Journal of Personality Disorders, 29(6), 735–754, 2015 © 2015 The Guilford Press

THE PREVALENCE OF COMORBID PERSONALITY DISORDERS IN TREATMENT-SEEKING PROBLEM GAMBLERS: A SYSTEMATIC REVIEW AND META-ANALYSIS Nicki A. Dowling, PhD, S. Cowlishaw, PhD, A. C. Jackson, PhD, S. S. Merkouris, GDipPsych, K. L. Francis, MSci, and D. R. Christensen, PhD The aim of this study was to systematically review and meta-analyze the prevalence of comorbid personality disorders among treatmentseeking problem gamblers. Almost one half (47.9%) of problem gamblers displayed comorbid personality disorders. They were most likely to display Cluster B disorders (17.6%), with smaller proportions reporting Cluster C disorders (12.6%) and Cluster A disorders (6.1%). The most prevalent personality disorders were narcissistic (16.6%), antisocial (14.0%), avoidant (13.4%), obsessive-compulsive (13.4%), and borderline (13.1%) personality disorders. Sensitivity analyses suggested that these prevalence estimates were robust to the inclusion of clinical trials and self-selected samples. Although there was significant variability in reported rates, subgroup analyses revealed no significant differences in estimates of antisocial personality disorder according to problem gambling severity, measure of comorbidity employed, and study jurisdiction. The findings highlight the need for gambling treatment services to conduct routine screening and assessment of cooccurring personality disorders and to provide treatment approaches that adequately address these comorbid conditions.

A diverse range of options for the treatment of problem gambling are available, with varying levels of empirical support. A Cochrane review (Cowlishaw et al., 2012) provided some evidence for the short-term efficacy of cognitivebehavioral therapies (CBT) and the efficacy of motivational interviewing (MI) This article was accepted under the editorship of Robert F. Krueger and John Livesely. From School of Psychology, Deakin University, Australia (N. A. D., S. S. M.); Problem Gambling Research and Treatment Centre, University of Melbourne, Australia (N. A. D., A. C. J., K. L. F., D. R. C.); School of Psychological Sciences, Monash University, Australia (N. A. D.); Centre for Academic Primary Care, Bristol University, U.K. (S. C.); and Faculty of Health Sciences, University of Lethbridge, Canada (D. R. C.). Azusa Umemoto assisted in scanning the titles and abstracts of the retrieved articles for inclusion. Address correspondence to Nicki A. Dowling, PhD, Associate Professor of Psychology, School of Psychology, Faculty of Health, Deakin University, Melbourne Burwood Campus, 221 Burwood Highway, Burwood, VIC, 3125, Australia; E-mail: [email protected]

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therapy in terms of reduced gambling behavior compared with control conditions. Although the studies on which these conclusions are based provide generally low-quality standards of evidence and no treatment satisfies the standards for classification as an empirically supported intervention (Chambless & Hollon, 1998), an evidence-based clinical practice guideline has provided one low-grade recommendation involving the cautious use of naltrexone, and several higher grade rec­om­men­dations for the use of CBT, MI therapies, and practitioner-delivered interventions (Thomas et al., 2011). The treatment of problem gambling is complicated by substantial comorbidity with other psychopathological disorders. Narrative reviews suggest that treatment-seeking problem gamblers display high rates of comorbid psychopathological conditions, including alcohol and other substance use disorders, mood and anxiety disorders, other impulse control disorders, and personality disorders (Crockford & El-Guebaly, 1998; Petry, 2005; Westphal & Johnson, 2007). It is important, however, to systematically review the empirical literature because such narrative reviews are unlikely to be based on all the available evidence. The findings from narrative reviews suggest that prevalence estimates of comorbid personality disorders in treatment-seeking problem gamblers vary widely. There is therefore a need to explore factors that may explain these variations. There is some evidence that pathological gamblers display higher rates of comorbid personality disorders than subclinical pathological gamblers (Lorains, Cowlishaw, & Thomas, 2011) and that self-report inventories produce higher rates than clinical interviews (Bagby, Vachon, Bulmash, & Quilty, 2008; Blaszczynski & Steel, 1998). There is also some indication that problem gamblers attending residential services report higher rates than those attending outpatient services (Blaszczynski & Steel, 1998; Petry, 2005) and that rates may be affected by region (Lorains et al., 2011; Specker, Carlson, Edmonson, Johnson, & Marcotte, 1996). The investigation of comorbid personality disorders in treatment-seeking problem gamblers allows for an enhanced understanding of individual treatment needs. Emerging evidence suggests that treatment-seeking problem gamblers with comorbid personality disorders have more complex clinical profiles than those without this comorbidity. These profiles are characterized by longer gambling histories, increased gambling severity, more gambling-related consequences, higher impulsivity, higher psy­ cho­ pathological symptoms, more substance use difficulties, and more medical problems (Blaszczynski & McConaghy, 1994; Blaszczynski & Steel, 1998; Blaszczynski, Steel, & McConaghy, 1997; Grall-Bronnec et al., 2011; Kruedelbach et al., 2006; Pietrzak & Petry, 2005). Most of these findings relate to antisocial personality disorder (Blaszczynski & McCon­ aghy, 1994; Blaszczynski & Steel, 1998; Blaszczynski et al., 1997; Pietrzak & Petry, 2005) with few findings relating to other personality disorders (Blaszczynski & Steel, 1998). Even when multiple disorders within the one individual are etiologically independent, the presence of comorbid personality disorders in people

