Psychopathy in a Multiethnic World: Investigating Multiple Measures of Psychopathy in Hispanic,African American,and Caucasian Offenders

Abstract

Despite the forensic relevance of psychopathy and the overrepresentation of Hispanics in the United States’ criminal justice system, these two issues remain underexplored, particularly with self-report measures of psychopathy. We investigated the criterion validity of three psychopathy measures among African Americans, Caucasians, and Hispanics in a sample of 1,742 offenders. More similarity than dissimilarity emerged across groups. The factor structures of psychopathy measures among Hispanic offenders were consistent with previous findings. Few significant differences emerged between Hispanic and Caucasian offenders, with most differences emerging between African Americans and the other ethnic groups. In such instances, the correlates of psychopathy were typically weaker for African Americans. The Psychopathy Checklist–Revised yielded fewer psychopathy × ethnicity interactions than the Psychopathic Personality Inventory and Levenson Primary and Secondary Psychopathy Scales. Overall, these psychopathy measures showed reasonable validity across these cultural groups.

Keywords

psychopathy ethnicity Psychopathy Checklist–Revised Psychopathic Personality Inventory Levenson Self-Report Psychopathy Scale

Psychopathy is a personality disorder comprising a broad array of behavioral, emotional, and interpersonal features. It is characterized by glibness, narcissism, deceitfulness, lack of empathy, poor impulse control, and disruptive behavior (Cleckley, 1941; Hare, 1991; Hart & Dempster, 1997). Psychopathy is associated with various negative outcomes, including antisocial conduct (e.g., Leistico, Salekin, DeCoster, & Rogers, 2008; Yang, Wong, & Coid, 2010), criminal recidivism (e.g., Douglas, Nikolova, Kelley, & Edens, 2015), and sexual recidivism (e.g., Hawes, Boccaccini, & Murrie, 2013).

Despite the consensus that psychopathy is an important forensic construct, initial research on the assessment of psychopathy focused largely on Caucasian men. For instance, the most widely used instrument for measuring psychopathy, the Psychopathy Checklist–Revised (PCL-R; Hare, 1991, 2003), was originally developed with, and validated on, predominantly Caucasian samples. In response, more emphasis has been given to potential ethnic differences in the measurement of psychopathy between African Americans and Caucasians (Cooke, Kosson, & Michie, 2001; Neumann & Hare, 2008; Skeem, Edens, Camp, & Colwell, 2004). Nevertheless, questions remain concerning the validity and applicability of psychopathy measures for certain ethnic groups, including Hispanic¹ individuals (e.g., Douglas et al., 2015; Sullivan, Abramowitz, Lopez, & Kosson, 2006).

In applied contexts, the label “psychopath” can influence important forensic decisions (Edens, Magyar, & Cox, 2013). Given psychopathy’s pejorative connotation and its role in legal decision making, it is important to discover if ethnic differences exist across multiple methods of assessment. To address this issue, we compare the reliability and mean scores of three measures of psychopathy among Hispanic, Caucasian, and African American offenders as well as the measures’ associations with commonly evaluated criteria (Hart & Storey, 2013; Patrick, 2006). In addition, this study gives particular accord to Hispanic offenders by examining the factor structure of psychopathy measures within this ethnic group.

Research Comparing Psychopathy Measures in African American and Caucasian Individuals

Factor analysis of the PCL-R originally yielded two correlated factors: Factor 1 (F1) or the Interpersonal/Affective factor and Factor 2 (F2) or the Social Deviance factor (Hare, 1991). Hare (2003) later proposed a four-factor model that split the original two broad factors into four facets: Interpersonal, Affective, Lifestyle, and Antisocial. Cooke and Michie (2001) had previously reported a competing three-factor model that was virtually identical except that it did not include the Antisocial facet. At the manifest level of the PCL, incongruent factor structure was reported for the two-factor model between African Americans and Caucasians (Kosson, Smith, & Newman, 1990). But do PCL-R score differences exist between African Americans and Caucasians? In a meta-analysis, Skeem et al. (2004) found only a 1-point difference in PCL-R total scores between African American and Caucasian individuals—a relatively trivial difference given that the standard error of measurement of the PCL-R is approximately 3 points (if not appreciably higher, at least in applied adversarial settings; see Edens, Cox, Smith, DeMatteo, & Sörman, 2015). Similarly, a meta-analytic review reported only negligible mean differences between African American and Caucasian adolescents on PCL measures (McCoy & Edens, 2006).

Although scale score differences are important, it is also important to establish measurement invariance to confirm if an instrument is assessing the same construct across subpopulations (e.g., ethnic groups) without bias (Millsap, 2007). A confirmatory factor analysis (CFA) revealed that the three-factor structure of the PCL-R was invariant between African American and Caucasian samples (Cooke et al., 2001). Additionally, item response theory analyses revealed that although certain items of the PCL-R demonstrated ethnic bias, item-level differences “cancelled out,” indicating that the measure as a whole did not demonstrate differences in test functioning between African American and European American samples (Cooke et al., 2001). The PCL: Screening Version (PCL: SV; Hart, Cox, & Hare, 1995) also evidenced structural invariance between African American and Caucasian adults (Neumann & Hare, 2008; Skeem, Mulvey, & Grisso, 2003; Vitacco, Neumann, & Jackson, 2005). For African American, Caucasian, and Hispanic adolescent offenders, the PCL: Youth Version (PCL: YV; Forth, Kosson, & Hare, 2003) was invariant across ethnicity (Jones, Cauffman, Miller, & Mulvey, 2006) but, in the same sample, differential item functioning emerged on 15 of 20 items (Tsang, Piquero, & Cauffman, 2014).

Similar findings have emerged in other ethnic groups. For instance, a CFA of Aboriginal and non-Aboriginal offenders revealed structural invariance of the PCL-R (Olver, Neumann, Wong, & Hare, 2013). The PCL-R has also generally evidenced structural invariance across nationalities (e.g., Cooke, Michie, Hart, & Clark, 2005; Mokros et al., 2011; cf. Mokros et al., 2014). Although the Interpersonal Measure of Psychopathy (Kosson, Steuerwald, Forth, & Kirkhart, 1997)—an observational measure of interpersonal interactions designed to supplement the PCL-R—displayed structural invariance between African American and Caucasian inmates (Vitacco & Kosson, 2010), research on measurement invariance across ethnicities using other psychopathy measures is scant.

In addition to testing measurement invariance, the criterion-related validity of psychopathy measures has been investigated among ethnicities. Certain findings have suggested that, across ethnicity, the PCL-R did not vary in its associations with external criteria. Vachon, Lynam, Loeber, and Stouthamer-Loeber (2012) found only 3 (out of a possible 125) ethnicity-based moderations in the criterion-related validity of the PCL-R. The number of moderations was less than the expected family-wise error rate, and the effect sizes were small in magnitude. Others have found that psychopathy is a significant predictor of violence in African American offenders (Walsh & Kosson, 2007), and that the PCL-R three- and four-factor models were not moderated by ethnicity in predicting aggressive behavior among civil psychiatric patients (Vitacco et al., 2005).

However, in other studies, the relationship between psychopathy and external correlates has varied by ethnicity. Meta-analytic reviews have reported that PCL measures display stronger effect sizes with antisocial outcomes (e.g., recidivism) when samples had greater ethnic homogeneity (i.e., Caucasian samples) for both adults (Leistico et al., 2008) and youth (Edens, Campbell, & Weir, 2007). Ethnicity has also moderated the relationship between psychopathy and impulsivity (Jackson, Neumann, & Vitacco, 2007; Kosson et al., 1990). In comparison with Caucasians, African Americans displayed weaker associations between impulsivity and both F1 and F2 scores. Moreover, African American inmates demonstrated differing patterns of emotional and informational processing in comparison with Caucasians such that reaction times on lexical decision making did not differentiate a low-anxiety psychopathy group from the comparison, nonpsychopathy group (Lorenz & Newman, 2002).

Most of the extant research has focused on the PCL-R and its derivatives (e.g., PCL: SV [Hart et al., 1995] and PCL: YV [Forth et al., 2003]). Yet the PCL-R is only one measure of psychopathy (see Skeem & Cooke, 2010), and other conceptualizations of the disorder exist. For instance, the Psychopathic Personality Inventory (PPI; Lilienfeld & Andrews, 1996), the most widely researched self-report measure of psychopathy, was developed to assess psychopathy with less emphasis on criminality or antisocial behavior. Still, investigations of ethnic differences among non-PCL-R conceptualizations and measures of psychopathy have been limited and mixed. Only 4 out of 672 potential racial and gender differences were found in an investigation of several self-report measures of psychopathy and external criteria, including normal-range personality traits and personality disorder symptoms (Benning, Patrick, Salekin, & Leistico, 2005). Similarly, no ethnic differences were reported between the self-report Levenson Primary and Secondary Psychopathy Scales (LPSP; Levenson, Kiehl, & Fitzpatrick, 1995) and passive avoidance learning in a sample of noninstitutionalized offenders (Epstein, Poythress, & Brandon, 2006).

Nevertheless, others have reported that the nomological nets of self-report psychopathy measures have differed between African Americans and Caucasians. For instance, in an offender sample, the LPSP was less strongly related to indices of antisociality, nonviolent criminality, and passive avoidance for African American inmates compared with Caucasians (Brinkley, Schmitt, Smith, & Newman, 2001). Similar ethnic variability was reported for the PPI (Lilienfeld & Andrews, 1996). Contrary to findings with the PCL-R (i.e., smaller relations with aggression for non-Caucasians), PPI total scores were predictive of proximate violence for African American inmates but not for Caucasians (Camp, Skeem, Barchard, Lilienfeld, & Poythress, 2013).

In sum, similar to the latent structure of psychopathy measures, there is generally evidence for consistency in the pattern of correlates across ethnic groups. However, there are scattered reports of ethnic differences that vary in effect size. Although scholars should be commended for examining the generalizability of psychopathy in African Americans—a group whose overrepresentation in prisons has been well documented (National Association for the Advancement of Colored People, 2014)—other ethnic minorities have been largely overlooked in the assessment of psychopathy. Hispanics are of particular forensic relevance in the United States, as they comprise 16% of the prison population (U.S. Census Bureau, 2012). Approximately 1 in 100 U.S. citizens are in prison, but roughly 1 in 36 Hispanic American men are in prison (Pew, 2008).

