Testing Factorial Structure and Validity of the PCL:SV in Lithuanian Prison Population

J Psychopathol Behav Assess (2010) 32:363 372 DOI 10.1007/s10862-009-9176-7 Testing Factorial Structure and Validity of the PCL:SV in Lithuanian Prison Population Rita Žukauskienė & Alfredas Laurinavičius & Ilona Čėsnienė Published online: 11 December 2009 # Springer Science+Business Media, LLC 2009 Abstract This study examined the factorial structure and validity of the Hare Psychopathy Checklist: Screening Version (PCL:SV) in a European forensic context. A random sample of 257 criminal offenders from the Lithuanian prison population were administered the PCL: SV (Hart et al. 1995). The pattern of validity coefficients in this sample was comparable to other North American and non-north American samples. Several theoretical factorial structures for the PCL:SV were tested and compared. The two-factor model was not supported, while three- and fourfactor models provided an acceptable fit to Lithuanian data. The four-factor model showed significantly better fit compared to the two-factor model. Correlations between PCL:SV factors and demographic variables confirm construct validity. However in the four-factor model, when controlling for correlations of the remaining three factors, only the Antisocial factor significantly correlated with variables related to criminal activity. It was concluded that the overall results of the PCL:SV in a male sample of Lithuanian offenders support cross-cultural generalizability of the construct of psychopathy as measured by the PCL:SV. Keywords Assessment. Validation. Psychopathy. PCL:SV The construct of psychopathy describes a personality pathology characterized by distinctive deficits in affect (i.e., callousness, shallow affect, lack of empathy, and guilt), R. Žukauskienė (*) : A. Laurinavičius : I. Čėsnienė Department of Psychology, Mykolas Romeris University, Ateities str. 20, LT-08303 Vilnius, Lithuania e-mail: rzukausk@mruni.eu URL: http://rzukausk.home.mruni.lt/ interpersonal relations (i.e., parasitic use of others, manipulativeness, dominance, grandiosity), and behavior (i.e., impulsiveness, aggression, risk-taking behavior) (Douglas et al. 2005). From the adult males in prison diagnosed with antisocial personality disorder it is thought that about 15 25% are psychopathic (Hare 1991). Psychopathic criminals begin their criminal careers earlier than non-psychopaths, have more varied victims and show criminal versatility in that they commit a greater variety of crimes (Hare 1998), and their crimes tend to be particularly coldblooded (Cornell et al. 1996). Psychopathic offenders commit more violent crimes, and recidivate at higher rates than non-psychopathic offenders (e.g., Hare 1991, 2003). They are less likely to show a decline in criminal activity after age 40 (Hart et al. 1988; Serin et al. 1990). Hare (1991, 2003) has provided influential measurement procedures for psychopathy, particularly for criminal and forensic settings. The most popular, reliable, and valid measure of psychopathy is the Psychopathy Checklist- Revised (PCL-R) (Hare 1998, 2003). The Psychopathy Checklist: Screening Version (PCL:SV) is derived directly from the PCL-R for use in forensic and civil settings (Hart et al. 1995). The two instruments (i.e., the PCL-R and the PCL:SV) are highly correlated (r=0.80; Hart et al. 1995) and measure the same construct (Cooke et al. 2004; Guy and Douglas 2006), have shown predictive validity for future violent and criminal behavior (Douglas et al. 2005; Fabian 2008; Hare et al. 2000; Hart 1998; Hemphill 2007; Leistico et al. 2008), poor institutional adjustment (Hobson et al. 2000), and reduced treatment efficacy (Richards et al. 2003). Despite empirical findings and advances in the measurement of psychopathy, there are few clear findings regarding the structural model of the construct of psychopathy. The PCL-R measures the two traditional factors of psychopathy:

364 J Psychopathol Behav Assess (2010) 32:363 372 Hare factor 1 measures interpersonal and affective features of the disorder and Hare factor 2 measures socially deviant conduct (Hare 2003). In their work with the PCL:SV using confirmatory factor analysis, Hart et al. (1995) have found that the 12 items in the PCL:SV loaded on two parts: interpersonal style and antisocial lifestyle. However, factor analytic research of the PCL-R and the screening version of the instrument (PCL:SV, Hart et al. 1995) have not always produced results completely consistent with this two-factor model (Kosson et al. 1990). For example, Cooke and Michie (2001) reanalyzed the PCL-R normative data and argued that psychopathy could be viewed as a superordinate, higher-order construct with three correlated factors. These authors found a three-factor (Affective, Interpersonal, and Behavioral) model more successful and superior for understanding the construct of psychopathy. More recently a two-factor, four-facet hierarchical model of the