Skip to content

Psychopathy ≠ untreatable: Comorbid psychopathy in forensic psychiatric patients

Psychopathy ≠ untreatable: Comorbid psychopathy in forensic psychiatric patients

Forensic-Training-Academy-150x150

Psychopathy is associated with greater therapy-interfering behavior, with PCL-R Factor 2 predicting institutional misconduct and PLC-R Factor 1 predicting dropout from treatment. This is the bottom line of a recently published article in the International Journal of Forensic Mental Health. Below is a summary of the research and findings as well as a translation of this research into practice.

ijfmh-Jan-09-2022-06-44-54-21-AM

Featured Article | International Journal of Forensic Mental Health | 2017, Vol. 16, No. 2, 149-160

Forensic Psychiatric Patients with Comorbid Psychopathy: Double Trouble?

Authors

Inge Jeandarme, Knowledge Center Forensic Psychiatric Care (KeFor)
Claudia Pouls, Knowledge Center Forensic Psychiatric Care (KeFor)
T. I. Oei, Department of Criminal Law, Tilburg University, Tilburg, The Netherlands
Stefan Bogaerts, Forensic Psychiatric Center the Kijvelanden, Rotterdam, The Netherlands

Abstract

Patients with psychopathy need intensive care and supervision. There is however reluctance to treat them because of (supposedly) limited chances of success and risk of therapy-interfering behavior. This study focused on inpatient disruptive behavior in mentally disordered offenders during medium security treatment. Patients (N = 224) were assessed using the Psychopathy Checklist- Revised total, factor and facet scores and divided into three groups depending on the presence of low, medium, and high psychopathy traits. Associations between psychopathy and criminogenic risk and need factors were analyzed. Additionally, the association between psychopathy and therapy-interfering behavior (non-compliance, drop-out, institutional misconduct) was investigated with correlational and logistic regression analyses. The results showed that psychopathy was associated with greater risk, needs, and therapy-interfering behavior. PCL-R Factor 2 predicted institutional misconduct, whereas PCL-R Factor 1 predicted drop-out from treatment. The study highlights the importance of responsive treatment climates in retaining this difficult-to-treat group in treatment.

Keywords

PCL-R, psychopathy, forensic psychiatric patients, internees, therapy-interfering behavior

Summary of the Research

“Under Belgian law, internment is a safety measure for offenders who are found not guilty for reason of insanity (NGRI). As in other countries, this specific legislation allows mentally disordered offenders (MDOs) to be transferred to (forensic) psychiatric facilities for mandatory treatment. In line with research on non-mentally ill offenders, antisocial and/or psychopathic personality traits are also strong risk factors for recidivism in MDOs. Comorbid psychopathic traits in MDOs are associated with more impulsive and coercive and less compliant interpersonal styles, premeditated aggression, and poor criminal outcomes.” (p. 149)

“Furthermore, it is generally believed that high levels of psychopathy guarantee a problematic course of treatment and thus present a serious challenge for therapists. Skeem, Manchak, and Peterson (2011) compared these patients with poor students in the classroom: verbally combative, hostile, prone to break rules, and not motivated to cooperate with treatment. According to Wong, Gordon, and Gu (2007), one of the most daunting responsivity factors in treatment is treating unmotivated, non-adherent and treatment-resistant clients such as many patients with psychopathy or (antisocial) personality disorder.” (p. 149)

“Meta-analytic research findings in different settings— including forensic psychiatric settings—have indicated that the PCL-R total score is associated with broadly defined institutional misconduct (rw = .29) and to a lesser extent, with physical violence (rw = .17). PCL-R Factor 2 was moderately predictive of institutional adjustment, whereas Factor 1 showed a less robust association. Of the PCL-R’s four facet scores, Facet 4 was the strongest and most incrementally valid predictor of institutional aggression in forensic psychiatric settings.” (p. 150)

“Given the abovementioned problems with non-compliance and institutional misconduct and the resulting security concerns, the increased treatment drop-out rates may not be surprising. A meta-analysis performed by Olver, Stockdale, and Wormith (2011) found that having an antisocial personality disorder or psychopathy (both the diagnosis and dimensional PCL-R scores) predicted attrition. In male sex offenders, PCL-R Facet 2 showed significant unique contributions to drop-out, whereas none of the other facets did. In female patients with substance abuse, a shorter treatment stay was associated with PCL-R Factor 1 personality characteristics.” (p. 150)

“The objective of this study was to investigate the relations between psychopathy measured with the PCL-R and indicators of therapy-interfering behavior, namely institutional misconduct, non-compliance and drop-out from treatment. We controlled for other risk/need factors because these may contribute to the associations of interest.” (p. 150)

