Abstract
There is a growing body of research demonstrating that the therapeutic alliance (TA) affects outcomes among specialized forensic populations, including sexual offenders. Despite this consensus, researchers continue to question whether higher levels of psychopathic traits are conducive to the formation of a therapeutic relationship for high-risk sexual offenders. Thus, the current study adds to the literature by examining the relationship between the TA and levels of psychopathy among a sample of incarcerated sexual offenders participating in sexual offender treatment. Overall, we found no significant relationships between Psychopathy Checklist–Revised (PCL-R) scores and the Working Alliance Inventory (WAI) for either client or therapist ratings. However, when we excluded those offenders who were participating in aftercare, a significant negative relationship was found between client ratings of the Bonds subscale and PCL-R total scores. Next, after controlling for risk and group status (aftercare/non-aftercare), we found no significant differences between either client or therapist total WAI scores when compared by level of psychopathy as measured by the PCL-R (low, >20; moderate, 20-30; and high, >30). Furthermore, when Factor 1 and Factor 2 scores of the PCL-R were examined individually, neither factor significantly predicted either client or therapist total WAI score after controlling for risk and group status. Findings are discussed as they pertain to the treatment of sexual offenders with elevated levels of psychopathic traits.
The client–therapist relationship, also referred to as the therapeutic alliance (TA) or working alliance, is defined by the feelings, attitudes, and perceptions that the therapist and client experience toward one another (Bordin, 1979). Specifically, the TA is focused on how the therapist and client work together in relation to the agreed upon goals of the treatment, the tasks of treatment, and the bond between therapist and client (Bordin, 1979). Numerous studies have demonstrated a positive relationship between the nature of the client–therapist relationship and client outcomes regardless of specific treatment interventions (Horvath & Bedi, 2002; Lambert & Barley, 2001; Norcross & Lambert, 2006). The therapeutic relationship accounts for approximately 25% to 30% of the variance in therapy outcomes (Lambert & Barley, 2001). Furthermore, the TA has now been shown to be significant to treatment outcomes among both noncriminal justice involved (e.g., Westen, Novotny, & Thompson-Brenner, 2004) and criminal justice involved populations (Blasko, Friedmann, Rhodes, & Taxman, 2015; Polaschek & Ross, 2010; Skeem, Eno Louden, Polaschek, & Camp, 2007; Tatman & Love, 2010), including individuals enrolled in sexual-offender-specific treatment (Blasko & Jeglic, 2016; DeSorcy, Olver, & Wormith, 2016). Some researchers, however, debate whether certain types of high-risk offenders, such as those with elevated levels of psychopathy, are able to truly form a TA (Cleckley, 1976; Harris & Rice, 2006; Olver & Wong, 2009; S. C. P. Wong & Hare, 2005). This debate stems from the question of whether characteristics defining psychopathic individuals, such as manipulative behaviors, lack of empathy, and interpersonal deficits (Thompson, Ramos, & Willett, 2014), inhibit the ability to form a real alliance between therapist and client. Thus, there are doubts and concerns about whether findings regarding the importance of the TA in the treatment of sexual offenders can be extended to those with psychopathic characteristics (Beech, Fisher, & Beckett, 1998; Blasko & Jeglic, 2016; DeSorcy et al., 2016; Marshall, 2005; Marshall & Serran, 2004; Marshall, Serran, Fernandez, et al., 2003; Marshall, Serran, Moulden, et al., 2003).
Psychopathy
Psychopathy is a classification applied to individuals who demonstrate specific personality and behavioral traits and characteristics, such as impulsivity, superficial charm, callousness, and guiltlessness (Cleckley, 1976; Hare, 2003). Although not recognized as a clinical disorder in the Diagnostic and Statistical Manual of Mental Disorders (5th ed.; DSM-5; American Psychiatric Association, 2013), psychopathy is an accepted construct within the field of psychology when applied to adults (Strickland, Drislane, Lucy, Kreuger, & Patrick, 2013).