REVIEW OF PERSONALITY DISORDERS IN PROBLEM GAMBLERS737

seeking gambling treatment has implications for individual case formulation, treatment planning and selection, the proposed objectives and expectations of the selected treatment, the level of structure and limit-setting required, and the length of treatment (Blaszczynski & Steel, 1998; Echeburua & Fernandez-Montalvo, 2008; Kruedelbach et al., 2006). Personality disorder comorbidity may also have a negative effect on treatment compliance and completion, treatment success, likelihood of relapse, and number of treatment attempts (Blaszczynski & Steel, 1998; Kruedelbach et al., 2006; Ledgerwood & Petry, 2006; Pelletier, Ladouceur, & Rheaume, 2008). Blaszczynski and Steel (1998) argue that comorbid personality disorders exacerbate the poor treatment motivation, resistance in therapy, denial of problems, and externalization of blame characteristic of problem gamblers. Despite the potential impact of comorbid personality disorders, their relevance to treatment outcomes for problem gambling has received little empirical attention. Pelletier et al. (2008) found that the presence of a comorbid Cluster B disorder was a significant predictor of dropout in a sample of problem gamblers seeking CBT. Ledgerwood and Petry (2010) found that a subtype of treatment-seeking problem gamblers with a high likelihood of antisocial personality disorder experienced greater gambling severity throughout Gamblers Anonymous and/or CBT, but demonstrated similar patterns and rate of treatment response to other subtypes. The aims of the current study are to (a) evaluate the prevalence of comorbid personality disorders among problem gamblers seeking treatment using meta-analytic techniques, (b) explore the factors that may explain the variability in the prevalence estimates of these comorbid personality disorders using subgroup analyses, and (c) examine whether findings were robust to the quality of the study methodologies using sensitivity analyses.

METHOD In this systematic review, the terms pathological gambling and disordered gambling are used to describe the diagnostic classifications in the fourth and fifth editions of the Diagnostic and Statistical Manual of Mental Disorders, respectively (American Psychiatric Association [APA], 2000, 2013), and problem gambling is used to describe any gambling that leads to adverse consequences for the gambler, others, or the community (including pathological or disordered gambling) (Neal, Delfabbro, & O’Neil, 2005). The methodology employed in this review is compliant with the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA; Moher, Liberati, Tetzlaff, & Altman, 2009) and the guidelines for the Meta-analysis of Observational Studies in Epidemiology (MOOSE; Stroup et al., 2000). SEARCH STRATEGY A systematic search was conducted for studies that provided prevalence estimates of psychopathological disorders in individuals seeking psycho-

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logical and/or pharmacological treatment for the index condition of problem gambling (including pathological or disordered gambling). This search procedure comprised a number of strategies. Electronic databases, including Medline, PsycInfo, EMBASE, and CINAHL, were searched. A number of specific journals that were not indexed in the electronic databases were also manually examined. These included Gambling Research (2003 onwards), International Gambling Studies (2001–2003) and Journal of Gambling Issues (2000–2006). Finally, the reference lists of all included studies and several narrative reviews were also searched manually. The search terms used incorporated a combination of keywords and wildcards relating to problem, disordered, or pathological gambling and treatment, therapy, or interventions. The search was restricted to articles published from January 1990 to August 2011, consistent with the development of the first standardized and validated assessment instrument for the identification of problem gambling in clinical settings (Lesieur & Blume, 1987). A detailed description of the search strategy is provided in Appendix 1.