PCL-R was reported in the second edition of the PCL-R manual after conducting a large sample multigroup analysis (Bolt et al. 2004; Hare 2003). The PCL:SV manual proposes a two factor structure with factors labeled as Part 1 and Part 2 (Hart et al. 1995). Recent studies, however, tend to support a four-factor model of psychopathy using different PCL-based instruments (Jackson et al. 2007; Salekin et al. 2006; Flores-Mendoza et al. 2008). Hare (2003) argues that four factors are needed to describe the structure of psychopathy, representing interpersonal, affective, behavioral, and anti-social features of the disorder. The theoretical foundation of this model is that behavioral characteristics, particularly antisocial and violent behavior, are necessary requirements (Andrade 2008). Recent studies also support this four-factor solution for both the PCL-R (Hare and Neumann 2008; Neumann et al. 2005) and the PCL:SV (Vitacco et al. 2005). Walters et al. (2007) performed a taxometric analysis of the PCL:SV (Hart et al. 1995) on a group of 2,250 male and female forensic/ psychiatric patients and jail/prison inmates. The four PCL: SV facet scores (Interpersonal, Affective, Impulsive Lifestyle, Antisocial Behavior) served as indicators in this study. The results show evidence of a dimensional structure of the PCL:SV in the full sample as well as in all eight subsamples (men, women, whites, blacks, hospital patients, jail/prison inmates, file review with an interview, file review without an interview). Authors concluded that scores on the PCL:SV differ quantitatively as points on a dimension (high vs. low psychopathy) rather than partitioning into qualitatively distinct categories of behavior (psychopath vs. nonpsychopath). In short, there is some dispute regarding the factor structure of the PCL-R. However, highly intercorrelated factors displayed in all of the factor models of the PCL-R indicate a general underlying dimension of psychopathy (Bolt et al. 2004). Additionally, there are important theoretical and practical questions regarding the appropriateness of applying the construct, as currently defined and measured, to discrete populations, such as diverse ethnic and cultural groups (e.g., Cooke and Michie 1999; Cooke et al. 2001; Nicholls and Petrila 2005; Rogers 2000; Skeem et al. 2004). The PCL-R was developed and evaluated using North American samples. This is of potential concern as the manifestations of personality disorders are likely to vary across cultures (Cooke and Michie 1999). The PCL-R has a strong body of clinical and experimental research supporting its validity as a measure of the construct of psychopathy, since numerous attempts have been undertaken for PCL-R evaluation in other cultures. For example, selected samples of English offenders (Hare 2003) demonstrated lower PCL-R scores than North American samples. Despite this emerging body of literature, there has been less research using the PCL:SV than the PCL-R. Recently, the PCL:SV has been submitted to different forms of validation and reliability verification in some countries outside of North America, e.g., in France (Toupin et al. 2008), Sweden (Strand and Belfrage 2005; Douglas et al. 2005), Germany (Huchzermeier et al. 2006), and England (Doyle et al. 2002). The psychometric properties of the PCL:SV, as well as its psychological and behavioral correlates, appear to be much the same in one country as in another. For example, the Toupin et al. (2008) study using the PCL:SV in a youth sample in France shows good internal consistency of scales. Correlations between the PCL:SV and related indices (antisocial personality disorder; frequency and range of delinquent activities; frequency and range of use of psychoactive substances, etc.) occurred much as expected. Doyle et al. (2002) explored the validity of the PCL:SV, VRAG and the Historical subscale of the HCR-20. Their findings suggest that the PCL:SV was the most robust predictor of in-patient violence in a British medium security forensic unit, where the Social deviance subscale of PCL:SV was the best predictor of serious violence. Douglas et al. (2005) evaluated the structural reliability, construct-related validity, and cultural validity generalization of the PCL:SV in a sample of more than 560 male and female Swedish forensic psychiatric treatment patients, forensic evaluation patients, and criminal offenders. Structural reliability was excellent for most indices. The structural reliability and pattern of validity coefficients were comparable in these Swedish samples to other non-north American samples. The Huchzermeier et al. (2006) study examined the predictive validity of the German translation of the Psychopathy Checklist:Screening Version (PCL:SV) for negative events during the course of the prison sentence of German inmates. Thus, discussion regarding the factor structure of the PCL-R generally centers on data sets obtained from developed western countries. However, to our knowledge,

