Running Head: PSYCHOPATHY TRAITS AND RESPONSE ...risk-resilience.berkeley.edu/sites/default/files/journal...Comparing Adolescent and Adult Offenders’ Patterns of Response Modulation

Running Head: PSYCHOPATHY TRAITS AND RESPONSE MODULATION 1

Comparing Adolescent and Adult Offenders’ Patterns of Response Modulation as a Function of Psychopathy

Jennifer L. Skeem

University of California, Berkeley

Patrick J. KennealyTravis County Community Supervision and Corrections Department

Stephanie K. ClarkUniversity of California, Irvine

PSYCHOPATHY TRAITS AND RESPONSE MODULATION 2

AbstractSince measures of psychopathy have been extended downward from adults to

adolescents, investigators have examined the validity of “juvenile psychopathy” by assessing

whether its pattern of association with other constructs (e.g., symptoms, antisocial behavior)

replicates the pattern found in adults. Few of these studies have focused on potentially

explanatory constructs like response modulation (RM). According to Newman (1998),

psychopathy reflects cognitive deficits in processing relevant peripheral stimuli while pursuing a

goal. These RM deficits could be less indicative of psychopathy during adolescence than

adulthood, given that cognitive control develops throughout adolescence. In this study of 84

adult and 98 adolescent offenders, we use a picture-word interference task and multiple measures

of psychopathy to assess how strongly RM deficits relate to psychopathy (affective,

interpersonal, & lifestyle features) and antisocial features, and explore the consistency of these

relationships across adults and adolescents. Although the picture-word task reliably created

semantic interference for both the adult and adolescent sample, we found that (a) among adults,

RM deficits (low semantic interference) related weakly to affective features of psychopathy (r =

-.25), whereas (b) among adolescents, enhanced RM (high semantic interference) related

moderately to antisocial features (r = .37). Beyond suggesting that RM relates less to global

psychopathy than specific trait constellations, these findings suggest that youth with classic

psychopathic features do not manifest the same cognitive deficits as psychopathic adults. The

possibility that immaturity in cognitive control acts as a confound is consistent with

developmental concerns about the downward extension of psychopathy to adolescents.

Keywords: psychopathy, antisocial behavior, juvenile psychopathy, response modulation


Comparing Adolescent and Adult Offenders’ Patterns of Response Modulation as a Function of Psychopathy

Psychopathy is a personality disorder characterized by traits including egocentricity,

superficial charm, lack of anxiety, shallow affect, lack of remorse, and unreliability (Cleckley,

1976). There has been debate about the appropriateness of extending psychopathy downward

from adults to adolescents. Some have expressed concern that psychopathy measures include

features that are quite normative during adolescence (e.g., egocentricity, irresponsibility)--and

therefore risk over-classifying youth as psychopathic (Hart, Watt & Vincent, 2002; Seagrave &

Grisso, 2002; Skeem & Cauffman, 2003). According to this view, psychopathy may present

differently in adolescence than adulthood and/or may change during the transition to adulthood.

Others have argued that juvenile psychopathy is a valid construct, principally because it relates to

other constructs in a pattern similar to that observed for adults (Salekin & Lynam, 2010; Lynam,

2010; Salekin, Rosenbaum, & Lee, 2008). Typically, however, these “other constructs” involve

symptoms, traits, and indices of antisocial behavior. Few generalizability efforts have focused

on explanatory constructs and operationalized these constructs in the same way across age

groups.A leading cognitive theory of psychopathy is the Response Modulation (RM) hypothesis.

According to Newman and colleagues (Newman, 1998; Patterson & Newman, 1993; Vitale,

Newman, Bates, Goodnight, Dodge, & Pettit, 2005), psychopathy results from a deficit in the

ability to shift attention from goal directed behavior to feedback from the environment.

Specifically, during a task, individuals with psychopathic traits become so focused on a dominant

response or goal that they fail to process relevant contextual information like environmental cues

that would help them appropriately modify their behavior. Using the same cognitive task and

comparable interview-based and self-report measures of psychopathy, the present study (a)


assesses the association between RM deficits and psychopathic traits and (b) explores whether

these relationships are consistent across adults and adolescents.Response Modulation and Global Indices of Psychopathy

Early research on the RM hypothesis treated psychopathy as a global entity (Newman,

Schmitt & Voss, 1997; Lorenz & Newman, 2002)—one operationalized by high scores on the

Psychopathy Checklist-Revised (PCL-R; Hare, 2003) and low scores on a measure of anxiety (as

low anxiety is included in key conceptualizations of psychopathy, but not assessed by the PCL-

R). For example, Hiatt, Schmitt, and Newman (2004) used the PCL-R and a measure of anxiety

to classify 75 offenders into extreme groups. They compared these groups’ performance on a

picture-word interference task that required naming pictures while ignoring peripheral distractor

words. The psychopathic/low anxious group (i.e., PCL-R > 29; anxiety below median; n = 12)

completed the task faster, F(1, 70) = 14.05, p < .001, than the non-psychopathic/low anxious

group (i.e., PCL-R < 20; anxiety below median anxiety; n = 24), suggesting that the former

group was less distracted by contextual information. This led the authors to conclude that

psychopathy is characterized by a RM deficit. Although the RM hypothesis has been understudied in adolescents, similar findings have

been observed in a juvenile sample using a similar task. Specifically, Vitale et al. (2005) used the

Antisocial Process Screening Device (APSD; Frick & Hare, 2001) and a measure of anxiety to

classify a community sample of male 16-year-olds into extreme groups. They found that the

psychopathic/low anxious group (n = 83) displayed moderately faster response times (d = .42)

on a picture-word interference task than the non-psychopathic/low anxious group (n = 84). They

concluded that psychopathic youth “demonstrate a response modulation deficit that could

undermine their ability to attend to the non-dominant interpersonal, affective, and inhibitory cues

that others use to achieve effective self-regulation” (Vitale et al., 2005, p. 468).


Despite the consistency of the pair of findings summarized above, support for the RM

hypothesis as a whole is mixed. For example, Howard, Payamal and Neo’s (1997) study of

Singaporean prisoners and Arnett, Smith and Newman’s (1997) study of Caucasian American

prisoners provided no support for the RM hypothesis. In fact, studies have reported everything

from moderate to large correlations consistent with the RM hypothesis to correlations in the

opposite direction (Smith, Lilienfeld, Jordan, & Kang, 2014). This variability may reflect

problems with the RM hypothesis itself or methodological differences, i.e., different samples,

RM tasks, and indices of psychopathy. Response Modulation and Specific Psychopathic Traits

With respect to the last point, studies that operationalize psychopathy as a global

construct may mask specific associations between RM deficits and particular psychopathic

features. For example, the PCL-R has subscales designed to measure four facets (Hare, 2003):

interpersonal (e.g., superficial charm, conning/manipulative), affective (e.g., shallow affect, lack

of empathy), lifestyle (e.g., impulsivity, irresponsibility), and antisocial (e.g., juvenile

delinquency, criminal versatility) features. These facets can be combined to form larger scales or

“factor scores” that reflect Interpersonal-Affective traits (i.e., Factor 1) and Social Deviance (i.e.,

Factor 2, including lifestyle/antisocial facets). These “factor scores…permit the social deviance

component of psychopathy to be separated from the cluster of personality traits that are

fundamental to the construct” (Hare et al., 1990, p. 340).