To better understand psychopathy as a construct, Karpman (1946) proposed a two-factor model of psychopathy comprised of a Primary factor and a Secondary factor. This model is currently considered the most popular conceptualization of psychopathy (Looman, Abracen, Serin, & Marquis, 2005) and has been empirically demonstrated using the Psychopathy Checklist–Revised (PCL-R; Hare, 1991). The two-factor model of the PCL-R labels the traits associated with the Primary factor (Karpman, 1946) as Factor 1 (Hare, 1991) and the traits associated with the Secondary factor (Karpman, 1946) as Factor 2 (Hare, 1991). Factor 1 traits are comprised of interpersonal characteristics (e.g., glibness, grandiose sense of self-worth, manipulative) and affective characteristics (e.g., remorselessness, lack of empathy, failure to accept responsibility). Furthermore, Factor 1 is correlated with narcissistic personality disorder, social potency, low stress reaction, and low suicide risk. In contrast, Factor 2 traits are comprised of lifestyle characteristics (e.g., impulsivity, need for stimulation, irresponsibility) and antisocial characteristics (e.g., poor behavioral control, juvenile delinquency, criminal versatility). In addition, Factor 2 correlates with antisocial personality disorder, social deviance, sensation seeking, and a high risk of suicide (Hare, 2003). Although there is a clear overlap between the two factors within the construct of psychopathy, research has demonstrated only a .5 correlation between the two factors using the PCL-R (Hare, 1991, 2003). Thus, it is possible for individuals demonstrating elevated levels of psychopathy to score substantially higher on one factor or the other. The low-to-moderate correlation between the factors, and the range in presentation of psychopathic characteristics associated with each factor, suggests that psychopathic individuals should not be treated as homogeneous population. Thus, it is important to study the individual impact of elevated Factor 1 and Factor 2 scores on outcomes.
Psychopathy and Treatment
It has long been clinical lore that psychopaths are not amenable to treatment and that they wreak havoc in treatment groups. This perception is supported by the fact that the hallmark characteristics of psychopathy (e.g., lack of empathy, manipulativeness), especially those described in Factor 1, are at odds with the foundation of the TA. Thus, it is believed that psychopathic individuals are incapable of engaging in a meaningful client–therapist relationship (D’Silva, Duggan, & McCarthy, 2004; Harris & Rice, 2006; S. C. P. Wong & Hare, 2005). Furthermore, some research suggests that psychopathic individuals respond poorly to treatment (Hare, Clarke, Grann, & Thornton, 2000; Hobson, Shine, & Roberts, 2000) or that treatment is ineffective (Harris & Rice, 2006) and that treatment in fact makes them worse (Cleckley, 1976; Hare et al., 2000; Seto & Barbaree, 1999). Consequently, it has been stated that those who undergo treatment after being diagnosed with psychopathy end up more likely to recidivate (Looman et al., 2005; Salekin, 2002).
Conversely, some researchers have argued there is little evidence that psychopaths cannot be treated and that the aforementioned findings are an artifact of poor definition of the construct of psychopathy and methodological limitations of the research (Salekin, 2002; Wilson & Tamatea, 2013). Furthermore, some research does support the effectiveness of treatment of psychopathic individuals. For example, Olver and Wong (2009) explored treatment dropout and treatment change in a sample of high-risk sexual offenders who were deemed psychopathic using a cutoff score of 25 on the PCL-R (Hare, 2003). They found that psychopathic offenders who completed treatment and showed therapeutic improvement demonstrated a reduction in both violent and sexual recidivism. More recently, Olver, Lewis and Wong (2013) conducted research that included an examination of reduction in recidivism and found that positive therapeutic change had a negative correlation with the PCL-R, specifically Factor 1 scores. The authors posited that the comprehensive findings of the study suggest that risk-related treatment changes and therapeutic change may be informative in recidivism prediction and treatment outcome in high-risk, psychopathic offender populations.
Psychopathy and Sexual Offenders
The prevalence of psychopathy among sexual offenders is not clear. Hare (1998) reported that psychopathy has a prevalence rate in the general population of approximately 1%, whereas this number increases to between 15% and 25% in federal corrections settings. Among sex offenders, Hare (1999) estimated that the prevalence of psychopathy as measured by the PCL-R was 10% to 15% among child molesters and around 40% to 50% for rapists and sex offenders who committed crimes against both children and adults. In addition, research suggests that elevated levels of psychopathy are associated with negative outcomes among sexual offenders including reduced treatment motivation (Olgoff, Wong, & Greenwood, 1990), higher levels of sadistic sexual arousal (Serin, Malcolm, Khanna, & Barbaree, 1994), more extensive criminal histories (Forth & Kroner, 1995), and high levels of violent and sexual recidivism (Quinse, Rice & Harris 1995). Given the serious nature of these characteristics and behaviors among sexual offenders, research specifically investigating psychopathy in relation to effective treatment is critical.
TA and Sex Offenders
It is only the last few decades that the researchers and clinicians have begun to study and acknowledge the role of the TA in treatment outcome among criminal justice populations in general and sexual offenders specifically. Sexual offenders present with several challenging treatment issues, such as victim blame, lack of motivation, and high rates of treatment attrition, that can impede the formation of a TA (Serran, Fernandez, Marshall, & Mann, 2003). Serran and colleagues (2003) investigated therapist behaviors that affected alliance formation with sexual offenders, and they found that therapist characteristics (e.g., warmth, empathy) and behaviors (reinforcement, directiveness) that have been found to be related to alliance formation in other populations also extended to sexual offenders. These results aligned with research conducted by Thornton, Mann, and Williams (2000) who demonstrated that sexual offenders engaged in treatment led by warm and supportive therapists improved across all treatment measures.