J Psychopathol Behav Assess (2010) 32:363 372 365 there are no known studies that have been conducted on the assessment of the reliability and construct validity of the PCL:SV (also as of the PCL-R) in the Eastern European context. Given the potential implications that lack of invariant structure and item functioning has for the use and interpretation of the PCL:SV, it is important to understand whether the scale performs differently as a function of culture. To address this question, we sought to test the structural equivalence and validity of the PCL:SV in a new cultural setting. The main objectives of this study were: 1. to investigate the fit of several alternative factor models in PCL:SV data collected from a Lithuanian criminal offender sample using confirmatory factor analysis (CFA). 2. to investigate values and to conduct reliability analysis of the PCL:SV parts, factors and total scores, and associations between PCL:SV psychopathy scores and demographic variables in a Lithuanian prisoner sample. Methods Sample The sample was recruited from 12 correctional facilities operating in Lithuania. Two hundred and ninety four (294 or 6.3%) out of a total of 4670 incarcerated males were randomly seleceted for this study. Random sampling was based on random numbers generated by SPSS 16.0. Data was collected by 20 PCL:SV-trained psychologists who worked at the time of the assessment in those 12 institutions. A small number (n=38) of correctional inmates (13.2% of the randomly selected sample) were not evaluated because of refusal to participate or due to transfer to other institutions in the course of data collection. In total, the study sample consisted of 257 male correctional inmates e.g., 86.8% from the initial sample in which 257 (100%) were real-life (in vivo) assessments. The mean age of the offenders in the study was 32.39 (SD= 9.60; range=19 67). Other descriptive information on the 257 participants used for statistical analyses is presented in Table 1. A total of 21.7% of the evaluated offenders had a history of psychiatric treatment (diagnoses not specified), 19.1% of the offenders had a convicted parent (one or both), and 78.9% of the evaluated offenders committed one or more offenses under the influence of alcohol or drugs. Measures and Procedures The Psychopathy Checklist: Screening Version (PCL:SV; Hart et al. 1995) is a 12-item measure derived from the 20-item PCL-R. The PCL:SV consists of two rationally derived, 6-item parts. Part 1 corresponds to Factor 1 of the PCL-R (Affective and Interpersonal Deficits), and Part 2 corresponds to Factor 2 of the PCL-R (Antisocial and Unstable Behavior). Part 1 consists of the following items: superficial, grandiose, deceitful, lacks remorse, lacks empathy, and doesn t accept responsibility. Part 2 consists of the following items: impulsive, poor behavioral controls, lacks goals, irresponsible, adolescent antisocial behavior, and adult antisocial behavior. Each item is rated on a 3-point scale, ranging from 0 (not present) to1(somewhat present) orto2(present). This gives the instrument a range of 0 24 points, where the cutoff for psychopathy is set to 18. Total scores equal to or above 18 on the PCL:SV are considered indicative of psychopathy (Hart et al. 1995). The PCL:SV (Hart et al. 1995) was scored for each inmate using file review and an individual interview. All offenders were subjected to real-life assessments (in vivo) with the PCL:SV; information from files and records was supplemented with an interview ranging from 1 to 2 h. Interviewers also gathered demographic and offense related data, some of which is presented in Table 1. Training All study personnel was trained by the authors of this study. Most of the training was carried out by AL, who was trained by Robert Hare. The remainder of the training was provided by authors RZ, who created the authorized version of the Lithuanian PCL:SV, and IC. These trainers/authors have substantial experience with the original PCL:SV and the concept of psychopathy and applied it, mutatis mutandis, to the Lithuanian raters and ultimately, the evaluees. Training consisted of didactic sessions, case examples, and related discussions. Data Analyses SPSS.16 and Mplus 5 (Muthén and Muthén 2007) software was used for the analysis. The PCL:SV item ratings are based on an ordinal rather than an interval scale. They reflect whether each trait is absent, possibly present, or definitely expressed. According to Neumann et al. (2007) it is more advantageous to treat PCL:SV items in factor analysis not as continuous but as ordinal variables. In processing this type of data, Mplus provides a robust weighted least square procedure for parameter estimation. For comparison of two-factor and four-factor models, an adjusted chi-square difference test for that type of estimation was performed. Correlations and partial correlations between PCL:SV factors and demographic data were computed using actual factor scores.