Are RM deficits specific to interpersonal and affective traits of psychopathy, or instead

related more broadly to social deviance? The few investigations that have addressed this

question have yielded inconsistent results. For example, based on a sample of 47 Spanish male

inmates, Molto, Poy, Segarra, Pastor and Montanes (2007; see also Heritage and Benning, 2013)

found that the PCL-R’s Social Deviance scale, but not its Interpersonal-Affective scale,


significantly predicted RM deficits (operationalized as perseveration on a card task, β = .38, p < .

05). However, based on a sample of 107 men drawn from the community, Sadeh and Verona

(2008) observed the opposite pattern: Scores on the Psychopathic Personality Inventory’s (PPI;

Lilienfeld & Andrew, 1996) Callous-Unemotional scale, but not its Impulsive Antisociality scale,

significantly predicted RM deficits (as indexed by less interference by distractors on a perceptual

load task). Thus, studies of adults vary in their findings, perhaps as a function of differences in

samples, psychopathy measures, and RM indices.Only one published study of adolescents has examined how RM relates to specific

psychopathic features. In this study of youth with behavioral problems (n = 79), Roose,

Bijttebier, Van der Oord, Claes, and Lilienfeld (2013) found that indices of callousness on two

self-report measures of psychopathy (Frick, 2004; van Barrdewijk et al., 2010) related weakly (r

= -.23, -.25) to RM deficits (as indexed by a self-regulation on a computer-based performance

task). RM deficits did not relate to any other psychopathy subscales. In summary, although growing evidence indicates that RM deficits among adults relate to

general social deviance, some studies indicate a more specific association with interpersonal-

affective features of psychopathy. Although the single study of adolescents is consistent with the

latter findings, the index of RM used in that study differed from that used in the adult studies.

We were unable to locate any study that compared (a) similar samples of adults and adolescents,

(b) on the same cognitive task, and (c) using parallel measures of psychopathic features. Present Study

For two reasons, a study of the nature just described is necessary to explore

developmental influences on the relation between RM and psychopathic features. First,

alternative measures of psychopathy assess only partially overlapping constructs (Poythress,

Lilienfeld, Skeem, Douglas, Edens, & Epstein, 2010; Skeem & Cauffman, 2003). Second and

similarly, alternative measures of RM (e.g. picture-word interference, flanker, stop-signal,


perceptual load tasks)—particularly with varying dependent variables (e.g. response time,

performance errors, ERN amplitude)—assess only partially overlapping constructs (Smith,

Lilienfeld, Jordan, & Kang, 2014). The present study addresses this issue by using multiple measures of psychopathy

(interview-based and self-report) and the same RM task (picture-word interference) across

matched samples of adult and adolescent offenders. The study has three aims. First, to

contextualize the present results against early RM findings (i.e., Newman & Schmitt, 1998;

Vitale et al., 2005), we assess how the RM index relates to global indices of psychopathy and

extreme groups (i.e., high PCL/low anxiety). Second, we assess the association between the RM

index and (a) interpersonal and affective features of psychopathy (within Factor 1) and (b) social

deviance (or impulsive, irresponsible, and antisocial features within Factor 2). Third, and most

importantly, we explore the consistency of these RM-psychopathy relationships across adults and

adolescents. Our primary hypothesis is that RM deficits relate to psychopathic features more weakly

among adolescents than among adults. Adolescents have more immature cognitive control

processes than adults (e.g., Crone, 2009; Casey et al., 1997). These cognitive control processes

include interference suppression (the ability to control for distracting stimuli) and response

inhibition (the suppression of a pre-potent response; see Bridges, Anderson, Reid & Fox, 2013;

Bunge et al., 2002), both of which can affect performance on tasks designed to tap RM. This

raises the possibility that developmental immaturity confounds the association between RM

deficits and psychopathy.Method

To address these study aims, adolescent and adult offenders were assessed for

psychopathy using alternate measures of psychopathy (one interview-based and one self-report)


and a self-report measure of anxiety. RM was assessed by response time on the picture-word

interference task.Participants

Participants were 85 adult and 99 juvenile male offenders incarcerated in correctional

facilities in a large Northeastern state. Adult participants were between the ages of 26 and 29 (M

= 27.50, SD = 1.16) and adolescent participants were between the ages of 14 and 17 (M = 15.69,

SD = 0.92) – both samples were predominantly African American and Caucasian. During

recruitment, efforts were made to obtain similar adolescent and adult samples (particularly with

respect to PCL scores). As shown in Table 1, there were no significant differences between the

adult and adolescent samples on PCL total scores, ethnicity, or estimated IQ. i However, adults

were most likely to be currently incarcerated for a violent offence (e.g. murder, assault), whereas

adolescents were most likely to be currently incarcerated for procedural offences (e.g. probation

violation), followed by violent offenses. Procedures

Recruitment chiefly focused on obtaining equivalent numbers of participants in the

psychopathic (total score ≥ 25) and non-psychopathic (total score < 25) range as indicated by

scores on the Psychopathy Checklist-Revised (PCL-R; Hare, 2003) and Psychopathy Checklist:

Youth Version (PCL:YV; Forth, Kosson, & Hare, 2003). Eligible inmates were approached for

recruitment and given a brief description of the study. Of those approached, 13% of adult, 11%

of juveniles, and 4% of juvenile parents declined to participate. Variables included in the current

study were collected at baseline (demographic information, IQ, anxiety, and psychopathy) and

the one year follow-up (picture-word task and psychopathy). The retention rate between these

two time points was 93%. Of those retained for the one year follow-up interview (n = 338),

approximately 54% (n = 85 adults, n = 99 adolescents) completed the picture-word task, which

was added after one-year data collection had begun. There were no significant differences in


ethnicity, age, number of prior offences, type of current offense, or IQ score between those who

completed the picture-word task and those who did not. In keeping with prior research (Hiatt et al., 2004; Vitale et al., 2005), and to control for a

trade-off effect between accuracy and speed on the picture-word task, participants (1 adult; 1

adolescent) who made more than 5 errors were excluded from analyses. This left a final sample

of 84 adults and 98 adolescents.Measures

Psychopathy. As noted earlier, multiple measures of psychopathy were used for both the

adult and adolescent samples. Specifically, we used (a) adult- and adolescent forms of the PCL,

which explicitly assesses criminal behavior, and (b) adult- and adolescent self-report measures of

psychopathy (the YPI and PPI) that explicitly omit criminal behavior. PCL. The Psychopathy Checklist – Revised (PCL-R; Hare, 2003) was used to assess

psychopathic traits in adults, and the Psychopathy Checklist: Youth Version (PCL:YV; Forth, et.

