-4.34, p=0.00). However, the hostile (M=79.23, SD=17.79) and the negative word lists (M=64.67, SD=9.11) did neither differ in negativity (t(6)=-1.63, p=0.16), nor did the hostile (M=46.95, SD=9.29) and the negative words lists (M=30.64, SD=25.92) differ in arousal (t(8)=-1.33, p=0.22). Furthermore, an analysis of variance (ANOVA) was conducted to check whether the neutral, negative and hostile words lists differed in word length. The overall ANOVA showed no differences between the negative, neutral and hostile words in words length (F(2, 14)=2.8, p=0.10). Follow up analysis showed no differences in average word length between the neutral (M=5.9, SE=0.6) and the negative word lists (M=7.2, SE=0.6, p=0.13), the neutral and the hostile word lists (M=7.2, SE=0.6, p=0.16), and the negative and the hostile word lists (p=1.00).

After hearing each list, subjects were required to work 30 seconds on a math problem, after which they had to write down the words that they memorized without guessing. Subjects had two minutes to recall the words from a particular list in any order. A total score of false memories was obtained by adding all the words that the subject wrote down that were not presented in the original neutral, negative and hostile lists. A total score of recalled neutral, negative and hostile words was obtained by only adding the words that the subject wrote down that were also presented in the original neutral, negative and hostile lists.

In addition, participants were subjected to a recognition task, where subjects heard a list of 89 words (with a rate of 2.0 seconds per word). The same list of 89 words was also presented to the participants on paper, where participants could state whether they recognized the words from the previous lists by selecting a yes or no answering option. The 89 words for the recognition task consisted of the 15 critical lures, 44 randomly selected words that were also presented in the DRM lists, 15 randomly selected words that were related to the 15 critical lures but not presented in the DRM lists and, 15 randomly selected words that were unrelated to the 15 critical lures and not presented in the DRM lists. A total score of falsely recognized neutral, negative and hostile stimuli and recognized neutral, negative and hostile stimuli was obtained in

the same manner as in the recall task. The DRM paradigm has good psychometric properties with good test-retest reliability (r=0.76) and moderate internal consistency (Cronbach’s alpha=0.69) (Blair, Lenton & Hastie, 2002).

Executive functioning

Performance on Theory of Mind tasks has been associated with executive functioning (Ahmed & Miller, 2011). Therefore, the Stroop Color Word Test (SCWT-short version; Klein, Ponds, Houx and Jolle, 1997) was administered. In this task, the participant had to read three cards out loud as fast as possible, while reaction time was recorded. Card one consisted of black words, card two consisted of colored patches and card three consisted of color names (printed ink was different than color name).

Operationalization and Design

For the first hypothesis three predictors were analyzed. The main predictor was psychopathic traits, which has been measured by the PPI-R as a dimensional construct. The relative hostility (HSrel) of the eyes in the RMET is a continuous predictor, which was obtained for each trial by taking the hostility score of the correct answering option (HS) and subtracting the highest hostility score of the three foils. Therefore, the more hostile the eyes are (relative to foil with the highest hostility score), the higher the HSrel of the trial. Also, a low HSrel score implies the presence of relatively hostile foils (Nentjes et al., in press). The stimulus length (short versus long) on the RMET is a dichotomous predictor. The dependent variable on the RMET is the chance of correctly identified trials. For the second hypothesis we analyzed two predictors: psychopathic traits and the stimulus length. The dependent variable was the HSrel of the incorrect answering option on the RMET that had been chosen, which was obtained by using the formula: HS of the chosen answering option – highest HS of the other incorrect answering options. For the third hypothesis we analyzed the degree of psychopathic traits as a covariate and the total amount of both falsely and correctly recalled/recognized hostile DRM words as outcome variables, which were thought to be mediated by the HSrel of the right answering option on the RMET.