Measures of Psychopathy in Hispanic Samples

Initial findings concerning the assessment of psychopathy in Hispanic samples have varied. In a study of Hispanic adolescent offenders, Roth (2006) reported that the PCL: YV (Forth et al., 2003) was positively correlated with the Structured Assessment of Violence Risk in Youth (Borum, Bartel, & Forth, 2006), and the PCL: YV displayed good concurrent validity. In contrast, Walsh (2013) found that for Latino American adult inmates, PCL-R scores were not predictive of future violence save for a small positive effect for the fourth (antisocial) facet.

There have also been several investigations of the psychometric properties of the PCL-R in Hispanic samples. Tubb (2002) found that the three-factor model proposed by Cooke and Michie (2001) afforded a better fit in a Hispanic offender sample than the two-factor model. Sullivan et al. (2006) found broad similarity in the reliability and construct validity of the PCL-R among European Americans, African American, and Latino inmates. Several interactions were reported between psychopathy and ethnicity in predicting outcomes. For example, the affective facet was positively related to the Interpersonal Measure of Psychopathy among European Americans, whereas a negative association was present among Latinos. A similar interaction was reported between the affective facet and socioeconomic status. However, the number of significant interactions was less than the expected family-wise error rate (i.e., 4 significant interactions out of 360).

Even less is known regarding the validity of self-report measures of psychopathy among Hispanic adults. In a youth community sample, the LPSP was invariant between Hispanic and African American youth on the basis of multigroup CFA (Horan, Brown, Jones, & Aber, 2015). Nevertheless, there is a need to examine similar ethnic differences in at-risk adult populations for both the LPSP and the PPI. In the revised PPI (PPI-R; Lilienfeld & Widows, 2005), an analysis of normative data did not reveal significant mean ethnic differences (i.e., Caucasian vs. other races). Yet, in a meta-analytic review, small moderating effects were reported for both PPI higher order factors (i.e., Fearless Dominance [FD] and Self-Centered Impulsivity) and the percentage of Caucasians in a sample (Miller & Lynam, 2012). Specifically, the relationship between the PPI factors and internalizing behaviors was stronger in studies with fewer Caucasian participants. Furthermore, small ethnic differences have been reported between primary and secondary psychopathy subtypes—derived by the PPI—whereby non-Caucasians were more likely to be classified as falling within the secondary subtype, which is associated with weak impulse control and antisocial behavior (Lee & Salekin, 2010).

Present Study

The purpose of the present study was to investigate potential ethnic differences in measures of psychopathy among Hispanic, African American, and Caucasian offenders. Our research questions were fourfold: (a) Does the internal consistency of psychopathy measures differ among ethnic groups? (b) Do mean differences exist among ethnic groups for measures of psychopathy? (c) Is the factor structure of psychopathy measures’ replicable in Hispanic offenders? and (d) Does the construct validity of psychopathy measures differ among ethnic groups? We used multiple methods of assessment to clarify potential ethnic differences. Despite a growing body of work focusing on differences in the assessment of psychopathy between particular ethnicities (e.g., Caucasian vs. African Americans), few studies have addressed differences in measures of psychopathy, especially self-report measures, among Hispanic populations.

Method

Participants

The sample consisted of 1,742 offenders who were participating in court-ordered residential community drug treatment programs or serving an institutional prison sentence in Nevada, Oregon, Florida, Texas, or Utah. Inclusion criteria included (a) English speaking, (b) not receiving psychotropic medication or residing on the mental health unit of a prison, and (c) having an IQ of at least 70 based on an intelligence screening measure (Quick Test; Ammons & Ammons, 1962). Participants in community drug treatment programs must have completed detoxification plans before enrollment in the study. The sample consisted predominantly of men (83%), and ages ranged from 17 to 59 years (M = 30.51, SD = 6.63) at the time of recruitment, although an effort was made to recruit participants aged 19 to 40 years.

Participants reported whether they identified as Caucasian or African American and then whether they identified as Hispanic or non-Hispanic. The sample consisted of 591 African Americans, of whom 27 identified as Hispanic, and 1,068 Caucasians, of whom 119 identified as Hispanic. Furthermore, 19 offenders reported being Hispanic, but had missing data for whether they identified as African American or Caucasian. Given the small sample sizes for the Hispanic Caucasians and Hispanic African Americans, we combined these individuals into an overall Hispanic group. Thus, the finalized ethnic composition was 10% Hispanic (n = 165), 32% non-Hispanic African American (n = 564), and 55% non-Hispanic Caucasian (n = 949), and 4% (n = 65) missing data. Participants were approximately evenly distributed between community drug programs (47.8%) and prisons (52%). Sample characteristics are described in more detail elsewhere (Poythress et al., 2010).

Measures

Measures of Psychopathy

PCL-R (Hare, 1991, 2003)

The PCL-R is a 20-item measure used to assess psychopathy based on an interview and file review. We used the four-factor model to examine mean-level differences in psychopathy features across groups and their relations with external criteria. Descriptive statistics and internal consistency (Cronbach’s alpha) for total and facet scores were as follows: PCL Total scores, M = 22.55, SD = 7.50, α = .82; Facet 1, M = 3.79, SD = 2.27, α = .70; Facet 2, M = 4.36, SD = 2.37, α = .77; Facet 3, M = 6.52, SD = 2.14, α = .60; Facet 4, M = 5.84, SD = 2.54, α = .63. The interrater reliability was high, with an intraclass correlation coefficient of .88. Across the sample, 15% had a score of 30 or higher, which has traditionally been considered a cutoff for diagnosing psychopathy.

PPI (Lilienfeld & Andrews, 1996)

The PPI is a self-report measure of psychopathy with 187 items that are answered on a 4-point Likert-type scale. The PPI contains eight content scales (subscales), seven of which have often been found to load onto two factors (Benning, Patrick, Hicks, Blonigen, & Krueger, 2003): FD comprising the Social Potency, Stress Immunity, and Fearlessness subscales and Impulsive Antisociality (IA; now commonly referred to as Self-Centered Impulsivity in relation to the PPI-R [Lilienfeld & Widows, 2005]) comprising the Impulsive Nonconformity, Blame Externalization, Machiavellian Egocentricity, and Carefree Nonplanfulness subscales (but see Neumann, Malterer, & Newman, 2008, for an alternative factor structure). The eighth scale, Coldheartedness, did not load onto either factor, and it is often considered a third dimension of psychopathy on its own, although it has been understudied (see Berg, Hecht, Latzman, & Lilienfeld, 2015; Marcus, Fulton, & Edens, 2013). Descriptive statistics and internal consistency for total and factor scores were as follows: PPI Total scores, M = 386.28, SD = 41.32, α = .91; FD scores, M = 144.68, SD = 20.13, α = .88; IA scores, M = 190.72, SD = 31.60, α = .93; Coldheartedness scores, M = 44.15, SD = 8.38, α = .78.

LPSP (Levenson et al.,1995)

The LPSP is a self-report measure of psychopathy consisting of 26 items that are scored on a 4-point Likert-type scale. The LPSP was intended to capture two broad forms of psychopathy: primary and secondary psychopathy. The Primary and Secondary scales were intended to be indices of PCL-R F1 and F2, respectively, although there is evidence to suggest that Primary scale may be a stronger marker of antisocial propensities (e.g., Lilienfeld & Fowler, 2006; Poythress et al., 2010). Descriptive statistics and internal consistency for the factor scores in this sample were as follows: LPSP Total score, M = 55.90, SD = 11.66, α = .85; Primary scale, M = 32.91, SD = 8.14, α = .76; Secondary scale, M = 22.99, SD = 5.27, α = .75.

Measures of External Correlates

Personality Assessment Inventory (PAI; Morey, 1991)

The PAI is a widely used multiscale self-report measure that focuses on distress-related psychopathology, personality disorder features, and treatment needs. Participants respond to 344 declarative statements on a 4-point scale by answering the degree to which each statement is true. The PAI includes 22 full, nonoverlapping scales, including 11 clinical scales, 5 treatment scales, and 2 interpersonal scales. In the present study, the Antisocial Features (ANT), Aggression (AGG), Borderline Features (BOR), and Drug Problems (DRG) subscales were selected for analyses because of their theoretical and empirical relevance to psychopathy (Edens, Hart, Johnson, Johnson, & Olver, 2000; Edens, Poythress, & Watkins, 2001; Miller et al., 2010; Taylor & Lang, 2006). The range of internal consistencies for the clinical scales used in this study was α = .79-.94.

Harm Avoidance (HA)

The HA scale from the Multidimensional Personality Questionnaire (Tellegen, 1982) consists of 28 true/false items. HA is negatively associated with psychopathy (see Lilienfeld & Andrews, 1996), and is considered a conceptual inverse of Lykken’s (1995) fearlessness construct, which is regarded by many scholars as central to primary psychopathy. For this sample, the internal consistency was high (α = .86).

Impulsivity

The Barratt Impulsiveness Scale (BIS Version 11; Barratt, 1994) is a 30 item self-report measure of impulsivity that has been defined as a “predisposition toward rapid, unplanned reactions to internal or external stimuli without regard to the negative consequences of these reactions to the impulsive individual or to others” (Moeller, Barratt, Dougherty, Schmitz, & Swann, 2001, p. 1784). Impulsivity is considered by many to be a central component of psychopathy (Cleckley, 1976; Hare, 2003), although it is more strongly associated with the behavioral than with the affective and interpersonal features of psychopathy (Edens & McDermott, 2010; Ruiz, Skeem, Poythress, Douglas, & Lilienfeld, 2010). For this sample, the internal consistency for the BIS was high (α = .86).

Criminal Recidivism

Offenders in community drug programs or inmates who were released from prison (n = 1,154) were monitored for recidivism over a 1-year follow-up period. Recidivism was coded on the basis of criminal record review from the National Crime Information Center. Two dichotomous recidivism variables were coded: the presence of any arrest and the presence of any violent arrest. A violent arrest was defined as any arrest for murder, manslaughter, robbery, assault, and/or sexual assault. Although 41% of offenders were rearrested for some type of criminal activity over the 1-year follow-up period, few were rearrested for a violent offense (4%).

