Journal of Substance Abuse Treatment 46 (2014) 574–583

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Journal of Substance Abuse Treatment

Offenders with mental health problems and problematic substance use: Affective psychopathic personality traits as potential barriers to participation in substance abuse interventions☆ Natalie Durbeej, M.Sc. a,⁎, Tom Palmstierna, M.D., Ph.D. a, b, Anne H. Berman, Ph.D. a, Marianne Kristiansson, M.D., Ph.D. a, Clara Hellner Gumpert, M.D., Ph.D. a a b

Department of Clinical Neuroscience, Division of Forensic Psychiatry, Karolinska Institutet, Stockholm, Sweden Forensic Department and Research Centre Brøset, Norwegian University of Science & Technology, Trondheim, Norway

a r t i c l e

i n f o

Article history: Received 14 March 2013 Received in revised form 10 December 2013 Accepted 3 January 2014 Keywords: Recidivism Problem severity Violence risk Psychopathic personality traits Substance abuse treatment

a b s t r a c t Substance abuse is related to re-offending, and treatment of substance abuse may reduce criminal recidivism. Offender characteristics including problem severity, violence risk and psychopathic personality traits may be positively or negatively associated with participation in substance abuse treatment. We explored the relationships between such characteristics and participation in substance abuse interventions among Swedish offenders with mental health problems and problematic substance use. Our analyses revealed that problem severity regarding drugs, employment, and family/social situations predicted intervention participation, and that affective psychopathic personality traits were negatively associated with such participation. Thus, affective psychopathic personality traits could be considered as potential barriers to participation in substance abuse interventions. Among offenders with mental health problems and problematic substance use, such personality traits should be taken into account in order to optimize treatment participation and treatment outcome. Approaches used in cognitive-behavioral therapy (CBT) and dialectical behavioral therapy (DBT) could be applicable for these patients. © 2014 Elsevier Inc. All rights reserved.

1. Introduction The associations between mental health problems, substance abuse and offending have been firmly established in research (Elbogen & Johnson, 2009; Fazel, Gulati, Linsell, Geddes, & Grann, 2009). The co-occurrence of substance abuse and mental health problems has been recognized as an important risk factor for criminal behavior that should be targeted in order to reduce the risk of reoffending (Douglas, Guy, & Hart, 2009; Douglas & Skeem, 2005; Elbogen & Johnson, 2009). Offenders with co-occurring mental health problems and problematic substance use 1 have multiple problems and treatment needs (Hartwell, 2004; Lindqvist, 2007). After release from prison or forensic psychiatric care, many end up homeless, unemployed, and with a high risk of criminal recidivism. From a crime prevention perspective, research has emphasized the need to refine and elaborate strategies for treatment and support targeting this ☆ Declaration of interest: None. ⁎ Corresponding author at: Department of Clinical Neuroscience, Division of Forensic Psychiatry, Karolinska Institutet. Karolinska University Hospital, Huddinge, SE- 141 86 Stockholm, Sweden. Tel.: +46 737041948. E-mail address: [email protected] (N. Durbeej). 1 In this paper, the term problematic substance use is used to subsume various levels of severity in alcohol- and drug-related problems, including hazardous use, harmful use, substance abuse or dependency (Berman, Wennberg, & Källmén, 2012). 0740-5472/$ – see front matter © 2014 Elsevier Inc. All rights reserved. http://dx.doi.org/10.1016/j.jsat.2014.01.002

particular population (Hartwell, 2004; Lindqvist, 2007). A study on Swedish offenders with mental health problems and problematic substance use suggested that substance abuse treatment participation was associated with a substantially reduced risk of re-offending (Gumpert et al., 2010). Also, other studies have highlighted the significance of substance abuse treatment for reducing criminal behavior (Bukten et al., 2012; Holloway, Bennet, & Farrington, 2006; Prendergast, Podus, Chang, & Urada, 2002). In addition to substance abuse and co-occurring mental health problems, psychopathic personality traits have been recognized as important predictors of criminal behavior, particularly violent acts (Hemphill, Hare, & Wong, 1998; Porter & Porter, 2007). The Canadian psychologist Robert Hare (2003) suggested that psychopathy should be viewed as a cluster of certain interpersonal and affective traits combined with antisocial behaviors, such as grandiosity, callousness, lack of empathy, impulsivity and criminal versatility. Others have proposed that the concept merely involves interpersonal and affective traits (Skeem & Cooke, 2010). Despite the different opinions on this topic, the definition suggested by Hare has been used frequently in research (Hare & Neumann, 2010). Studies have confirmed that psychopathic personality traits are prevalent in both prison- (Coid & Ullrich, 2010; Hare, 2003; Hobson & Shine, 1998) and forensic psychiatric populations (Laajasalo, Salenius, Lindberg, Repo-Tiihonen, & Hakkanen-Nyholm, 2011;

