© 2013 American Psychological Association 1040-3590/14/$12.00 DOI: 10.l037/a0034861

Psychological Assessment 2014. Vol. 26. No. 1. 138-147

Sadism in Sexual Offenders: Evidence for Dimensionality Frank Schilling

Andreas Mokros

Federal Evaluation Center for Violent and Sexual Offenders, Vienna, Austria

University Hospital of Psychiatry Zurich

Joachim Nitschke

Karien Weiss

Ansbach District Hospital, Ansbach, Germany

University of Klagenfurt

Reinhard Eher Federal Evaluation Center for Violent and Sexual Offenders, Vienna, Austria, and University of Ulm Recurrent and intense sexual fantasies and urges that circle around the infliction of pain or humiliation on another human being may predispose individuals toward acts of sexual aggression against nonconsenting victims. Consequently, sexual sadism is a paraphilia with particular relevance for forensic psychology and psychiatry. Using behavioral indicators derived from crime scene actions as well as clinical data, we sought in the present study to identify the latent structure of the disorder. We analyzed data from a national sample of male sexual offenders from Austria (N = 1,020). In addition to latent profile analysis, 3 conceptually different taxometric methods were applied. The results of the analyses were more in accordance with a dimensional interpretation than with a categorical distinction. That is, sadistic conduct in sexual offenses is likely an extreme form of coercion, but not a qualitatively different entity. The implications with respect to the current debate on the diagnostic criteria for sadism are discussed. Keywords: sadism, paraphilia, taxometrics, latent structure, SeSaS

Depending on the sample, between 13% and 54% of men admitted to sexual fantasies that involved elements of domination, according to a review by Leitenberg and Henning (1995). In a national telephone survey conducted in Australia, 2.2% of male respondents reported that they had practiced sadomasochistic role play in the previous year (Richters et al., 2008). In contrast to mutually consentaneous sadomasochistic role play, sexual sadism involves coercion and is directed at unwilling victims. The exertion of sexual violence against nonconsenting individuals is forensically relevant. It is estimated that about 5% of rapes involve a sadistic motivation on behalf of the perpetrator (Groth, 1979). Compared with other sexual offenders, sexually sadistic individuals may have a stronger propensity to commit further sexual offenses after release from custody (Berner, Berger, & Hill, 2003; Kingston, Seto, & Bradford, 2009; but see Hill, Habermann, Klusmann, Berner, & Briken, 2007). Consequently, sexual sadism is regarded as a relevant disorder in civil commitment proceedings under sexually violent predator laws (e.g., Levenson, 2004).

It is characteristic of these unfortunates that they suffer not only from an inferior health but also from an inferior disease. Nature has a peculiar predilection for producing such persons in abundance; natura non fecit saltus, she makes no jump, she loves transitions and even on the grand scale she keeps the world in a transitional state between idiocy and sanity. —Robert Musil, The Man Without Qualities

Sexual sadism is a paraphilia in which the infiiction of pain or the humiliation of others is experienced as sexually gratifying. Prevalence estimates of sexual sadism are scarce. According to a study by Ahlers et al. (2011), only 1 out of 363 men (0.3%) in a community sample from a metropolitan area in Germany admitted to sexually sadistic fantasies or behaviors that they regarded as problematic. Sadomasochistic fantasies seem to be more common:

This article was published Online First November 11, 2013. Andreas Mokros, Department for Forensic Psychiatry, University Hospital of Psychiatry Zurich, Zurich, Switzerland; Frank Schilling, Federal Evaluation Center for Violent and Sexual Offenders, Vienna, Austria; Karien Weiss, Department of Psychology, University of Klagenfurt, Klagenfurt, Austria; Joachim Nitschke, Forensic Psychiatric Hospital, Ansbach District Hospital, Ansbach, Germany; Reinhard Eher, Federal Evaluation Center for Violent and Sexual Offenders, Vienna, Austria, and Faculty of Medicine, University of Ulm, Ulm, Germany. Correspondence concerning this article should be addressed to Andreas Mokros, Department for Forensic Psychiatry, University Hospital of Psychiatry Zurich, Lenggstrasse 31, P.O. Box 1931, CH-8032 Zurich, Switzerland. E-mail: [email protected]

Sadism, Coercive Sexuality, and Sexual Arousal The notion of sadism is linked with the current debate on the concept of paraphilic coercive disorder. In paraphilic coercive disorder, coerciveness in sexual acts is experienced as sexually exciting, either causing the individual afflicted to force sexual activity upon others or to otherwise feel distressed by their own condition (Thornton, 2010). In a critical appraisal of the pros and cons concerning a potential diagnostic category of paraphilic co138