al., 2003) was used for participants under the age of 18. The PCL:YV is a downward extension

of the PCL-R with similar items. Both versions of the PCL consist of a 20-item checklist of

behaviors and characteristics thought to be emblematic of psychopathy (e.g. grandiosity, flat

affect, callousness, antisocial behavior). Ratings of each item range from 0 (not present) to 2

(definitely present), and are based on a semi-structured interview and inmate file review. Both

PCLs render a total score and four facet scores: Interpersonal, Affective, Lifestyle, and

Antisocial.

Prior to completing any PCL ratings, research personnel (n = 17) completed 8 hours of

training. This included reviewing and scoring 5 practice cases as well as observing and

discussing two live interviews. To protect against rater drift, research personnel attended monthly

meetings to discuss scoring issues, and rated 3 review cases during data collection. Inter-rater

reliability as indexed by the intra-class correlation (ICC). An ICC of .40-.75 is considered


"adequate" and above .75 is "good" (Parkerson, Broadhead, & Tse, 1993). For total scores, good

levels of reliability were observed for the PCL-R (ICC = .91) and PCL:YV (ICC = .81). At the

factor level, ICCs for the Interpersonal, Affective, Lifestyle, and Antisocial facets were .78, .84, .

69, and .83 for the PCL-R, and for the .71, .47, .73, and .75 PCL:YV, respectively.

PPI-SF. Adult participants also completed the Psychopathic Personality Inventory-Short

Form (PPI-SF; Lilienfeld, 1990, as cited in Lilienfeld & Hess, 2001), a self-report measure of

psychopathy containing 56 items on a 4-point Likert scale. Exploratory factor analyses of the

short form (Smith, Edens, & Vaughn, 2011) reveals a two-factor structure similar to the factor

structure of the full PPI (Benning, Patrick, Hicks, Blonigen, & Krueger, 2003; Malterer,

Lilienfeld, Neumann, & Newman, 2009), including Fearless Dominance (FD) and Self-Centered

Impulsivity (SCI) with Coldheartedness (CH) as a potential third factor (Edens & McDermott,

2010; Lilienfeld & Widows, 2005). Internal consistency for the two factors of the PPI-SF has

been demonstrated in both community and incarcerated samples (FD α = .62 - .83, SCI α = .78;

Smith et al., 2011). Cronbach’s alphas for the two factors for the current study are .62 and .83

(FD and SCI factors respectively) and .70 for Coldheartedness. YPI. Adolescents completed the Youth Psychopathic Traits Inventory (Andershed, Kerr,

Stattin, & Levander, 2002), a 50 item self-report measure of psychopathy for youths ages 12 and

older. Each item is scored on a 4-point Likert scale. Prior factor analytic research suggests these

items map onto three factors: Interpersonal, Affective, and Lifestyle (Andershed et al., 2002).

Validity of the YPI is suggested by the significant correlations with measures of conduct

problems (Andershed, Hodgins, & Tengstrom, 2007) and the PCL:YV among community

samples (Cauffman, Kimonis, Dmitrieva, & Monahan, 2009). In keeping with past research

(where α =.66-.93; Andershed et al., 2002) the YPI manifested good internal consistency in the


present study (α=.94 for the YPI total and α= .90, .68, and .84 for the Interpersonal, Affective,

and Lifestyle scales, respectively).Anxiety

For adults, anxiety was assessed with the 20 items from the trait (TAI) subscale of the

State-Trait Anxiety Inventory (Spielberger, 1983). Trait anxiety assesses how a participant

generally feels and has been shown to have a strong association with psychopathy (Hicks,

Markon, Patrick, Krueger, & Newman, 2004). Previous research suggests that the TAI has high

internal consistency (α= .90 in the present study) and adequate convergent and divergent validity

with other measures of anxiety (Barnes, Harp, & Jung, 2002; Stanley, Beck, & Zebb, 1996). For adolescents, anxiety was assessed using the 37 item self-report Revised Children’s

Manifest Anxiety Scale (RCMAS; Reynolds & Richmond, 1985). The RCMAS is internally

consistent (α = .85 in the present sample), manifests good test-retest reliability (r = .63;

Reynolds, 1981), and is highly correlated with other measures of anxiety (r = .88; Muris,

Merckelbach, Ollendick, King, & Bogie, 2002). Response Modulation

Performance on the Picture-Word interference task (PW; see Golinkoff & Rosinski, 1976;

Rosinski, Golinkoff, & Kukish, 1975) was used to assess RM. The task consists of four 8” x 11”

stimulus cards with 20 equal sized cells. The first two cards are a warm-up exercise, where

participants name what they see in each cell as quickly as possible. Card 1 contains the printed

name of an object or an animal in each cell (e.g. pot, cup, and bear) and card 2 contains single

line drawings of objects or animals in each cell. The third and fourth cards contain lined

drawings with distractor stimuli where participants must name only the lined drawings. The

distractor stimuli are superimposed words (e.g. hen, gun, seal) on card 3, and superimposed

nonsensical stings of letters (e.g. cag, lup) on card 4. The nonsensical condition manipulates the

strength of the interference of the distractor stimulus because nonsensical words have no


meaning for the subjects to process or inhibit alternative responses (Golinkoff & Rosinski, 1976;

Rosinski et al., 1975). Response times and errors were recorded for each stimulus card. (To reduce the influence

of outliers, response times greater than three standard deviations away from the group mean were

reduced to the value at three standard deviations). RM--or semantic interference--scores were

calculated by subtracting the response time on card 4 (i.e., non-word distractors) from the

response time on card 3 (i.e., incongruent word distractors; in keeping with Hiatt et al., 2004;

Vitale et al., 2005). Higher RM scores (i.e., faster response times on card 4 than 3) indicate

greater semantic interference. Low and negative RM scores (i.e., faster response times on card 3

than 4) indicate lesser semantic interference and RM deficits. As shown later, semantic

interference effects were observed on this task in both our adult and adolescent samples. These

types of semantic interference effects seem to reflect selective attention and response suppression

processes (e.g., de Zubicaray, Wilson, McMahon, & Muthiah, 2001).Vocabulary & Intelligence

There is evidence that semantic interference effects in picture-word tasks do not depend

on reading skill (Piai, Roelofs, & Roete, 2014) or reading automaticity (MacLeod, 1991).