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Tengström, Grann, Långström, & Kullgren, 2000; Wallinius, Nilsson, Hofvander, Anckarsäter, & Stålenheim, 2012), and that psychopathy is predictive of re-offending in these populations (Hemphill et al., 1998; Porter & Porter, 2007; Tengström et al., 2000). Research has also found a link between psychopathy and problematic substance use (Taylor & Lang, 2006; Walsh, Allen, & Kosson, 2007), but indicated that drop-out rates from substance abuse treatment are higher among those with psychopathic personality traits, relative to those without psychopathic personality traits (Alterman, Rutherford, Cacciola, McKay, & Boardman, 1998; Richards, Casey, & Lucente, 2003; Van Stelle, Blumer, & Moberg, 2004). It has been suggested that the less frequent treatment utilization in this population may be explained by interpersonal and affective psychopathic personality traits (Hobson, Shine, & Roberts, 2000; Olver & Wong, 2011). For example, those with grandiosity - a core trait of psychopathy - may fail to identify aspects of themselves that they need to change, and those with lack of empathy and shallow affect may have difficulties in establishing a therapeutic alliance with treatment staff (Thornton & Blud, 2007). Apart from psychopathic personality traits, other treatment barriers, i.e. factors negatively associated with treatment utilization, have been identified. Some examples are elevated violence risk profile, i.e. higher violence risk scores, specific historical and current risk factors of future violence (Hiller, Knight, & Simpson, 1999; Nunes, Cortoni, & Serin, 2010) e.g. criminal history and lack of motivation to change (Condelli & De Leon, 1993; Mowbray, Perron, Bohnert, Krentzman, & Vaughn, 2010; Nunes et al., 2010), and characteristics of the treatment system such as poor availability of services (Rapp et al., 2006; Tucker, Vuchinich, & Rippens, 2004). Also, treatment facilitators, i.e. factors positively associated with treatment utilization, have been identified. Such facilitators can be severity of alcohol- and drug-related problems, psychiatric problems, employment problems as well as previous treatment experiences (Finney & Moos, 1995; Hasin, 1994; Storbjörk & Room, 2008). Given their multiple treatment needs and risk of criminal recidivism, offenders with mental health problems and problematic substance use are of great concern to society. Participation in planned substance abuse treatment has previously been associated with lower frequencies of crime relapse (Gumpert et al., 2010). However, such results may indicate a selection bias favoring patients with certain characteristics; i.e. low problem- and risk profiles in such treatment (Geirstein & Johnson, 2001; Gumpert et al., 2010; McCollister et al., 2003). An important follow-up question is if the treatment system reaches out to all those in need of its services. Exploring whether certain offender characteristics function as barriers or facilitators to substance abuse treatment can assist professionals in their work to increase motivation and/or reduce drop-out (Tsogia, Copello, & Orford, 2001). 1.1. Aims The aim of this study was to explore the relationship between participation in substance abuse interventions and relevant offender characteristics including problem severity, previous treatment experiences, violence risk profile and degree of psychopathic personality traits among Swedish offenders with self-reported mental health problems and problematic substance use. Based on findings from previous research, we hypothesized that severity of alcohol- and drug-related problems, psychiatric problems, employment problems and previous treatment experiences would function as facilitators to participation in substance abuse interventions (Finney & Moos, 1995; Hasin, 1994; Storbjörk & Room, 2008). We also hypothesized that interpersonal and affective psychopathic personality traits and elevated violence risk profile (i.e. higher violence risk scores) would function as barriers to such participation (Hiller et al., 1999; Hobson et al., 2000; Olver & Wong, 2011).

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2. Materials and methods 2.1. Participants The present study was conducted within the larger Swedish ongoing prospective study Mental disorder, Substance Abuse and Crime (MSAC), which explores the significance of substance abuse treatment among offenders with mental health problems and cooccurring problematic substance use (Durbeej et al., 2010). According to the Swedish Penal Code, a person convicted of a crime committed under the influence of a severe mental disorder should not be sentenced to prison, but instead referred to compulsory inpatient forensic psychiatric care. The court refers all suspects with a previous history or current indication of a mental disorder to the National Board of Forensic Medicine for a forensic psychiatric assessment (FPA), usually starting with a minor FPA, involving an hour-long forensic interview. If needed, the minor FPA is followed by a major FPA involving 4 weeks of inpatient observation by a multidisciplinary forensic psychiatric team. The study population was recruited through this system; i.e. all invited participants were under investigation for a crime, and had been identified by the legal system as individuals with past or current indication of mental health problems. Those with problematic substance use were invited to participate in the MSAC-study. Inclusion criteria for the MSAC-study were (a) having been refereed to either a minor and/or major FPA, (b) being a resident of Stockholm County (population: 1.9 million) and (c) having a record of hazardous use of alcohol and/or illicit drugs. All participants who consented to participation were invited to a baseline-interview and 3 follow-ups. The baseline-interview took place during the time for the FPA, and the first follow-up assessment was conducted shortly before release from prison or compulsory inpatient forensic psychiatric care.2 Six months later, a second follow-up assessment was administered, and the third and final follow-up took place 12 to 18 months after the second follow-up. Recruitment and follow-up assessments within the MSAC-study took place between February, 2, 2006 and January, 18, 2012. The mean time between the baseline assessment and the third follow-up assessment, and thus the length of the follow-up period within the MSAC-study, was 34.17 months, i.e. close to 3 years (range = 19–63 months, SD = 9.19). In total, 208 individuals gave their written informed consent to participate in the MSAC-study. One participant withdrew his informed consent and was deleted from the data-sets, and the study thus included 207 individuals who participated in baseline assessment. Among these, 39 individuals were still in prison or admitted to a forensic psychiatric clinic during the study time and were excluded from follow-up. In addition, 11 individuals could not be found, 10 declined further study participation, 4 died and 3 emigrated from Sweden and could thus not participate in all follow-up assessments. Accordingly, 140 individuals completed the third follow-up assessment, and were eligible for inclusion in the present study. Since the focus was on voluntary treatment participation, 6 participants were removed as they had been subjected to compulsory treatment. Thus, the sample of the present study comprised 134 MSAC-participants. 2.2. Treatment context In Sweden, two principal systems are responsible for providing substance abuse treatment: the health care system managed by the County Councils, and the social services system managed by the local municipalities. The health care system is responsible for providing specialist medical and psychiatric treatment related to substance abuse, such as detoxification, emergency services, and 2 Participants sentenced to non-institutional treatment, such as probation, participated in the first follow-up assessment 6 months after inclusion to the MSAC-study.