SADISM IN SEXUAL OFFENDERS

ercive disorder. Knight (2010) reviewed the evidence from penile plethysmography studies with rapists (e.g.. Barbaree, Seto, Serin, Amos, & Preston, 1996; Seto & Kuban, 1996) and stated that physiological arousal in response to rape stimuli was associated with sadism. Knight (2010) therefore concluded that there was not sufficient evidence to assume a distinct category of paraphilic coercive disorder. Furthermore, Knight referred to the results of studies from related fields (such as psychopathy, hypersexuality, or psychopathic sexuality) and reported that these studies (e.g., Guay, Ruscio, Knight, & Hare, 2007; Walters, Knight, & Lângström, 2011; Walters, Marcus, Edens, Knight, & Sanford, 2011) had shown dimensional latent structures, thus supporting the notion that coercive violent sexuality may have a dimensional latent structure as well. As this hypothesis does not seem to have been tested for sadism specifically yet, we sought in the current study was to address this issue. Two recent psychophysiological experiments were conducted to assess the sexual arousability of rapists (Harris, Lalumière, Seto, Rice, & Chaplin, 2012) and of sadistic men sampled from the community (Seto, Lalumière, Harris, & Chivers, 2012). The authors of these studies interpreted their findings in such a way that signs of nonconsent in a sexual eontext on the one hand and of violence or injury on the other hand would represent distinct phenomena, with the sadistic individuals showing greater sexual arousability to descriptions of sexual violence and injury than did the nonsadistie controls (Seto et al., 2012). The rapists in the study by Harris et al. (2012), however, were nearly as sexually aroused by descriptions of sexual violence as they were by descriptions of sexual coercion (without injuries). Furthermore, Sims-Knight and Guay (2011) showed in a self-report study that items pertaining to sexual coercion and items corresponding with sexual sadism loaded onto a single factor, with the two sets of items located at opposite ends of the factor. Finally, Knight (2012) presented the results from taxometric analyses based on self-report data of sexual offenders, suggesting that both items representing a preference for sexual coercion and items refiecting sexually sadistic conduct can be conceived of as belonging to a single dimension of agonistic sexuality rather than having a categorical (or taxonic) stmcture.

Assessment of Sexual Sadism Based on OffenseRelated Behavioral Criteria In a comparative study, Kingston, Seto, Firestone, and Bradford (2010) showed that behavioral indieators of sexual sadism based on crime scene actions better predicted violent (including sexual) offense recidivism than the clinical diagnosis according to the standard of the Diagnostic and Statistical Manual of Mental Disorders (DSM-IV-TR) of the American Psychiatric Association (2000). Furthermore, Yates, Hucker, and Kingston (2008; see also Healey, Lussier, & Beauregard, 2013) posited that various types of behavior assoeiated with sexual sadism would generally become apparent in the way in which a sexually sadistic offender committed his crime. A list of 18 pertinent types of behavior was developed by Marshall, Kennedy, Yates, and Serran (2002; see also Marshall & Hueker, 2006) following a survey among 15 forensicpsychiatric experts in the area. On the basis of the set of criteria put forward by Marshall et al. (2002), Nitschke, Osterheider, and Mokros (2009) derived a cu-

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mulative scale empirically: For a sample of 100 male sexual offenders from a high-security institution in Germany (50 had been clinically diagnosed as sexual sadists), 11 items fulfilled the criteria of a reliable and homogeneous Guttman scale (Guttman, 1944). These 11 items represent the items pertaining to crime scene actions that make up Part 1 of the instrument used to measure sadism in the present study (see Table 1 and the Appendix). The notion of a Guttman scale implies a deterministie ordering of items according to their difficulty levels: Persons for whom the rarest (most difficult) items are coded as being present are most likely fulfilling the criteria for all the easier (more frequent) items as well. A replication study with another sample of 105 male sexual offenders from Austria (Mokros, Schilling, Eher, & Nitsehke, 2012) corroborated the one-dimensional structure of the scale but not the deterministic properties. Together with two further applications of the 11-item set from the United States (Pflugradt & Bradley, 2011; Wilson, Pake, & Duffee, 2011), its overall sensitivity and specificity with regard to the clinical diagnosis of sexual sadism were estimated at 95% and 99%, respectively, in a meta-analysis (Nitschke, Mokros, Osterheider, & Marshall, 2012).'

The Latent Structure of Sexual Sadism The most common method to differentiate between dimensional and eategorical structures in psychopathology is to utilize taxometrie analysis procedures (see Haslam, Holland, & Kuppens, 2012, for examples). The term taxon means order. In this regard, taxometrie methods allow identification of the underlying nature of phenomena. Most taxometric methods need two or more valid indicator variables. Given its diagnostic utility for the clinical diagnosis of sadism (Nitschke et al., 2012), the 11 items coding the respondent's crime scene actions (Mokros et al., 2012; Nitschke et al., 2009) were used as indieators in the present study. In addition, biographical items derived from a clinical assessment instrument of sadism (Schilling, Ross, Pfäfflin, & Eher, 2010) were included. Both developments—the set of 11 items related to crime scene actions (Nitschke et al., 2009) and the biographical items (Schilling et al, 2010)—were derived from the expert survey by Marshall et al. (2002). Both strands of information—crime scene actions and biographical data are currently being prepared as a struetured professional judgment instrument for diagnosing sadism, the Sexual Sadism Scale (SeSaS; see the Appendix for a brief description of the items). We assumed that sexually sadistic behavior would conform to a latent dimensional structure in a large sample of male sexual offenders. We used three conceptually different taxometric procedures to analyze the latent structure of sadism as evidenced by SeSaS items: maximum eovariance (MAXCOV; Meehl & Yonce, 1996), mean above minus mean below a cut (MAMBAC; Meehl & Yonce, 1994), and latent mode factor analysis (L-Mode; Waller & Meehl, 1998). In addition, latent profile analysis (LPA; Vermunt & Magidson, 2006) was employed. ' One of the studies (Mokros et al., 2012) included in the meta-analysis by Nitschke et al. (2012) is based on a subsample (n = 105) from the present sample.