Data analysis

Statistical analyses were performed using the Statistical Package for Social Sciences (SPSS) for Windows, version 20.0 (IBM, 2011). Statistical significance was determined using an alpha level

of .05. Regarding hypothesis one, a multilevel logistic regression analysis was conducted to test whether the chance to answer correctly on the RMET is predicted by psychopathic traits (Factor 1 and Factor 2 on the PPI-R were analyzed separately), the HSrel of the trail, stimulus length, and all the higher order interactions between these predictors. We expected a significant effect of the interaction term ‘psychopathy x stimulus duration x HSrel’. Regarding hypothesis two, a multilevel linear multiple regression analysis was conducted to test whether psychopathic traits predict the tendency to choose more hostile answering options when a mistake has been made. We neither expected main effects of psychopathy and stimulus duration, nor an interaction between psychopathy and stimulus duration. Regarding hypothesis three, four repeated measures ANOVAs were conducted to test whether the scores on the DRM (true recall, false recall, true recognition, false recognition) were different for the neutral, negative and hostile word lists (valence). The within-subject variables for the repeated measurements ANOVAs were the performance on the neutral, negative and hostile word lists. Each of the four repeated measurements ANOVAs were conducted two times. For the first analysis, the PPI-R Factor 1 and Factor 2 scores were added as covariates and for the second analysis only the Total PPI-R score was added as a covariate. We expected an interaction between the PPI-R Factor 1 and Factor 2 scores and valence, and between the total PPI-R score and valence. Subsequently, a mediation analysis would have been conducted to test whether the effect of psychopathic traits on the DRM is mediated by a tendency to correctly identify relatively hostile eyes on the RMET (HSrel correct). However, since the results (see below) indicated that there was no effect of psychopathy on RMET performance, mediation analysis could not be performed.

Results

Demographic and Clinical Characteristics

Demographic and clinical characteristics of the sample are summarized in Table 1. In this study, 56 participants were tested. One participant was excluded from further analysis because the DRM had been administered incorrectly. Furthermore, one participant was excluded from the sample because the inconsistency score on the PPI-R was considered highly atypical. For the RMET task, one participant was excluded because the entire dataset was missing. A missing value analysis (MVA) was used to correct for the two missing values in the Stroop test data. Subsequently, two participants were considered statistical outliers because their scores deviated more than 3 SD from the mean score on the DRM subscales. These scores were replaced by the mean plus or minus 3 SD. After adjusting the data, a dataset of 54 participants remained. About

80 percent of the sample were (working) students (43 participants), whilst the rest was working, searching for a job and/or currently unemployed.

RMET: The chance of a correctly chosen answer by hostility level, stimulus length and psychopathic traits (total score)

To assess whether psychopathic traits predict the chance of choosing the right answering option on the RMET (hypothesis 1), a multilevel logistic regression analysis was used. All main effects (PPI-R Total, stimulus length, HSrel), as well as the two-way and three-way interactions of HSrel, stimulus length (short vs. long) and the Total PPI-R score, were entered into the model. Interaction terms that were non-significant (p >0.10) were deleted from the model (first the three-way interaction, then the two-way interaction and finally the main effect was deleted), resulting in the model that is shown in Table 2. Results showed that there was neither a main effect for the Total PPI-R score, nor for the RMET HSrel. However, results indicated that there is a trend towards a significant main effect for the RMET stimulus duration. Further examination of this trend suggested that in the short stimulus duration, people tend to give less correct answers on the RMET (M=61.6 %) than in the long stimulus duration (M=65.7 %). Furthermore, findings showed a significant interaction effect between RMET HSrel and RMET stimulus duration. Further examination of this interaction effect showed that for the short stimulus duration, higher HSrel was associated with worse performance on the RMET. For the long stimulus duration, higher HSrel was associated with better performance on the RMET (Figure 2). Running the model with age and the inference score of the Stroop task included as variables, did not reveal appreciatively significantly different results. The effect of HSrel and stimulus duration was further examined for the short and the long stimulus duration separately. For the short duration there was no main effect of Total PPI-R score (F(1,96)=0.01, p=0.94) or the RMET HSrel (F(1,96)=1.01, p=0.32). For the long duration, there was also no main effect of the Total PPI-R score (F(1,98)=0.25, p=0.62) or the RMET HSrel (F(1,98)=3.33, p=0.07).