Nevertheless, because adolescent and adult groups could differ in such factors, we measured

reading-relevant skills (vocabulary) and general abilities (intelligence) as potential covariates to

allow for a conservative tests of our hypotheses. Specifically, we administered the Wechsler

Abbreviated Scale of Intelligence (WASI; Wechsler, 1999), which estimates general intellectual

ability based on two subtests (Vocabulary and Matrix Reasoning). The WASI is strongly

associated with full measures of IQ, learning disability diagnoses, and traumatic brain injury

(Wechsler, 1999). Results

The aims of the present study were to (a) assess how RM relates to global psychopathy

indices (i.e., psychopathy/low anxiety) examined in past research, (b) assess the association


between RM and specific psychopathic and antisocial features, and (c) explore the consistency of

these relationships across adults and adolescents. These aims were addressed using hierarchical

logistic regression and bivariate and partial correlational analyses. Preliminary Analyses

Interference manipulation check. Before addressing the aims, we first conducted a

manipulation check on the PW task—and found that it created a semantic interference effect in

both samples. The effect of card type on reaction time was analyzed using a within group

repeated measures ANOVA. As shown in Table 2, there was a significant difference in reaction

time between the incongruent-word distractor card (Card 3) and the non-word distractor card

(Card 4) for both the adult [Wilks’ Lambda = .40, F(1, 83) = 124.38, p


aims and finding, we first conducted analyses designed to replicate early suggestions that RM

deficits are characteristic of classic psychopathy.First, we conducted extreme group analyses with both the adult- and adolescent- samples.

Specifically, we used a 2 (high- versus low-PCL) X 2 (high- versus low-anxious) ANOVA for

each age group. The ANOVAs did not reveal a significant effect for RM deficits in adolescents,

F (3, 51) = .141, p = .94, nor adults, F (3, 44) = .524, p = .67.Second, to rule out the possibility that these null effects were a function of issues

involving extreme group analysis (Lilienfeld, 1998), we directly tested the interaction.

Specifically, we conducted a series of hierarchical regressions in which the main effects of PCL

Total scores and anxiety were entered at step 1 and the two-way interaction was entered at step 2.

There were no significant interactions between psychopathy and anxiety in predicting PW

performance for the PCL-R in adolescents (Δ�2 =_.01, ΔF [1, 92] = 1.32, p = .25) nor adults

(Δ�2 =_.01, ΔF [1, 80] = 0.29, p = .59). Similarly, no such interactions between psychopathy and anxiety were observed for self-report psychopathy measures in either age group.Aim 2: Calculate the Association between Response Modulation and Specific Constellations

of Psychopathic and Antisocial FeaturesBivariate correlations between RM and specific features of psychopathy among adults are

shown in Table 3. The PCL-R Affective facet and (at a trend level) the PPI Coldheartedness


subscale weakly predicted RM deficits (r=-.21-.23). Because subscales within psychopathy

measures are often intercorrelated (partly because of shared method), we computed semi-partial

correlations to assess the independent relationship between RM and each psychopathy subscale.

As shown in Table 5, the PCL-R Affective facet and PPI Coldheartedness (CH) (again) predicted

low semantic interference, when controlling for their association with other psychopathy

subscales. Together, these results indicate that—among adults--affective features of psychopathy

(but not general social deviance) weakly predict RM deficits.

Aim 3: Compare the Relationship between Response Modulation and Psychopathic Traits

across Adults and AdolescentsTo permit comparisons with the adult sample, we conducted bivariate correlations to

determine the association between psychopathy and RM among adolescents. As shown in Table

4, the PCL:YV Antisocial facet moderately predicted greater RM. This suggests that antisocial

behavior (not affective features specific to psychopathy) predicts RM among youth –i.e.,

increased semantic interference (not deficits).As shown in Table 5, this finding held when controlling for the effect of the other

subscales: The PCL:YV Antisocial facet remained significantly predictive of increased RM, and

a similar trend-level finding emerged for the YPI Lifestyle subscale. The only finding that was

partially consistent with those for adults was that the YPI Interpersonal subscale displayed a

modest, trend-level independent association with low interference (semi-partial r = -.17). Discussion

According to the RM hypothesis, psychopathy reflects deficits in response modulation

(RM), or the ability to attend to relevant contextual information while engaged in a goal directed

response (Newman, 1998; Patterson & Newman, 1993). This study is the first to assess whether

multiple measures of psychopathy (i.e. PCL- and self-report) predict performance on an RM

task, based on a matched sample of adolescent and adult offenders. Because adolescents have


relatively immature systems of cognitive control and RM, we wanted to explore whether the

psychopathy-RM association varied across developmental samples. Our main findings may be organized into two points. First, we did not replicate past

findings that global psychopathy (i.e., high psychopathy/low anxiety) relates to RM deficits. For

example, none of the psychopathy measures interacted with anxiety to predict RM performance

for either adults or adolescents. Second, the relationship between psychopathy and RM was

inconsistent across developmental samples. For adults, scales that assessed affective deficits

predicted deficits in RM, i.e. low semantic interference. In contrast, for adolescents, scales

indexing antisocial behavior and/or disinhibition predicted enhanced RM, i.e. high semantic

interference. This is consistent with developmental concerns about the generalizability of

psychopathy measures (and/or the RM hypothesis) from adults to adolescents.Limitations

Before unpacking these findings, we present the study’s limitations to contextualize the

results. First, although our adult and adolescent groups were matched across key variables (e.g.,

psychopathy, intelligence, demographics), group differences other than age may have influenced

the results, so they must be replicated in a longitudinal study. Second, there was a delay between administration of the psychopathy measures

(completed at baseline, when data were most complete) and the RM task (completed at the one-

year follow-up). This delay allowed us to assess whether psychopathy was a risk factor for RM

deficits (i.e., whether psychopathy preceded and increased the likelihood of RM deficits) – but

may have attenuated relationships. To rule out this possibility, we examined psychopathy and

RM assessments from the same interview (at one year) and found a similar (and not stronger)

pattern of results. Third, the stages of information processing involved in interference during the PW task

(encoding, response selection, or both) are unclear (e.g., Dell’Acqua, Job, Peressotti, & Pascali,

2007; de Zubicaray et al., 2001; Schnur & Martin, 2011; van Maanen, van Rijn, & Borst, 2009).