Some of the limited research exploring the role of the TA in sex offender treatment has included sexual offenders considered to be high risk (Blasko & Jeglic, 2016; Polaschek & Ross, 2010). In addition to treatment challenges observed when working with sex offenders in general, high-risk sexual offenders may present with additional issues that may interfere with therapy, such as an increased propensity for violent behavior, elevated levels of psychopathy or other personality disorders, and more extensive criminal histories. Thus, the challenge is that, with these additional risk factors, high-risk offenders require cognitive and behavioral interventions to reduce future offending, but these same characteristics and behaviors make the formation of a TA more difficult. To overcome this dilemma, several studies have examined factors that contribute to or inhibit alliance formation in high-risk sexual offenders. For example, Polaschek and Ross (2010) used the Working Alliance Inventory (WAI; Horvath & Greenberg, 1989) to analyze three perspectives of the TA: the therapist’s, the client’s, and an independent observer’s. They found significant correlations between (a) the offenders’ ratings of the alliance with their therapists, (b) the therapists’ ratings of the alliance with the offenders, and (c) the observers’ ratings of individual offender alliance with each therapist. Additional research examining the TA with high-risk sexual offender populations has included relationships between early-treatment alliance formation and therapists’ global ratings of motivation to change (Polaschek & Ross, 2010) and client and therapist characteristics and their association with the formation of the alliance (Blasko & Jeglic, 2016).
The Current Study
While a number of studies (Doren & Yates, 2008; Hanson & Morton-Bourgon, 2004; Polaschek & Ross, 2010) have examined the TA and its relation to either incarcerated sexual offenders (Blasko & Jeglic, 2016; Hanson et al., 2002; Marshall et al., 2003) or offenders with elevated levels of psychopathy (Harris & Rice, 2006; Polaschek & Ross, 2010; Skeem et al., 2007), there is scant research examining these factors in combinations, and thus, the current study is one of the first to study the TA among sexual offenders presenting with elevated levels of psychopathy and their therapists.
Sexual offenders who exhibit psychopathic traits often score higher on measures assessing for recidivism risk (Andrews, Bonta, & Wormith, 2006; Hanson & Morton-Bourgon, 2009). They may also display characteristics that inhibit the formation of a TA with treatment providers (Galloway & Brodsky, 2003; S. C. P. Wong & Hare, 2005). Therefore, it is crucial to conduct research specifically focusing on psychopathy to gain a better understanding of this subgroup of sexual offenders. Thus, the primary goal of this study was to assess the relationship between psychopathy and the TA, both from the client and therapist perspective, among a sample of high-risk sexual offenders participating in sexual-offender-specific treatment. In addition, this study examined the impact of Factor 1 and Factor 2 scores on the formation of the TA, as there is evidence to suggest that elevated levels of Factor 1 in particular may be related to poor alliance formation.
Based upon the extant literature, it was hypothesized that (a) total PCL-R scores would demonstrate an inverse relationship with client and therapist ratings on the WAI (Horvath & Greenberg, 1989), (b) sexual offenders with the highest psychopathy scores would have the lowest ratings on both the client and therapist WAI, and (c) PCL-R Factor 1 scores would better predict WAI ratings than PCL-R Factor 2 scores.
Method
Sample and Program Description
The current study utilized archival data from a study conducted by Blasko and Jeglic (2016). Data were collected over a 3-year period from 202 male sexual offenders incarcerated in a state maximum-security prison. The sexual offenders were enrolled in 19 consecutive treatment cohorts with 10 different therapists. The program utilized a manualized cognitive-behavioral treatment (CBT) program for sexual offenders conducted in a group format. Low-intensity programming was between 12 and 14 months in length, met once weekly, and was composed of three modules: (a) responsibility taking, (b) sex education, and (c) relapse prevention and life management plans. Moderate-high-intensity programming lasted between 24 and 30 months, met once weekly, and had seven modules: (a) responsibility taking, (b) behavioral techniques, (c) emotional well-being, (d) victim empathy, (e) anger management, (f) sex education, and (g) relapse prevention and life management plans. Attendance in the program was voluntary; however, participation in treatment likely contributed to early release on parole.