RMET: The chance of a correctly chosen answer by hostility level, stimulus length and psychopathic traits (Factor 1 and Factor 2)

The analysis described above was repeated for each factor separately, in order to further examine whether there would be an interaction effect between HSrel, stimulus duration and psychopathic traits for the two factors of the PPI-R separately. Factor 1 and Factor 2 were

analyzed separately in order to prevent non-convergence due to too many predictors in the model. For Factor 1, all main effects (PPI-R Factor 1, stimulus length, HSrel), as well as the two-way interactions and three-two-way interactions of HSrel, stimulus length (short vs. long) and PPI-R Factor 1, were entered into the model. Results revealed no significant main effects but did show a significant interaction between HSrel and RMET stimulus duration (B= -0.01, p<0.05). When these analyses were repeated for Factor 2, the results revealed no significant main effects, but results did show a significant interaction effect between HSrel and RMET stimulus duration (B=-0.01, p<0.05). Running the models for Factor 1 and Factor 2 with age and the inference score on the Stroop task included as variables, did not reveal significantly different results. In sum, these results showed very similar patterns for the Total PPI-R score, as for Factor 1 and Factor 2 separately.

RMET: The chosen hostility level within the incorrect answers

To assess whether psychopathic traits are not predictive for the tendency to choose more hostile answering options on the RMET when making mistakes (hypothesis 2), a multilevel linear multiple regression analysis was used. All main effects (PPI-R Total and stimulus length), as well as the two-way interaction between stimulus length (short vs. long) and the Total PPI-R score were entered into the model (Table 3). Results showed a main effect for RMET stimulus duration. Further examination of this effect suggested that in the long stimulus duration, individuals tend to choose more hostile answering options (M=24.49, SD=19.75), than in the short stimulus duration (M=20.23, SD=19.29). Furthermore, there was no significant association between the outcome variable HSrel of the incorrect response and the predictor Total PPI-R. There was also no significant interaction effect between the Total PPI-R and RMET stimulus duration. When age was included in the model as a covariate, the model did not reveal significantly different results.

The analyses described above were also conducted for the two PPI-R Factors. When Factor 1 and Factor 2 were added to the model, the results again showed a main effect for RMET stimulus duration (F(1,700)=8.33, p=0.00). Furthermore, the results revealed no significant association between the outcome variable HSrel of the incorrect response and the predictor Factor 1 (F(1,700)=0.09, p=0.77), or the predictor Factor 2 (F(1,700)=0.04, p=0.84). There was also no significant interaction effect between Factor 1 and RMET stimulus duration (F(1,700)=0.01, p=0.93), or between Factor 2 and RMET stimulus duration (F(1,700)=0.03,

p=0.86). When age was included in the model as a covariate, the model did not reveal significantly different results.

The DRM

Recall

Three one-way repeated measures ANOVAs investigate the main and interaction effects of valence (neutral, negative and hostile) and psychopathy on the total amount of recalled items (true recall), the total amount of falsely recalled non-critical items (false recall non-critical) and the total amount of falsely recalled critical items (false recall critical). These analyses were conducted separately for Factor 1 and Factor 2, and for the Total PPI-R score. For true recall, a repeated measures ANOVA with Factor 1 and Factor 2 as covariates was firstly performed. Results revealed no main effect for Factor 1, but did show a significant main effect for Factor 2. This indicates that there is an association between Factor 2 and the amount of correctly recalled items. In addition, the results showed no significant effect of valence, suggesting that there was no difference in the amount of correctly recalled items between the neutral, negative and hostile word lists. Furthermore, the results showed no interaction effect between Factor 1 and valence, and between Factor 2 and valence (Table 4). Secondly, a repeated measurements ANOVA with the Total PPI-R score as a covariate was performed. The results did not reveal a main effect of the Total PPI-R score or a main effect of valence. In addition, the results showed no interaction between the Total PPI-R score and valence (Table 5). Running the model with age included as a variable did not reveal significantly different results.

For the falsely recalled non-critical items, a repeated measurements ANOVA with Factor 1, Factor 2 and age included as covariates, was firstly performed1_{. Result showed no main effect}

for Factor 1 or Factor 2. However, there was a significant effect of valence. Further inspection of this effect by use of contrast tests (simple) revealed a significance difference in the amount of falsely recalled non-critical items between the neutral and the hostile lists (F(1, 50)=4.56, p=0.04, ηp=0.08), and between the negative and the hostile lists (F(1, 50)=5.63, p=0.02, ηp=0.10).