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pharmacological treatment. The interventions provided by the social services system include all support that does not require medical expertise; i.e. motivational interventions, individual or group counseling, and social support related to economy, family issues, and even housing if necessary. The social services collaborate with the health care system, and in more severe abuse, coordinated treatment plans are often necessary. Thus, the social services and health care systems are to be seen as complementary to one another. The fee for the individual is none or modest. For the outcome measure of this study, we included participation in two particular interventions; one from the health care system and one from the social services system. The reason for choosing these two was that both are known to include abstinence control. Given that abstinence control is a core requisite for providing substance abuse treatment, our assumption was that it could be used as a relevant proxy for willingness to participate in substance abuse treatments in general. The substance abuse interventions chosen for the purpose of this study included either a) participation in planned visits to specialized substance abuse outpatient clinics provided by the health care system and/or b) residence in housing that required control of abstinence (“dry housing”) provided by the social services system. An outpatient visit included any appointment with a counselor, nurse, psychologist, psychiatrist or case manager at an outpatient clinic. Besides regular substance abuse treatment (e.g. collecting one's medicine), it regularly includes urine tests for drug intake and breath analyses of alcohol. Living in dry housing included residence e.g. at a treatment or a supportive facility, where regular urine tests for drug intake and breath analyses of alcohol was part of the routine. With this design, we included planned health care visits and some of the housing interventions. The study participants may have had other support from the social services (e.g. low threshold housing without abstinence control, counseling, or financial support), but data on such interventions could not be collected in retrospect. 2.3. Measurements and sources of data 2.3.1. Alcohol Use Disorders Identification Test and Drug Use Disorders Identification Test Screening of participants for hazardous use of alcohol and/or illicit drugs was performed with the 10-item Alcohol Use Disorders Identification Test (the AUDIT; Saunders, Aasland, Babor, De la Fuente, & Grant, 1993), developed by the World Health Organization (WHO) and the 11-item Drug Use Disorders Identification Test (the DUDIT; Berman, Bergman, Palmstierna, & Schlyter, 2005) developed at Karolinska Institutet. The questionnaires have demonstrated good psychometric properties among Swedish offenders with mental health problems and problematic substance use as well as among Swedish drug users (Berman et al., 2005; Durbeej et al., 2010). Hazardous use of alcohol was defined as an AUDIT score of 8 or more points for men and 6 or more points for women, whereas hazardous use of illicit drugs was defined as a DUDIT score of 1 point or more for both men and women. These cut-off scores were based on the WHO recommendations for hazardous drinking (Saunders et al., 1993) and on the guiding principles of the Swedish National Board of Health and Welfare for hazardous drug use (Socialstyrelsen [The Swedish National Board of Health and Welfare], 2007). 2.3.2. The Addiction Severity Index, sixth version The participants were interviewed with the Swedish translation of the sixth version of the Addiction Severity Index (ASI-6; Cacciola, Alterman, Habing, & McLellan, 2011; Öberg, Sallmén, Berman, & Horner, 2006). The ASI is a semi-structured interview, designed for the assessment of current and prior problem severity in 9 different domains; i.e. medical, employment, alcohol, drug, legal, psychiatric, and family/social domains with the latter subdivided into family/ social problems, family/social support, and child problems. The

responses on the items that concern problematic behaviors during the last 30 days can be computed into 9 Recent Status Scores, ranging from 0 to 100. Higher scores indicate greater problem severity. According to recent studies, the ASI-6 scales demonstrate acceptable psychometric properties (Cacciola et al., 2011; Kessler et al., 2012). 2.3.3. The Historical, Clinical, Risk Management Scale The participants were also assessed with The Historical, Clinical, Risk Management Scale (HCR-20; Webster, Douglas, Eaves, & Hart, 1997) The HCR-20 is a violence risk assessment tool used for structured clinical decisions about risk for violent recidivism. It is based on file and interview information and contains 20 items that can be divided into 3 scales: Historical, Clinical and Risk. The Historical scale has 10 items that refer to static background factors of violence, such as history of mental illness, personality disorder, and substance abuse whereas the Clinical scale involves 5 items that concern current dynamic risk factors such as lack of insight or negative attitudes. In addition, the Risk scale has 5 items that refer to current dynamic risk factors present in the individuals' environment e.g. lack of personal support and exposure to stress. Each item is scored 0 to 2 to indicate if the characteristic is not present, partially present or definitely present. The total maximum score of the Historical subscale is 20 points, whereas the Clinical and Risk subscales each have a total score of 10 points. The HCR-20 has satisfactory psychometric properties and has been shown to be a robust predictor of institutional and community violence (Belfrage, 1998; Gray, Taylor, & Snowden, 2008; Webster et al., 1997). 2.3.4. The Psychopathy Checklist-Revised Psychopathic personality traits were assessed with the Swedish translation of the Psychopathy Checklist-Revised (PCL-R; Hare, 2003). The PCL-R is a semi-structured interview, which consists of 20 items, rated by a trained interviewer. On the basis of the interview as well as on institutional file records, each item is scored 0, 1, or 2 to indicate absence, partial presence, or presence of the trait or behavior referenced in the item. The total possible score for the PCL-R is 40 points. In Sweden, a cut-off score of 26 points for psychopathy has been proposed among offenders with mental health problems (Grann, Långström, Tengström, & Stålenheim, 1998). The items of the PCL-R can be divided into 4 facets (Hare, 2003). The Interpersonal facet has a total score of 8 points and includes traits such as grandiosity and manipulative behavior, whereas the Affective facet, also with a total score of 8 points, comprises traits such as lack of empathy and shallow affect. In addition, the Lifestyle and the Antisocial facet, each with total scores of 10 points, include traits such as impulsivity and proneness to boredom as well as criminal versatility and juvenile delinquency, respectively. Two of the PCL-R items (many short-term marital relationships and sexual promiscuity) do not load on any of the facets. The PCL-R has demonstrated good psychometric properties in various offender samples (Fulero, 1995; Shine & Hobson, 1997) and can be considered to reflect either a categorical or dimensional construct of psychopathy (Guay, Ruscio, Knight, & Hare, 2007). 2.3.5. Data on outpatient visits and dry housing residence Data on outpatient visits were extracted from the official registry on health care utilization in Stockholm County Council. The registry contains data on about 95% of all consumed care in the county and involves in- and outpatient treatment, i.e. the number of admissions to substance abuse treatment as well as the number of visits to public service providers of such treatment (e.g. counselors, psychologists, psychiatrists, registered nurses, or case managers). The data are divided into planned or emergency visits/admissions. Data on dry housing residence were provided by the social services system in Stockholm County through the collection of social services records, requested from the local districts in the municipalities of the