Measures of Antisocial Personality Disorder (ASPD)

Psychopathy and ASPD are moderately correlated (Lilienfeld, 1994), stemming largely from the shared impulsive and antisocial behavioral components of psychopathy (Hare, Neumann, & Widiger, 2012). In the present study, ASPD was measured using the Structured Clinical Interview for the DSM-IV Axis II Personality Disorders (SCID-II; First, Gibbon, Spitzer, Williams, & Benjamin, 1996). The internal consistency for the SCID ASPD was α = .83.

Behavioral Inhibition System (BIS) and Behavioral Activation System (BAS; Carver & White, 1994)

The BIS and BAS scales consist of 20 total items in a 4-point Likert-type scale format. Gray’s (1987) reinforcement sensitivity theory has been used to explain differences between primary psychopathy, which is ostensibly associated with weak BIS reactivity (Fowles, 1980), and secondary psychopathy, which is ostensibly associated with strong BAS reactivity (Lykken, 1995). The internal consistency for the BIS scale was adequate (α = .70) as were the internal consistencies of the BAS Drive (α = .85) and BAS Fun scales (α = .78).

Child Abuse and Trauma Scale (CATS; Sanders & Giolas, 1991)

The CATS is a self-report measure focusing on negative experiences in childhood and adolescence such as physical, sexual, and psychological abuse. It consists of 38 items that are answered on a 5-point scale. Porter (1996) theorized that childhood abuse and trauma is an etiological mechanism for secondary psychopathy (but see Poythress, Skeem, & Lilienfeld, 2006). In this sample, the internal consistency was excellent (α = .95).

Procedure

The current study derived from a larger multisite research project focusing on psychopathic personality (e.g., Poythress et al., 2010). Research assistants were advanced graduate students in clinical psychology or social work. After receiving formal training by published experts on study measures, they scored 10 training tapes for PCL-R and ASPD diagnoses and required an interrater reliability above .80 before starting data collection. Every 6 months, the project manager observed two interviews conducted by research assistants to examine interrater reliability for these rating scales.

Participants were sampled randomly from an institutional list of offenders who met basic eligibility criteria. Enrollment procedures were completed in private rooms, and on informed consent, IQ screening tests were administered. In a fixed order, self-report measures were completed on a laptop except for the PAI, which was completed in paper-and-pencil form. Participants without a 10th-grade education or who could not read the first few items of the PAI were assessed for reading ability using the Basic Reading Inventory (Johns, 1997). Items were read out loud if participants did not achieve a 9th-grade level on this measure. The research protocol lasted approximately 4.5 hours, and was typically completed over two sessions. Participants received $20 for their participation aside from one institutional site that did not allow financial reimbursement.

Data Analytic Strategy

Cronbach’s alpha and mean interitem correlation (MIC) values were calculated to examine potential ethnic differences in the reliability of the psychopathy measures. Potential differences in mean levels of psychopathy across ethnic groups were calculated using Tukey’s Honestly Significant Difference procedure. To investigate the criterion validity of psychopathy across ethnic groups, bivariate analyses were completed by computing zero-order Pearson product–moment correlations for each ethnic group (i.e., Hispanic, Caucasian, and African American) between total and subscale scores of the PCL-R, PPI, LPSP, and external correlates. Given the large number of analyses, differences were considered statistically significant using a conservative alpha level of .001.

Next, CFAs were conducted for the PCL-R, PPI, and LPSP within the Hispanic subsample to examine if models could be replicated in this ethnic group. CFAs were computed in “lavaan,” a structural equation modelling package for R (Rosseel, 2012), using robust weighted least squares estimation given the ordinal nature of the PCL-R and LPSP indicators. Maximum likelihood estimation was used for the PPI three-factor model given the continuous nature of its subscale indicators. As suggested by Hu and Bentler (1999), in addition to the χ² goodness-of-fit statistic, model fit was evaluated with the comparative fit index (CFI) and root-mean-square error of approximation (RMSEA). Given the sensitivity of χ² values to sample size and model correlations, normed chi-square (NC; i.e., χ²/df) values below 2.00 were used to represent acceptable model fit (Kline, 2005). Other commonly used thresholds of acceptable fit include CFI >.90 and RMSEA <.08, although some argue these rules of thumb are too strict (Marsh, Hau, & Wen, 2004). Using statistical code to calculate power for RMSEA in R (Preacher & Coffman, 2006), power was greater than .98 for both the LPSP and PCL-R models, but only .42 for the PPI three-factor model; hence, the results for the lattermost measure should be interpreted with some caution.

Hierarchical regression was used to analyze the potential moderating effect of ethnicity on the relation between measures of psychopathy and external correlates. Dummy-coded ethnicity variables were created to examine differences between each unique ethnicity pairing. Because the ethnic groups differed by IQ screening score, F(2, 1653) = 104.31, η² = .11, p < .001, gender, χ² = 7.15, df = 2, φ = .07, p = .028, and the proportion of participants in community drug treatment programs, χ² = 99.11, df = 2, φ = .24, p < .001, these variables were entered as covariates. After mean centering, the psychopathy variable and dummy coded variables were entered into the second step of the regression models. Next, psychopathy × ethnicity interaction terms were entered in the third step. Moderation analyses were conducted for each total and subscale score for each theoretically relevant criterion variable. Interactions are challenging to detect because they can be attenuated by the multiplicative of the main effects’ error terms (Cohen, Cohen, West, & Aiken, 2003). Therefore, the alpha level was kept at .05; we focused on the consistency in patterns of interactional differences in interpreting these results.

Results

Reliability Analyses

Table 1 presents the Cronbach’s alpha and MIC values for the PCL-R, PPI, and LPSP among Hispanic, African American, and Hispanic offenders. For the PCL-R and LPSP scales, no internal consistency differences emerged. However, Cronbach’s alpha was somewhat higher for Caucasians compared with African Americans for the PPI total (χ² = 52.38, φ = .26, p < .001), FD (χ² = 38.74, φ = .23, p < .001), and IA (χ² = 29.14, φ = .19, p < .001) scales. No significant differences emerged in the internal consistency of the PPI Coldheartedness scale, nor were significant differences observed between Hispanic offenders and the other ethnic groups.

Table 1.

Internal Consistency of Psychopathy Measures Between Ethnic Groups.

Measure	Hispanic		Caucasian		African American
Measure	α	MIC	α	MIC	α	MIC
PCL-R
Total	.81	.17	.82	.19	.82	.19
Facet 1	.64	.31	.70	.37	.70	.36
Facet 2	.72	.40	.76	.44	.76	.44
Facet 3	.70	.32	.61	.24	.58	.22
Facet 4	.62	.25	.64	.26	.60	.22
PPI
Total	.91	.06	.93	.07	.88	.04
FD	.87	.11	.90	.14	.84	.09
IA	.94	.14	.94	.15	.91	.11
Cold	.70	.06	.79	.16	.78	.15
Levenson
Total	.87	.21	.87	.20	.83	.16
Primary	.79	.19	.79	.19	.71	.13
Secondary	.76	.24	.76	.24	.72	.21

Note. α = Cronbach’s alpha; PPI = Psychopathic Personality Inventory; PCL-R = Psychopathy Checklist–Revised; MIC = mean interitem correlation; FD = PPI Fearless Dominance; IA = PPI Impulsive Antisociality; Cold = PPI Coldheartedness.

Differences in Psychopathy Scores

Analysis of variance revealed ethnic differences for PCL-R Total, F(2, 1542) = 22.26, p < .001, Facet 1, F(2, 1542) = 20.52, p < .001, Facet 2, F(2, 1542) = 33.40, p < .001, and Facet 4 scores, F(2, 1531) = 15.89, p < .001 (see Table 2 for descriptive statistics). Post hoc analyses revealed higher mean scores for African Americans than Caucasians for these PCL-R scales (d = .36-.37). No significant ethnic differences emerged for the PPI and LPSP scales, nor were significant differences observed between Hispanic offenders and the other ethnic groups.

Table 2.

Descriptive Statistics of Measures of Psychopathy Across Ethnic Groups.

Scale	Hispanic		Caucasian		African American		d1	d2	d3
Scale	M	SD	M	SD	M	SD	d1	d2	d3
PCL-R Tot	22.78	7.37	21.48	7.44	24.21	7.23	.18	.20	.37***
Facet 1	3.88	2.13	3.49	2.25	4.29	2.26	.18	.18	.36***
Facet 2	4.60	2.18	3.94	2.36	4.98	2.30	.28	.17	.46***
Facet 3	6.67	2.32	6.53	2.13	6.42	2.08	.07	.12	.05
Facet 4	5.82	2.54	5.53	2.54	6.32	2.44	.11	.21	.32***
PPI Tot	388.39	41.93	388.22	42.89	382.52	37.13	.00	.15	.14
PPI FD	145.21	20.18	144.74	20.89	144.47	18.52	.02	.04	.01
PPI IA	191.84	34.40	192.55	31.76	187.52	29.72	.02	.13	.16
PPI Cold	44.18	7.72	44.27	8.21	43.78	8.70	.11	.05	.06
LPSP Tot	56.22	12.56	55.69	11.61	56.22	11.39	.04	.00	.05
LPSP Pri	33.54	8.46	32.41	8.07	33.61	8.11	.14	.01	.15
LPSP Sec	22.69	5.75	23.27	5.19	22.62	5.24	.11	.01	.12

Note. d1 = Cohen’s d between Hispanic and Caucasian groups; d2 = Cohen’s d between Hispanic and African American groups; d3 = Cohen’s d between Caucasian and African American groups; PCL-R Tot = PCL-R Total Score; Facet 1 = PCL-R Facet 1 Score; Facet 2 = PCL-R Facet 2 Score; Facet 3 = PCL-R Facet 3 Score; Facet 4 = PCL-R Facet 4 Score; PPI Tot = PPI Total Score; PPI FD = PPI Fearless Dominance Score; PPI IA = PPI Impulsive Antisociality Score; PPI Cold = PPI Coldheartedness Score; LPSP Tot = LPSP Total Score; LPSP Pri = LPSP Primary Scale Score; LPSP Sec = LPSP Secondary Score.