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Table 1 Agreement Among Five Raters in 20 Randomly Chosen Cases on Items of the Sexual Sadism Scale and Clinical Diagnosis Intraclass correlation 95% confidence interval bounds

Parti 1 2 3 4 5 6 7 8 9

10 11 Part 2

1 2

3

Lower

Upper

.81 .64 .79 .65 .83 .81 .59

.68

1.00 .62 .66

na .43 .48

.48

.28 .84

.91 .81 .90 .82 .92 .90 .11 na .79 .82 .70 .96

Value

Variable

Part/No.

Crime scene behavior Sexual arousal during offense(s) Power/control/dominance Torture Degradation/humiliation Mutilation (genitals) Mutilation (other body parts) Excessive physical violence Object insertion Ritualistic behavior Confinement Taking trophies/keeping records Sum score Part I (Variables 1-11) Biographical variables Planful conduct Sadistic acts outside listed offenses Arousability through sadistic acts/fantasies Clinical diagnosis: Sexual sadism"

.91 .56 .46 .56 .75

.45 .66 .47 .71 .67

.40

.36 .26 .36 .60

.76 .68 .76 .88

Note. Variables 1-11 (Part I) as well as Variable 1 (Part II) refer to behavior associated with listed offenses. " As defined by the Diagnostic and Statistical Manual for Mental Disorders (4th ed., text rev.; American Psychiatric Association, 2000).

IVlethod Participants Participants were 1,020 adult male sexual offenders who had been evaluated consecutively between 2001 and 2011 at the Federal Evaluation Center for Violent and Sexual Offenders (FECVSO) of the Austrian Prison Service. In Austria, about 60% of all sexual offenders are referred to the evaluation center for mental health and risk assessment. For the present study, we included all male participants assessed at the FECVSO who were at least 18 years old at the time of the assessment and who had been convicted of a sexual offense (such as rape, sexual offenses against children, or sexual homicide). For a subgroup of 36 individuals, the legal definition of their index offense was not that of a sexual crime per se (e.g., homicide, assault, or property crime). For purposes of comparison, we note that according to the 2011 annual federal Austrian prosecution statistics (Statistik Austria, 2012), there were 171 cases in total in which adult male offenders had been convicted and sentenced to a prison term (without immediate parole) for sexual offenses like rape, sexual assault, or sexual abuse of children. At the time of the assessment, the offenders were on average 40 years old (SD = 12 years; range = 18-72 years; median = 39 years). At the time of the judicial verdict that led to their current incarceration, the men were on average 38 years old (SD = 1 2 years; range = 15-71 years; median = 37 years). Most of the offenders were White.

Design and Procedure The data for the present study were extracted from the case files of the offenders, including the judicial verdicts, the prison files, and the criminal records as well as written reports of prior mental health assessments (if available). Furthermore, the forensic assessment reports produced through the FECVSO were available for screening. At the FECVSO, a comprehensive forensic assessment is routinely perfonned by at least three experienced forensic psychologists or psychiatrists. The aim of the assessment is to facilitate correctional planning and treatment. The management of the FECVSO assures confidentiality with regard to scientific analyses of the data. For this reason, the present data were anonymized prior to statistical analysis. The evaluation was in accordance with the legal and ethical requirements of the Austrian Ministry of Justice and in accordance with the Austrian Data Protection Act. The SeSaS items were scored dichotomously (with a numerical value of 1 if an item was present and 0 otherwise). A brief description of the items with guidelines for coding is provided in the Appendix. The use of dichotomous indicators within taxometric analysis is controversial, however. First, the covariance estimates derived from dichotomous indicators may be unstable (Ruscio, 2000). Second, the use of dichotomous indicators can lead to erroneous conclusions of taxonicity unless the number of indicators is large (Maraun, Slaney, & Goddyn, 2003). It has been recommended that instead of dichotomous indicators, composite indices obtained through summing dichotomous indicators be employed (Ruscio, 2000). Therefore, composite indices based on the SeSaS were used for the taxometric and latent profile analyses.