366 J Psychopathol Behav Assess (2010) 32:363 372 Table 1 Demographic characteristics of Lithuanian sample of male offenders N Minimum Maximum Mean SD Age 257 19 67 32.38 9.60 Years of education (total) 254 4 17 10.31 2.38 Number of previous convictions 256 0 14 4.51 2.89 Number of violent offences 244 0 10 1.34 1.29 Age at time of first contact with police 252 5 62 17.76 7.04 Age at time of first conviction 253 14 62 20.62 6.44 Time spent in correctional institutions (total in months) 245 1 409 70.09 74.47 Number of stable jobs ( 6 months) 253 0 3 1.49 1.21 Results Descriptive and Reliability Information of the PCL:SV Scales Means, standard deviations, mean inter-item correlations and Cronbach s alphas were computed for the whole scale and for scales of two-factor and four-factor solutions. Mean PCL:SV Total score was 14.59 (SD=5.12; range from 2 to 24). A total of 34.6% of the assessed offenders reached the cut-off of 18. Table 2 presents descriptive and reliability statistics of the PCL:SV scales. In a two-factor model, Part 2 had higher mean and smaller SD compared to Part 1. In a four-factor model, the highest mean M=4.45 and smallest SD=1.49 was for the Antisocial scale. Table 2 shows that the structural reliability estimates of mean inter-item correlation and alpha were acceptable for the PCL:SV Total score, Part 1, and Part 2. For all four factors in the four-factor model of the PCL:SV, alpha coefficients varied from 0.62 to 0.85. Reliability was lowest for the fourth factor/facet. Lowest reliabilities for the fourth factor were also found in the Swedish sample (Douglas et al. 2005). Scales of Part 1 (Interpersonal and Affective) had higher alpha coefficients compared to Part 2 (Lifestyle and Antisocial) scales in cases of both, two-factor and fourfactor solutions. In this study, the lowest alpha coefficient of 0.62 and mean inter-item correlation coefficient of 0.36 were for the Antisocial scale, the highest for the Affective. Similar alpha coefficients have been reported by other investigators (Hart et al. 1995; Wogan and MacKenzie 2007; Cornell et al. 1996; Rogers et al. 2000). Construct Validity of the PCL:SV The construct validity of the PCL:SV was examined by calculating Pearson correlations between the PCL:SV actual scores and demographic characteristics theoretically associated with the construct of psychopathy. Some demographic characteristics such as number of convictions, total time spent in correctional institutions can theoretically be age-dependent. In order to exclude possible impact of age on correlations between the PCL:SV scores and other external variables, partial correlations between these variables and the PCL:SV were computed controlling for age. As factors are intercorrelated in order to evaluate their independent relationship with demographic variables, partial correlations were computed controlling the remaining three factors. All types of correlations are presented in Table 3. Results presented in Table 3 show that, as expected, most of the demographic variables were correlated with the PCL: SV Total score and factors. The PCL:SV scores negatively correlated with age at time of first contact with police, age at time of first conviction, years of education and positively with history of psychiatric treatment. Parent s conviction was positively correlated with the Antisocial factor, offending under the influence of alcohol/drugs Table 2 Values and reliability analysis of the PCL:SV parts, factors and total scores M mean, SD standard deviation, MIC mean inter-item correlation PCL:SV M SD Range MIC Alpha PCL:SV Total score (12 items) 14.59 5.12 2-24.33.85 PCL:SV Part 1 (Interpersonal/Affective, 6 items) 6.76 3.03 0-12.42.81 PCL:SV Part 2 (Lifestyle/Antisocial, 6 items) 7.82 2.79 1-12.37.78 Factor 1 (Interpersonal, 3 items) 2.99 1.75 0-6.46.72 Factor 2 (Affective, 3 items) 3.80 1.77 0-6.62.83 Factor 3 (Lifestyle, 3 items) 3.68 1.59 0-6.39.66 Factor 4 (Antisocial, 3 items) 4.45 1.49 0-6.36.62