“The following categorical variables were considered indicators of therapy-interfering behavior (TIB) during inpatient treatment: (1) treatment drop-out, (2) non-compliance, and (3) institutional misconduct. Non-compliance was defined as a report to the CPS that the treatment rules had not been respected (such as the use of alcohol during treatment or failure to cooperate with treatment). Institutional misconduct was defined as (1) absconding (such as escaping from the institution or absconding from supervised or unsupervised leave), (2) violating individually formulated judicial conditions, and (3) engaging in offense related behavior, which was defined as incidents coded under offending categories in the Belgian penal code, regardless of whether they led to further prosecution or sentencing.” (p. 152)

“In the current study, psychopathy was significantly associated with greater risks, needs and TIB. PCL-R Factor 2 predicted institutional misconduct, whereas PCL-R Factor 1 predicted drop-out from treatment.” (p. 155)

“Considered together, our findings support other research stating that treatment should focus on criminogenic PCL-R Factor 2 features while also carefully accounting for PCL-R Factor 1 characteristics to keep patients in treatment.” (p. 156)

“Although it is understandable that clinicians often prefer highly motivated and compliant low-risk patients, the RNR model states that most resources should be deployed to treat more difficult, less compliant patients. Forensic mental health professionals therefore face a great challenge. They must tolerate difficult interpersonal behavior, such as hostility and manipulation, and control their countertransference while still motivating forensic patients who seemingly do not want to change or even stay in treatment. This is clearly not an easy task, but as shown by international research, it is not impossible. Difficult-to-treat should not become synonymous with untreatable.” (p. 158)

Translating Research into Practice

“Therapeutic settings involved in the treatment of MDOs with psychopathic traits face major challenges. Psychopathy is linked to institutional maladjustment, lack of motivation, early drop-out from treatment, and slower progression as well as poor treatment outcomes, for example, in terms of reducing recidivism. The behavioral manifestations of these traits can significantly interfere with treatment, as they impede the formation of a good working alliance and therefore must be appropriately managed. The current study found support for the two-component model proposed by Wong, Gordon, Gu, Lewis, and Olver (2012). The Criminogenic component, or Factor 2, was significantly associated with greater criminogenic need/risk factors and institutional misconduct and reflected an established pat- tern of antisocial behavior and dysfunctional lifestyle both inside and outside the institution. While the Criminogenic component should be the focus of forensic treatment, the Interpersonal component, or Factor 1, is equally important. Factor 1 was significantly associated with drop-out and can thus also contribute to poor out- comes if TIBs are not appropriately managed. As noted by Wong et al. (2012), it is important to distinguish between using risk reduction versus personality change interventions when designing and implementing treatment programs (p. 157).

“[A]s observed, psychopathic and other personality disorder traits in MDOs may be barriers to forensic psychiatric treatment and can lead to premature interruption or discontinuation of treatment. Clinicians are advised to develop a responsive treatment climate with staff and management who are willing to invest time and effort in these personality disordered patients (for good practices, please see Bulten & Decoene, 2015). Instead of viewing poor motivation as a contraindication to treatment, motivation should be evaluated and innovative treatment studies should be designed to enhance individual’s motivation for treatment.” (p. 157)

“A meta-analysis revealed that treatment responsivity indicators such as disruptive behavior during treatment and negative treatment attitudes were among the strongest predictors of increased attrition rates, while higher levels of motivation and treatment engagement predicted decreased attrition. Therefore, it is also important to measure progress in therapy in a uniform manner, with tools specifically developed for thera-peutic measurement, such as the Instrument for Forensic Treatment Evaluation (p. 157).

Other Interesting Tidbits for Researchers and Clinicians

“When comparing the groups with low, medium, and high psychopathic traits, a small significant difference was found, indicating that patients with more psychopathic traits were less compliant. However, when investigating the correlations between the PCL-R total, factor, and facet scores and non-compliance, no significant associations were found, which contradicts other research reporting associations with PCL-R total, Factor 1, and Factor 2 scores. The differences in the operationalization of non-compliance may have contributed to these different findings. Additionally, it should be noted that in the current study, non-compliance might have been underreported.” (p. 156)

“[L]imitations of this study warrant caution when interpreting and generalizing the current findings. First, the PCL-R scores used in the current study were field validity scores with a low IRR. This finding is generally consistent with a growing body of field research that suggests that the high levels of reliability reported in many controlled research studies are not generalizable to practice. However, it calls into question how reliable clinical scores truly are.” (p. 156)

Join the Discussion

As always, please join the discussion below if you have thoughts or comments to add!