***

p < .001.

Confirmatory Factor Analysis

For the PCL-R, when specifying a four-factor model (Hare, 2003), the results indicated inadequate fit, χ²(129) = 193.21, p < .001, CFI = .87, RMSEA = .06, 90% confidence interval (CI) [.04, .08]. Correlations between factors and most of their loadings were significant at a level of p ≤ .001, except for PCL-R Items 15 (p = .007) and 19 (p = .090). Yet for the PCL-R three-factor, hierarchical model with parcels (Cooke & Michie, 2001), the results indicated good fit, χ²(56) = 94.72, p = .001, CFI = .91, RMSEA = .07, 90% CI [.04, .09]. All correlations between the three factors and their respective loadings were significant at p < .001. For the LPSP, the two-factor model (Levenson et al., 1995) had inadequate fit, χ²(298) = 410.06, p < .001, CFI = .87, RMSEA = .05, 90% CI [.04, .06]; but the factor loading of Item 11 was nonsignificant and small (z = 1.22, p = .222). By removing LPSP Item 11 and 6 other items that have been previously removed (see Brinkley, Diamond, Magaletta, & Heigel, 2008), the respecified model demonstrated good fit, χ²(151) = 208.70, p = .001, CFI = .92, RMSEA = .05, 90% CI [.03, .06]. All correlations between LPSP factors and their respective loadings were significant at a level of p < .001. In contrast, the PPI three-factor model (Benning et al., 2005) had inadequate fit (CFI = .47, RMSEA = .33, 90% CI [.28, .38]).

Criterion Validity Across Ethnicity

Bivariate Analyses

For each ethnic group, the relationship between the PCL-R, PPI, LPSP, and external criteria was generally consistent with the existing literature (see Tables 3, 4, 5, respectively). Across ethnic groups, the PCL-R shared a modest association with LPSP total scores (r = .22-.33) and a moderate to high association with PPI total scores (r = .40-.46), whereas the PPI and LPSP total scores were highly correlated (r = .66-.70). Of note, PPI FD was negatively associated with PAI DRG for African Americans, but not for Hispanics or Caucasians. The associations across measures of psychopathy and indices of antisociality were generally consistent across groups. Last, the relationship between psychopathy scores and other external criteria were typically consistent among ethnic groups. For Hispanic offenders, but not other offenders, the Levenson Secondary scale was positively associated with the presence of a future arrest. In contrast, PCL-R total and facet scores typically shared small negative associations with general and violent arrests among Hispanics.

Table 3.

Relations Between the PCL-R Total, Facet, and External Criteria Scores.

Criteria	PCL-R Total			PCL-R Facet 1			PCL-R Facet 2			PCL-R Facet 3			PCL-R Facet 4
Criteria	H	C	AA	H	C	AA	H	C	AA	H	C	AA	H	C	AA
Antisocial
PCL-R Total	—	—	—	.71	.73	.72	.76	.75	.79	.73	.73	.70	.68	.72	.70
Factor 1	.85	.84	.86	.86	.88	.88	.87	.89	.88	.49	.43	.44	.38	.38	.39
Factor 2	.87	.85	.85	.42	.40	.38	.48	.44	.50	.79^b	.82^a	.80	.83	.87	.85
PPI Total	.41	.46	.40	.25	.30	.25	.23	.29	.30	.43	.39	.35	.30	.37	.31
FD	.22	.29	.27	.20	.27	.29	.15	.20	.24	.08	.15	.13	.17	.22	.18
IA	.33	.37	.27	.16	.20	.10	.13	.20	.16	.42	.40	.33	.25	.30	.23
Cold	.17	.18	.21	.10	.09	.11	.23	.20	.23	.18	.06	.09	.02	.16	.14
LPSP Total	.27	.33	.22	.09	.19^a	.06	.13	.20	.17	.31	.31	.24	.24	.28	.21
LPP	.27	.32	.25	.09	.22	.13	.15	.23	.23	.27	.25	.19	.25	.25	.20
LPS	.19	.25^a	.10	.06	.09^a	−.06	.06	.11	.03	.29	.32	.24	.16	.23	.13
SCID	.68	.66	.58	.36	.37	.28	.42	.35	.35	.48	.54	.48	.66	.63	.61
PAI
AGG	.35	.31^a	.17	.08	.22^a	−.03	.19	.21^a	.05	.26	.29	.19	.50	.42	.30
ANT	.14	.24^a	.18	.14	.24^a	.14	.11	.18	.17	.36	.43^a	.31	.29	.36	.26
BOR	.17	.20^a	.01	−.01	.08^a	−.09	−.01	.03	−.06	.27	.30	.19	.26	.17	.06
DRG	.12	.13	−.03	.05	.04	−.05	.00	−.11	−.16	.27	.30	.19	.06	.12^a	−.10
Other criteria
BIS 11	.20	.20	.14	.03	.05	.02	.07	.05	.04	.39	.34	.28	.18	.14	.11
BIS	−.12	−.15	−.13	−.10	−.16	−.12	−.20	−.15	−.19	−.08	.02	−.11	−.03	.11	.01
Drive	.12	.16	.13	.07	.15	.13	.06	.10	.03	.04	.11	.16	.21	.12	.10
Fun	.20	.21	.10	.05	.08	.02	.14	.10	.01	.21	.25	.22	.18	.19	.07
CATS	.23	.22^a	.00^c	.06	.06	−.05	.08	.04^a	−.09	.22	.23^a	.08	.27	.27^a	.04^c
HA	−.25	−.18	−.13	−.16	−.10	−.04^c	−.20	−.17	−.11	−.15	−.12	−.16	−.21	−.16	−.11
Arrest	−.06	.13	.10	−.08	.02	.02	−.18^b	.06	.10	.05	.08	.03	−.08	.16	.10
Vio Arrest	−.07	.08	.10	−.14	.03	.06	.02	.08	.15	−.04	.02	−.02	−.10	.13	.15^c

Note. PPI = Psychopathic Personality Inventory; PCL-R = Psychopathy Checklist–Revised; H = Hispanic; C = Caucasian; AA = African American; Factor 1 = PCL-R Factor 1; Factor 2 = PCL-R Factor 2; FD = PPI Fearless Dominance; IA = PPI Impulsive Antisociality; Cold = PPI Coldheartedness; LPSP Total = Levenson Psychopathy Total Score; LPP = Levenson Psychopathy Primary Scale; LPS = Levenson Psychopathy Secondary Scale; SCID = SCID APD Total Symptom Count; PAI = Personality Assessment Inventory; AGG = PAI Aggression; ANT = Antisocial Features; BOR = PAI Borderline Features; DRG = PAI Drug Problems; BIS 11 = BIS-11 Total; BIS = BIS Scale; Drive = BAS Drive Scale; Fun = BAS Fun; CATS = CATS Total; HA = Harm Avoidance; Arrest = Any Arrest; Vio Arrest = Any Violent Arrest.

Presence of an interaction between African Americans and Caucasians. ^bPresence of an interaction between Hispanics and Caucasians. ^cPresence of an interaction between African Americans and Hispanics.

Table 4.

Relations Between the PPI Total, Higher Order Factors, and External Criteria Scores.

Criteria	PPI Total			FD			IA			Coldheartedness
Criteria	H	C	AA	H	C	AA	H	C	AA	H	C	AA
Antisocial
PPI Total	—	—	—	.48	.59^a	.50	.86	.84^a	.82	.14^b	.32^a	.26
FD	.48	.59	.50	—	—	—	.00	.10^a	−.02	−.09^b	.11	.07
IA	.86	.84	.82	.00	.10^a	−.02	—	—	—	.01	.09^a	.00
Coldheartedness	.14^b	.32	.26	−.09	.11	.07	.01	.09	.00	—	—	—
PCL-R Total	.41	.46	.40	.22^b	.29	.27	.33	.37	.27	.17	.18	.21
Factor 1	.28	.34	.31	.21	.27	.30	.17	.22	.15	.19	.16	.19
Factor 2	.45	.45	.40	.15	.22	.18	.40	.41	.34	.13	.14	.14
LPSP Total	.69	.70	.66	−.03	.09	.03	.79	.79	.75	.13	.23^a	.12
LPP	.67	.70	.66	.07	.22	.17	.70	.69	.62	.21	.32	.25
LPS	.52	.43	.43	−.17	−.14	−.20	.70	.70	.67	−.03^b	.01^a	−.12
SCID	.43	.50	.48	.13	.21	.18	.39	.46	.44	.16	.21	.12
PAI
AGG	.61	.54	.53	.11	.19	.07	.62	.54	.54	.00	.13^a	.02
ANT	.71	.72	.66	.23	.33^a	.20	.70	.69	.67	−.08	.13^a	.02
BOR	.54^b	.35	.33^c	−.11	−.20	−.21	.74	.63	.61	−.24	−.20^a	−.32
DRG	.43	.28^a	.11^c	.01	−.02^a	−.20	.51	.39	.30	−.09	−.05^a	−.18
Other criteria
BIS 11	.52	.44	.43	−.19	−.11	−.17	.72	.65	.65	−.05	−.02	−.11
BIS	−.14	−.22	−.15	−.46	−.46	−.38	.14	.12	.15	−.25	−.41	−.36
Drive	.38	.40	.29	.37	.30	.16^c	.26	.33	.27	−.20^b	−.01	−.11
Fun	.57^b	.49^a	.31^c	.35	.35^a	.16^c	.44	.48	.32^c	−.11	−.08^a	−.20
CATS	.35^b	.13	.16	−.04	−.11	−.03	.44	.26	.25	−.07	−.11	−.16
HA	−.46	−.45^a	−.21^c	−.49	−.43^a	−.21^c	−.25	−.29^a	−.13	.00	−.09	.00
Arrest	.09	.04	−.01	.05	.02	.06	.10	.04	−.06	−.13	−.01	.05
Violent Arrest	.06	.03	.01	.14	−.01	.06	−.01	.06	−.03	.04	−.03	.04

Note. PPI = Psychopathic Personality Inventory; PCL-R = Psychopathy Checklist–Revised; H = Hispanic; C = Caucasian; AA = African American; FD = PPI Fearless Dominance; IA = PPI Impulsive Antisociality; Coldheartedness = PPI Coldheartedness; Factor 1 = PCL-R Factor 1; Factor 2 = PCL-R Factor 2; LPSP Total = Levenson Psychopathy Total Score; LPP = Levenson Psychopathy Primary Scale; LPS = Levenson Psychopathy Secondary Scale; SCID = SCID APD Total Symptom Count; PAI = Personality Assessment Inventory; AGG = PAI Aggression; ANT = Antisocial Features; BOR = PAI Borderline Features; DRG = PAI Drug Problems; BIS 11 = BIS-11 Total; BIS = BIS Scale; Drive = BAS Drive Scale; Fun = BAS Fun; CATS = CATS Total; HA = Harm Avoidance; Arrest = Any Arrest; Violent Arrest = Any Violent Arrest.