J Psychopathol Behav Assess (2010) 32:363 372 367 Table 3 Correlations and partial correlations between four-factor PCL:SV scores and demographic data No. Demographic characteristics PCL:SV Total score PCL:SV factors Interpersonal Affective Lifestyle Antisocial 1. Years of education (total) -.16*.05 -.11 -.22** -.27** (.14) (.01) (-.07) (-.21**) 2. Age at time of first contact with police -.31** -.05 -.27** -.29** -.44** (.10) (-.13) (.07) (-.37**) 3. Age at time of first conviction -.23** -.01 -.17** -.23** -.34** (.12) (-.07) (.02) (-.28**) 4. Parent's (stepparent's) conviction.06 -.08.04.06.18* (.07) (-.05) (.02) (-.10) 5. History of psychiatric treatment.13*.03.07.17**.16** (.01) (.05) (-.07) (-.06) 6. Offense while intoxicated.07 -.08.05.14*.13* (.13) (-.05) (-.05) (-.07) Partial correlations (controlling for age) 7. Number of convictions.26**.09.25**.26**.24** (-.05) (.13) (.07) (.09) 8. Number of violent offenses.22**.04.18**.19**.31** (-.07) (.09) (-.02) (.22**) 9. Total time spent in correctional institutions.20**.03.19**.19**.26** (-.08) (.07) (.01) (.18**) 10. Number of stable jobs (>6 months) -.20** -.03 -.19** -.18* -.24** (-.07) (-.08) (-.00) (-.18**) Demographic variables No. 4-6 are dichotomous with values 0 for characteristic not present and 1 for present. Partial correlations of PCL:SV factors with demographic variables after controlling for the remaining three PCL:SV factors are given in brackets **p<.01, * p<.05, two-tailed significance correlated with Lifestyle and Antisocial factors. Most of the significant correlations were found between demographic characteristics and Lifestyle and Antisocial factors. Age at the time of first contact with police and age at the time of first conviction were negatively correlated with the Affective factor showing the importance of emotional factors in the genesis of criminality. No significant correlations were found between demographic data and the Interpersonal factor of psychopathy. Partial correlations presented in Table 3 show associations between the PCL:SV Total score and number of convictions, number of violent offenses, total time spent in correctional institutions and number of stable jobs. These correlations were obtained after eliminating the influence of age and they show that psychopathy plays an important role in an individual s psychosocial adjustment through adulthood, at all ages. Higher PCL:SV scores are associated with more convictions and more violent offenses, number of years spent in correctional institutions and inability to keep a steady job when released. Once again, no significant associations were found between the Interpersonal factor and number of convictions, number of violent offenses, total time spent in correctional institutions, and number of stable employments. As expected, the number of significant partial correlations between a given PCL:SV factor and a demographic variable was smaller after controlling for the remaining three factors. The Antisocial factor was negatively correlated with age at the time of first contact with police, age at the time of first conviction, total number of years of education and number of stable jobs. The Antisocial factor positively correlated with number of violent offenses and total time spent in correctional institutions. Control of the remaining three factors eliminated significant correlations of the first three factors with demographic variables. Testing the Factorial Structure of the PCL:SV Confirmatory Factor Analyses (CFA) were conducted in order to compare the fit of the two-, three- and four-factor models of psychopathy to the Lithuanian sample. Only complete assessment data of 247 offenders was used for the CFA. When evaluating CFA results, we followed the recommendations of Hu and Bentler (1999), who suggest