Furthermore, results showed that hostile non-critical words (M=2.56, SD=1.96) are more often falsely recalled than neutral (M=1.44, SD=1.37) and negative words (M=1.54, SD=1.50). In

1 _{The total amount of falsely recalled non-critical items on the DRM did not meet the assumption of} sphericity (χ2(2) = 7.27, p = 0.03). Therefore, the degrees of freedom were corrected using Greenhouse-Geisser estimates of sphericity (ε = 0.88).

addition, the results indicated no interaction effect between Factor 1 and valence, and between Factor 2 and valence (Table 4). Secondly, a repeated measurements ANOVA with the Total PPI-R score and age as covariates was performed. The results did not reveal a main effect of the Total PPI-R score. However, the results did show a main effect of valence. Further inspection of this effect by use of contrast tests (simple) revealed a significance difference in the amount of falsely recalled non-critical items between the neutral and the hostile lists (F(1, 51)=4.32, p=0.04, ηp=0.08), and between the negative and the hostile lists (F(1, 51)=5.25, p=0.03, ηp=0.09).

Furthermore, results showed that hostile non-critical words (M=2.59, SD=1.96) are more often falsely recalled than neutral (M=1.44, SD=1.37) and negative words (M=1.54, SE=1.50). In addition, a significant interaction effect between the Total PPI-R score and valence was found (Table 5). Further examination of this effect with partial correlational analysis (corrected for age), revealed that the Total PPI-R score shows a higher correlation with falsely recalling non-critical hostile words (rS =.29, p=0.03) than with the neutral (rS =-0.06, p=0.66) or negative words

(rS =0.01, p=0.96).

For the falsely recalled critical items, a repeated measurements ANOVA with Factor 1 and Factor 2 included as covariates, was firstly performed. Results did not show a main effect for Factor 1 or Factor 2. Furthermore, the results showed no significant effect of valence, suggesting that there was no difference in the amount of falsely recalled critical items between the neutral, negative and hostile word lists. In addition, the results revealed neither an interaction effect between Factor 1 and valence, nor an interaction effect between Factor 2 and valence (Table 4). Secondly, a repeated measurements ANOVA with the Total PPI-R score as a covariate was performed. Results revealed a main effect of the Total PPI-R score. This indicates that there is an association between the Total PPI-R score and the amount of falsely recalled critical items. In contrast, no main effect of valence and no interaction effect of the Total PPI-R score and valence were found (Table 5). Running the model with age included as a variable did not reveal significantly different results.

Recognition

Three one-way ANOVAs with repeated measures were carried out to assess the main and interaction effects of valence (neutral, negative and hostile) and psychopathy on the total amount of recognized items (true recognition), the total amount of falsely recognized non-critical items (false recognition non-non-critical) and the total amount of falsely recognized non-critical

items (false recognition critical). These analyses were conducted separately for Factor 1 and Factor 2, and for the Total PPI-R score. For true recognition, a repeated measures ANOVA with Factor 1 and Factor 2 as covariates was firstly performed. Results revealed no main effect for Factor 1, but did reveal a main effect for Factor 2. This indicates that there is an association between Factor 2 and the amount of correctly recognized items. Furthermore, the results showed no significant main effect of valence, suggesting that there was no difference in the amount of correctly recognized items between the neutral, negative and hostile word lists. In addition, no interaction effect between Factor 1 and valence, and Factor 2 and valence was found (Table 4). Secondly, a repeated measurements ANOVA with the Total PPI-R score as a covariate was performed. Results showed a significant main effect for the total PPI-R score. This indicates that there is an association between the Total PPI-R score and the amount of correctly recognized items. In contrast, no main effect for valence was found. In addition, the results indicated no interaction effect between the Total PPI-R score and valence (Table 5). Running the model with age included as a variable did not reveal significantly different results.