This limits the ability of the task to shed light on hypotheses that RM deficits occur at different

stages for specific psychopathic traits versus social deviance or disinhibition (Baskin-Sommers

& Newman, 2013). Nevertheless, our focus is on comparing the relation between RM deficits

(at whatever stage they occur a task that is held constant) and psychopathic features across adults

and adolescents.Fourth, given sample size limitations, we were unable to directly test whether age

moderated the relation between psychopathy and RM. The present findings must be replicated in

future research that directly tests for moderation – ideally, using multiple measures of response

modulation and multiple measures of psychopathy.Global Indices of Psychopathy Did Not Predict Response Modulation

We were unable to replicate the results of two prior studies that -- based on extreme

group analyses -- revealed an association between global indices of psychopathy (i.e., high

psychopathy + low anxiety) and RM deficits (operationalized with the picture-word-stroop).

One study was conducted with adults (Hiatt et al., 2004); the other was conducted with

adolescents (Vitale et al., 2005). In the current study, neither extreme group- nor dimensional-

analyses indicated that psychopathy and anxiety interacted to predict reduced interference on the

PW task. This was true for both the adult- and adolescent- matched samples. This failure to

replicate earlier effects could reflect a problem with the RM hypothesis itself (see Smith et al.,

2014 for variability in psychopathy-RM findings), sampling differences, and/or a failure to

account for the multidimensional nature of psychopathy in analyses.Different Features of Psychopathy Predict RM, for Adults vs. Adolescents

Affective and interpersonal traits specific to psychopathy. In keeping with the last

interpretation (that it may be important to attend to specific trait constellations), we found that –

among adults -- affective features of psychopathy independently predicted RM deficits. This

finding is consistent with the spirit of Newman's hypothesis, in that specific psychopathic traits

(rather than general social deviance) predicted RM deficits. The consistency of this relationship


across psychopathy measures is noteworthy. The PCL-R Affective facet and PPI Coldheartedness

scale both assess affective features of psychopathy, but are only weakly correlated ( r=.24 ).

PPI Coldheartedness reflects a lack of imagination, sentiment, and reactivity to the distress of

others (Benning et al., 2003), whereas PCL-R Affective facet represents a deficient affective

experience, callousness, and failure to accept responsibility (Hare et al., 1990). The similarity of

findings across measures suggests that shared features of a lack of emotional reactivity predict

RM deficits, when operationalized as low semantic interference. For adolescents, affective features of psychopathy did not significantly predict RM

deficits. Of the four scales that assess affective and interpersonal features of psychopathy, one

related to RM deficits at a trend level: the YPI Interpersonal scale. This scale assesses dishonest

charm and manipulation, which are consistent with classic conceptions of psychopathy

(Cleckley, 1976; Skeem & Cooke, 2010). Still, the PCL:YV Interpersonal scale (which also

assesses such features) did not predict RM deficits.General social deviance. Among adults in this study, indices of social deviance did not

predict RM deficits. This finding is consistent with the results of some past studies of adults

(Sadeh & Verona, 2008), but not others (Heritage & Benning, 2013; Molto et al., 2007). In contrast with findings for adults, social deviance was associated with RM for

adolescents—in fact, social deviance predicted greater semantic interference effects among

youth. Specifically, the PCL:YV Antisocial facet (which taps poor anger control and criminal

behavior) moderately predicted longer response times on the distractor task; and the YPI

Lifestyle scale (which assesses impulsiveness, thrill-seeking and irresponsibility) manifested a

trend-level association in the same direction. Both of these psychopathy subscales are

moderately associated with temperance, an element of psychosocial maturity that captures the

extent to which young people are able to control their impulses and suppress aggression (Skeem


& Cauffman, 2003). It is possible that the greater semantic interference observed among youth

with higher social deviance scores is partially indicative of immature cognitive control. Conclusions

Effect sizes obtained in past research range from moderate to large correlations consistent

with the RM hypothesis to correlations in the opposite direction (Smith et al., 2014). Although

group comparisons are relatively uncommon, this variability underscores the need to hold

method factors as constant as possible, when comparing groups. In the present study, we used

multiple indices of psychopathy and a uniform measure of response modulation to compare the

performance of a matched sample of adolescents and adults.Our results suggest that psychopathic traits relate differently to RM across development.

Affective traits predicted less semantic interference among adult offenders, whereas disinhibition

and antisocial behavior predicted greater semantic interference in a matched sample of

adolescent offenders. This raises questions about the generalizability of psychopathy measures

and/or the RM hypothesis across developmental groups. Broadly speaking, although measures

of psychopathy relate to many features similarly across groups of adolescents and adults, there

are important exceptions like anxiety (which relates more strongly to psychopathy measures for

young people; for a review, see Skeem et al., 2014). Future research is needed to directly test the possibility that developmental immaturity

confounds the association between psychopathic and antisocial features on one hand, and RM on

the other. Longitudinal research that follows young people through the transition to adulthood is

sparse, but necessary to provide definitive answers to questions about whether and how measures

of psychopathy assess the same construct during adolescence as adulthood.


ReferencesAndershed, H. A., Hodgins, S., & Tengstrom, A. (2007). Convergent validity of the Youth

Psychopathic Traits Inventory (YPI): Association with the Psychopathy Checklist: Youth

Version (PCL:YV). Assessment, 14, 144-154. doi: 10.1177/1073191106298286Andershed, H. A., Kerr, M., Stattin, H., & Levander, S. (2002). Psychopathic traits in non-

referred youths: A new assessment tool. In E. Blaauw & L. Sheridan (Eds.), Psychopaths

current international perspectives (pp. 131-158). Den Hagg: Elsevier. Arnett, P. A., Smith, S. S., & Newman, J. P. (1997). Approach and avoidance motivation in

psychopathic criminal offenders during passive avoidance. Journal of Personality and

Social Psychology, 72, 1413–1428. doi:10.1037/0022-3514.72.6.1413Barnes, L. L. B., Harp, D., & Jung, W. S. (2002).Generalization of scores on the Spielberger

State-Trait Anxiety Inventory. Educational and Psychological Measurement, 62, 603-

618. doi: 10.1177/0013164402062004005Benning, S. D., Patrick, C. J., Hicks, B. M., Blonigen, D. M., & Krueger, R. F. (2003). Factor

structure of the Psychopathic Personality Inventory: Validity and implications for clinical

assessment. Psychological Assessment, 15, 340-350. doi: 10.1037/1040-3590.15.3.340Brydges, C. R., Anderson, M., Reid, C. L., & Fox, A. M. (2013). Maturation of cognitive control:

delineating response inhibition and interference suppression. PloS one, 8(7), e69826.Bunge, S. A., Dudukovic, N. M., Thomason, M. E., Vaidya, C. J., & Gabrieli, J. D. (2002).

Immature frontal lobe contributions to cognitive control in children: evidence from fMRI.

Neuron, 33(2), 301-311.Casey, B. J., Trainor, R. J., Orendi, J. L., Schubert, A. B., Nystrom, L. E., Giedd, J. .N, . .