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Stockholm County. Data on outpatient visits and dry housing residence concerned the time period from the date of the first follow-up assessment, (i.e. shortly before release from prison or compulsory inpatient forensic psychiatric care), until the date of the third follow-up assessment of each participant included. The mean time between the first and third follow-up assessment, and thus the length of the treatment period within the current study, was 20.08 months (range = 11–43 months, SD = 4.32). 2.3.6. The Central Archive of the National Board of Forensic Medicine We also collected data from files of the Central Archive of The National Board of Forensic Medicine. This archive contains data on all FPA's performed in Sweden, such as court record data on index crimes; i.e., crimes committed prior to the FPA, and sentences meted out as a consequence of such crimes. 2.4. Procedure Five research assistants carried out interviews at the different assessments of the MSAC-study. The research assistants had clinical experience of compulsory inpatient forensic psychiatric care in FPA units or a B.Sc. degree in the behavioral sciences. The process of recruiting and interviewing participants to the study took place at the National Board of Forensic Medicine in Stockholm and at the Huddinge and Kronoberg remand prisons in Stockholm. Individuals who fulfilled the criteria for participating in the MSAC-study (described above) were offered study participation (see Durbeej et al., 2010). Follow-up assessments took place in quiet places of the participants' choice such as at cafés or libraries in the Stockholm city center, or in remand- or prison settings, and lasted between 1 and 3 hours. Before the MSAC-study started, all research assistants completed 2 days of training in administering the ASI-6 and 3 days of training in administering the PCL-R and the HCR-20. The training consisted of lectures on the development and use of the instruments within research and clinical settings, rules for coding and interviewing style as well as case studies and role-play during which the research assistants were able to practice the interview procedures. Given that training is an important qualification in order to produce accurate ratings and valid results for research purposes (Hare, 1998; McLellan, Luborsky, Woody, & O´Brien, 1980; Webster et al., 1997), we assumed that the research assistants were qualified to assess the participants with regard to the instruments used in the MSAC-study. 2.5. Statistical analyses Means, standard deviations, frequencies and ranges were used to describe the participants. In addition, chi-square analyses were used to test differences in prevalence, while means were compared using independent t-tests, one-way repeated measures analysis of variance (ANOVA) and Bonferroni post-hoc tests for multiple comparisons. In order to explore the relationships between the offender characteristics and participation in the substance abuse interventions, point-biserial correlations were computed. The point-biserial correlation coefficient is a statistic used to estimate the degree of a relationship between an interval or ratio scale and a dichotomous nominal scale (Brown, 1988). The interpretation of the coefficient is very similar to the more commonly reported Pearson product– moment correlation coefficient. It ranges from − 1 to + 1; a value closer to the extremes indicates a stronger relationship between the two variables. The independent variables entered in the analyses were previous experiences of substance abuse treatment, the ASI-6 Recent Status Scores reflecting problem severity in nine domains, the 3 subscales of the HCR-20, and the 4 PCL-R facets. Given that the distributions of the treatment participation variables were highly

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skewed, they were treated as dichotomous yes or no variables, defined as a) at least 3 planned visits to an outpatient clinic delivering substance abuse treatment during the study period and b) living in a residential environment that required abstinence control at least once during the study period. Our assumption was that at least 3 planned visits could indicate some stability in treatment attendance, and therefore be considered as treatment participation. The range of time spent in a residential environment that required abstinence control on one occasion varied between 1 week and 55 weeks among the participants. We also sought to explore the predictive capacity of the independent variables in relation to the dependent variables by computing 2 multiple hierarchical logistic regression models. In both models we included those independent variables that were significantly associated with the dependent variables, as shown by the point-biserial correlations. The analyses were performed in three blocks in order to explore how the different types of independent variables (i.e. the ASI-6 problem severity variables, the HCR-20 scales and the PCL-R facets) would contribute to the prediction of the treatment participation variables. As we had no specific hypotheses about the order or the importance of the independent variables in relation to the dependent variables, they were entered simultaneously in each block (Tabachnick & Fidell, 2007). All independent data were collected from the ASI-6, the HCR-20 and the PCL-R administered at the first follow-up assessment of the MSAC-study. Before computing the analyses, the data were checked for intercorrelations. The intercorrelations between independent variables in regression models should not exceed .70, and none did so in our data set. All data were analyzed using SPSS version 20. 2.6. Ethical issues All participants were given oral and written information about study participation and signed a written consent form at recruitment for the MSAC-study. Ethical permission for the study was granted by the regional ethical review board in Stockholm on December 7, 2005 (permit no. 2005/1265–31). 3. Results 3.1. Sample characteristics Among the 134 participants, 121 (90%) were men, and 13 (10%) were women. The mean age was 35 years (range = 19–62 years, SD = 10.81). Most of the participants (68%) were born in Sweden. The majority had been subjected to a minor FPA only (56%), whereas the remaining participants had been subjected to a major FPA only (25%) or to a major and a minor FPA (18%). For 2 participants, the FPA was cancelled. Further descriptions of the sample are presented in Table 1. The participants had just over 5 previous convictions on average. At recruitment to the MSAC-study, all participants fulfilled criteria for hazardous use of alcohol and/or illicit drugs. The mean number of years with regular use of alcohol and/or illicit drugs after 18 years of age was just over 6 and 7 years, respectively. The mean HCR-20 and PCL-R scores for the total sample were about 16 and 14 points, respectively. The participants had a higher mean score of the Historical HCR-20 scale, relative to the mean scores of the Clinical- and Risk HCR-20 scales (ANOVA repeated measures, F(2, 266) = 74.22, p b .001, Bonferroni's test for multiple comparisons: Historical N Risk N Clinical). In addition, they mainly had personality traits referring to the Lifestyle PCL-R facet and few traits of the Interpersonal PCL-R facet (ANOVA repeated measures, F(3, 399) = 77.22, p b .001, Bonferroni's test for multiple comparisons: Lifestyle N Antisocial, Affective N Interpersonal). A total of 15 individuals (11%) had a PCL-R score equal or higher to 26 points.

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Table 1 Criminality, sentences, psychiatric symptoms, substance use, ASI-6 problem severity scores, HCR-20-scores, and PCL-R-scores among the participants. Frequencies, means (M), standard deviations (SD), and ranges presented (n = 134).a Variables Index crimes associated with the FPAb Threats Assault Drug-related Theft Robbery Murder/Attempted murder/Manslaughter Sex-crime Traffic-related Arson Sentences in association with the index crime Institutional treatmentc Non-institutional treatmentd None (found not guilty) Prior psychiatric symptomse Felt anxious, nervous or worried most part of the day Felt depressed or down most of the day Had trouble thinking/concentrating/remembering Pushed, hit, thrown things at, or used a weapon Had serious thoughts of committing suicide Had difficulty controlling temper/urges to hit or harm Had hallucinations Attempted suicide Prior criminality and substance use Mean number of previous convictions Mean AUDIT total score Mean DUDIT total score Mean number of years with regularf use of alcohol Mean number of years with regular use of illicit drugs Mean ASI-6 problem severity scores Drug problem severity Family/Child problem severity Alcohol problem severity Psychiatric problem severity Medical problem severity Legal problem severity Employment problem severity Family/Social support problem severity Family/Social problem severity Mean HCR-20 scores Total HCR-20 Historical scale Clinical scale Risk scale Mean PCL-R scores Total PCL-R Interpersonal PCL-R facet Affective PCL-R facet Lifestyle PCL-R facet Antisocial PCL-R facet