INCLUSION CRITERIA Studies were considered eligible for the current review if they met the following inclusion criteria: (a) The study sample comprised adults recruited from treatment services where problem gambling is the index condition or clinical trials of gambling treatment for problem gamblers recruited from these services or the community. Gambling treatment included any treatment primarily delivered for the index condition of problem gambling, including psychological treatments (including self-help and Gamblers ­ Anonymous) or pharmacological treatments. These treatments could be delivered in any setting, including specialist gambling services, addiction services, impulse control disorders services, or mental health services. They could be delivered in any modality, including outpatient, residential, online, or telephone. Studies were not excluded on the basis of theoretical orientation, setting, modality, or method of delivery of gambling treatment. (b) The study provided an estimate of the prevalence of one or more psychopathological conditions that correspond to a DSM-IV diagnosis (APA, 2000) identified using standardized and validated self-report measures or clinical interviews. (c) The full-text report was available in English. (d) The study was reported in a complete manuscript outlining original work published in a peer-reviewed journal from 1990 to 2011. Studies were not eligible if they (a) applied inclusion or exclusion criteria (for participant admission to the study) based on DSM-IV diagnostic conditions (e.g., a clinical trial that excluded participants on the basis of all current Axis I disorders); studies that excluded participants on the basis of conditions that preclude completion of assessment measures or treatment (e.g., cognitive impairment, such as intellectual disability, delirium, dementia, or amnesia; or acute/uncontrolled psychopathological disorders, such as psychotic disorder or suicidality) were included; (b) assessed

REVIEW OF PERSONALITY DISORDERS IN PROBLEM GAMBLERS739

clinical characteristics that do not correspond to DSM-IV diagnostic conditions (e.g., impulsivity, suicidality, personality traits, substance use, sensation seeking); or (c) failed to provide sufficient data (e.g., providing only means or standard deviations, combining prevalence estimates for multiple comorbid disorders, or failing to identify the measure employed). Where there were multiple articles based on the same sample: (a) only the study with the larger sample was included when a larger sample in one study subsumed a smaller sample in another study, (b) only the study with the most prominently reported prevalence data was reported when two studies reported the same prevalence data from the same sample, and (c) both studies were included and are listed together in the table of included studies (Table 1) when two studies with the same sample reported different prevalence data. Data from each sample were included only once in any given analysis.

SEARCH RESULTS A PRISMA flow diagram of the search results is displayed in Appendix 2. The search identified 3,587 citations after removal of duplicate records. The title and abstracts of these records were independently reviewed for inclusion by two separate authors. The full texts of the 257 articles that were deemed potentially eligible were retrieved and 42 studies, published in 46 articles, met the inclusion criteria. Of these, 15 studies, published in 16 articles, provided prevalence estimates for personality disorders and are reported in this article. Prevalence estimates for DSM-IV Axis I disor-

TABLE 1. Characteristics of Included Studies

Study Blaszczynski & McConaghy (1994) Blaszczynski & Steel (1998) Echeburua & FernandezMontalvo (2008) Grall-Bronnec et al. (2011) Ibanez et al. (2001) Jimenez-Murcia et al. (2009) Kerber et al. (2008) Kroeber (1992) Kruedelbach et al. (2006) Ledgerwood & Petry (2010) Pelletier et al. (2008) Petry & Steinberg (2005) Pietrzak & Petry (2005) Sander & Peters (2009) Specker, Carlson, Christenson, & Marcotte (1995)/ Specker et al. (1996) NR: Not reported.

Country

Sample Size (n)

Average age (years)

Gender (% male)

Study Type (Treatment or Trial)

Restriction to Pathological Gamblers

Australia Australia

306  82

38.4 38.0

 89  73

treatment treatment

yes yes

Spain France Spain Spain U.S. Germany U.S. U.S. Canada U.S. U.S. Germany

 50  84  69 498  40  43 162 229 100 149 237 281

NR 41.8 NR 41.5 62.0 32.2 46.7 44.8 42.7 47.6 45.0 38.2

100  86  68  88  63  98  98  45  72  48  56  88

treatment treatment treatment treatment treatment treatment treatment trial treatment treatment trial treatment

yes no yes yes no no yes yes yes no yes yes

U.S.

 40

41.1

 63

treatment

yes

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ders were provided in 36 studies, published in 39 articles, and are reported in a separate article.