Prior to beginning the treatment program, offender risk was assessed using the Static-99 risk assessment tool (Hanson & Thornton, 2000). Risk for sexual recidivism, as measured by the Static-99, guided group placement per Department of Corrections (DOC) policy (see Blasko, Jeglic, & Mercado, 2011, for a description of this process). Sexual offenders were placed into one of two groups: low intensity (Static-99 score ≤ 3, n = 95) or moderate-high intensity (Static-99 score ≥ 4, n = 107). Policy outlined dynamic risk factors (e.g., primary attraction to children) that would warrant the placement of sexual offenders in moderate-high-intensity treatment, despite scoring 3 or below on the Static-99 (n = 13). Of the moderate-high-intensity participants included in this sample, some were participating in Aftercare Programming at the time of the administration. These participants had previously completed sexual offender treatment programs and were transitioned to Aftercare Programming, which took place once a month for the remainder of their incarceration. DOC policy also required that all sexual offenders placed in moderate-high sexual offender treatment also participate in an interview for the purposes of scoring the PCL-R (Hare, 1991).
Participants rated the relationship with each of their two therapists (primary and secondary) at the completion of Modules 1 and 3 for those in low-intensity groups or Modules 1, 3, and 7 for those in moderate-high-intensity groups; therapists rated their clients at the same intervals. Because low-intensity programming comprised only three modules, the WAI was administered twice, once after the first module (Module 1) and once after the last module (Module 3). Thus, to compare across intensity levels, we considered Time 2, the final administration in the moderate-high-intensity groups which corresponds to the administration after Module 7. All participants completed an informed consent agreeing their data could be used for research purposes. At the time of the study, 100% of sexual offenders enrolled in the groups agreed to participate. The study received approval from both the DOC and an affiliated university’s Institutional Review Board.
Sexual offenders
Of the 202 adult male sexual offenders who participated in the original study (see Blasko & Jeglic, 2016, for a full description of the original study sample), 107 participated in moderate-high-intensity sexual offender treatment. PCL-R (Hare, 2003) scores were available for 89 of the 107 participants 1 in the moderate-high-intensity treatment group, and thus, these participants comprised the sample for the current study.
Of the 89 participants, ages ranged from 23 to 60 years (M = 41.54, SD = 9.87) at the start of treatment. The participants were predominantly Black (60.7%), or White, non-Hispanic (36.0%). The majority of the participants (85.3%, n = 76) were deemed to be between moderate and high risk for sexual recidivism as determined by Static-99 scores (i.e., scores ≥ 4). The other 13 participants were deemed low or low-moderate risk (i.e., scores ≤3) but were assigned to the moderate-high-intensity treatment group due to dynamic risk.
Of the participants, 32.6% were previously convicted as an adult for a sexual offense and 52.8% for a violent offense. Slightly less than half of the participants had a history of juvenile convictions (44.9%), with 11.2% having a previous conviction as a juvenile for sexually related offense and 84.3% for nonsexual offense. Regarding the participants’ relationship to their victim(s) in their index offenses, two participants sexually abused their wives or girlfriends, 33 had victims who were considered acquaintances, 41 sexually abused stranger victims, eight offended against related victims, and the remainder (n = 5) were not identified. The number of victims ranged from one to seven (M = 1.97, SD = 1.12). Fifty-four of the index offenses involved child victims (61.0%) whereas 35 involved adult victims (39.0%).
Therapists
Over the study period, a total of 10 therapists (five female, five male) facilitated groups. Therapists ranged in age from 26 to 64 years (M = 39.94, SD = 9.61) and were predominantly White, non-Hispanic (70.0%). All therapists were required to have a minimum of a graduate degree in a human services field. Two therapists were licensed psychologists with doctorate degrees, one was a psychiatrist, and seven master’s-level clinicians. All but one of the therapists were trained in graduate school to provide CBT, with the exception of a Licensed Clinical Social Worker who identified with the humanistic orientation. All therapists completed training to provide the manualized program during a 5-day intensive training. Following training, therapists were required to observe the groups of previously trained therapists who had been facilitating the manualized program for at least a year prior to leading their own groups. All therapists participated in a required, weekly supervision group. Each therapist who participated in the original study had a minimum of 3 years prior experience conducting manualized group interventions with sexual offender and general offender populations.
Measures
WAI
The WAI (Horvath & Greenberg, 1989) is designed to measure the quality of the TA between the therapist and client from the perspective of the client. Both the Therapist and Client forms are comprised of 36 items, including three subscales (Tasks, Goals, Bonds) with 12 items in each subscale. The subscales measure specific features of the therapeutic relationship: the therapeutic bond (e.g., “I appreciate my therapist as a person”), task agreement (e.g., “____ and I agree about the steps to be taken to improve his or her situation”), and agreement on the goals (e.g., “I have doubts about what we are trying to accomplish in counseling”). These subscales are operationalized following Bordin’s (1979, 1994) theoretical conceptualization of the working alliance. A 7-point Likert-type scale is used to rate each question (1 = never, 2 = rarely, 3 = occasionally, 4 = sometimes, 5 = often, 6 = very often, and 7 = always). The WAI has been researched extensively over the past 30 years and has been demonstrated to be both a reliable and valid measure of the TA (Horvath & Greenberg, 1986, 1989, 1994). For the current study, both therapist and client WAI scores at the beginning and end of treatment were of interest for the primary therapist only. Although data were gathered for the secondary therapist, it was not available for all clients at both time points. Furthermore, the groups were predominantly led by the primary therapist and that is the therapist with which the client would have had most interaction.