n

% 60 41 29 22 20 13 9 9 7

45 31 22 16 15 10 7 7 5

101 30 3

76 22 2

110

82

107 103 97 90 82

80 77 72 67 62

M 5.57 14.93 16.58 6.24

71 68 SD 8.61 10.76 14.53 8.03

53 51 Range 0–64 0–39 0–44 0–35

7.28

9.33

0–40

37.83 48.14 44.73 48.97 43.81 48.19 49.13 47.94 43.73

7.25 2.32 7.05 8.87 10.78 5.34 9.71 10.53 7.56

31–59 31–60 38–66 31–68 29–71 34–72 21–67 27–73 27–66

15.91 7.72 3.97 4.72

8.15 4.38 2.45 3.64

0–31 1–18 0–10 0–10

13.87 1.52 2.87 4.66 3.22

8.17 1.57 2.02 2.83 2.62

1–33 0–6 0–7 0–10 0–10

a

Data presented according to the Central Archive of The National Board of Forensic Medicine, the sixth version of the Addiction Severity Index (ASI-6), the Alcohol Use Disorders Identification Test (AUDIT), the Drug Use Disorders Identification Test (DUDIT), the Historical, Clinical, Risk management Scale (HCR-20) and the Psychopathy Checklist-Revised (PCL-R). b Forensic psychiatric assessment. c Imprisonment or compulsory inpatient forensic psychiatric care. d Probation or fines. e Data on prior psychiatric symptoms, criminality and substance use concern the time period after 18 years of age. f More than 3 days per week.

During the treatment period, 44 individuals (33%) had a record of at least 3 planned visits to an outpatient clinic delivering substance abuse treatment, whereas 31 (23%) had resided in dry housing. Among the former, 20 individuals (45%) had also lived in dry housing, whereas 24 (55%) had no such experiences (χ 2(1, 134) = 18.35,

p b .001). Among those with less than 3 planned visits to outpatient clinics (n = 90), eleven (12%) had lived in dry housing. To establish whether the 134 individuals in the current study were representative of the entire MSAC-sample (n = 207), they were compared on relevant variables (gender, age at study recruitment, country of birth, type of index crime, sentences in association with the index crime and mean AUDIT and DUDIT total scores) with the 73 individuals that did not participate in the current study. A larger proportion of the latter was charged with murder/attempted murder/ manslaughter in association with the FPA (χ 2(1, 207) = 12.51, p b .001), and was sentenced to imprisonment or compulsory inpatient forensic psychiatric care (χ 2(1, 202) = 9.81, p b .05), relative to the former. None of the remaining comparisons yielded any significant differences, suggesting that the participants of the present study were largely representative of the entire MSAC-sample. 3.2. Problem severity, violence risk and psychopathic personality traits in relation to participation in substance abuse interventions The point-biserial correlation coefficients for the associations between the offender characteristics and participation in the substance abuse interventions are presented in Table 2. As shown, drug problem severity and employment problem severity were positively related to participation in planned visits to outpatient substance abuse clinics. In addition, drug problem severity, legal problem severity, and family/social problem severity were positively associated with dry housing residence. There was no correlation between previous treatment participation and the interventions. Positive correlations were found between the scores on the Historical and Risk scales of the HCR-20 and dry housing residence, as well as between the scores of the Interpersonal, Lifestyle and Antisocial PCL-R facets and this outcome. The Affective PCL-R facet was negatively associated with both planned outpatient visits and dry housing residence.

Table 2 Point-biserial correlations between ASI-6 problem severity variables, HCR-20 scales, PCL-R facets and a) participation in planned visits to outpatient substance abuse clinics and b) dry housing residence (n = 134).a

ASI-6 problem severity variables Drug problem severity Family/Child problem severity Alcohol problem severity Psychiatric problem severity Medical problem severity Legal problem severity Employment problem severity Family/Social support problem severity Family/Social problem severity No of previous treatment experiences for problematic substance use HCR-20 scales Historical scale Clinical scale Risk scale PCL-R facets Interpersonal PCL-R facet Affective PCL-R facet Lifestyle PCL-R facet Antisocial PCL-R facet

Participation in planned visits to outpatient substance abuse clinics

Dry housing residence

.35⁎⁎ −.08 .09 .16 .04 .09 .22⁎

.30⁎⁎ −.03 .12 .14 .11 .24⁎⁎

.07 .04 .04

.12 .01 −.01 .14 −.27⁎⁎ .07 .12

.15 .06 .30⁎⁎ .05

.27⁎⁎ .07 .18⁎ .21⁎ −.18⁎ .26⁎⁎ .33⁎⁎

⁎ p b .05. ⁎⁎ p b .01. a Data collected from the sixth version of the Addiction Severity Index (ASI-6), the Historical, Clinical, Risk management Scale (HCR-20) the Psychopathy ChecklistRevised (PCL-R), the official registry on health care utilization in Stockholm County Council, and social services records.

N. Durbeej et al. / Journal of Substance Abuse Treatment 46 (2014) 574–583 Table 3 Model I. Variables contributing to participation in planned visits to outpatient substance abuse clinics in multiple hierarchical logistic regression. B Block I Drug problem severity Legal problem severity Employment problem severity Family/Social problem severity Nagelkerke R Square = .224 Block II Drug problem severity Legal problem severity Employment problem severity Family/Social problem severity Historical scale Risk scale Nagelkerke R Square = .246 Block III Drug problem severity Legal problem severity Employment problem severity Family/Social problem severity Historical scale Risk scale Interpersonal PCL-R facet Affective PCL-R facet Lifestyle PCL-R facet Antisocial PCL-R facet Nagelkerke R Square = .368

SE

Wald

p

OR

Table 4 Model II. Variables contributing to participation in dry housing residence in multiple hierarchical logistic regression.