DATA EXTRACTION The first author (N. A. D.) extracted data from the included studies. In most cases, the prevalence estimate was available from the primary study. In other instances, it was necessary to combine findings reported for separate groups (e.g., males and females) to produce total sample prevalence rates. To ensure the data extraction was accurate, a third of the articles (33%; k = 15) were randomly chosen for double data extraction by two independent reviewers (A. C. J. and K. L. F.). The interrater agreement across the multiple reviewers was 98.2%.

DATA ANALYSIS Meta-analyses. Findings from primary studies were synthesized in metaanalyses using the Comprehensive Meta-Analysis program (Version 2.0; Borenstein, Hedges, Higgins, & Rothstein, 2009). A series of separate meta-analyses were conducted to provide the current best estimate of the prevalence of comorbid personality disorders in treatment-seeking problem gamblers, all using a random effects model. When differences across studies are attributed mainly to sampling error, a random effects analysis provides an estimate of the weighted mean effect and a 95% confidence interval (CI; which indicates the precision of this estimate). The I 2 statistic is also produced and indicates the amount of variation across studies due to true differences (heterogeneity) rather than chance (sampling error), and is expressed as a proportion (%) of the total observed variance. This statistic ranges from 0% to 100%, whereby values of 25%, 50%, and 75% are tentatively suggested to represent low, moderate, and high levels of heterogeneity, respectively (Higgins, Thompson, Deeks, & Altman, 2003). Subgroup Analyses. The observation of heterogeneity across studies precipitated consideration of study characteristics that could explain these between-study differences. Only antisocial personality disorder had a sufficient number of primary studies available (10 or more) to conduct subgroup analyses to examine potential sources of heterogeneity. This involved the production of separate estimates of summary effect (with 95% CIs) for subgroups of studies. Significant differences were assumed when the confidence intervals did not overlap (Hunter & Schmidt, 2004). Based on previous literature, several study characteristics potentially explaining the observed variance were identified a priori. These were: (a) gambling problem severity (pathological gamblers compared to problem gamblers); (b) the measure of comorbidity employed (clinician-administered interviews compared to self-report questionnaires); (c) the type of treatment facility (outpatient treatment services only compared to residential treatment services only); and (d) the jurisdiction in which the study was con-

REVIEW OF PERSONALITY DISORDERS IN PROBLEM GAMBLERS741

ducted (treatment services located in the United States compared to treatment services located in Europe); other jurisdictions were not included in the subgroup analyses because of an insufficient number of studies. Sensitivity Analyses. As recommended by experts in the area of risk of bias assessment (Stroup et al., 2000), sensitivity analyses were conducted to examine whether findings were robust to the quality of the methodological approaches of the included studies. For the purpose of these analyses, the studies were sequentially limited to (a) observational studies of treatment in naturalistic settings (versus clinical trials, which were excluded), and (b) random samples or recruitment of consecutive admissions (versus self-selected samples or studies failing to indicate sampling strategies, which were excluded). These analyses were conducted for all types of comorbidity, irrespective of number of studies.

STUDY AND SAMPLE CHARACTERISTICS The characteristics of the primary studies included in this review are presented in Table 1. The sizes of the samples ranged from 40 to 498 (M = 158.0, SD = 130.7, median = 100). The average age of study participants ranged from 32.2 to 62.0 years (M = 42.4, SD = 7.2, median = 41.7) and the proportion of males in the samples ranged from 45% to 100% (M = 75.6%, SD = 18.3, median = 73). Most samples were restricted to pathological gamblers only (73.3%) who were treated in gambling services (93.3%) and recruited from treatment services, not trials (86.7%). Most samples were recruited from the United States (40.0%) and Europe (40.0%), and most studies (73.3%) were published between 2001 and 2011. Less commonly reported data were the problematic gambling activity (60.0% mixed, 40.0% not reported), the type of treatment facility (33.3% outpatient facilities, 13.3% residential facilities, 26.7% recruitment from multiple types of facilities, 26.7% not reported), the type of treatment delivered (33.3% psychological treatments, 13.3% recruitment from multiple types of treatments, 53.3% not reported), and the method of participant recruitment (66.7% consecutive, 20.0% other, 13.3% not reported). One third of studies (k = 5, 33.3%) indicated that they excluded participants who were unable to complete assessment measures or treatment. A subgroup analysis revealed that there was no significant difference in the prevalence estimates for antisocial personality disorder between studies that excluded participants on this basis and those that did not.

RESULTS META ANALYSES Any Personality Disorder. Prevalence estimates for any personality disorder were provided by nine studies (Table 2). There was a weighted mean effect of 47.9% for any personality disorder, with very high between-study heterogeneity.