.Rapopart, J. L. (1997). A developmental functional MRI study of prefrontal activation

during performance of a go-no-go task. Journal of Cognitive Neuroscience, 9, 835-847.

doi: 10.1162/jocn.1997.9.6.835Cauffman, E., Kimonis, E.R., Dmitrieva, J., & Monahan, K.C. (2009). A multimethod

assessment of juvenile psychopathy: Comparing the predictive utility of the PCL:YV,

YPI, and NEO PRI. .NIH Public Assess, 21, 528-542. doi:10.1037/a0017367


Cauffman, E., Skeem, J. L., & Dmitrieva, J. (under review).Comparing the stability of

psychopathy scores in adolescence and adulthood: How often do we capture the

“fledgling psychopath?". Manuscript under review.Cleckley, H. (1976). The mask of sanity (5thed.). St. Louis, MO: MosbyCrone, E. A. (2009). Executive functions in adolescence: inferences from brain and

behavior. Developmental science, 12(6), 825-830. doi: 10.1111/j.1467-

7687.2009.00918.xde Zubicaray, G. I., Wilson, S. J., McMahon, K. L., & Muthiah, S. (2001). The semantic

interference effect in the picture‐word paradigm: An event‐related fMRI study employingovert responses. Human brain mapping, 14(4), 218-227. doi: 10.1002/hbm.1054

Dell’Acqua, R., Job, R., Peressotti, F., & Pascali, A. (2007). The picture–word interference effect

is not a stroop effect. Psychonomic Bulletin & Review, 14, 717-722. doi:

10.3758/PBR.16.6.987Edens, J. F., & McDermott, B. E. (2010). Examining the construct validity of the Psychopathic

Personality Inventory – Revised: Preferential correlates of fearless dominance and self-

centered impulsivity. Psychological Assessment, 22, 32-42. doi: 10.1037/a0018220Forth, A. E. Kosson, D. S., & Hare, R. D. (2003).Psychopathy Checklist: Youth Version manual.

Toronto: Multi-Health Systems.Frick, P. J. (2004). Inventory of Callous-unemotional traits. Unpublished rating scale, University

of New Orleans.Frick, P. J., & Hare, R. D. (2001).The Antisocial Process Screening Device. Toronto: Multi-

Health Systems.Golinkoff, R. M., & Rosinski, R. R. (1976).Decoding, semantic processing, and reading

comprehension skill. Child Development, 47(1), 252-258.


Hare, R. D. (2003).The Hare Psychopathy Checklist—Revised (PCL–R) manual (2nd ed.).

Toronto, Ontario, Canada: Multi-Health Systems.

Hare, R. D., Harpur, T. J., Hakstian, A. R., Forth, A. E., Hart, S. D., & Newman, J. P. (1990). The

Revised Psychopathy Checklist: Reliability and factor structure. Psychological

Assessment: A Journal of Consulting and Clinical Psychology, 2(3), 338-341.

doi:10.1037/1040-3590.2.3.338

Hart, S. D., Watt, K. A., & Vincent, G. M. (2002). Commentary on Seagrave and Grisso:

Impressions of the state of the art. Law and Human Behavior, 26(2), 241-245.

doi:10.1023/A:1014648227688

Heritage, A. L., & Benning, S. D. (2013). Impulsivity and response modulation deficits in

psychopathy: Evidence from the ERN and N1. Journal of Abnormal Psychology, 122,

215-222. doi: 10.1037/a0030039Hiatt, K. D., Schmitt, W. A., & Newman, J. P. (2004). Stroop tasks reveal abnormal selective

attention among psychopathic offenders. Neuropsychology, 18, 50-59. doi:10.1037/0894-

4105.18.1.50Hicks, B. M., Markon, K. E., Patrick, C. J., Krueger, R. F., & Newman, J. P. (2004). Identifying

psychopathy subtypes on the basis of personality structure. Psychological Assessment,

16, 276-288. doi:10.1037/1040-3590.16.3.276Howard, R., Payamal, L. T., & Neo, L. H. (1997). Response modulation deficits in psychopaths:

A failure to confirm and a reconsideration of the Patterson-Newman model. Personality and individual differences, 22, 707-717. doi:10.1016/j.bbr.2011.03.031

Ladouceur, C. D., Dahl, R. E., & Carter, C. S. (2007). Development of action monitoring through

adolescence into adulthood: ERP and source localization. Developmental Science, 10,

874-891 doi:10.1111/j.1467-7687.2007.00639.x


Lilienfeld, S. O., & Andrews, B. (1996). Development and preliminary validation of a self-report

measure of psychopathic personality traits in noncriminal populations. Journal of

Personality Assessment, 66, 488-524. doi:10.1207/s15327752jpa6603_3Lilienfeld, S. O., & Hess, T. H. (2001). Psychopathic personality traits and somatization: Sex

differences and the mediating role of negative emotionality. Journal of Psychopathology

and Behavioral Assessment, 23, 11–24.doi:10.1023/A:101103530Lilienfeld, S.O., & Widows, M. (2005). Professional Manual for the Psychopathic Personality

Inventory-Revised (PPI-R). Lutz, Florida: Psychological Assessment Resources.Lorenz, A. R., & Newman, J. P. (2002). Deficient response modulation and emotion processing

in low-anxious Caucasian psychopathic offenders: results from a lexical decision

task. Emotion, 2(2), 91. doi: 10.1037/1528-3524.2.291

Lynam, D. R. (2010). Child and adolescent psychopathy and personality. In R.T. Salekin & D. R.

Lynam (Eds.), Handbook of child and adolescent psychopathy (pp. 179-201). New York,

NY: Guilford Press.

MacLeod, C. M. (1991). Half a century of research on the Stroop effect: an integrative

review. Psychological bulletin, 109(2), 163-203. doi: 10.1037/0033-2909.109.2.163Malterer, M. B., Lilienfeld, S. O., Neumann, C. S., & Newman, J. P., (2009). Concurrent validity

of the Psychopathic Personality Inventory with offender and community samples.

Assessment, 17, 3-15. doi: 10.1177/1073191109349743Miltner, W. H., Braun, C. H., & Coles, M. G. H. (1997). Event-related brain potentials following

incorrect feedback in time-estimation task: Evidence for a "generic" neural system for

error detection. Journal of Cognitive Neuroscience, 9, 788-

798.doi:10.1162/jocn.1997.9.6.788Molto, J., Poy, R., Segarra, P., Pastor, M. C., & Montanes, S. (2007). Response preservation in

psychopaths: Interpersonal/affective of social deviance traits? Journal of Abnormal

Psychology, 116, 632-637. doi: 10.1037/0021-843X.116.3.632


Muris, P., Merckelbach, H., Ollendick, T., King, N., & Bogie, N. (2002). Three traditional and

three new childhood anxiety questionnaires: Their reliability and validity in a normal

adolescent sample. Behavior Research and Therapy, 40, 753-772. doi: 10.1016/S0005-

7967(01)00056-0Newman, J. P. (1998). Psychopathic behavior: An information processing perspective. In R. D.