95 % CI for OR

.119 −.011 .070

.033 .038 .034

13.123 .080 4.294

.000 .777 .038

1.126 .989 1.072

1.056–1.201 .919–1.065 1.004–1.145

−.025

.029

.722

.395

.975

.921–1.033

.121 .006 .079

.033 .040 .035

13.089 .024 5.005

.000 .878 .025

1.128 1.006 1.082

1.057–1.205 .930–1.088 1.010–1.159

−.025

.030

.680

.410

.975

.919–1.035

.020 −.108

.052 .076

.142 2.047

.706 .153

1.020 .897

.920–1.130 .774–1.041

.114 −.012 .078

.036 .046 .035

9.759 .064 4.995

.002 .800 .025

1.120 .988 1.081

1.043–1.203 .904–1.081 1.010–1.158

−.033

.033

1.020

.313

.968

.908–1.031

.064 −.034 .381 −.499 −.019 −.054

.088 .084 .199 .150 .132 .143

.525 .167 3.668 11.136 .020 .140

.469 .683 .055 .001 .888 .708

1.066 .966 1.464 .607 .982 .948

.897–1.267 .821–1.138 .991–2.161 .453–.814 .758–1.271 .715–1.255

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B Block I Drug problem severity Legal problem severity Employment problem severity Family/Social problem severity Nagelkerke R Square = .239 Block II Drug problem severity Legal problem severity Employment problem severity Family/Social problem severity Historical scale Risk scale Nagelkerke R Square = .273 Block III Drug problem severity Legal problem severity Employment problem severity Family/Social problem severity Historical scale Risk scale Interpersonal PCL-R facet Affective PCL-R facet Lifestyle PCL-R facet Antisocial PCL-R facet Nagelkerke R Square = .426

SE

Wald

p

OR

95 % CI for OR

.061 .051 .058

.033 .040 .039

3.471 1.601 2.200

.062 .206 .138

1.063 1.052 1.060

.997–1.133 .972–1.139 .981–1.145

.075

.032

5.636

.018

1.078

1.013–1.148

.054 .036 .043

.033 .042 .041

2.693 .732 1.113

.101 .392 .292

1.056 1.037 1.044

.990–1.126 .955–1.126 .964–1.132

.075

.032

5.485

.019

1.078

1.012–1.148

.102 .017

.058 .065

3.100 .073

.078 .787

1.107 1.018

.989–1.239 .896–1.155

.019 .028 .030

.039 .052 .038

.250 .293 .604

.617 .589 .437

1.020 1.028 1.030

.945–1.100 .929–1.139 .956–1.110

.085

.037

5.394

.020

1.089

1.013–1.170

.076 .066 .137 −.660 .084 .214

.103 .072 .229 .198 .144 .160

.548 .829 .361 11.129 .342 1.802

.459 .363 .548 .001 .559 .179

1.079 1.068 1.147 .517 1.088 1.239

.882–1.320 .927–1.231 .733–1.796 .351–.762 .820–1.443 .906–1.694

B-values, Standard Errors (SE), Wald chi-square values, p-values, Odds Ratios (OR), 95% Confidence Intervals (CI) and Nagelkerke R Squares presented (n = 134).

B-values, Standard Errors (SE), Wald chi-square values, p-values, Odds Ratios (OR), 95% Confidence Intervals (CI) and Nagelkerke R Squares presented (n = 134).

In order to explore the predictive capacity of those offender characteristics that had been significantly correlated with the outcomes, we computed 2 multiple hierarchical logistic regression models. The results from these analyses are presented in Tables 3 and 4. As shown in the third block of both models, drug problem severity (OR: 1.12) and employment problem severity (OR: 1.08) predicted planned visits to outpatient substance abuse clinics, whereas family/ social problem severity (OR: 1.09) predicted dry housing residence. Also, there were negative associations between the Affective PCL-R facet and participation in both planned outpatient visits (OR: .61) and dry housing residence (OR: .52). Moreover, the explained variance increased across the three blocks of the models. In block I of the first model, the Nagelerke R Square was .22 indicating that the ASI-6 problem severity variables alone explained 22% of the variance of participation in planned visits to outpatient substance abuse clinics. The explained variance increased to 25% when the HCR-20 scales were entered and to 37% when the PCL-R facets were added. Also, in the second model, the explained variance increased to 43% when the PCL-R facets were added to the ASI-6 and HCR-20 variables for the prediction of dry housing residence.

point-biserial correlations, problem severity regarding drugs and employment was associated with participation in planned outpatient visits, and problem severity regarding drugs, legal and family/social areas was associated with dry housing residence. These findings are in line with previous research that has found high levels of drug-related problems, employment problems and criminal behavior, among those who participate in substance abuse treatment (Finney & Moos, 1995; Storbjörk & Room, 2008; Tucker, 1995). We also found significant correlations between higher risk of future violence (both historical and current risk factors) and dry housing residence. With regard to psychopathic personality traits, 3 of the PCL-R facets (Interpersonal, Lifestyle and Antisocial) were positively correlated with living in dry housing. These findings contradict previous studies suggesting that both certain psychopathic traits and higher violence risk scores are associated with poor treatment participation (Alterman et al., 1998; Hiller et al., 1999; Richards et al., 2003). Contrary to our predictions, the number of previous treatment experiences was not significantly correlated with the outcomes. Our results indicate that this particular population of individuals with a problematic criminal track record, problematic substance use and mental health problems, may behave similarly to other patient groups with regard to substance abuse treatment participation (Finney & Moos, 1995; Storbjörk & Room, 2008; Tucker, 1995). The Swedish treatment system for problematic substance use seems to also reach those with risk factors of future violence and certain psychopathic personality traits. As shown by the regression analyses, drug, employment and family/social problem severity predicted participation in the substance abuse interventions. These factors may be considered as

4. Discussion The present study sought to explore the associations between various offender characteristics and participation in substance abuse interventions among offenders with mental health problems and problematic substance use in the Stockholm County. As shown by the