SADISM IN SEXUAL OFFENDERS

We carried out a check of interrater agreement for the items of the SeSaS and for the diagnosis of sexual sadism according to DSM-IV-TR using a selection of 20 cases from the sample. Table 1 summarizes the results of the interrater reliability check. Adopting the rules of thumb published by Landis and Koch (1977),^ the level of interrater agreement for the individual items was moderate (.40 < K :£ .60) for two SeSaS items dedved from the offense(s) as such (keeping trophies and excessive violence) as well as for the three biographical items (planful conduct, sadistic acts outside the listed offenses, and general arousability through sadistic acts). For the remaining offense-related items, the interrater agreement ranged from substantial levels (.60 < K :£ .80) for five items to excellent levels (K > .80) for another four items. Similarly, the observer agreement with regard to a clinical diagnosis of sexual sadism according to DSM-IV-TR cdteda was substantial. Finally, the observer agreement in terms of the sum score on the 11 offense-related vadables can be regarded as excellent (intraclass correlation [ICC] = .91). Data analysis. The SeSaS data were first subjected to a confirmatory factor analysis (CFA) in order to assess whether the items would conform to a homogeneous latent construct. Prior to the present study, only the cdme-scene-related items of the SeSaS, not the additional biographical items, had been subjected to factor analysis (Mokros et al., 2012). Given the categorical nature of the items, their interrelations were estimated using a matdx of tetrachodc correlations. That is, correlations were estimated under the assumption that the dichotomous item codings were instances of underlying continuous, normally distdbuted traits. We used a robust weighted least squares method within the program Mplus, Version 6.12 for Mac (Muthén & Muthén, 2011), for the estimation of the factor solution. In taxometric research, it is paramount to test whether divergent methods yield consistent results about the latent' structure of the construct in question (Ruscio, Walters, Marcus, & Kaczetow, 2010). Therefore, we relied on three conceptually different methods; First, one method from Meehl's coherent cut kinetics family of algodthms; MAXCOV (Meehl & Yonce, 1996). MAXCOV compares the covadance between two indicator vadables across the range of a third indicator. Given a taxonic structure, the covariance changes markedly at the boundaries between homogeneous types. If a sample of men and women was ordered according to body height, for example, the correlation between two traits like voice pitch and nonverbal sensitivity would be more pronounced in a subgroup of intermediate height that compdses both women and men (and thus affords variation of these traits). At the lower and upper extremes, predominantly smaller women or taller men would be found, respectively. Any covadance of voice pitch and nonverbal sensitivity would vanish within these homogeneous subgroups (example taken from Ruscio, Haslam, & Ruscio, 2006, p. 125). Second, MAMBAC (Meehl & Yonce, 1994) analyses were carded out. MAMBAC is based on the notion that if a taxonic structure was underlying the data at hand, then there would be a steep increase at some point in the mean difference between two complementary groups on an indicator variable when moving along the range of a second indicator vadable. Third, an L-Mode factor analysis was conducted. In L-Mode, the emergence of local maxima within the factor score distdbution can be indicative of a taxonic stmcture (Steinley & McDonald,

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2007) even though the emergence of more than one mode is not a sufficient sign of taxonic structure (Ruscio & Walters, 2009; Steinley & McDonald, 2007). In other words, bumps to the left or dght from the peak of a factor score distdbution can be indicative of an underlying categodcal structure. For all three taxometdc methods aforementioned, the compadson curve fit index (CCFI; Ruscio et al., 2010) from 1,000 bootstrap samples was used to decide between a likely dimensional or taxonic structure. The CCFI gauges the relative fit between the empidcal data and simulated data that reflects either a dimensional or a taxonic stmcture but otherwise keep the distdbution properties of the actual data. CCFI values below .50 are regarded as indicative of a dimensional stmcture; CCFI values above .50 point toward a taxonic stmcture (Ruscio et al., 2010). CCFI values around .50 are inconclusive. To avoid ambiguity, Ruscio et al. (2010; cf. Ruscio, Ruscio, & Carney, 2011) recommended CCFI thresholds of lower than .45 (for likely dimensional stmcture) and higher than .55 (for likely taxonic stmcture) based on an extensive simulation study. Instead of a stopping mle or absolute fit index, the CCFI is a general measure of relative fit indicating whether the data at hand are more commensurate with a dimensional (CCH < .45) or categodcal stmcture (CCFI > .55). The taxometdc analyses were performed with the program TaxProg, Version 201307-23 (Ruscio, 2013; cf. Ruscio, 2010), within R, Version 2.15.0 for Mac (R Development Core Team, 2012). For both the estimation of model parameters and for the bootstrap simulation of categodcal compadson data, the putative taxon was approximated through the subgroup of individuals in the sample who had a clinical diagnosis of sadism. Finally, and in addition to the narrow-sense taxometdc analyses descdbed previously (i.e., methods such as MAXCOV, MAMBAC, and L-Mode developed by Paul Meehl and his colleagues), an LPA (Vermunt & Magidson, 2006) was performed. LPA allows for the differential testing of unitary versus multiple-group solutions, with conditional independence of indicators serving as the cdtedon for within-group homogeneity. For the LPA, we specified 5,000 random sets of starting values and 1,000 optimizations of the Expectation Maximizadon algodthm within Mplus, Version 6.11 for Mac (Muthén & Muthén, 2011). The estimator option chosen was the robust maximum likelihood method. The maximum number of iterations within the initial stage was set to 20. A modified likelihood ratio test (Lo, Mendell, & Rubin, 2001) allowed us to establish whether a model with two latent classes yielded a better fit than a simpler unitary model.