Table 5.

Relations Between the Levenson Self-Report Psychopathy Scales and External Criteria.

Criteria	Levenson Total			Levenson Primary			Levenson Secondary
Criteria	H	C	AA	H	C	AA	H	C	AA
Antisocial
LPSP Total	—	—	—	.93	.93	.93	.83	.81	.81
LPP	.93	.93	.93	—	—	—	.55	.53	.44
LPS	.83	.81	.81	.55	.53^a	.44	—	—	—
PCL-R Total	.27	.33	.22	.27	.32	.25	.19	.25^a	.10
Factor 1	.12	.22	.13	.14	.25	.20	.07	.11^a	−.02
Factor 2	.34	.35	.28	.32	.30	.24	.27	.32	.23
PPI Total	.69	.70^a	.66	.67	.70^a	.66	.52	.43	.43
FD	−.03	.09	.03	.07	.22	.17	−.17	−.14	−.20
IA	.79	.79^a	.75	.70	.69^a	.62^c	.70	.70	.67
Coldheartedness	.13	.23	.12	.21	.32	.25	−.03	.01^a	−.12
SCID	.37	.41	.35	.37	.37	.32	.26	.35	.26^c
PAI
AGG	.59	.54	.55	.53	.45	.43	.50	.42	.54
ANT	.64	.65	.61	.58	.57	.57	.54	.55^a	.45
BOR	.65	.54^a	.46^c	.49^b	.34^a	.24^c	.69	.69^a	.62
DRG	.42	.33	.22^c	.32	.22	.11^c	.44	.39	.30
Other criteria
BIS 11	.74^b	.62	.60	.59^b	.42	.39^c	.75	.75^a	.70
BIS	.14	.05	.03	.06^b	−.09	−.12	.23	.24	.24
Drive	.15^b	.33	.30^c	.19^b	.37	.33	.06	.16	.14
Fun	.38	.45	.27	.36	.36^a	.22^c	.29	.32	.26
CATS	.37^b	.16	.15^c	.34^b	.07	.02^c	.32	.25	.29
HA	−.21	−.19	−.07	−.21	−.20^a	−.05	−.15	−.12	−.06
Arrest	.13	.06	.00	.07	.06	.04	.18	.04	−.05^c
Violent Arrest	.03	.05	.01	.04	.03	.03	.01	.06	−.04

Note. PPI = Psychopathic Personality Inventory; PCL-R = Psychopathy Checklist–Revised; H = Hispanic; C = Caucasian; AA = African American; LPSP Total = Levenson Psychopathy Total Score; LPP = Levenson Psychopathy Primary Scale; LPS = Levenson Psychopathy Secondary Scale; Factor 1 = PCL-R Factor 1; Factor 2 = PCL-R Factor 2; FD = PPI Fearless Dominance; IA = PPI Impulsive Antisociality; Coldheartedness = PPI Coldheartedness; SCID = SCID APD Total Symptom Count; PAI = Personality Assessment Inventory; AGG = PAI Aggression; ANT = Antisocial Features; BOR = PAI Borderline Features; DRG = PAI Drug Problems; BIS 11 = BIS-11 Total; BIS = BIS Scale; Drive = BAS Drive Scale; Fun = BAS Fun; CATS = CATS Total; HA = Harm Avoidance; Arrest = Any Arrest; Violent Arrest = Any Violent Arrest.

Moderation Analyses

To investigate potential ethnic differences in the relationship between psychopathy and external criteria, 828 moderating effects were tested across the three ethnic groups, 12 psychopathy scales, and 23 external criteria (see the online Supplemental material for the standardized beta weights available at http://asm.sagepub.com/content/by/supplemental-data). The expected number of Type I errors (828 × 0.05) was 41.40, but a total of 98 significant psychopathy × ethnicity interactions occurred—2.37 times or 56 more interactions than expected by chance.² The most common interaction was between Caucasian and African American offenders (54%), then Hispanic and African Americans (25%), and the least frequently occurring interaction was between Caucasians and Hispanics (21%). The significant psychopathy × ethnicity interaction terms contributed very small incremental effects to the extant models (mean ΔR² = .005), and the significant unique contributions of these interactions were also small in magnitude (mean β = .09).³

PCL-R

Despite having the most scales of the psychopathy measures, the PCL-R evidenced only 23 psychopathy × ethnicity interactions—fewer than the PPI and LPSP. The number of significant moderation analyses expected by chance is 17.25. As seen in Table 3, a large proportion (i.e., 17) of these psychopathy × ethnicity interactions were observed between Caucasians and African Americans in which the relationships between PCL scores and external criteria were weaker for African Americans than Caucasians. For instance, for both CATS total and PAI Aggression scores, the relationships with Facet 1 scores were of stronger magnitude for Caucasians. Similarly, in most interactions between Hispanic and African Americans, the relationships between PCL scores and external criteria were generally weaker for African Americans. However, Facet 4 scores were negatively predictive of violent arrests among Hispanics, but positively predictive for African Americans. Only two psychopathy × ethnicity interactions were observed between Hispanics and Caucasians, with stronger relations for Caucasians.

PPI

Across the PPI Total, FD, IA, and Coldheartedness scales, 13.80 interactions were expected by chance. Nevertheless, a total of 40 significant psychopathy × ethnicity interactions were observed (see Table 4). Eight psychopathy × ethnicity interactions emerged between Hispanics and African Americans, where the relationships between PPI scores and external criteria were typically weaker for African Americans. Of the 21 interactions between Caucasian and African Americans, the relationships were generally stronger for Caucasians. However, in several instances there were stronger associations for African Americans that were theoretically unexpected in the context of psychopathy (e.g., stronger negative relations with PAI DRG and FD scores). A total of 11 psychopathy × ethnicity interactions were found between Hispanic and Caucasians; most were stronger for Caucasian offenders with the exception of CATS and PAI Borderline Features scores.

LPSP

The expected number of interactions by chance across the Levenson Total, Primary, and Secondary scales was 10.35, and yet 35 psychopathy × ethnicity interactions were observed (see Table 5). There were 15 psychopathy × ethnicity interactions between Caucasian and African Americans and 12 interactions between African American and Hispanics. As was the case for the PPI and PCL-R, weaker associations were observed between LPSP scale scores and external criteria for African Americans in comparison with other ethnic groups. A total of eight psychopathy × ethnicity moderations emerged between Hispanics and Caucasians; the relations with external criteria were stronger for Hispanics in five of eight instances.

Discussion

The current study investigated potential ethnic variability in the reliability, mean scores, and criterion-related validity in multiple psychopathy measures. We accorded particular emphasis to Hispanic offenders, including psychopathy factor structure testing, given that the implications of measuring psychopathy in this ethnic group have been substantially understudied. To our knowledge, this study is the first to explicitly investigate self-report measures of psychopathy among Hispanic offenders in comparison with Caucasian and African American offenders. Broadly, there were more similarities than differences among ethnic groups in the psychometric performance of the psychopathy measures. Hispanics did not differ in the reliability and mean scores of psychopathy measures compared with other ethnic groups. It appears that—at the manifest or observable level—the assessment of psychopathy is comparable between Hispanics and Caucasian offenders.

Differences, however, did emerge between Caucasians and African Americans, as the latter group displayed slightly higher scores. This finding is broadly consistent with the meta-analysis of Skeem et al. (2004), who reported that African Americans exhibited slightly higher scores but well within the range of the instrument’s standard error of measurement. Moreover, these mean differences do not necessarily indicate inherent differences in psychopathy, as they could be measure specific. That is, our study is limited such that differences in test scores may reflect either true variance, variance due to error, or both. Future research should build on past analyses of measurement bias (e.g., Cooke et al., 2001) using classical and modern test theory (e.g., factor and item response theory analysis) that compare Hispanic people with Caucasian and African American people.

Nevertheless, the factor structure of the three psychopathy measures was examined in the Hispanic subsample. The PCL-R three-factor model fit the Hispanic offenders, which is in keeping with the work of Cooke and Michie (2001). In contrast, the four-factor model (Hare, 2003) did not demonstrate adequate fit. Yet the PCL-R four-factor model yielded two of three acceptable fit indices, and the CFI was approaching the threshold for appropriate model fit. With respecification, the two-factor structure of the LPSP evidenced good model fit, suggesting—as others have (see Brinkley et al., 2008)—that consideration should be given to revising redundant or poor functioning items.

In comparison with the PCL-R and LPSP, the PPI three-factor structure could not be reproduced. Although controversies surrounding the PPI factor structure have been previously reported (Neumann et al., 2008; cf. Benning et al., 2003), power was low for the three-factor model, as it comprised only eight indicators (i.e., the PPI subscales). Overall, our findings offer provisional evidence that the factor structure of psychopathy measures for Hispanics is broadly similar to that in African Americans and Caucasians, although these findings will require replication in other samples, including nonforensic samples.

The moderating effect of ethnicity was examined across multiple methods of measurement. Of the 85 psychopathy × ethnicity interactions, there were 22 ethnicity moderations for the PCL-R, 39 for the PPI, and 24 for the LPSP. In consideration of the different number of scales per measure, the proportion of significant interactions was highest for the LPSP (18% of total tested interactions) and lowest for the PCL-R (7% of total tested interactions). The Primary scale of the LPSP was particularly noteworthy given its 17 moderated effects. The PPI—with 15% significant psychopathy × ethnicity analyses—may generalize slightly more across different ethnic groups in comparison with the LPSP. These differences in generalization across measures, although important and worthy of replication, do not address the competing possibility that such ethnic differences are genuine (i.e., they exist in reality) and reflect variations in the conceptualizations used to derive the PCL-R, LPSP, and PPI. That is, greater ethnic differences for a given psychopathy measure could reflect actual differences in the manifestation of the disorder rather than a bias in the measure.