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potential facilitators to substance abuse interventions; a finding that has been supported by research on other populations (Finney & Moos, 1995; Hasin, 1994; Storbjörk & Room, 2008). However, some personality traits seem to have been of importance for poor treatment participation. Individuals with a higher degree of affective psychopathic traits, i.e. lack of empathy and shallow affect, were less prone to participate in the chosen interventions, relative to those with fewer such traits. Such traits may therefore be considered as potential barriers to this type of substance abuse treatment participation. Our results are in line with one previous study showing that the Affective PCL-R facet predicts treatment drop-out (Olver & Wong, 2011). As suggested by previous research, affective psychopathic personality traits tend not to be particularly predictive of criminal recidivism (Wallinius et al., 2012; Walters, Grann, Knight, & Dahle, 2008). In addition, there are no specific treatment approaches aimed to reduce such traits, and they may not even be amenable to treatment and change (Wong, 2000). According to Olver and Wong (2011), such traits do not need to be directly targeted in order to reduce the risk of re-offending, but they could be considered as important in order to prevent treatment drop-out or poor treatment participation. Given that offenders with affective psychopathic traits may have difficulties in establishing a therapeutic alliance with treatment staff, potentially leading to poorer treatment participation, such traits could be properly managed in treatment settings (Olver & Wong, 2011; Thornton & Blud, 2007). Efficient management of such traits could imply delivery of treatment programs that aim to establish a working relationship highly focused on tasks and goals (i.e. a more psychoeducative approach) rather than programs that focus on the affective bond between the patient and the treatment provider. As suggested by Olver and Wong (2011), cognitive-behavioral therapy (CBT) interventions could be beneficial for those with affective psychopathic personality traits in order to ensure treatment participation and to produce positive outcomes, rather than unstructured and nondirective treatment approaches. A parallel can also be made with treatment for patients suffering from borderline personality disorder, for which dialectical behavior therapy (DBT; Linehan, 1993) has been found useful. Patients with affective psychopathic personality traits tend to be callous but easily offended by treatment providers, and thereby difficult to engage in treatment (Thornton & Blud, 2007). Research describing an adaptation of DBT for psychopathic offenders has proposed that validation, i.e. the treatment provider being non-judgmental and non-confrontational, seeing the patients' point of view and communicating to the patient that his/her thoughts and feelings are valid, is an important treatment component that may facilitate treatment engagement, treatment retention and positive outcomes in this population (Galietta & Rosenfeld, 2012; Rosenfeld, 2011). The effectiveness of DBT- and CBTinterventions has been established among individuals with problematic substance use (Linehan et al., 1999; Magill & Ray, 2009), but has, according to our knowledge, not yet been established among offenders with psychopathic personality traits. Thus, this could be a topic for future studies. It has been recommended that personality traits should be routinely assessed in clinical settings, and that such traits should be taken into account for treatment delivery (Gudonis, Derefinko, & Giancola, 2009; Harkness & Lilienfeld, 1997; Staiger, Kambouropoulos, & Dawe, 2007). Assessments of affective psychopathic personality traits may be important as such traits may indicate treatment dropout or low participation in treatment. Such traits are commonly evaluated in individuals with high risk of criminal recidivism, but they could also be assessed in those with low risk of re-offending given the relationship between such traits and treatment behavior. The administration of the PCL-R for such assessment requires specialized training, and the instrument is generally used mainly for high-risk offenders within correctional settings (Hare, 2003). Thus, the use of the PCL-R on patients in regular clinical settings may be inappropriate.

However, the Psychopathic Personality Inventory-Revised (PPI-R; Lilienfeld & Widows, 2005); a self-report measure aimed to assess psychopathic personality traits in various populations and settings, could be useful for this purpose. In addition, assessments of personality disorders through instruments such as the Structured Clinical Interview for DSM-IV Axis II Disorders (SCID-II; First, Spitzer, Gibbon, & Williams, 1995) could serve as an alternative and give indications of personality traits that need to be further explored. As mentioned above, substance abuse treatment has been associated with positive outcomes such as lower rates of re-offending and reduced substance use (Bukten et al., 2012; Prendergast et al., 2002). Thus, such treatment is important to offenders with problematic substance use regardless of type of personality traits. For offenders with psychopathic personality traits, high risk of criminal recidivism, and lack of motivation to participate in treatment, extensive diagnostic procedures and thorough assessments may aid the delivery of appropriate substance abuse interventions. To increase treatment retention for these individuals, outpatient, forensic or correctional settings providing substance abuse treatment might seek inspiration from treatment contexts such as DBT or CBT. Treatment that merely targets affective psychopathic personality traits may, however, be less efficient given that such traits may neither be amenable to treatment and change, nor predict criminal recidivism (Wallinius et al., 2012; Walters et al., 2008; Wong, 2000). It should be noted that the individuals in our study population did not have extremely high psychopathy and violence risk scores, despite the fact that they had committed varying types of crimes. Regardless, these individuals suffered from various psychiatric symptoms and problematic substance use and are most likely quite common clients in services that provide substance abuse treatment and/or social support. Thus, they are of great concern to society. Due to their complex treatment needs, coordinating treatment interventions for this population may be challenging (Taylor, McMurran, & Reiss, 2007), but without proper treatment, these individuals are highly likely to recidivate into criminal behavior (Hartwell, 2004; Lindqvist, 2007). Delivery of substance abuse treatment to this particular population may be beneficial in order to reduce both their risk of criminal recidivism and problematic substance use (Gumpert et al., 2010; Jaffe, Du, Huang, & Hser, 2012; Sacks, Chaple, Sacks, McKendrick, & Cleland, 2012). Treatment participation and retention may be associated with positive outcomes, which in turn may lead to an increased well-being and safety for citizens in society. 4.1. Strengths and limitations The conclusions that can be drawn from the results of the present study are limited due to the observational study design, and the relationships between the independent and dependent variables should be considered as correlational rather than causal. Many of the ORs in the logistic regression analyses were close to 1, e.g. for drug-, employment-, and family/social problem severity in relation to the outcomes, and thus, they suggested a small increase in probability of intervention participation associated with the independent variables. Given that the problem severity variables were continuous ranging from 1 to 100, we expected the ORs to be small since they represent the change in odds per unit increase of the variables. Research has highlighted the importance of considering p-values to determine significance (Szumilas, 2010), and we therefore interpreted variables with p-values below .05 as significantly associated with the outcomes and thus as predictors and potential facilitators to the interventions. A larger study group may have improved the results, as well as controlling for factors such as the motivation to change. Inclusion of individuals with higher PCL-R and HCR-20 scale scores might also have produced larger ORs, relative to those obtained. We did not control for intake of psychiatric medications or medication adherence. Given that such factors have been positively associated with