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TABLE 2. Prevalence of Any Personality Disorder in Treatment-Seeking Problem Gambling Samples Comorbidity Measure

Any Personality Disorder (%)

PDQ-R IPDE SCID (DSM-III-R) PDQ-4 Clinical diagnosis (DSM-III-R) SCID (DSM-III-R) SCID (DSM-IV ) Clinical diagnosis (DSM-IV/ICD-10) SCID (DSM-III-R)

93.0 32.0 42.0 60.0 35.9 61.1 64.0 12.4 25.0

Study Blazczynski & Steel (1998) Echeburua & Fernandez-Montalvo (2008) Ibanez et al. (2001) Kerber et al. (2008) Kroeber (1992) Kruedelbach et al. (2006) Pelletier et al. (2008) Sander & Peters (2009) Specker et al. (1996) Summary effect (95% CI)

47.9 (29.8, 66.7)

I (%)

95.54

2

PDQ-R: Personality Disorder Questionnaire-Revised, IPDE: International Personality Disorders Examination, SCID (DSM-III-R): Structured Clinical Interview for DSM-III-R, PDQ-4: Personality Disorder Questionnaire-4, SCID (DSM-IV): Structured Clinical Interview for DSM-IV.

Cluster A Disorders. Prevalence estimates for Cluster A personality disorders were provided by eight studies (Table 3). There was a weighted mean effect of 6.1% for any Cluster A disorder. For specific Cluster A disorders, the highest weighted mean effect was for paranoid personality disorder (10.1%), with smaller weighted mean effects for schizoid (6.0%) and schizotypal (4.1%) personality disorders. There was high to very high between-study heterogeneity for comorbid Cluster A disorders. Cluster B Disorders. Prevalence estimates for Cluster B personality disorders were provided by 14 studies (Table 4). There was a weighted mean

TABLE 3. Prevalence of Comorbid Cluster A Personality Disorders in Treatment-Seeking Problem Gambling Samples

Study Blaszczynski & Steel (1998) Echeburua & FernandezMontalvo (2008) Echeburua & FernandezMontalvo (2008) Jimenez-Murcia et al. (2009) Kerber et al. (2008) Kroeber (1992) Kruedelbach et al. (2006) Pelletier et al. (2008) Specker et al. (1996) Summary effect (95% CI) I (%) 2

Comorbidity Measure

Paranoid Personality Disorder (%)

Schizoid Personality Disorder (%)

Schizotypal Personality Disorder (%)

40.2

20.7

37.8

 8.0

 0.0

 0.0

 8.0

 0.0

 0.0

10.0

15.0

 7.5

 4.3 24.0  5.0

 9.3  2.5 18.0  2.5

 9.3  1.2  4.0  2.5

 1.2  3.0  0.0

6.1 (1.5, 22.1)

10.1 (4.2, 22.1)

6.0 (2.5, 13.7)

4.1 (0.8, 19.4)

94.33

88.94

79.18

91.49

Any Cluster A Disorder (%)

PDQ-R IPDE MCMI-II SCID (DSM-IV) PDQ-4 Clinical diagnosis (DSM-III-R) SCID (DSM-III-R) SCID (DSM-IV) SCID (DSM-III-R)

 2.2

PDQ-R: Personality Disorder Questionnaire-Revised, IPDE: International Personality Disorders Examination, MCMIII: Millon Clinical Multiaxial Inventory-II, SCID (DSM-IV): Structured Clinical Interview for DSM-IV, PDQ-4: Personality Disorder Questionnaire-4, SCID (DSM-III-R): Structured Clinical Interview for DSM-III-R.

743

Study

Comorbidity Measure DSM III checklist for APD PDQ-R IPDE MCMI-II MINI SCID (DSM-III-R) SCID (DSM-IV) PDQ-4 Clinical diagnosis (DSM-III-R) SCID (DSM-III-R) SCID (DSM-IV) SCID (DSM-IV) SCID (DSM-III-R) SCID (DSM-IV) SCID (DSM-III-R) 96.72

17.6% (6.0, 41.8)

 7.5

42.0

30.2

 6.5

76.11

14.0 (10.5, 18.4)

 7.5 20.9  9.9 15.3 29.0  7.4 16.5  0.0

15.4 29.3  8.0 16.0  4.9 14.5

Antisocial Personality Disorder (%)

94.48

13.1 (4.3, 33.5)