Static-99
The Static-99 (Hanson & Thornton, 2000) is an actuarial tool designed to assess risk for recidivism. Hanson and Thornton (2000) created this measure by combining the four items from the Rapid Risk Assessment for Sex Offense Recidivism (RRASOR; Hanson, 1997) with six additional items from the Structured Anchored Clinical Judgment (SACJ; Thornton, 1997). The Static-99 assigns offenders to one of four risk categories: (a) low, with scores of 0 and 1; (b) moderate-low, with scores of 2 and 3; (c) moderate-high, with scores of 4 and 5; and (d) high, with scores of 6 and above. The Static-99 is one of the most widely researched assessments used for determining sexual recidivism (Barbaree, Seto, Langton, & Peacock, 2001; Hanson & Thornton, 1999, 2000; Nunes, Firestone, Bradford, Greenberg, & Broom, 2002). Research indicates that this actuarial risk assessment tool demonstrates moderate accuracy in predicting both sexual and violent recidivism with research demonstrating receiver operating characteristic (ROC) scores of .62 (Harris et al., 2003)).
PCL-R
The PCL-R (Hare, 2003) was designed to assess for psychopathy using a semistructured interview and/or file information, and is commonly utilized in legal, clinical, and research settings (Cooke & Michie, 1997; Fulero, 1995). The scale consists of 20 items scored according to the degree of applicability (0 = not present, 1 = possibly present, 2 = definitely present). Total scores range from 0 to 40, with higher scores indicating a higher level of psychopathic traits. The most common factor model associated with the PCL-R is the two-factor model: Factor 1, which can be subdivided into Interpersonal (e.g., superficiality, grandiosity) and Affective (e.g., callousness, lack of remorse) facets, and Factor 2, subdivided into Lifestyle (e.g., irresponsibility, impulsivity) and Antisocial (e.g., criminal versatility, early behavior problems) facets. Each individual factor can receive a score ranging from 0 to 20. PCL-R total scores range from 0 to 40, with scores of 30 or higher traditionally used to indicate the presence of psychopathy (Hare, 2003).
Analytic Plan
We first assessed the relationship between total psychopathy score and total WAI ratings by both clients and therapists. We decided to examine participants by therapy placement separately (aftercare/moderate-high-intensity treatment), because there is some evidence suggesting that the frequency of sessions is positively related to the formation of the TA (Schiff & Levit, 2009). Next, we analyzed the individual subscales (Tasks, Goals, Bonds) to gain more information about the specific WAI components. We then separated offenders into three groups based upon PCL-R scores: high (>30), moderate (between 20 and 30), and low (<20) and compared ratings on the average WAI scores and subscale scores for clients and therapists. We were then interested in whether the characteristics of Factor 1 and Factor 2 scores on the PCL-R would affect therapist WAI ratings over the course of the WAI administrations. We conducted two regression analyses to see whether WAI therapist and client total scores were predicted by Factors 1 and/or 2 controlling for risk (Static-99).
Results
Means and standard deviations for sexual offender and therapist WAI ratings among the sample and WAI ratings by treatment placement category are shown in Tables 1 and 2. Among the sexual offenders in the sample, the mean sum rating on the WAI was 197.88 (SD = 33.16) (Goals subscale, M = 66.05, SD = 11.66; Tasks subscale, M = 67.41, SD = 12.83; Bonds subscale, M = 64.41, SD = 11.99). Among the therapists, the mean sum rating on the WAI was 194.73 (SD = 24.96) (Goals subscale, M = 64.14, SD = 9.94; Tasks subscale, M = 66.81, SD = 8.33; Bonds subscale, M = 64.71, SD = 7.94). Ratings were comparable with those reported at treatment completion across a range of client types (cf. Busseri & Tyler, 2004; Safran & Wallner, 1991). The average PCL-R score for the sample was 20.36 (SD = 7.55; range = 5-37). This was comparable with the scores obtained by Boccaccini, Murrie, Rufino, and Gardner (2014) in a sample of sex offenders being evaluated for sexually violent predator (SVP) civil commitment in Texas, but below the 24.2 listed for sex offenders in the PCL-R manual.
Summary Statistics of Working Alliance Inventory Scores (SDs in Parentheses).
Summary Statistics of PCL-R Scores (SDs in Parentheses).