For the falsely recognized non-critical items, a repeated measurements ANOVA with Factor 1 and Factor 2 included as covariates, was firstly performed2_{. Results revealed neither a}

main effect for Factor 1, nor a main effect for Factor 2. Furthermore, no main effect was found for valence, suggesting that there was no difference in the amount of falsely recognized non-critical items between the neutral, negative and hostile word lists. In addition, no interaction effects between Factor 1 and valence, and Factor 2 and valence were found (Table 4). Secondly, a repeated measurements ANOVA with the Total PPI-R score as a covariate was performed. Results showed no main effect of the Total PPI-R and no main effect for valence. In addition, the results indicated no interaction effect between the Total PPI-R score and valence (Table 5). Running the model with age included as a variable did not reveal significantly different results.

For the falsely recognized critical items, a repeated measurements ANOVA with Factor 1 and Factor 2 included as covariates, was firstly performed. Results showed no main effect for Factor 1, but did show a main effect for Factor 2. This indicates that there is an association between the Factor 2 and the amount of falsely recognized critical items. Furthermore, this analysis showed no significant effect of valence, suggesting that there was no difference in the amount of falsely recognized critical items between the neutral, negative and hostile word lists.

2 _{The total amount of falsely recalled non-critical items on the DRM did not meet the assumption of} sphericity (χ2(2) = 8.47, p = 0.02). Therefore, the degrees of freedom were corrected using Greenhouse-Geisser estimates of sphericity (ε = 0.87).

In addition, the results showed neither an interaction effect between Factor 1 and valence, nor an interaction effect between Factor 2 and valence (Table 4). Secondly, a repeated measurements ANOVA with the Total PPI-R score as a covariate was performed. Results did not reveal a main effect of the Total PPI-R score. Furthermore, no main effect of valence and no interaction effect between the Total PPI-R score and valence were found (Table 5). Running the model with age included as a variable did not reveal significantly different results.

Since no interaction effect had been found between psychopathic traits and the relative hostility score of the RMET, no mediation analysis was performed.

Discussion

Previous studies showed that psychopathy might be related to deficits in ToM. However, a specific aspect of ToM, the attribution of hostile intentions to others (HAB), has not been widely investigated yet. In addition, it might be the case that there is an associative process that underlies HAB deficits and that predispose psychopathic individuals to exhibit a superior memory for hostile information, alongside to falsely remember hostile information. The purpose of this study was to investigate the relationship between psychopathic traits, ToM and hostile attributions. In addition, both true and false memory for hostile stimuli was investigated. Specifically, two aspects of memory were tested; recall and recognition, which were assessed by a memory test that included neutral, negative and hostile word lists.

Based on previous studies, it was firstly expected that psychopathic traits can predict ToM performance, but only when the stimulus duration was unlimited and when the stimulus that had to be identified was relatively hostile. Contrary to the expectations, no relationship was found between psychopathic traits and performance on the RMET. This suggests that the relative ease with which an individual can identify hostility (with unlimited amount of time or with time restrictions), is unrelated to the level of psychopathic traits. These findings are not in line with previous research, that showed that psychopath’s hostile ToM abilities are relatively intact (Nentjes et al., in press). An explanation for these inconsistent findings could be that Nentjes et al., (in press) included individuals with a clinical psychopathic disorder, whilst our study was conducted in a sample of individuals with psychopathic traits. Considering the estimated prevalence of psychopathy in the general population to be 1-3 %, whereas the prevalence rises to 15-30% in prison and forensic samples (Vitale et al., 2005), it might have been the case that individuals in our sample (that were mostly students) did not show enough

psychopathic traits to be able to find an effect on ToM performance.

The current study did reveal a difference between the short and long stimulus duration on RMET performance for the total sample (unrelated to psychopathic traits), when the relative hostility of the eyes was taken into account. When stimuli were presented with time-restrictions, a higher level of relative hostility predicted worse performance in identifying the correct mental state. In contrast, when stimuli were presented for an unlimited amount of time, more relative hostility predicted better performance in identifying the correct mental state. This indicates that being able to process the stimuli for a longer amount of time, enhances the likelihood that a mental state is correctly identified as being hostile. A possible explanation for this finding could be that psychopathic individuals tend to exhibit diminished threat-avoidance tendencies when confronted with a direct hostile gaze. These threat-avoidance tendencies that are exhibited, are associated with hostility and aggression. Moreover, this effect is only found when hostility is directly communicated (direct gaze), but not when averted hostile stimuli are shown. Therefore, this could explain why only in the long stimulus duration (with gazing stimuli) of the RMET, the likelihood of correct identification of relative hostile stimuli is enhanced (Von Borries et al., 2012). However, the findings of our study are not in line with previous ToM research, that showed that during the long stimulus duration of the RMET, a higher relative hostility was associated with better performance in a psychopathic group, but with worse performance in a non-offenders group (Nentjes et al., in press). Taken these findings into account, it would have been expected that only psychopathic individuals are better at correctly identifying the relative hostile stimuli, when the eyes are gazing. An explanation for these contrasting findings could be that individuals in general tend to interpret the gaze of the eyes in the long stimulus duration as provocative and hostile, which might be due to the more elaborate and focused way that the stimuli are being processed (Pedersen et al., 2011).