Consideration of the associations with external correlates revealed a fair number of psychopathy × ethnicity interactions (i.e., 85 moderations out of 726 analyses, or 12%). These findings are fairly consistent with the work of Sullivan et al. (2006), who found that differences were evident primarily between African Americans and the other ethnic groups. Specifically, after controlling for gender, intelligence, and the site of the offender (i.e., prison vs. community drug treatment program), over three quarters (79%) of the moderating effects were observed between African Americans and the two other ethnic groups. In contrast, only 21% of the moderating effects emerged between Hispanics and Caucasians. Parallel to the reliability and mean scores, there appears to be substantial overlap in the criterion-related validity of psychopathy measures for Caucasian and Hispanic offenders.

The strength of validity coefficients is capped by the reliability of the two indices in question (see Winne & Belfry, 1982). Consequently, the differences in the criterion validity of psychopathy measures for African Americans could be partially attributed to the relatively lower levels of internal consistency in comparison with Caucasian offenders. Specifically, Cronbach’s alpha was lower for PPI Total, FD, and IA scales among African Americans. However, these differences were small in magnitude and isolated to the PPI. Other psychopathy scales demonstrated as many criterion-related ethnic differences without diminished reliability coefficients for African Americans. It is likely that differential reliabilities account for at least some of the observed ethnic differences. Future latent analyses will be necessary to fully disentangle the role of true variance and error variance.

Despite their high alpha coefficients, PPI total and subscale MIC coefficients—which are less influenced by the total number of items in a scale—were low across all three ethnic groups. In particular, Coldheartedness, a single subscale, should contain items that better reflect a unitary construct. Weak MIC values for the PPI total scale are consistent with the relative orthogonality of the FD and IA factors, and they suggest that future research should place less emphasis on the total composite score. These inadequate MIC coefficients are congruent with other findings (Neumann, Uzieblo, Crombez, & Hare, 2013), suggesting low internal consistency of the PPI factors—a necessary component of unidimensionality (Clark & Watson, 1995). A lack of unidimensionality of the subscales might also explain the poor factorial model fit for this Hispanic sample and other factor analyses of the PPI (e.g., Neumann et al., 2008).

The latent properties of psychopathy measures are important to consider in the context of the current findings. The PCL-R measurement invariance between African Americans and Caucasians (e.g., Cooke et al., 2001) provides support for the validity of the differences we found between these two groups. Because the PCL-R measures the content of psychopathy comparably between these groups, the differences can be interpreted with some confidence. This is particularly the case, as all mean score differences and the majority of criterion-related differences occurred between African Americans and Caucasians. Similarly, evidence suggests that the LPSP is structurally invariant between Hispanic and African American adolescents (Horan et al., 2015), suggesting that the differences we observed for the LPSP may be interpreted with reasonable confidence. Because PPI measurement invariance remains untested across ethnicities, our findings for differences on this measure must be interpreted with caution.

Although many moderations were reported, and a notable difference emerged in the associations between psychopathy and external criteria for African Americans, the effect sizes of the interactions were typically small. Although not dispositive, small incremental effects are common in regression models with a large number of predictors (Hunsley & Meyer, 2003). When a significant moderation effect appeared, the relationship between psychopathy and the external criterion usually presented itself in the same direction for both ethnic groups. That is, unlike Sullivan et al. (2006), opposing associations between ethnicities were generally not observed. Hence, our findings do not point to major ethnic differences in the relationship between psychopathy and other psychological or criminogenic variables, but rather a small, consistent pattern of findings of modest magnitude that fits with the extant literature (e.g., Jackson et al., 2007; Walsh, 2013). Clinically, it is promising that the most frequently used measure of psychopathy (i.e., PCL-R) yielded the fewest ethnic discrepancies.

Implications

One area of caution concerns the slightly substandard criterion-related validity for African Americans. Theoretically, this finding may suggest slight differences in the nomological network of psychopathy for African Americans in comparison with other ethnic groups. Consequently, clinicians may want to accord additional consideration to the case formulations of African American offenders who obtain high scores on psychopathy measures, including the PCL-R. Techniques that include the clustering of risk factors with psychopathy as the central or precipitating factor may be less effective if its association with other risk factors is diminished. Ultimately, formulation is conducted at the individual level, but it is also theoretically driven. Our findings suggest that the interplay between psychopathy and other criminogenic variables may differ slightly for African Americans, and clinicians may want to consider this possibility when relying on theory to facilitate their formulation.

Across the different measures of psychopathy, criterion-related validity was relatively similar between Hispanics and Caucasians. Nevertheless, our findings were consistent with the work of Walsh (2013), who reported that PCL-R scores did not significantly predict violence for Latinos. In the current study, psychopathy was approaching a significant negative relationship with criminal offending among Hispanic offenders. Granted, the predictive validity of the PCL-R vis-à-vis criminal recidivism was modest for all ethnic groups. This lack of predictive power raises concerns about incorporating the PCL-R into risk assessments for Hispanics, and is consistent with meta-analytic work suggesting that the PCL-R is slightly less accurate in its prediction of violence in samples with a higher proportion of ethnic minorities (e.g., Singh, Grann, & Fazel, 2011). This possibility should be investigated using a variety of recidivism variables and employing a longer follow-up period.

Strengths and Limitations

The current study addressed a novel research question by comparing ethnic differences in a large sample of Hispanic, Caucasian, and African American offenders using a multimethod assessment of psychopathy. Nonetheless, our large sample size was not evenly distributed among the three ethnic groups. Although the Hispanic subsample size (n = 165) was large in comparison with other studies, it precluded multiple group CFA to test factorial invariance. Hispanic offenders’ disproportionately small sample (i.e., Caucasian [n = 949], African American [n = 564]) may have affected analyses of ethnic differences in mean levels and criterion validity. Nonetheless, the power for detecting beta coefficients was extremely strong for all ethnic comparisons (i.e., Power > .99). Furthermore, if the differing sample sizes affected the number of moderations, we would expect to see the fewest number of moderations between African Americans and Hispanics (n = 729). However, this was not the case, as the least frequently occurring moderation occurred between Caucasians and Hispanics (n = 1,114). In addition, because the term “Hispanic” is an ethnonym (Martinez-Brawley & Gualda, 2011) that comprises a variety of languages and cultural norms originating from various nationalities, it is likely that this group was heterogeneous in its ethnic composition. Additionally, Hispanics, Caucasians, and African Americans were not mutually exclusive; in the present study, African American and Caucasian participants also self-identified as Hispanic or non-Hispanic. However, for statistical purposes (sizes of subsamples), we were unable to conduct analyses with a reasonable degree of power that further classified individuals (e.g., Caucasian and Hispanic vs. African American and not Hispanic). We advise for research to further parse these cultural groups.

Footnotes

Declaration of Conflicting Interests

The author(s) declared the following potential conflicts of interest with respect to the research, authorship, and/or publication of this article: Dr. Scott O. Lilienfeld is the first author of the Psychopathic Personality Inventory.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This research was supported by a grant from the National Institute of Mental Health. This research was supported by the Social Sciences and Humanities Research Council of Canada.

Notes

References

Ammons

R. B.

Ammons

C. H.

(1962). The Quick Test (QT): Provisional manual. Psychological Reports, 11, 111-161.

Barratt

E. S.

(1994). Impulsiveness and aggression. In Monahan

Steadman

H. J.

(Eds.), Violence and mental disorder: Developments in risk assessment (pp. 61-80). Chicago: University of Chicago Press.

Benning

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:10.1037/1040-3590.15.3.340

Benning

S. D.

Patrick

C. J.

Salekin

R. T.

Leistico

A. R.

(2005). Convergent and discriminant validity of psychopathy factors assessed via self-report: A comparison of three instruments. Assessment, 12, 270-289. doi:10.1177/1073191105277110

Berg

J. M.

Hecht

L. K.

Latzman

R. D.

Lilienfeld

S. O.

(2015). Examining the correlates of the coldheartedness factor of the Psychopathic Personality Inventory–Revised. Psychological Assessment, 27, 1494-1499.

Borum

Bartel

Forth

A. E.

(2006). Structured assessment of violence risk in youth: Professional manual. Lutz, FL: Psychological Assessment Resources.

Brinkley

C. A.

Diamond

P. M.

Magaletta

P. R.

Heigel

C. P.

(2008). Cross-validation of Levenson’s Psychopathy Scale in a sample of federal female inmates. Assessment, 15, 464-482. doi:10.1177/1073191108319043

Brinkley

C. A.

Schmitt

W. A.

Smith

S. S.

Newman

J. P.

(2001). Construct validation of a self-report psychopathy scale: Does Levenson’s Self-Report Psychopathy Scale measure the same constructs as Hare’s Psychopathy Checklist-Revised? Personality and Individual Differences, 31, 1021-1038. doi:10.1016/S0191-8869(00)00178-1

Camp

J. P.

Skeem

J. L.

Barchard

Lilienfeld

S. O.

Poythress

N. G.

(2013). Psychopathic predators? Getting specific about the relation between psychopathy and violence. Journal of Consulting and Clinical Psychology, 81, 467-480. doi:10.1037/a0031349

10.

Carver

C. S.

White

T. L.

(1994). Behavioral inhibition, behavioral activation, and affective responses to impending reward and punishment: The BIS/BAS Scales. Journal of Personality and Social Psychology, 67(2), 319-333. doi:10.1037/0022-3514.67.2.319

11.

Clark

L. A.

Watson

(1995). Constructing validity: Basic issues in objective scale development. Psychological Assessment, 7, 309-319. doi:10.1037/1040-3590.7.3.309

12.

Cleckley

(1941). The mask of sanity. St. Louis, MO: Mosby.

13.