Results Confirmatory Factor Analysis Inspection of the matdx of tetrachodc intercorrelations of the SeSaS items (the 11 offense-related items plus the three biographical vadables) revealed that three items (sexual arousal dudng the ^ Landis and Koch (1977) provided these benchmarks for weighted kappa coefficients. Weighted kappa and the two-way random/single measure variant of the ICC used herein are equivalent (Fleiss & Cohen, 1973) if the number of cases being rated is sufficiently high. Therefore, the use of the benchmarks provided by Landis and Koch (1977) seems appropdate within the present context.

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offense[s], inflicting humiliation, and keeping trophies) correlated negatively with other items of the scale to a significant degree. Consequently, these three items were omitted from further analyses. Recoding these variables was not an option because the three items had been expected to correlate positively with the remaining items for conceptual reasons. Previous tests of the item intercorrelations had been based on smaller samples than the present one. Previous analyses of the SeSaS, albeit limited to the offenserelated items (without the biographical items), supported the notion of a one-dimensional scale (Mokros et al, 2012; Nitschke et al., 2009). However, the previous results of a single factor underlying the items does not necessarily translate to the full SeSaS instmment, especially given the conceptual difference between items coding for crime scene actions and items referring to biographical data. In fact, a one-dimensional CFA model based on the 11 remaining items fit the data to a moderate degree only: x^(22) = 118.60, p < .001, comparative fit index (CFI) = .88, root-mean-square error of approximation (RMSEA) = .04 (95% confidence interval [CI] for the RMSEA coefficient: [.03, .05]). The RMSEA coefficient as an absolute measure of fit indicated a good match between the model specifications and the empirical data—RMSEA values of .07 and below are considered as signifying model fit (Steiger, 2007). The incremental fit index (CEI), however, fell short of the commonly accepted level of above .95 (Hu & Bentler, 1999). Given the suboptimal fit of the one-dimensional solution, the items were split into three sets. This was done because all latent stmcture procedures employed (MAXCOV, L-Mode, and LPA, with the exception of MAMBAC) necessitate use of at least three indicator variables. Eirst, the biographical items were kept separate. Second, the offense-related items were divided evenly based on their factor loadings from the one-factor solution in descending order. As a result, the three items sets comprised the OffenseRelated Items 2,6, 7, and 10 (Eactor 1), the Offense-Related Items 3, 5, 8, and 9 (Factor 2), and the three biographical items (Eactor 3; see Table 1 for item labels). A CFA in which the variables were set to load on three latent factors accordingly yielded an improved overall model fit: ^2(41) = 107.12, p < .001, CFI = .90, RMSEA = .04 (95% CI for the RMSEA coefficient: [.03, .05]). According to a chi-square difference test, the three-factor model fit the data significantly better than the one-dimensional solution: Ax^(3) = 13.98, p .003. Consequently, the three-factor model was used as the frame of reference for the present study. Although the CEI still fell short of recommendations for good model fit (> .95; West, Taylor, & Wu, 2012), it would comply with an earlier cutoff (.90; Hoyle, 1995). The value of .95 has been criticized as being overly conservative (Marsh, Hau, & Wen, 2004). In the three-factor model, the standardized loadings of the variables ranged between .25 (sadistic acts beyond the listed offenses) and .93 (mutilation of nongenital body parts), all p < .001 (two-sided). The average standardized loading was .67. The 11 items were combined through summation into three composite indicators according to the three factors from the CEA, given the risk of biased results in taxometric studies with dichotomous indicators (Maraun et al., 2003; Ruscio, 2000). The first composite was obtained through summing the variables exertion of power or domination, mutilation of nongenital body parts, exertion of excessive violence, and confinement of the victim. The second

composite comprised the items torture of the victim, mutilafion of victim's genitalia, insertion of objects into victim's bodily orifices, and ritualistic sequencing of the offense(s). The third composite consisted of the three biographical variables not immediately associated with crime scene actions, namely, planful conduct, sadistic behavior outside listed offenses, and general arousability by sadistic acts. The means (SDs) on the three composite indices were 0.71 (0.77), 0.41 (0.63), and 0.25 (0.50), respectively. The ranges were 0 - 4 (for Composite Indices 1 and 2) and 0-3 (for Composite Index 3). Each of the three composite indices was significantly correlated (at p < .001, two-sided) with the clinical diagnosis of sadism. The corresponding polychoric correlation coefficients were .62, .69, and .66 for Composites 1-3, respectively.