368 J Psychopathol Behav Assess (2010) 32:363 372 that at least two indices should be used to determine goodness of model fit. In this study, the standardized rootmean-square residual (SRMR) and two incremental fit indices were considered: the comparative fit index (CFI) and the Tucker Lewis index (TLI). The SRMR is an index of the average discrepancy between model-estimated statistics and observed sample statistics. Incremental fit indices compare the model to a baseline model in which covariances among all the variables are assumed to be zero. Traditionally, a good model fit is indicated when CFI and TLI are 0.90 or above, whereas more recent recommendations are 0.95 or more (Hu and Bentler 1999). SRMR indicates good model fit when its values are 0.08 or lower. In our study, the CFA two-factor model demonstrated an unsatisfactory model fit: CFI=0.89, TLI=0.92, SRMR= 0.09. In four-factor and three-factor models, indices showed acceptable model fit. For the four-factor model, CFI=0.94, TLI=0.95, SRMR=0.08. For three-factor model, indices appear to be slightly better: CFI=0.97, TLI=0.97, SRMR= 0.06. Factorial structure and factor loadings of the fourfactor solution are presented in Fig. 1. Figure 1 displays standardized parameters. All factor loadings and correlations were significant (p<0.001). Factor loadings for different factors varied from 0.65 to 0.91. Particularly good at assessing their latent variables were items which have the largest factor loadings. These are Deceitful (0.81) for latent variable Interpersonal, Lacks empathy (0.91) for Affective, Irresponsible (0.77) for Lifestyle and Poor behavioral controls (0.82) for Antisocial factor. The lowest factor loadings were for the latent variable Antisocial. Correlations between latent variables varied from 0.45 to 0.99. Weakest correlations were between latent variable Antisocial and two variables of Part 1: Interpersonal (r= 0.45) and Affective (r=0.58). However, the association between the latent variables Antisocial and Lifestyle was extraordinarily strong (r=0.99), revealing that in the fourfactor model, behavioral factors are inseparable. Factorial structure and factor loadings of three-factor solution is presented in Fig. 2. In the three-factor solution, all factor loadings and correlations were also significant (p<0.001). Factor loadings varied from 0.59 to 0.89, and correlations between factors varied from 0.64 to 0.82. There was no possibility to compare the three-factor and the four-factor models directly because the models are not nested. However, a comparison of nested two- and fourfactor models was carried out. Since data is treated as ordinal, the usual chi-square difference test cannot be used. In this case, Mplus provides a robust chi-square difference test where the degrees of freedom are estimated according to a formula given in the Mplus Technical Appendices. The results show that the four-factor model fits significantly better to Lithuanian data than two-factor model (Δχ 2 = 54.673, Δdf=4, p<0.0001). Discussion Assessment scales are often used in populations that differ from those on which the instrument was developed. Crosscultural use of measures without investigation into the their structure and metric equivalence can pose potential problems. Several studies have already confirmed the validity of the PCL:SV psychopathy construct across cultures and ethnic groups (Sullivan and Kosson 2006). In the present study, some findings from North American samples were replicated, whereas other results point to possible cultural differences in the Lithuanian prison population. The PCL: Fig. 1 Confirmatory factor analysis results for the four-factor PCL:SV model of psychopathy (standardized parameters) superficial.76.72 impulsive grandiose.72 Interpersonal.65 Lifestyle.66 lack goals deceitful lack remorse.81.86.66.83.45.99.77.82 irrespons. poor behav. control lack empathy not accept respons..91.84 Affective.58 Antisocial.65.65 adol. antisoc. adult antisoc.