Note. PCL-R = Psychopathy Checklist–Revised.
Total Psychopathy Scores and Total WAI Scores
For the first set of analyses, a two-tailed Pearson’s correlation was calculated to assess the relationship between total psychopathy scores, as determined by the PCL-R, and the client’s rating of their primary therapist at the beginning (T1) and end (T2) of treatment, as determined by the total WAI score. Using the complete sample (n = 89), no significant correlations were found for the therapist at T1 or T2 (r = −.150, n = 64, p > .05 and r = −.223, n = 63, p > .05, respectively). Next two-tailed Pearson’s correlations were conducted to assess the relationship between total psychopathy scores and therapist ratings on the WAI. No significant correlations were found using the total sample for T1 or T2 (r = −.096, n = 69, p > .05 and r = −.315, n = 30, p > .05, respectively), or using the sample excluding aftercare participants at T1 or T2 (r = −.218, n = 39, p > .05 and r = −.374, n = 27, p > .05, respectively). As there were no significant correlations between PCL-R scores and WAI total scores for either T1 or T2 and that T1 and T2 WAI total scores were highly correlated (r = .61, p < .01 client WAI total T1 and T2; r = .51, p < .01 therapist WAI total T1 and T2), further analyses combined T1 and T2 data and are hence referred to average WAI total score.
The averaged WAI total scores were used to calculate a second set of two-tailed Pearson’s correlation analyses excluding those participants who entered the study assigned as aftercare participants (n = 59). Patients in aftercare met once per month whereas those in moderate/high treatment met weekly. Results indicated there was a significant negative correlation between total psychopathy and clients’ average WAI total score (r = −.402, p < .05) but not between average therapist WAI total and PCL-R score. To further investigate the negative correlation for the non-aftercare participants, additional analyses were run for each of the averaged WAI subscales (e.g., Tasks, Bonds, Goals). No significant correlations were found for the averaged Tasks and Goals subscales. However, the average Bonds subscale was significantly negatively associated with PCL-R score for the client rating only (r = −.442, p < .01). Because therapy group placement affected outcome, it was used as a covariate in subsequent analyses.
Psychopathy Group and Total WAI Scores
Next, clients were separated into three groups based upon PCL-R scores: low (n = 44, PCL-R score < 20), moderate (n = 34, PCL-R score between 20 and 30), and high (n = 11, PCL-R score > 30). A PCL-R score of 30 was used as the cut-point for high, as this is the most conservative cutoff score for diagnosing psychopathy (Hare, 2003; Olver & Wong, 2009). Means for client and therapist average WAI total scores by group are presented in Table 3. Two ANCOVAs were then used to determine whether there was a significant difference between either the average client or therapist WAI total score and PCL-R group (low, moderate, high), controlling for risk (Static-99 score) and group placement (aftercare, moderate/high intensity). Overall, there was no significant effect of PCL-R group on WAI total score for either the client average total WAI score, F(2, 65) = 0.47, p = .63, or therapist average total WAI score, F(2, 68) = 0.55, p = .58, after controlling for risk and group placement. The same analyses were conducted for the averaged subscales (Goals, Tasks, Bonds) and PCL-R group controlling for risk and group placement for both client and therapist, and no further significant differences emerged.
Mean WAI Score by PCL-R Group.
Note. WAI = Working Alliance Inventory; PCL-R = Psychopathy Checklist–Revised.
Impact of Factor 1 and Factor 2 Scores
In an effort to determine whether characteristics associated with Factor 1 and Factor 2 scores predicted clients and therapists’ ratings on the average total WAI scores, two separate multiple regression analyses were conducted, controlling for risk (Static-99) and group placement. All assumptions of linearity, normality of residuals, and homoscedasticity were met for both regression equations. Regression coefficients and standard errors for both models are found in Tables 4 and 5. The first multiple regression model tested whether it was possible to predict average total therapist WAI score from PCL-R Factor 1 and Factor 2 scores, controlling for risk (Static-99) and group placement (aftercare, moderate/high intensity). This model did not prove significant, F(4, 67) = 2.446, p = .055. The only significant predictor was group placement (β = −13.35, p < .01). This model explained a total of 13.4% of the variance. A second regression model was run to predict average total client WAI score from PCL-R Factors 1 and 2, controlling for risk and group placement. This regression model was also nonsignificant, F(4, 64) = 1.51, p = .21, accounting for 9.2% of the variance. None of the individual variables were significant predictors of the average client total WAI score.
Summary of Multiple Regression Analysis Therapist WAI Rating.
Note. WAI = Working Alliance Inventory; B = unstandardized regression coefficient; SE B = standard error of the coefficient; β = standardized coefficient; PCL-R = Psychopathy Checklist–Revised.
p < 05.