Taxometric Analyses For the taxometric analyses, we estimated the putative taxon through the individuals in the sample who were diagnosed as sexual sadists according to DSM-IV-TR criteria (5%, n = 51). The validities (expressed through the mean difference between taxonmembers and nonmembers in standard-deviation units, or Cohen's d) were 1.47, 2.00, and 1.81 for the Composite Indicators 1-3, respectively. The skewness statistics of the three composite scores were 0.81 (Composite 1), 1.64 (Composite 2), and 1.96 (Composite 3). In both the putative taxon and complement groups, the correlation coefficients between the composite indicators were below .30 (see Table 2). Therefore, Meehl's (1995) recommendations for taxometric analysis of indicator validities of at least d = 1.25 and within-group correlations of at most r = .30 were fulfilled (cf Beauchaine, 2007; Ruscio et al., 2006). The indicator validities express the size of the mean differences between individuals assigned to the presumable taxon class (based on a diagnosis of sadism) and the remainder of the sample (the complement group) in terms of the three composite scores used as indicators. In the present study, the indicator validities were large enough to warrant their use in taxometric analyses. Furthermore, the correlations between the composite variables within the subgroups (the presumable taxon of diagnosed sadists vs. the complement group without such a diagnosis) were considerably lower than the corresponding correlations in the sample as a whole. This means that the taxon and complement groups were likely homogeneous. Maximum covariance. As can be seen from Eigure 1, the resampling analysis indicated a dimensional structure for the three composites under the MAXCOV framework. The overlap of the empirical data was higher with the simulated dimensional data (top right panel of Figure 1) than with the simulated categorical data (top left panel of Figure 1). The resulting CCFI

Table 2 Indicator Correlations in the Full Sample as Well as in the Complement and Taxon Groups

Composite variable Composite 1 Composite 2

Full sample iN == 1,020)

Complement (n = 969)

Taxon (n = 51)

2

3

2

3

2

3

.22

.26 .30

.14

.20 .20

-.19 —

-.23 .07

SADISM IN SEXUAL OFFENDERS

MAXCOV (CCFl = .44) Categorical Comparison t)aU

Dimensional Comparison Data

MAMBAC(CCFI = .41) Categorical Comparison Data

200

41»

60O

800

Dimensional Comparison Data

1000

200

50 Cub

400

600

800 1000

50 Cub

L-Mode (CCFI = .49) Categorical Comparison Data 0.6

Dimensional Comparison Data

Discussion In the present study, we sought to explore the latent structure of sadism in sexual offenders, as measured primarily through behavioral indicators derived from crime scene actions. Using three different narrow-sense taxometric techniques as well as LPA, the underlying structure of sadism was found to be more likely dimensional than categorical: The average CCFI value from the three taxometric procedures (MAXCOV, MAMBAC, and L-Mode) was .44 and thus within the margin regarded as indicative of dimensionality (CCFI < .45). One of the three individual CCFI values (pertaining to the L-Mode analysis) was within the range that renders the result inconclusive (i.e., .45 ^ CCFI < .55), however. On the other hand, a fourth and conceptually different statistical technique (LPA) also supported the conclusion of dimensionality: The attempt to identify a putatively sadistic homogeneous subgroup within the sample using LPA did not lead to a significant improvement in model fit compared with the baseline model of a unitary group solution. Consequently, it seems unlikely that sadistic sexual offenders would represent a distinct type. Rather, sexually sadistic conduct during the commission of offenses appears to be an exaggerated form of sexual violence, which is located at the upper range of a continuum of sexual aggression. This outcome is in accordance with previous studies from the area, such as the finding of a single-factor solution for both items pertaining to sexual violence (i.e., sadism) and items pertaining to sexual coercion (Sims-Knight & Guay, 2011). More specifically, the present results mirror the findings of Knight (2012), who reponed that items from a self-report questionnaire on various kinds of sexually aggressive and sa-

1 2-^'

} ^^_

DO

- 1 0

1 2

3

Factor Scores

4

5

ilarly, the overlap of the empirical data was higher with the simulated data generated to follow a dimensional distribution (Figure 1, center, right panel) than with the data simulating a categorical distribution (Figure 1, center, left panel). The CCFI value was .41. Latent mode factor analysis. The results from the L-Mode analysis were ambiguous. The factor score distribution did not have any distinctive local maxima to the right of zero on the abscissa. The absence of local maxima on the right-hand side of the abscissa can be interpreted as supporting a dimensional interpretation of the latent structure. However, at a CCFI coefficient of .49, the resampling analyses did not yield a conclusive match with data generated to mimic dimensional distributions (see Figure 1, bottom right) or categorical distributions (Figure 1, bottom left). Latent profile analysis. In contrast to the previous three types of analysis (MAXCOV, MAMBAC, and L-Mode), LPA capitalizes on stochastic independence between indicator variables within homogeneous groups. Although LPA identified two differently sized groups (n = 227 vs. n = 793), these groups were not distinct. The model fit of the solution with two latent classes was not better than for a unitary (single-class) solution. In a modified likelihood ratio test (Lo et al., 2001), the difference in model fit did not reach statistical significance (test statistic = 1192.33, p = .15). This means that the addition of a latent class did not improve the fit compared with a unitary solution.