J Psychopathol Behav Assess (2010) 32:363 372 369 Fig. 2 Confirmatory factor analysis results for the three-factor PCL:SV model of psychopathy (standardized parameters) superficial grandiose.76.75 Interpersonal deceitful lack remorse.79.76.66.82.64 Lifestyle.59.83.71 impulsive lack goals lack empathy.89 Affective irrespons. not accept respons..84 SV mean total score of 14.59 (SD=5,12) in the Lithuanian offender sample was close to the means reported by Hart et al. (1995) for North American prison inmates, which range from 12.97 (SD=4.92) to 15.77 (SD = 4.34). In the Wogan and MacKenzie (2007) study, the PCL:SV mean Total score in three North American medium security prison samples was 15.12 (SD=3.89). The PCL:SV mean Total score of 14.88 (SD=6.07) in a Swedish correctional institution sample (Douglas et al. 2005) also resembles Lithuanian results. Additionally, Part 2 scores were higher than Part 1 scores, which is not surprising in a samples of offenders. Using the cutoff point of 18, the prevalence of psychopathy in the Lithuanian prison population sample was 34.6%. This result is very similar to findings presented in the PCL:SV Manual (e.g., prevalence of psychopathy was 30.2% in a forensic non-psychiatric sample) (Hart et al. 1995). In a recent review by Sullivan and Kosson (2006), the prevalence of psychopathy among prison inmates ranged from 15% to 38% in studies from different countries. Psychometric properties of the PCL:SV in the Lithuanian prison population appear to be as good as in studies conducted in other cultures. The internal consistency of the PCL:SV and its scales is similar to that found by other studies and follows the same pattern of higher alpha coefficients for Part 1 (Interpersonal/Affective) (Cornell et al. 1996; Douglas et al. 2005; Hart et al. 1995; Rogers et al. 2000; Wogan and MacKenzie 2007). According to the authors of the PCL:SV symptoms related to Part 1 are naturally more cohesive or their evaluation is more affected by a halo effect which increases internal consistency. On the other hand, Part 2 items are less cohesive but have slightly higher inter-rater reliability (Hart et al. 1995). Confirmatory factor analysis revealed that Lithuanian PCL:SV data disconfirms the two-factor model, whereas the three- and four-factor models of psychopathy proved to be an acceptable fit. Additionally, the adjusted chi-square difference test showed that the four-factor model was significantly better compared to the two-factor model. The results complement the growing amount of scientific research disconfirming the earliest factor structure proposed by the authors of PCL-based instruments.when comparing the non-rejected models, we see that the three-factor model indices are slightly better than those of the four-factor model. This could be due to the relatively weak factor loadings of latent variable Antisocial. When data of the Lithuanian prison population is compared with findings in the North American psychiatric sample (Jackson et al. 2007), the item Adult Antisocial Behavior is relatively of less value in discriminating individuals on the latent Antisocial factor (0.65 vs. 0.93). The variance of this item in a population of offenders is likely smaller than variance in a psychiatric patient sample. This makes the Adult Antisocial Behavior item relatively less informative in a population of offenders compared to other populations. Relatively low factor loadings of Adult Antisocial Behavior and Adolescent Antisocial Behavior items suggest that the specificity of the PCL:SV decreases when applying it to a population of offenders. Extremely strong correlation was found between latent variables Antisocial and Lifestyle in the four-factor model. This is not surprising, as the sample consists of incarcerated male offenders. Most of the variance in the Antisocial factor is explained by variance of the Poor Behavioral Controls item, which in this sample can be coherent with items from the Lifestyle factor (Impulsive, Lacks Goals, Irresponsible). For comparison: in the non-criminal North American psychiatric sample, where the highest loading was from item Adult Antisocial Behavior, correlation

370 J Psychopathol Behav Assess (2010) 32:363 372 between Antisocial and Lifestyle factors was 0.77 (Jackson et al. 2007). Psychopathy, as conceptualized by authors of the PCLbased assessment instruments and confirmed by numerous studies, is associated with certain demographic characteristics. Higher rates of psychopathy are associated with lower socioeconomic status, lower level of education, early criminal activity, psychiatric treatment, substance abuse, criminal versatility, socioeconomic status, years of education, and use of instrumental aggression (for review, see Hare 2003). Correlations between the PCL:SV and demographic variables occurred much as expected and are theoretically consistent with the construct of psychopathy as measured by the