It was secondly expected that individuals with psychopathic traits do not show a hostility bias, but are actually better at identifying hostility when presented. Therefore, it was investigated whether psychopathic traits were related to mistakes made on the task that were considered relatively hostile. This would indicate false perception, because hostility would be identified that is actually not demonstrated. The results indicate that psychopathic traits are not related to the tendency to attribute hostility to stimuli, when no hostility is present. However, results do indicate that when stimuli can be processed for a longer period of time, individuals (that score from low to high on the psychopathy measurement) tend to identify mental states as

being hostile (when no hostility is actually presented). This finding is not in line with research by Nentjes et al., (in press), that showed that psychopathy is not related to an over-attribution of hostility, but rather to a superior identification of hostility. The findings of Nentjes et al., (in press) were explained by the theory that individuals tend to make more accurate inferences about the world when information is congruent to an individuals' mood (Rusting, 1998). The mood congruency theory also explains that an individual is more sensitive to information congruent with their mood. Since psychopathy is related to hostility and anger, they are also more sensitive to hostile stimuli (Nentjes et al., in press). Therefore, this would explain why psychopathic individuals are better at identifying hostility when present (as the study by Nentjes et al., in press, showed). However, the mood-congruency effect could also explain why individuals tend to over-attribute hostility when eyes are gazing (as results in our study showed). A study by Fox, Calder, Mathews and Yiend (2011) showed that anxious individuals tend to enhance orientation to direct gazing eyes (compared to averted eyes) of fearful faces. In addition, this study shows that attention is held more potently by mood-congruent gazing facial expressions. Therefore, the mood-congruency theory could also form an explanation for the results found in our sample. Since it is not self-evident what mental state the eyes in the ToM task are expressing (they may be slightly ambiguous), it might be the case that the long gaze of the eyes causes individuals to attribute a hostile emotion to the eyes that is congruent with their own mental state.

Thirdly, it was expected that individuals with psychopathic traits show a tendency to remember more (false) information with a hostile content compared to a neutral or a negative content. The results only partly support these expectations. As was expected, results indicate that individuals with psychopathic traits tend to falsely recall more hostile information, than neutral or negative information. This finding is in line with previous studies showing that psychopathy is associated with deficits in emotional memory (Christianson et al., 1996; Wilson et al., 2008). Based on previous research from Takarangi et al., (2008) which indicated that aggressive individuals tend to falsely remember hostile information, it would be expected that especially Factor 2 on the PPI-R (that measures antisocial traits) is associated with false recall of hostile information. However, results indicated that false recall of hostile stimuli in psychopathic individuals is associated with both affective and antisocial psychopathy traits. This finding underlines the fact that not only aggression and anti-social traits are associated with memory dysfunction, but that psychopathy as a construct is related to impairments in hostile memory. It

should be noted that this result was found for the falsely recalled words, but it was neither found for the items that were correctly recalled nor for the recognition measures. This indicates that individuals with psychopathic traits do not have a superior memory for hostile stimuli, but that they tend to remember hostility that is actually not present. An implication of these findings is that hostile false memories could activate cognitive schemas that causes an individual to interpret the environment as being hostile (HAB), which often leads to aggression and revenge. This would provide empirical support for the grudge feelings that psychopathic individuals tend to hold against other individuals (Staffort & Cornell, 2003; Miller & Lynam, 2003).