Hare, D. Cooke, & A. Forth (Eds.), Psychopathy: Theory, Research and Implications for

Society (pp. 81-104). The Netherlands: Kluwer Academic Publishers. Newman, J. P., Schmitt, W. A., & Voss, W. D. (1997). The impact of motivationally neutral cues

on psychopathic individuals: Assessing the generality of the response modulation

hypothesis. Journal of Abnormal Psychology, 106(4), 563-575. Parkerson, G., Broadhead, E., & Tse, C.-K. (1993). The Duke Severity of Illness Checklist

(DUSOI) for measurement of severity and co-morbidity. Journal of Clinical Epidemiology, 46, 379–393.

Patrick, C. J., & Bernat, E. M. (2010). Neuroscientific foundations of psychopathology. In T.

Millon, R. F. Krueger, & E. Simonsen (Eds.), Contemporary Directions in

Psychopathology: Toward the DSM-V (pp. 419-452). New York, NY: Guilford Press.

Patrick, C. J., Venables, N. C., & Skeem, J. (2012). Psychopathy and brain function: Empirical

findings and legal implications. In H. Hakkanen-Nyholm, & J. Nyholm (Eds.),

Psychopathy and Law: A Practitioner's Guide (pp. 39-78). New York, NY: Wiley-

Blackwell.

Patterson, C. M., & Newman, J. P. (1993). Reflectivity and learning from adverse events: Toward

a psychological mechanism for the syndromes of disinhibition. Psychological Review,

100(4), 716-736.


Piai, V., Roelofs, A., & Roete, I. (2014). Semantic interference in picture naming during dual-

task performance does not vary with reading ability. The Quarterly Journal of

Experimental Psychology, (ahead-of-print), 1-11. doi: 10.1080/17470218.2014.985689Poythress, N., Lilienfeld, S., Skeem, J., Douglas, K., Edens, J., & Epstein, M. (2010). Using the

PCL-R to help estimate the validity of two self-report measures of

psychopathy. Assessment, 17, 206-219. doi:10.1177/1073191109351715Reynolds, C. R. (1981). Long term stability of scores on the Revised-Children’s Manifest

Anxiety Scale. Perceptual and Motor Skills, 53, 702-702.doi: 10.2466/pms.1981.53.3.702Reynolds, C. R., & Richmond, R. O. (1985). Revised Children’s Manifest Anxiety Scale. Los

Angeles, CA: Western Psychological Services.Roose, A., Bijttebier, P., Van der Oord, S., Claes, L., &Lilienfeld, S. O. (2013). Psychopathic

traits in youth and associations with temperament features: Results from a performance-

based measure. Journal of Individual Differences, 34, 1-7. doi:10.1027/1614-

0001/a000090Rosinski, R. R., Golinkoff, R. M., & Kukish, K. S. (1975). Automatic semantic processing in a

picture-word interference task. Child Development, 46(1), 247-253. Sadeh, N., & Verona, E. (2008). Psychopathic personality traits associated with abnormal

selective attention and impaired cognitive control. Neuropsychology, 22, 669-680.

doi:10.1037/a0012692

Salekin, R. T., & Lynam, D. R. (2010). Child and adolescent psychopathy: The road ahead. In

R.T. Salekin & D. R. Lynam (Eds.), Handbook of child and adolescent psychopathy (p.

401-420). New York, NY: Guilford Press.

Salekin, R. T., Rosenbaum, J., & Lee, Z. (2008). Child and adolescent psychopathy: Stability and

change. Psychiatry, Psychology and Law, 15(2), 224-236.

doi:10.1080/13218710802014519

Schnur, T. T., & Martin, R. (2011). Semantic picture–word interference is a post perceptual

effect. Psychonomic Bulletin Review, 19, 301-308. doi: 10.3758/s13423-011-0190-x

http://risk-resilience.berkeley.edu/sites/default/files/wp-content/gallery/publications/2010.Using_the_PCL-R_to_estimate_the_validity_of_two_self-report_measures_of_psychopathy1.pdfhttp://risk-resilience.berkeley.edu/sites/default/files/wp-content/gallery/publications/2010.Using_the_PCL-R_to_estimate_the_validity_of_two_self-report_measures_of_psychopathy1.pdfhttp://risk-resilience.berkeley.edu/sites/default/files/wp-content/gallery/publications/2010.Using_the_PCL-R_to_estimate_the_validity_of_two_self-report_measures_of_psychopathy1.pdf


Seagrave, D., & Grisso, T. (2002). Adolescent development and the measurement of juvenile

psychopathy. Law and Human Behavior, 26, 219-239. doi: 10.1023/A:1014696110850Skeem, J. L., & Cauffman, E. (2003). Views of the downward extension: Comparing the youth

version of the psychopathy checklist with the youth psychopathic traits inventory.

Behavioral Sciences and the Law, 21, 727-770. doi: 10.1002/bsl.563Skeem, J., & Cooke, D. (2010). Is criminal behavior a central component of psychopathy?

Conceptual directions for resolving the debate. Psychological Assessment, 22, 433-445.

doi: 10.1037/a0008512Skeem, J. L., Polaschek, L. L., Patrick, C. J., & Lilienfeld, S. O. (2011). Psychopathic

personality: Bridging the gap between scientific evidence and public policy.

Psychological Science in the Public Interest, 12, 95-162. doi:

10.1177/1529100611426706Smith, S. T., Edens, J. F., & Vaughn, M. G. (2011).Assessing the external correlates of alternative

factor models of the Psychopathic Personality Inventory-Short Form across three

samples. Journal of Personality Assessment, 93, 244-256. doi:

10.1080/00223891.2011.558876Smith, S., Lilienfeld, S., Jordan, D., & Kang, W. (March, 2014). A meta-analytic examination of

the response modualtion hypothesis of psychopathy. Poster session presented at the

meeting of American Psychology-Law Society, New Orleans, LA.Spielberger, C. D. (1983). Manual for the State-Trait Anxiety Inventory. Palo Alto, CA:

Consulting Psychologists Press.Stanley, M. A., Beck, J. G., & Zebb, B. J. (1996). Psychometric properties of four anxiety

measures in older adults. Behaviour Research and Therapy, 34, 827-838.

doi:10.1016/0005-7967(96)00064-2van Baardewijk, Y., Andershed, H., Stegge, H., Nilsson, K. W., Scholte, E., & Vermeiren, R.