PCL: SV. Offenders with higher PCL:SV Total scores were less educated, have a history of less stable employment, their contacts with police started at an earlier age, they were more often referred for psychiatric treatment, they have a greater number of convictions and violent offenses, and have spent more time in correctional institutions. Analysis of correlations of separate PCL:SV factors and demographic variables revealed that there were no significant correlations between demographic data and the Interpersonal factor. The same results were found in a study of prisoners in England and Wales using the PCL-R (Roberts and Coid 2007). Results show that the only factor not related to demographic data and offense related information was the Interpersonal factor. This can be due mainly to the nature of the demographic and offense related data (information about interpersonal style isn t documented in offenders files). As the psychopathy factors are highly correlated with each other, partial correlations between separate factors and demographic data were calculated after controlling the remaining three factors. Results show that only the Antisocial factor is correlated with demographic variables after removing the effects of the remaining three PCL:SV factors. Although the variables are postdictive, results are in line with a study where the predictive validity of the PCL:SV was examined (Walters et al. 2008). The research of Walters et al. (2008) shows that the Antisocial factor achieves incremental validity above and beyond the remaining three factors, but the first three factors generally fail to achieve incremental validity relative to the Antisocial factor. Likewise, our study has shown that only the Antisocial factor has the independent ability to explain variation of different demographic variables closely related to criminality. The role of the Antisocial factor in the concept of psychopathy remains the subject of continuous debate. The authors of PCL-based instruments insist on the four-factor psychopathy model where the Antisocial factor is part of the psychopathy construct. Cooke et al. (2007) uphold the view that the Antisocial factor is not a component but rather a consequence of psychopathy. In our study, both three- and four-factor models were supported. Some problems concerning the Antisocial factor appeared in the sample of Lithuanian offenders. The Antisocial factor had the highest mean, the lowest variation and reliability coefficients. In CFA, the Antisocial factor had the smallest factor loadings and correlated extremely strongly with the Lifestyle factor. On the other hand, the Antisocial factor was the only factor which had an independent correlation with demographic variables traditionally associated with psychopathy. Therefore, elimination of antisocial items from the PCL:SV lowers its validity as a risk assessment tool and may reduce its utility in the criminal justice system (Blackburn 2007). Limitations and Future Research Although the results of the PCL:SV in a male sample of Lithuanian offenders support the cross-cultural generalizability of the psychopathy construct as measured by the PCL:SV, the study has its limitations. Data reflecting interrater reliability was not collected in this study. Thus, there is no possibility to determine how well the PCL:SV protects the evaluation process from a rater s subjectivity in the Lithuanian context. The authors are aware of some weaknesses in the construct validity analysis. Demographic data and PCL:SV ratings were not collected independently, demographic data was used by evaluators to make their own decisions during the evaluation process. Thus, our study cannot be accepted as a strict confirmation of the convergent validity of the PCL:SV. On the other hand, obtained correlations with demographic- and criminalityrelated variables are consistent with a significant amount of research confirming the association between measures of psychopathy, criminality, substance abuse, and level of education (Hare 1991). Psychometric characteristics of the PCL:SV appear to be good for continuing adaptation of the instrument for everyday use in the correctional system of Lithuania. The authors are in the process of collecting offense-related data of evaluated prisoners in order to analyze the predictive validity of the PCL:SV. Acknowledgments We thank Robert D. Hare, Ronald Roesch and Craig S. Neumann for their advice and assistance. This study was supported by the Prison Department under the Ministry of Justice of the Republic of Lithuania. References Andrade, J. T. (2008). The inclusion of antisocial behavior in the construct of psychopathy: a review of the research. Aggression and Violent Behavior, 13, 328 335. Blackburn, R. (2007). Personality disorder and psychopathy: conceptual and empirical integration. Psychology, Crime and Law, 13 (1), 7 18.

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