Limitations

Several limitations of this study must be taken into account. Firstly, this research is based on associations between psychopathic traits and memory, therefore no interpretations regarding causality can be drawn. Secondly, Theory of Mind has been measured in earlier research with a variety of different tests (Blair et al., 1996; Dolan & Fullam, 2004; Richell et al., 2003; Nentjes et al., in press), and only Nentjes et al., (in press) made a separation between different emotions and mental states by including hostility in the trails. This can be an explanation for the inconsistent findings regarding psychopathy and hostile Theory of mind abilities, but may also complicate the comparison of the results of this study to earlier research. Furthermore, as stated above, the memory deficits that were found in psychopathic individuals are only found for hostile falsely recalled words, but it was neither found for the items that were correctly recalled nor for the recognition measures. Since this is the first study that used a DRM task with hostile word lists, it might have been the case that methodological weaknesses reduced potential effects. A further limitation of this study is that only one measure of executive functioning has been assessed. Since performance on ToM tasks has repeatedly been associated with executive functioning, more measurements that assess distinct domains of executive functioning, such as IQ, could have yield different results. Finally, this study was aimed to investigate psychopathic traits in the general population. Despite this aim, most of the individuals in the sample were students, which makes it harder to generalize the findings of this study to the clinical population.

Conclusions and future research

research. This is one of the first studies that investigated hostile ToM and hostile memory in relation to psychopathic traits. Contrary to the expectations, this study did not find an association between psychopathy and the ability to attribute feelings and thoughts to others. However, an unexpected finding was that when stimuli are processed for an unlimited amount of time, individuals (independently from psychopathy), are better at identifying real hostility, but also seem to identify hostility that is not actually there. Although psychopathic traits did not seem to predict ToM performance, replication of these findings is needed. Moreover, psychopathic traits were associated with false memory for hostile information. These hostile memory distortions could have serious consequences for information processing and subsequent behavior towards other individuals. Therefore, further research is needed in order to generalize these findings to the clinical psychopathic population. Moreover, further research should aim to further extent the hostile memory task, in order to replicate and optimize the findings that were found. Findings could be supported by measuring the reported confidence level of the hostile false memories (Takarangi et al., 2008). To conclude, this study can be regarded as the first step to investigate psychopath’s hostile memories.

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Table 1

Demographic and Clinical Characteristics (N= 54)

M (SD) range Age (Years) 24.94 (7.84) 18-57 Stroop inference 52.44(23.03) 3.8-106.3 PPI-R total 303.65(24.22) 253-377 PPI-R F1 117.65(14.91) 86-151 PPI-R F2 150.82(16.31) 118-188

% correct RMET short 61.6 39-89

% correct RMET long 65.7 28-94

DRM true recall 86.93(16.27) 52-120

DRM false recall (non-critical) 5.57(3.70) 0-15 DRM false recall (critical) 2.54(1.98) 0-8

DRM true recogntion 36.43(4.29) 24-43

DRM false recognition (non-critical) 5.04(2.32) 1-13 DRM false recognition (critical) 9.86(2.39) 4-15

Note. Data are means (standard deviations). PPI-R = Psychopathic Personality Inventory revised; F1 = Factor 1; F2 = Factor 2. % correct RMET = percentage of correctly identified trails on the Reading the Mind in the Eyes Test. DRM = Deese-Roediger-McDermott paradigm, amount recalled/recognized items are reported.

Table 2

Multilevel Logistic Regression Analysis of Predictors of the Correctly Chosen Answering Option in the Reading the Mind in the Eyes Test

Estimate (B) SE p

Intercept -0.56 0.07 0.00**

Total PPI-R 0.00 0.00 0.75

RMET HSrel -0.00 0.00 0.58

RMET Stimulus duration -0.18 0.10 0.07

HSrel x Stimulus duration -0.01 0.00 0.05*

Table 3

Multilevel Linear Multiple Regression Analysis of Predictors of the Incorrectly Chosen Answering option in the Reading the Mind in the Eyes Test

F p

Intercept 1.87 1.00

RMET stimulus duration 8.39 0.00 **

Total PPI-R 0.00 0.99

Stimulus duration x Total PPI-R 0.02 0.89

Table 4

Analysis of Variance of the Deese-Roediger-McDermott Paradigm Outcome Measures for Factor 1 and Factor 2