0.6

A

0.2

0.4

0.6

ci -

143

- 1 0

1 2

3

4

5

FiKlor ScoiBS

Figure 1. Results of maximum covariance (MAXCOV; top), mean above minus mean below a cut (MAMBAC; center), and latent mode factor (L-Mode; bottom) analyses. Bold lines refer to the empirical data. Fine solid lines refer to the minimum and maximum from 1,000 samples of comparison data. Light gray shading denotes the areas ± 1 standard deviation around the means of the comparison data. Left panel: Categorical comparison data. Right panel: Dimensional comparison data. CCFI = comparison curve fit index.

was .44—a value in the range indicative of a dimensional interpretation (i.e., CCFI < .45). Both the dimensional data (on the right of Figure 1) and the categorical data (on the left-hand side of Figure 1 ) were generated based on the three composite indicators keeping distributions and overall correlations constant (Ruscio et al., 2010). However, the dimensional and categorical comparison data differ in terms of parameters such as the ratio of variances between taxon and complement groups, within-group correlations, and standardized between-group differences (i.e., indicator validities). Mean above minus mean below a cut. The outcome of the MAMBAC analyses corroborated the MAXCOV results. Sim-

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distic conduct were also in line with a dimensional (nontaxonic) interpretation. Moreover, O'Meara, Davies, and Hammond (2011) recently reported that sadistic impulsivity (in the sense of sadistic personality disorder as listed in DSM-III-R; American Psychiatric Association, 1987) could be conceived of as a dimensional personality trait. Finally, Walters, Marcus, and their colleagues (2011) observed that psychopathic personality traits can be regarded as a dimensional construct in the domain of coercive sexuality as well, just as others found for psychopathic personality in general (e.g., Guay et al., 2007). Psychopathy and sexual sadism (as measured with the SeSaS) are different, yet correlated clinical constructs (Mokros, Osterheider, Hueker, & Nitschke, 2011). The outcome that sadism among sexual offenders is most likely a dimensional construct does not render a clinical diagnosis of sadism meaningless. In fact, a recent review of taxometric studies indicated that the majority of psychopathological phenomena were dimensional, not categorical (Haslam et al., 2012). Therefore, the items of the SeSaS can be conceived of as measuring the intensity of sadism (Marshall, Hueker, Nitschke, & Mokros, in press). In this regard, the items can serve as a structured professional judgment instrument for diagnosing sexual sadism. The result that sadism among sexual offenders is most likely dimensional has implications for etiological considerations as well. While taxa are presumed to evolve from specific and discrete mechanisms (Meehl, 1977, 1992; cf Haslam et al., 2012), dimensional phenomena are more likely due to the interplay of several additive factors. Specific etiological assumptions on the development of sexual sadism such as the notion of sensory preconditioning through sexually traumatic experienees in childhood (MaeCulloch, Gray, & Watt, 2000) have not been tested yet. The present results make it more plausible, though, that such a particular process would be only one aspect among several precursors, as expressed in the integrative theory of sexual offending by Marshall and Barbaree (1990), for example. Finally, the finding that sadism is presumably distributed continuously among sexual offenders could help explaining the divergent results on the agreement across diagnosticians concerning the clinical diagnosis of sexual sadism (Nitschke et al., 2012). Given the previous finding that researehers tend to adopt idiosyncratic criteria rather than stringently adhering to the DSM criteria (Marshall & Kennedy, 2003), it is conceivable that different clinicians apply divergent implicit thresholds before assigning the label of sadism. Such diversity in diagnosis is disconcerting, particularly given the ramifications of falsepositive and false-negative decisions (Levenson, 2004). Understanding sadism as a dimensional construct and using behavioral indicators to gauge its intensity (Marshall et al., in press; cf. Kingston et al., 2010) may help to ameliorate the agreement of diagnosticians in the long run.

Limitations Unlike in previous analyses of items from the SeSaS scale (Mokros et a l , 2012; Nitschke et al., 2009), three of the offense-related items had to be omitted because these items

correlated negatively with some of the remaining items. This is surprising since the data used in one of these earlier studies (Mokros et al., 2012) were a subsample of 105 cases from the present sample. One pertinent explanation could be that—judging from the clinical diagnosis—the prevalence of sexually sadistic individuals was far lower in the present study (5%) than in the previous studies (17% in Mokros et al., 2012, and 50% in Nitschke et al., 2009). Albeit more ecologically valid and in accordance with prior studies (e.g., Groth, 1979), the comparatively low prevalence in the current study possibly affected the scale properties: For instance, the item of the offender feeling sexually aroused through the crime scene actions was present for virtually all sexual offenders but incurred a negative correlation with rare items such as the mutilation of the victim's genitals since both items co-occurred only in the small subgroup of severely sadistic individuals. Furthermore, upon including three biographical items (offense planning, sadistic acts outside listed offenses, and general arousability through sadistic acts), one-dimensionality of the construct could not be ascertained since the incremental fit index fell below the acceptable margin. On the other hand, the notion of different latent variables underlying the items opened up the possibility of running taxometric analyses that necessitate use of three or more indicator variables. Given the dichotomous nature of the SeSaS items, the items were summed to form composite scores based on the three latent factors. Although this procedure is not uncritical for the reason that splitting up one instrument runs the risk of creating nearly parallel and thus redundant composite variables (Ruscio et al., 2006), it seems unlikely that this problem applied to the present study because the indicator correlations in the full sample were moderate (see Table 2). Nevertheless, future taxometric studies of sadism should strive for including conceptually more diverse indicators such as physiological (Harenski, Thomton, Harenski, Decety, & Kiehl, 2012; Harris et al, 2012; Seto et al., 2012) and self-report data (Knight, 2012; Sims-Knight & Guay, 2011). In order to ascertain statistical power, those conducting taxometric studies should aim for sample sizes of at least 300 subjects (Meehl, 1995) while also making sure that the presumable base rate of the taxon in question is not too low, lest the taxon go unnoticed (Ruscio et al., 2006). The presumably low base rate of sexual sadists in the sample (5% judging from the DSM-IV-TR diagnosis) should not be problematic since there would have been enough members of a putative taxon in absolute number due to the large sample size (> 1,000). According to Ruscio et al. (2011), the absolute and the relative taxon size should be at least 50 cases and 5%, respectively. The present data narrowly meet these margins. Finally, one should acknowledge that some offenders in the sample (n = 36) had been convicted of another kind of offense than a sexual one (such as assault, homicide, or property crime). Nevertheless, offenses that do not fulfill the legal definition of a sexual crime can still be due to a sexual motivation on the part of the perpetrator. A famous example of this circumstance is von Krafft-Ebing's (1886) description of an offender who cut women's braids in the street. In a similar case from the early 20th century in Berlin, the perpetrator was sentenced for theft, assault, and insult even though he was clearly acting out his fetishism (Friedlaender, 1913).