Cleckley

(1976). The mask of sanity (5th ed.). St. Louis, MO: Mosby.

14.

Cohen

West

S. G.

Aiken

L. S.

(2003). Applied multiple regression/correlation analysis for the behavioral sciences (3rd ed.). Mahwah, NJ: Lawrence Erlbaum.

15.

Cooke

D. J.

Kosson

D. S.

Michie

(2001). Psychopathy and ethnicity: Structural, item, and test generalizability of the Psychopathy Checklist–Revised (PCL-R) in Caucasian and African American participants. Psychological Assessment, 13, 531-542. doi:10.1037/1040-3590.13.4.531

16.

Cooke

D. J.

Michie

(2001). Refining the construct of psychopathy: Towards a hierarchical model. Psychological Assessment, 13, 171-188. doi:10.1037/1040-3590.13.2.171

17.

Cooke

D. J.

Michie

Hart

S. D.

Clark

(2005). Searching for the pan-cultural core of psychopathic personality disorder. Personality and Individual Differences, 39, 283-295. doi:10.1016/j.paid.2005.01.004

18.

Douglas

K. S.

Nikolova

N. L.

Kelley

S. E.

Edens

J. F.

(2015). Psychopathy. In Cutler

B. L.

Zapf

P. A.

(Eds.), APA handbook of forensic psychology, Vol. 1: Individual and situational influences in criminal and civil contexts (pp. 257-323). Washington, DC: American Psychological Association. doi:10.1037/14461-009

19.

Edens

J. F.

Campbell

J. S.

Weir

J. M.

(2007). Youth psychopathy and criminal recidivism: A meta-analysis of the Psychopathy Checklist measures. Law and Human Behavior, 31, 53-75. doi:10.1007/s10979-006-9019-y

20.

Edens

J. F.

Cox

Smith

S. T.

DeMatteo

Sörman

(2015). How reliable are Psychopathy Checklist–Revised scores in Canadian criminal trials? A case law review. Psychological Assessment, 27, 447-456. doi:10.1037/pas0000048

21.

Edens

J. F.

Hart

S. D.

Johnson

D. W.

Johnson

J. K.

Olver

M. E.

(2000). Use of the Personality Assessment Inventory to assess psychopathy in offender populations. Psychological Assessment, 12, 132-139. doi:10.1037/1040-3590.12.2.132

22.

Edens

J. F.

Magyar

M. S.

Cox

(2013). Taking psychopathy measures “out of the lab” and into the legal system: Some practical concerns. In Kiehl

K. A.

Sinnott-Armstrong

W. P.

Kiehl

K. A.

Sinnott-Armstrong

W. P.

(Eds.), Handbook on psychopathy and law (pp. 250-272). New York, NY: Oxford University Press.

23.

Edens

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/a0018220

24.

Edens

J. F.

Poythress

N. G.

Watkins

M. M.

(2001). Further validation of the psychopathic personality inventory among offenders: Personality and behavioral correlates. Journal of Personality Disorders, 15, 403-415. doi:10.1521/pedi.15.5.403.19202

25.

Epstein

M. K.

Poythress

N. G.

Brandon

K. O.

(2006). The self-report psychopathy scale and passive avoidance learning: A validation study of race and gender effects. Assessment, 13, 197-207. doi:10.1177/1073191105284992

26.

First

M. B.

Gibbon

Spitzer

R. L.

Williams

J. B. W.

Benjamin

(1996). User’s guide for the structured clinical interview for DSM-IV Axis II Personality Disorders (SCID-II, Version 2.0, July 1996 Final Version). New York: Biometrics Research Department, New York State Psychiatric Institute.

27.

Forth

A. E.

Kosson

D. S.

Hare

R. D.

(2003). The Psychopathy Checklist: Youth Version. Toronto, Ontario, Canada: Multi-Health Systems.

28.

Fowles

D. C.

(1980). The three arousal model: Implications of Gray’s two-factor learning theory for heart rate, electrodermal activity, and psychopathy. Psychophysiology, 17, 87-104. doi:10.1111/j.1469-8986.1980.tb00117.x

29.

Gray

J. A.

(1987). Perspectives on anxiety and impulsivity: A commentary. Journal of Research in Personality, 21(4), 493-509. doi:10.1016/0092-6566(87)90036-5

30.

Hare

R. D.

(1991). The Hare Psychopathy Checklist–Revised. Toronto, Ontario, Canada: Multi-Health Systems.

31.

Hare

R. D.

(2003). The Hare Psychopathy Checklist–Revised (2nd ed.). Toronto, Ontario, Canada: Multi-Health Systems.

32.

Hare

R. D.

Neumann

C. S.

Widiger

T. A.

(2012). Psychopathy. In Widiger

T. A.

(Ed.), The Oxford handbook of personality disorders (pp. 478-504). New York, NY: Oxford University Press. doi:10.1093/oxfordhb/9780199735013.013.0022

33.

Hart

S. D.

Cox

D. N.

Hare

R. D.

(1995). Manual for the Psychopathy Checklist: Screening Version (PCL: SV). Toronto, Ontario, Canada: Multi-Health Systems.

34.

Hart

S. D.

Dempster

R. J.

(1997). Impulsivity and psychopathy. In Webster

C. D.

Jackson

M. A.

(Eds.), Impulsivity: Theory, assessment, and treatment (pp. 212-232). New York, NY: Guilford Press.

35.

Hart

S. D.

Storey

J. E.

(2013). Clinical and forensic issues in the assessment of psychopathy. In Otto

R. K.

Weiner

I. B.

Otto

R. K.

Weiner

I. B.

(Eds.), Handbook of psychology: Forensic psychology (Vol. 11, 2nd ed., pp. 556-578). Hoboken, NJ: John Wiley.

36.

Hawes

S. W.

Boccaccini

M. T.

Murrie

D. C.

(2013). Psychopathy and the combination of psychopathy and sexual deviance as predictors of sexual recidivism: Meta-analytic findings using the Psychopathy Checklist—Revised. Psychological Assessment, 25, 233-243. doi:10.1037/a0030391

37.

Horan

J. M.

Brown

J. L.

Jones

S. M.

Aber

J. L.

(2015). Assessing invariance across sex and race/ethnicity in measures of youth psychopathic characteristics. Psychological Assessment, 27, 657-668. doi:10.1037/pas0000043

38.

Bentler

P. M.

(1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling, 6, 1-55. doi:10.1080/10705519909540118

39.

Hunsley

Meyer

G. J.

(2003). The incremental validity of psychological testing and assessment: Conceptual, methodological, and statistical issues. Psychological Assessment, 15, 446-455. doi:10.1037/1040-3590.15.4.446

40.

Jackson

R. L.

Neumann

C. S.

Vitacco

M. J.

(2007). Impulsivity, anger, and psychopathy: The moderating effect of ethnicity. Journal of Personality Disorders, 21, 289-304.

41.

Johns

(1997). The Basic Reading Inventory (7th ed.). Dubuque, IA: Kendall/Hunt.

42.

Jones

Cauffman

Miller

J. D.

Mulvey

(2006). Investigating different factor structures of the Psychopathy Checklist: Youth Version: Confirmatory factor analytic findings. Psychological Assessment, 18, 33-48. doi:10.1037/1040-3590.18.1.33

43.

Kline

R. B.

(2005). Principles and practice of structural equation modelling (2nd ed.). New York, NY: Guilford Press.

44.

Kosson

D. S.

Smith

S. S.

Newman

J. P.

(1990). Evaluating the construct validity of psychopathy in Black and White male inmates: Three preliminary studies. Journal of Abnormal Psychology, 99, 250-259. doi:10.1037/0021-843X.99.3.250

45.

Kosson

D. S.

Steuerwald

B. L.

Forth

A. E.

Kirkhart

K. J.

(1997). A new method for assessing the interpersonal behavior of psychopathic individuals: Preliminary validation studies. Psychological Assessment, 9, 89-101.

46.

Lee

Salekin

R. T.

(2010). Psychopathy in a noninstitutional sample: Differences in primary and secondary subtypes. Personality Disorders: Theory, Research, and Treatment, 1(3), 153-169. doi:10.1037/a0019269

47.

Leistico

A. R.

Salekin

R. T.

DeCoster

Rogers

(2008). A large-scale meta-analysis relating the Hare measures of psychopathy to antisocial conduct. Law and Human Behavior, 32, 28-45. doi:10.1007/s10979-007-9096-6

48.

Levenson

M. R.

Kiehl

K. A.

Fitzpatrick

C. M.

(1995). Assessing psychopathic attributes in a noninstutionalized population. Journal of Personality and Social Psychology, 68, 151-158.

49.

Lilienfeld

S. O.

(1994). Conceptual problems in the assessment of psychopathy. Clinical Psychology Review, 14, 17-38.

50.

Lilienfeld

S. O.

Andrews

B. P.

(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_3

51.

Lilienfeld

S. O.

Fowler

K. A.

(2006). The self-report assessment of psychopathy: Problems, pitfalls, and promises. In Patrick

C. J.

(Ed.), Handbook of psychopathy (pp. 107-132). New York, NY: Guilford Press.

52.

Lilienfeld

S. O.

Widows

M. R.

(2005). Psychopathic Personality Inventory–Revised: Professional manual. Lutz, FL: Psychological Assessment Resources.

53.

Lorenz

A. R.

Newman

J. P.

(2002). Do emotion and information processing deficiencies found in Caucasian psychopaths generalize to African-American psychopaths? Personality and Individual Differences, 32, 1077-1086. doi:10.1016/S0191-8869(01)00111-8

54.

Lykken

(1995). The antisocial personalities. Hillsdale, NJ: Lawrence Erlbaum.

55.

Marcus

D. K.

Fulton

J. J.

Edens

J. F.

(2013). The two-factor model of psychopathic personality: Evidence from the Psychopathic Personality Inventory. Personality Disorders: Theory, Research, and Treatment, 4, 67-76. doi:10.1037/a0025282

56.

Marsh

H. W.

Hau

Wen

(2004). In search of golden rules: Comment on hypothesis-testing approaches to setting cutoff values for fit indexes and dangers in overgeneralizing Hu and Bentler’s (1999) findings. Structural Equation Modeling, 11, 320-341. doi:10.1207/s15328007sem1103_2

57.