Factor 1 Factor 2 Valence Factor 1 x valence Factor 2 x valence

True recall F(1, 51)=1.04, p=0.31, ηp=0.02 F(1, 51)=6.27, p=0.02*, ηp=0.11 F(2, 102)=2.05, p=0.13, ηp=0.04 F(2, 102)=2.05, p=0.13, ηp2=0.04 F(2, 102)=2.19, p=0.12, ηp=0.04

False recall non-critical F(1, 50)=0.85, p=0.36, ηp=0.02 F(1, 50)=3.81, p=0.06, ηp=0.07 F(1.76, 87.88)=3.88, p=0.03*, ηp=0.07 F(1.76, 87.88)=2.48, p=0.10, ηp=0.05 F(1.76, 87.88)=1.88, p=0.16, ηp=0.04

False recall critical F(1, 51)=2.58, p=0.11, ηp=0.05 F(1, 51)=2.46, p=0.12, ηp=0.05 F(2, 102)=0.36, p=0.70, ηp=0.01 F(2, 102)=0.60, p=0.55, ηp=0.01 F(2, 102)=0.10, p=0.91, ηp=0.00

True recognition F(1, 51)=0.40, p=0.53, ηp=0.01 F(1, 51)=6.83, p=0.01*, ηp=0.12 F(2, 102)=0.18, p=0.84, ηp=0.00 F(2, 102)=0.04, p=0.96, ηp=0.00 F(2, 102)=0.40, p=0.67, ηp=0.01

False recognition non-critical F(1, 51)=0.87, p=0.36, ηp=0.02 F(1, 51)=0.97, p=0.33, ηp=0.02 F(1.73, 88.25)=0.08, p=0.90, ηp=0.00 F(1.73, 88.25)=0.36, p=0.67, ηp=0.01 F(1.73, 88.25)=0.89, p=0.40, ηp=0.02

False recognition critical F(1, 51)=1.91, p=0.17, ηp=0.04 F(1, 51)=4.17, p<0.05*, ηp=0.08 F(2, 102)=0.17, p=0.85, ηp=0.00 F(2, 102)=0.90, p=0.41 ηp=0.02 F(2, 102)=0.51, p=0.60, ηp=0.01

Note. PPI-R = Psychopathic Personality Inventory revised; F1 = Factor 1; F2 = Factor 2. F- and p- values are within differences of repeated measurements ANOVA tests. *p < .05.

Table 5

Analysis of Variance of the Deese-Roediger-McDermott Paradigm Outcome Measures for the Total PPI-R score

PPI-R Total Valence PPI-R Total x valence

True recall F(1, 52)=1.82, p=0.18, ηp=0.03 F(2, 104)=2.90, p=0.06, ηp=0.05 F(2, 104)=0.34, p=0.71, ηp=0.01

False recall non-critical F(1, 51)=0.92, p=0.34, ηp=0.02 F(1.75, 89.43)=3.65, p=0.04*, ηp=0.07 F(1.75, 89.43)=4.15, p=0.02*, ηp=0.08

False recall critical F(1, 52)=4.96, p=0.03*, ηp =0.09 F(2, 104)=0.27, p=0.76, ηp=0.01 F(2, 104)=0.42, p=0.66, ηp=0.01

True recognition F(1, 52)=4.14, p<0.05*, ηp=0.07 F(2, 104)=0.27, p=0.76, ηp=0.01 F(2, 104)=0.44, p=0.65, ηp=0.01

False recognition non-critical F(1, 52)=0.06, p=0.81, ηp=0.00 F(1.74, 90.4)=0.07, p=0.91, ηp=0.00 F(1.74, 90.4)=0.43, p=0.62, ηp=0.01

False recognition critical F(1, 52)=0.17, p=0.68, ηp=0.00 F(2, 104)=0.36, p=0.70, ηp=0.01 F(2, 104)=0.30, p=0.74, ηp=0.01

Note. PPI-R = Psychopathic Personality Inventory revised; F1 = Factor 1; F2 = Factor 2. F- and p- values are within differences of repeated measurements ANOVA tests. *p < .05.

Figure 2. The relations between the relative hostility scores of the trials (HSrel) and the chance of choosing the right answering option on the Reading the Mind in the Eyes Test, corrected for age and the inference score on the Stroop task.