Summary of Multiple Regression Analysis Client WAI Rating.
Note. WAI = Working Alliance Inventory; B = unstandardized regression coefficient; SE B = standard error of the coefficient; β = standardized coefficient; PCL-R = Psychopathy Checklist–Revised.
Discussion
The current study was one of the first to explore the relationship between psychopathy and the TA as assessed by both the therapist and the client among a sexual offender sample. In addition, this study examined the relationship between psychopathy, as assessed by both Factors 1 and 2 on the PCL-R (Hare, 2003) and WAI (Horvath & Greenberg, 1989). Overall, no significant relationship was found between PCL-R scores and total WAI scores for either the client or the therapist on the overall sample. However, when Aftercare Treatment participants were removed from the analyses, a significant negative correlation between client WAI ratings and PCL-R scores emerged. Yet, when the WAI subscales were considered separately, this relationship only held true for the Bonds subscale and not the Tasks and Goals subscales. Furthermore, results from the current study do not support the hypothesis that the characteristics associated with Factor 1 and Factor 2 scores significantly affect the TA as reported by either the client or the therapist.
It was hypothesized that total psychopathy score, as measured by the PCL-R, would have an inverse relationship with WAI ratings for both clients and therapists. Contrary to this hypothesis, no significant correlation was found. This is contrary to past findings suggesting that those with psychopathy responded poorly to treatment (D’Silva et al., 2004; Hare et al., 2000; Harris & Rice, 2006; Hobson et al., 2000; S. C. P. Wong & Hare, 2005). This finding, however, is more in accordance with the findings of Polaschek and Ross (2010), indicating that some high-risk sexual offenders were capable of forming an alliance and making treatment changes. Although this study did not examine treatment outcome, it is encouraging that both therapists and clients reported the ability to form an alliance, regardless of psychopathy score.
When treatment participants enrolled in Aftercare programming were excluded from the analysis, a significant negative correlation was demonstrated between total psychopathy score and client ratings on the WAI at both the beginning and end of treatment, but not with therapist ratings. There are several possible explanations for these findings. First, aftercare participants had received previous treatment. Thus, it is plausible that their previous participation in treatment programs and exposure to multiple therapists improved their ability to create a TA. This explanation would support past research positing that exposure to, and completion of, treatment programs is associated with change in psychopathic, high-risk, sexual offenders (Polaschek & Ross, 2010). Another hypothesis would be that, because the aftercare groups met only once per month, the frequency of contact affected the relationship as perhaps meeting only once per month was too infrequent to form a TA in either direction (positive/negative). It could also be that the aftercare therapists may have already been familiar with these clients from previous therapy groups, and thus, therapists would have more negative expectations of forming a TA with those with elevated levels of psychopathy. It is also plausible that with longer prison sentences, periods in treatment, and exposure to psychological assessment tools, aftercare participants were more likely to understand and comply with what was expected of them from therapists during groups. However, if this were indeed the case, it would be anticipated that therapists would perceive this compliance as a positive relationship and assess a more positive TA. But this was not the case, and thus, it is plausible that with lengthy exposure to the criminal justice system (some up to 40 years), aftercare participants were less likely to trust that negative responses on the WAI would not be shared with their therapists or others in the criminal justice system. Thus, the offenders could fear impact on later discretionary release decisions. Consequently more research with larger samples is needed to understand this relationship.
When the subsample that did not include aftercare participants was explored further, it was determined that the only subscale to demonstrate the inverse relationship between total psychopathy score and client WAI ratings was the Bonds subscale. This would suggest that the presence of elevated levels of psychopathy did not affect the clients’ perception of tasks or goals within the TA, but had a negative impact only on the client–therapist bond. This finding is similar to one made in the original study by Blasko and Jeglic (2016) who found that the Bonds subscale was the only subscale significantly correlated with participants’ Static-99 scores. This finding further aligns with the work of Ross, Polaschek, and Wilson (2011) who found that a two-factor model of the Working Alliance Inventory Short-form (WAI-S) was the best fit in a sample of prisoners with high PCL-R scores in that both the therapists and clients distinguished the work part of psychotherapy (goals, tasks) from the therapeutic bond. Although creating a mutual bond between client and therapist is an integral aspect of a successful TA (Stiles et al., 2004), identifying this subscale as a specific area of weakness within the TA for this population, as opposed to the entire construct of the TA, is important for future research and practice. Furthermore, it is unclear how important the Bonds subscale is to outcome especially for those with elevated levels of psychopathy, and thus, future studies should examine these findings using recidivism rates. The significant finding related to the Bonds subscale demonstrates that, while they may not feel connected to their therapists, participants may still reach agreement with their therapists about work that needs to be done in treatment and pursue that work.