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substance abuse treatment participation among individuals with cooccurring mental health problems and problematic substance use (Kaminer, Tarter, Bukstein, & Kabene, 1992; Magura, Laudet, Mahmood, Rosenblum, & Knight, 2002), they might have predicted participation in the interventions examined in study. At the time of the third follow-up, some of the participants in the MSAC-study were still in prison or compulsory inpatient forensic psychiatric care (n = 39). It is likely that these individuals had committed more serious types of crimes or shown higher PCL-R or HCR-20 total scores, in comparison with the participants available for the present study. The participants mainly had personality traits referring to the Lifestyle PCL-R facet and fewer traits of the Interpersonal PCL-R facet. In addition, their violence risk scores were not extremely high. Accordingly, our participants should be considered as an intermediate sample; i.e. not truly “psychopathic” or as the highest risk group of offenders per se. The results should thus be interpreted in such a way that they concern a group of offenders with some psychopathic personality traits, a medium risk of future violence, and a problematic criminal history. The findings may still be relevant, since such offenders often are present in the community (i.e. they spend shorter time periods in closed institutions) and they depend on the health care and social service systems to assist them in their readjustment process. Individuals with higher PCL-R scores may have behaved differently with regard to treatment participation, and a different study design could have been needed for the inclusion of such individuals (i.e. assessing the degree to which prisoners in high secure institutions participated in interventions during their time in prison). Hypothetically, given that only the Affective PCL-R facet was negatively associated with the outcome variables, the total score on this facet may be of importance for poor treatment participation, rather than the total PCL-R score per se. Research assistants collecting the data received formal ASI-6, PCLR and HCR-20 training prior to participant recruitment. No reliability testing (e.g. test-retest reliability or inter-rater reliability) of the assessments was conducted. Previous research has, however, demonstrated adequate reliability of the PCL-R, the HCR-20 as well as the nine problem severity domains of the ASI-6, reflecting problematic behaviors during the last 30 days (Douglas, Ogloff, & Hart, 2003; Fulero, 1995; Kessler et al., 2012). As far as we are aware, there are no studies specifically exploring the psychometric properties of other areas of the ASI-6, such as the items covering problematic behaviors after 18 years of age. Future studies should explore the reliability and validity of ASI-6 areas other than the nine problem scales, in order to draw conclusions about the psychometric properties of the full instrument. Some strengths of the present study should also be emphasized. By using formal records for assessing the dependent variables, the outpatient treatment visits and the dry housing residence could be firmly established; i.e., this information was not based on self-reportdata. It was not possible to control for more specific details about additional types of interventions, e.g. pharmacological treatment or housing without abstinence control. Although our dependent variables did not concern participation in a defined substance abuse treatment program per se, they involved the willingness to accept control of abstinence in an outpatient as well as in a residential setting. As mentioned, abstinence control is often a prerequisite for any other specific substance abuse treatment, and thus we used it as a relevant proxy for willingness to accept the conditions related to substance abuse treatment interventions in general. As far as we are aware, no previous study has explored the relationship between various offender characteristics and participation in substance abuse treatment in a similar population, but some studies have explored the relationship between psychopathic personality traits and treatment behavior in a civil setting (Alterman et al., 1998; Skeem, Monahan, & Mulvey, 2002). Thus, our study can be considered to contribute to this body of research. Finally, our

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participants were followed during a relatively long time. This should be considered a methodological strength, given the challenges related to maintaining contact with similar study populations, and that similar studies have had shorter follow-up periods (Jaffe et al., 2012; McLellan, McKay, Forman, Cacciola, & Kemp, 2005; Sacks et al., 2012). 4.2. Conclusions In a sample of offenders with both mental health problems and problematic substance use, those who did participate in the substance abuse interventions displayed high problem severity with regard to substance use, legal affairs, employment, and family. Thus, they did not seem to stand out as different from other study populations who participate in substance abuse treatment. In addition, those who participated in such interventions had higher risk of future violence and some psychopathic personality traits (i.e. interpersonal, lifestyle and antisocial traits). One possible conclusion is that the Swedish treatment system for problematic substance use also reaches this group of substance users. However, even though drug, employment and family/social problem severity seemed to function as facilitators to substance abuse interventions, the results indicated that affective psychopathic personality traits were related to lower participation in outpatient treatment and living in dry housing. Affective psychopathic personality traits could therefore be considered as potential barriers to substance abuse treatment and as factors related to a higher risk of drop-out. Both from a societal as well as an individual perspective, it is important that the treatment system seeks to optimize its outcomes. Offenders with mental health problems and problematic substance use should be offered interventions in order to increase their well-being and reduce their criminal behavior, and interventions that target problematic substance use may be beneficial for this purpose. In settings that may encounter individuals with pronounced affective psychopathic personality traits, it might be useful to assess affective personality traits and adapt the interaction with patients according to approaches used in treatment programs such as DBT or CBT. Acknowledgments Preparation of this article was financially supported by the Swedish Council for Working Life and Social Research (Grant 2005/ 5:11). The authors thank Professor John Monahan, University of Virginia, for support and advice. References Alterman, A. I., Rutherford, M., Cacciola, J. S., McKay, J., & Boardman, C. (1998). Prediction of 7 months methadone maintenance treatment response by four measures of antisociality. Drug and Alcohol Dependence, 49, 217–223. Belfrage, H. (1998). Implementing the HCR-20 scheme for risk assessment in a forensic psychiatric hospital: Integrating research and clinical practice. Journal of Forensic Psychiatry, 9, 328–338. Berman, A. H., Bergman, H., Palmstierna, T., & Schlyter, F. (2005). Evaluation of the Drug Use Disorders Identification Test (DUDIT) in criminal justice and detoxification settings and in a Swedish population sample. European Research Addiction, 11, 22–31. Berman, A. H., Wennberg, P., & Källmén, H. (2012). AUDIT och DUDIT – Identifiera problem med alkohol och droger. [AUDIT and DUDIT- Identifying problematic alcohol and drug use]. Stockholm: Gothia Förlag. Brown, J. D. (1988). Understanding research in second language learning: A teacher's guide to statistics and research design. Cambridge: Cambridge University Press. Bukten, A., Skurtveit, S., Gossop, M., Waal, H., Stangeland, P., Havnes, I., et al. (2012). Engagement with opioid maintenance treatment and reductions in crime: A longitudinal national cohort study. Addiction, 107, 393–399. Cacciola, J. S., Alterman, A. I., Habing, B., & McLellan, A. T. (2011). Recent status scores for version 6 of the Addiction Severity Index (ASI-6). Addiction, 106, 1588–1602. Coid, J., & Ullrich, S. (2010). Antisocial disorder is on a continuum with psychopathy. Comprehensive Psychiatry, 51, 426–433. Condelli, W. S., & De Leon, G. (1993). Fixed and dynamic predictors of client retention in therapeutic communities. Journal of Substance Abuse Treatment, 10, 11–16. Douglas, K. S., Guy, L. S., & Hart, S. D. (2009). Psychosis as a risk factor for violence to others: A meta-analysis. Psychological Bulletin, 135, 679–706.

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