(2010). Development and tests of short versions of the youth psychopathic traits


inventory and the youth psychopathic traits inventory-child version. European Journal of

Psychological Assessment, 26(2), 122-128. doi: 10.1027/1015-5759/a000017van Maanen, L., van Rijn, H., & Borst, J. P. (2009). Stroop and picture—word interference are

two sides of the same coin. Psychonomic Bulletin & Review,16(6), 987-999. doi:

10.3758/PBR.16.6.987Viljoen, J. L., MacDougall, E. A., Gagnon, N. C., & Douglas, K. S. (2010). Psychopathy

evidence in legal proceedings involving adolescent offenders. Psychology, Public Policy,

and Law, 16, 254-283. doi: 10.1037/a0019649

Vitale, J. E., Newman, J. P., Bates, J. E., Goodnight, J., Dodge, K. A., & Pettit, G. S. (2005).

Deficient behavioral inhibition and anomalous selective attention in a community sample

of adolescents with psychopathic traits and low-anxiety traits. Journal of Abnormal Child

Psychology, 33, 461-470. doi: 10.1007/s10802-005-5727-X

Wechsler, D. (1999). Wechsler Abbreviated Scale of Intelligence. The Psychological Corporation:

Harcourt Brace & Company. New York, NY.

Running Head: PSYCHOPATHY TRAITS AND RESPONSE MODULATION 1

Table 1Adult and Adolescent Sample ComparisonCharacteristic Adult

(n = 84)Adolescent

(n = 98)Effect Size

WASI IQ estimateb 88.34 (12.66)

87.94 (13.62)

.03

PCL psychopathy estimate

EthnicityAfrican American

16.10(4.42)

53.6

16.21(4.07)

36.7

-.02

.13

Caucasian 29.8 37.8Hispanic/Latino 8.3 13.3

Index offense typea (%) .27*Procedural/Technical 6.6 37.6Violent 73.7 28.0Property 3.6 14.0Drug 15.8 12.9

Note. Standard deviations are in parentheses. WASI = Wechsler Abbreviated Scale of Intelligence. PCL= Psychopathy Checklist.a Φ2 reported for chi-square analyses. b Cohen's d reported for t-test analyses.†p


Table 3Distributions of and Correlations among PW Interference, Psychopathy, and Anxiety for Adults

1 2 3 4 5 6 7 8 9 10 11 121. PW Interference -2. PCL-R Total -.16 -3. PCL-R Interpersonal -.07 .81** -4. PCL-R Affective -.23* .78** .51** -5. PCL-R Lifestyle .02 .63** .22* .25* -6. PCL-R Antisocial .05 .37** .20† .27* .39** -7. PPI Total -.20† .20† .05 .20† .26* .25* -8. PPI-FD .00 .20† .23* .21† .03 .15 .34** -9. PPI-SCI -.13 .00 -.15 -.04 .21† .15 .73** -.31** -10.PPI-CH -.21† .20† .10 .24* .14 .03 .42** -.13 .18† -11.Anxiety .02 -.04 -.04 -.15 .07 .09 .20 -.41** .54** .02 -12. WASI -.11 .10 .13 .03 .06 -.02 .19† .11 .05 .19† .00 -

Mean (SD)

7.13(5.86)

16.10(4.42)

4.54(2.24)

4.79(1.85)

6.82(1.84)

6.23(1.89)

133.57(10.88)

57.92(7.13)

61.12(9.42)

14.50(3.78)

40.45(9.67)

88.59(12.60)

Note. PW = Picture-Word task; PCL-R = Psychopathy Checklist – Revised; PPI = Psychopathic Personality Inventory-Short Form; FD = Fearless Dominance; SCI = Self-Centered Impulsivity; CH = Coldheartedness†p


Table 4Distributions of and Correlations among PW Interference, Psychopathy, and Anxiety for Adolescents

1 2 3 4 5 6 7 8 9 10 11 121. PW Interference -2. PCL:YV Total -.06 -3. PCL:YV Interpersonal -.04 .75** -4. PCL:YV Affective -.04 .76** .31** -5. PCL:YV Lifestyle -.05 .70** .26* .38** -6. PCL:YV Antisocial .31** .42** .37** .29** .26** -7. YPI Total .00 .30** .26* .22* .17 .18† -8. YPI-Interpersonal -.07 .31** .32** .19† .15 .14 .92** -9. YPI-Affective .03 .15 .08 .19† .07 .21* .70** .46** -10.YPI-Lifestyle .10 .24* .15 .19† .22* .13 .81** .65** .43** -11. Anxiety .05 -.09 .00 -.09 -.13 -.11 .06 .11 -.09 .14 -12. WASI .13 -.04 -.04 .01 -.21* -.03 .07 .05 -.10 -.20† -.19† -

Mean (SD)

6.56(6.81)

16.21(4.07)

4.48(2.05)

4.80(1.87)

6.94(1.60)

8.30(1.70)

123.78(25.21)

45.88(12.80)

36.85(8.17)

42.28(8.40)

13.73(6.66)

88.86(13.13)

Note. PW = Picture-Word task; PCL:YV = Psychopathy Checklist – Youth Version; YPI = Youth Psychopathic Traits Inventory; Anxiety = Revised Children’s Manifest Anxiety Scale Total score. * p


Table 5

Semi-Partial Correlations Between PW Interference and Psychopathy

Adults (n=84) PW interferencePCL-R Interpersonal .05 Affective -.25* Lifestyle .04 Antisocial .10PPI Fearless Dominance -.06 Self Centered Impulsivity -.10 Coldheartedness -.24*Adolescents (n=98)PCL:YV Interpersonal -.12 Affective -.07 Lifestyle -.08 Antisocial .37**

YPI Interpersonal -.17† Affective .03

Lifestyle .18†

Note. Semi-partial correlations were corrected for the subscales of the same instrument. PW = Picture-Word task; PCL-R = Psychopathy Checklist Revised; PCL:YV = Psychopathy Checklist-Youth Version; PPI = Psychopathic Personality Inventory-Short Form; YPI = Youth Psychopathic Traits Inventory.†p


Endnotes

i Because the adult sample had a slightly greater proportion of African Americans than the youth

sample, we sub-divided the sample into non-Caucasian and Caucasian group to explore whether

observed age-related differences were partially attributable to racial differences. Differences between

the adult and adolescent samples remained, independent of race. For example, within Caucasian

subsamples, (a) antisocial features were positively associated with greater interference for adolescents

(r = .52 for PCL:YV Antisocial) but not adults (r = -.06 for PCL-R Antisocial), and (b) affective

features were inversely associated with interference for adults (r = -.49 for PCL-R Affective) but not

adolescents (r = -.02 for PCL:YV Affective).

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Running Head: PSYCHOPATHY TRAITS AND RESPONSE ...risk-resilience.berkeley.edu/sites/default/files/journal...Comparing Adolescent and Adult Offenders’ Patterns of Response Modulation