Contrary to our hypothesis, there was no significant correlation between total psychopathy score and therapist WAI ratings in either the total sample or when we separated offenders by therapy placement (aftercare and moderate/high). In line with past research (Galloway & Brodsky, 2003; S. C. P. Wong & Hare, 2005), it was theorized that the presence of characteristics associated with elevated levels of psychopathy (e.g., manipulativeness, lying, impulsivity) would negatively affect the therapists’ ratings of the alliance across the sample. This finding suggests that, from the therapists’ perspective, elevated levels of psychopathy do not negatively affect the TA. It is possible that sexual offenders did not engage in, or present, behaviors and traits that are typically associated with psychopathy at a high-enough frequency to alter the therapists’ ratings. However, considering the length of treatment and likelihood of masking these characteristics and behaviors effectively, this seems unlikely. Although this study did not specifically investigate recidivism as a result of the TA, these results are more in line with research that disputes the claim that psychopathic individuals cannot form a TA and are capable of benefiting from treatment programs (Olver & Wong, 2009; Salekin, 2002; Wilson & Tamatea, 2013).
This study additionally endeavored to explore the impact that characteristics associated with each individual PCL-R factor may have on the TA. Contrary to expectation, individual factor scores were not significantly correlated to the WAI. Due to the distinct characteristics and traits associated with each factor, many of which seem likely to come into play both during treatment and during an assessment of a TA, these findings are surprising. Motivation, or the lack of it, may affect an individual’s scores and so could be responsible for the lack of significant results. Individuals with higher Factor 1 scores, who may be capable of appearing to be engaged, may simply be disinterested in doing so. Alternatively, the individual factors may be nonsignificant because psychopathy may be less important to the ability of the offender to form a TA than previously believed.
This study is not without limitations. Although the overall sample for the initial study was large (N = 202), there were significantly fewer offenders who completed all the measures used in the present study, and thus, we had relatively small sample sizes for several of the analyses. Furthermore, there were only 11 offenders in the high psychopathy category, and thus, findings should be interpreted with caution. However, given that few studies have examined these individual factors at all, much less in combination, these findings still bring value to the literature and can produce data for future hypothesis generation. In addition, 13 of the participants in the moderate-high-intensity group had Static-99 scores below 3 (which would warrant placement in the low-intensity group), but they were placed in the moderate-high-intensity group as they were determined to be at higher risk for reoffending based upon a DOC dynamic risk assessment (e.g., primary sexual attraction to children or violence); but even after controlling for risk as assessed by the Static-99, results remained the same.
Although the current study was affected by some clear limitations, it did provide important preliminary information about the specific relationship between psychopathy and the TA. There are numerous references in the literature about the inability of psychopathic individuals to engage in and to develop TAs (Harris & Rice, 2006; Skeem, Monahan & Mulvey, 2002; Skeem et al., 2007; Wilson & Tamatea, 2013). However, these claims are largely justified by examining recidivism rates (Doren & Yates, 2008; Murrie, Boccaccini, Caperton, & Rufino, 2013) using populations that are not selected with psychopathy as a primary focus of analysis (Blasko & Jeglic, 2016; Langevin, 2006; Olver, Nicholaichuk, Gu, & Wong, 2013; Serran et al., 2003) . Furthermore, although there is clear evidence that Factor 1 and Factor 2 characteristics and behaviors are distinct (Hare, 2003; Wilson & Tamatea, 2013), to our knowledge, there are no studies examining how these factors affect the relationship between psychopathy and the TA. Future research should continue to study the role of psychopathy in the therapeutic process in general and among sex offenders specifically using larger samples and gathering long-term outcome data.
The findings of this study go against much of the clinical lore suggesting that those with psychopathic characteristics are untreatable and wreak havoc in group therapy. While this study does not examine outcome data, if those with high levels of psychopathy were very disruptive to the therapeutic process, their behavior would be noted in alliance formation. While there are still few studies examining the role of psychopathy in treatment generally (D’Silva et al., 2004; Hare, 1998), and sex offender treatment specifically (Blasko & Jeglic, 2016; Polaschek & Ross, 2010), it is worthwhile highlighting that these studies do not support the supposition that those with psychopathic traits cannot form a therapeutic relationship with their therapist. The results of the current study suggest that we may be doing a great disservice to both the community and to those offenders who exhibit high levels of psychopathy and are considered difficult, or even impossible, to treat. In many cases, these individuals may be prevented from participating in treatment and thus may be released without addressing their risk factors in treatment. The findings of this study suggest that treatment selection guidelines which prevent those with elevated psychopathy scores from participating in treatment should be revisited.
Footnotes
Declaration of Conflicting Interests
The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.
Funding
The author(s) received no financial support for the research, authorship, and/or publication of this article.