Martinez-Brawley

E. E.

Gualda

(2011). Latinos in the US and Spain: Demographics, designations and political identities. European Journal of Social Work, 14, 155-175. doi:10.1080/13691451003744366

58.

McCoy

W. K.

Edens

J. F.

(2006). Do black and white youths differ in levels of psychopathic traits? A meta-analysis of the Psychopathy Checklist measures. Journal of Consulting and Clinical Psychology, 74, 386-392. doi:10.1037/0022-006X.74.2.386

59.

Miller

J. D.

Dir

Gentile

Wilson

Pryor

L. R.

Campbell

W. K.

(2010). Searching for a vulnerable dark triad: Comparing Factor 2 psychopathy, vulnerable narcissism, and borderline personality disorder. Journal of Personality, 78, 1529-1564. doi:10.1111/j.1467-6494.2010.00660.x

60.

Miller

J. D.

Lynam

D. R.

(2012). An examination of the Psychopathic Personality Inventory’s nomological network: A meta-analytic review. Personality Disorders: Theory, Research, and Treatment, 3, 305-326. doi:10.1037/a0024567

61.

Millsap

R. E.

(2007). Invariance in measurement and prediction revisited. Psychometrika, 72, 461-473. doi:10.1007/s11336-007-9039-7

62.

Moeller

F. G.

Barratt

E. S.

Dougherty

D. M.

Schmitz

J. M.

Swann

A. C.

(2001). Psychiatric aspects of impulsivity. American Journal of Psychiatry, 158, 1783-1793. doi:10.1176/appi.ajp.158.11.1783

63.

Mokros

Habermeyer

Neumann

C. S.

Schilling

Hare

R. D.

Eher

(2014). Assessment of psychopathy in Austria: Psychometric properties of the Psychopathy Checklist-Revised. European Journal of Psychological Assessment, 30, 243-250. doi:10.1027/1015-5759/a000177

64.

Mokros

Neumann

C. S.

Stadtland

Osterheider

Nedopil

Hare

R. D.

(2011). Assessing measurement invariance of PCL-R assessments from file reviews of North American and German offenders. International Journal of Law and Psychiatry, 34, 56-63. doi:10.1016/j.ijlp.2010.11.009

65.

Morey

L. C.

(1991). Personality Assessment Inventory professional manual. Odessa, FL: Psychological Assessment Resources.

66.

National Association for the Advancement of Colored People. (2014). Criminal justice fact sheet. Retrieved from http://www.naacp.org/pages/criminal-justice-fact-sheet

67.

Neumann

C. S.

Hare

R. D.

(2008). Psychopathic traits in a large community sample: Links to violence, alcohol use, and intelligence. Journal of Consulting and Clinical Psychology, 76, 893-899. doi:10.1037/0022-006X.76.5.893

68.

Neumann

C. S.

Malterer

M. B.

Newman

J. P.

(2008). Factor structure of the Psychopathic Personality Inventory (PPI): Findings from a large incarcerated sample. Psychological Assessment, 20, 169-174. doi:10.1037/1040-3590.20.2.169

69.

Neumann

C. S.

Uzieblo

Crombez

Hare

R. D.

(2013). Understanding the Psychopathic Personality Inventory (PPI) in terms of the unidimensionality, orthogonality, and construct validity of PPI-I and -II. Personality Disorders: Theory, Research, and Treatment, 4, 77-79. doi:10.1037/a0027196

70.

Olver

M. E.

Neumann

C. S.

Wong

S. P.

Hare

R. D.

(2013). The structural and predictive properties of the Psychopathy Checklist–Revised in Canadian Aboriginal and non-Aboriginal offenders. Psychological Assessment, 25, 167-179. doi:10.1037/a0029840

71.

Patrick

C. J.

(2006). Handbook of psychopathy. New York, NY: Guilford Press.

72.

Pew. (2008). One in 100: Behind bars in America. Retrieved from http://www.pewtrusts.org/en/research-and-analysis/reports/2008/02/28/one-in-100-behind-bars-in-america-2008

73.

Porter

(1996). Without conscience or without active conscience? The etiology of psychopathy revisited. Aggression and Violent Behavior, 1, 179-189.

74.

Poythress

N. G.

Lilienfeld

S. O.

Skeem

J. L.

Douglas

K. S.

Edens

J. F.

Epstein

Patrick

C. J.

(2010). Using the PCL-R to help estimate the validity of two self-report measures of psychopathy with offenders. Assessment, 17, 206-219. doi:10.1177/1073191109351715

75.

Poythress

N. G.

Skeem

J. L.

Lilienfeld

S. O.

(2006). Associations among early abuse, dissociation, and psychopathy in an offender sample. Journal of Abnormal Psychology, 115, 288-297.

76.

Preacher

K. J.

Coffman

D. L.

(2006). Computing power and minimum sample size for RMSEA [Computer software]. Retrieved from http://www.quantpsy.org/rmsea/rmsea.htm

77.

Rosseel

(2012). lavaan: An R package for structural equation modeling. Journal of Statistical Software, 48(2), 1-36.

78.

Roth

E. V.

(2006). Assessment of violence risk and psychopathy in a population of incarcerated, adolescent, Hispanic males. Dissertation Abstracts International: Section B. Sciences and Engineering, 66(10).

79.

Ruiz

M. A.

Skeem

J. L.

Poythress

N. G.

Douglas

K. S.

Lilienfeld

S. O.

(2010). Structure and correlates of the Barratt Impulsiveness Scale (BIS-11) in offenders: Implications for psychopathy and externalizing pathology. International Journal of Forensic Mental Health, 9, 237-244. doi:10.1080/14999013.2010.517258

80.

Sanders

Giolas

M. H.

(1991). Dissociation and childhood trauma in psychologically disturbed adolescents. American Journal of Psychiatry, 148, 50-54.

81.

Skeem

J. L.

Cooke

D. J.

(2010). One measure does not a construct make: Directions toward reinvigorating psychopathy research—Reply to Hare and Neumann (2010). Psychological Assessment, 22, 455-459. doi:10.1037/a0014862

82.

Skeem

J. L.

Edens

J. F.

Camp

Colwell

L. H.

(2004). Are there ethnic differences in levels of psychopathy? A meta-analysis. Law and Human Behavior, 28, 505-527.

83.

Skeem

J. L.

Mulvey

E. P.

Grisso

(2003). Applicability of traditional and revised models of psychopathy to the Psychopathy Checklist: Screening Version. Psychological Assessment, 15, 41-55. doi:10.1037/1040-3590.15.1.41

84.

Singh

J. P.

Grann

Fazel

(2011). A comparative study of violence risk assessment tools: A systematic review and metaregression analysis of 68 studies involving 25,980 participants. Clinical Psychology Review, 31, 499-513.

85.

Sullivan

E. A.

Abramowitz

C. S.

Lopez

Kosson

D. S.

(2006). Reliability and construct validity of the Psychopathy Checklist-Revised for Latino, European American, and African American male inmates. Psychological Assessment, 18, 382-392. doi:10.1037/1040-3590.18.4.382

86.

Taylor

Lang

A. R.

(2006). Psychopathy and substance use disorders. In Patrick

C. J.

(Ed.), Handbook of psychopathy (pp. 495-511). New York, NY: Guilford Press.

87.

Tellegen

(1982). Brief manual for the Multidimensional Personality Questionnaire. Unpublished manuscript, University of Minnesota, MN.

88.

Tsang

Piquero

A. R.

Cauffman

(2014). An examination of the Psychopathy Checklist: Youth Version (PCL:YV) among male adolescent offenders: An item response theory analysis. Psychological Assessment, 26, 1333-1346. doi:10.1037/a0037500

89.

Tubb

V. A.

(2002). The factor structure and psychometric properties of the Psychopathy Checklist-Revised: Data from an Hispanic federal-inmate sample. Dissertation Abstracts International: Section B. Sciences and Engineering, 62(11), 5426.

90.

U.S. Census Bureau. (2012). Law enforcement, courts, and prisons. Retrieved from http://www.census.gov/prod/2011pubs/12statab/law.pdf

91.

Vachon

D. D.

Lynam

D. R.

Loeber

Stouthamer-Loeber

(2012). Generalizing the nomological network of psychopathy across populations differing on race and conviction status. Journal of Abnormal Psychology, 121, 263-269. doi:10.1037/a0024683

92.

Vitacco

M. J.

Kosson

D. S.

(2010). Understanding psychopathy through an evaluation of interpersonal behavior: Testing the factor structure of the interpersonal measure of psychopathy in a large sample of jail detainees. Psychological Assessment, 22, 638-649. doi:10.1037/a0019780

93.

Vitacco

M. J.

Neumann

C. S.

Jackson

R. L.

(2005). Testing a four-factor model of psychopathy and its association with ethnicity, gender, intelligence, and violence. Journal of Consulting and Clinical Psychology, 73, 466-476. doi:10.1037/0022-006X.73.3.466

94.

Walsh

(2013). Psychopathy and criminal violence: The moderating effect of ethnicity. Law and Human Behavior, 37, 303-311. doi:10.1037/lhb0000017

95.

Walsh

Kosson

D. S.

(2007). Psychopathy and violent crime: A prospective study of the influence of socioeconomic status and ethnicity. Law and Human Behavior, 31, 209-229. doi:10.1007/s10979-006-9057-5

96.

Winne

P. H.

Belfry

M. J.

(1982). Interpretive problems when correcting for attenuation. Journal of Educational Measurement, 19, 125-134. doi:10.1111/j.1745-3984.1982.tb00121.x

97.

Yang

Wong

S. P.

Coid

(2010). The efficacy of violence prediction: A meta-analytic comparison of nine risk assessment tools. Psychological Bulletin, 136, 740-767. doi:10.1037/a0020473

Supplementary Material

Please find the following supplemental material available below.

For Open Access articles published under a Creative Commons License, all supplemental material carries the same license as the article it is associated with.

For non-Open Access articles published, all supplemental material carries a non-exclusive license, and permission requests for re-use of supplemental material or any part of supplemental material shall be sent directly to the copyright owner as specified in the copyright notice associated with the article.

0.00 MB

0.12 MB