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contributions of sexual activity, nonconsent, and violence with injury. Archives of Sexual Behavior, 41, 221-229. doi:10.1007/sl0508-012All in all, the extant literature as well as the present findings 9940-8 point in the direction of sexual sadism as a dimensional conHaslam, N., Holland, E., & Kuppens, P. (2012). Categories versus dimenstruct. This view is in accordance with the current conceptualsions in personality and psyehopathology: A quantitative review of ization of DSM-5 that clearly emphasizes a dimensional intertaxometric research. Psychological Medicine, 42, 903-920. doi:10.1017/ S0O33291711001966 pretation through the differentiation between paraphilia and Healey, J., Lussier, P., & Beauregard, E. (2013). Sexual sadism in the paraphilic disorder (American Psychiatric Association, 2013). context of rape and sexual homicide: An examination of crime scene It follows from this that the potential diagnostic category of indicators. 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Appendix Brief Item Descriptions of the Sexual Sadism Scale (SeSaS) Part 1 : Analysis of crime scene actions (coding based on official files about previous convictions or current charges) 1. Sexual arousal during the crime scene behaviors: Subject admitted to feeling sexually aroused, or the victim statements, witness statements, or crime scene details such as trace evidence make this apparent. 2. Exertion of power, control, or dominance: Exaggerated degree of intimidation toward the victim by the perpetrator. Markedly higher level of power exerted than necessary for a sexual offence. 3. Torturing the victim: Perpetrator used methods expected to result in the infliction of pain (physical torture) or actions (including verbal behavior) expected to elicit extreme fear (psychological torture). 4. Degrading or humiliating behavior directed toward the victim: Subject exhibited behavior (verbal or physical) expected to evoke feelings of shame or disgust in the victim. 5. Mutilation of sexual areas of the victim's body: Mutilation of vulva/vagina, penis, or breasts in terms of (partial) amputation or disfiguration through use of considerable physical force, either pre- or postmortem. 6. Mutilation of other parts of the victim's body: As in Item 5 (above) if body parts other than vulva/vagina, penis, or breasts were involved. 7. Excessive physical violence: Level of violence exceeded the level necessary to control the victim. 8. Insertion of objects into the victim's bodily orifices: Attempted or accomplished insertion of an object into the vagina, anus, or urethra of a victim, either pre- or postmortem. 9. Ritualistic behavior: Carrying out peculiar actions, sequences, patterns, or circumstances resembling a screenplay was important to the perpetrator during commission of the offense. 10. Confinement of the victim (spatial coercion): Subject deprived the victim of his or her liberty beyond the immediate time and situation of the sexual activity. 11. Taking trophies: Taking personal (identifiable) objects belonging to the victim for him- or herself. Taking parts of the victim's body (such as hair) or recordings (photographs, video, audio) arc subsumed. Part 2: Biographical variables 1. Planful conduct: The subject planned the offense in advance (coding also based on official files about previous convictions or current charges only.) 2. Indications of sadistic acts in the past beyond listed offenses: Positive information of cruelty to human beings or to animals. 3. Arousability through sadistic fantasies or acts: Self-reported or observer-rated indication of pleasurable arousal on the part of the subject in response to witnessing acts of torture, humiliation, fear, or hurting of others. Note. The items of Part I refer to crime scene behavior and were tested empirically by Nitschke et al. (2009) and by Mokros et al. (2012). The items of Part 2, referred to as biographical items, do not exclusively deal with crime scene actions. The items of Part 2 were contributed by Schilling et al. (2010). A published manual of the SeSaS with detailed item descriptions is currently in preparation.

Received January 25, 2013 Revision received July 26, 2013 Accepted September 23, 2013 •

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