 2.5

10.0

10.0  4.7 11.7

69.5 16.0  0.0

Borderline Personality Disorder (%)

95.29

6.3 (1.0, 30.4)

 0.0

 1.0

 6.8

12.5

65.9  0.0  0.0

Histrionic Personality Disorder (%)

90.84

16.6 (8.0, 31.2)

 5.0

15.0

17.5 11.6 18.5

57.3  8.0 32.0

Narcissistic Personality Disorder (%)

DSM-III checklist for APD: DSM-III checklist for Antisocial Personality Disorder, PDQ-R: Personality Disorder Questionnaire-Revised, IPDE: International Personality Disorders Examination, MCMI-II: Millon Clinical Multiaxial Inventory-II, MINI: Mini International Neuropsychiatric Interview, SCID (DSM-III-R): Structured Clinical Interview for DSM-III-R, SCID (DSM-IV): Structured Clinical Interview for DSM-IV, PDQ-4: Personality Disorder Questionnaire-4.

I 2 (%)

Summary effect (95% CI)

Blaszczynski & McConaghy (1994) Blaszczynski & Steel (1998) Echeburua & Fernandez-Montalvo (2008) Echeburua & Fernandez-Montalvo (2008) Grall-Bronnec et al. (2011) Ibanez et al. (2001) Jimenez-Murcia et al. (2009) Kerber et al. (2008) Kroeber (1992) Kruedelbach et al. (2006) Ledgerwood & Petry (2010) Pelletier et al. (2008) Petry & Steinberg (2005) Pietrzak & Petry (2005) Specker et al. (1996)

Any Cluster B Disorder (%)

TABLE 4. Prevalence of Comorbid Cluster B Personality Disorders in Treatment-Seeking Problem Gambling Samples

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DOWLING ET AL.

effect of 17.6% for any Cluster B disorder. For specific Cluster B disorders, the highest weighted mean effect was for narcissistic personality disorder (16.6%), followed by antisocial (14.0%) and borderline (13.1%) personality disorders. There was high to very high between-study heterogeneity for Cluster B disorders. Cluster C Disorders. Prevalence estimates for Cluster C personality disorders were provided by eight studies (Table 5). There was a weighted mean effect of 12.6% for any Cluster C disorder. For specific Cluster C disorders, the highest mean effects were for avoidant (13.4%) and obsessive-compulsive (13.4%) personality disorders. There was very high between-study heterogeneity for Cluster C disorders.

SUBGROUP ANALYSES Based on previous literature, several potentially relevant sources of heterogeneity identified a priori were the subject of subgroup analyses. Only antisocial personality disorder had sufficient (10 or more) primary studies available to conduct subgroup analyses. The results revealed no evidence of significant variation in point estimates of antisocial personality disorder according to gambling problem severity, measure of comorbidity, or study jurisdiction (Table 6). There were insufficient (three or more) primary studies in both treatment facility subgroups for antisocial personality disorder to conduct a subgroup analysis.

SENSITIVITY ANALYSES These analyses considered whether findings were robust to approaches adopted in this review, and involved sequentially limiting studies to (a) observational studies of treatment in naturalistic settings (i.e., clinical trials were excluded), and (b) random samples or recruitment of consecutive admissions (i.e., self-selected samples or studies failing to indicate sampling strategies were excluded). Results were compared to findings based on all studies, and were analyzed for all personality disorders irrespective of number of studies. Given the number of analyses conducted, these results are not presented but can be obtained from the corresponding author. Across all types of personality disorder comorbidity, results based on studies of naturalistic treatment varied minimally relative to all studies, suggesting that findings were robust to inclusion of clinical trials. Results based on random samples or consecutive admissions also varied minimally (relative to analyses based on all studies, including self-selected samples) for most types of personality disorder comorbidity. The largest difference was observed for “Any Cluster B disorder,” whereby studies of random or consecutive samples suggested lower estimates (k = 3; weighted mean = 0.12; 95% CI = 0.03 to 0.37) relative to all studies (k = 4; weighted mean = 0.18; 95% CI = 0.06 to 0.42). The remaining differences

745

PDQ-R IPDE MCMI-II SCID (DSM-IV ) PDQ-4 Clinical diagnosis (DSM-III-R) SCID (DSM-III-R) SCID (DSM-IV ) SCID (DSM-III-R)

Comorbidity Measure

93.94

12.6 (4.8, 29.1)

13.0 27.0 17.5

 3.7

Any Cluster C Disorder (%)

88.49

13.4 (5.9, 27.5)

93.21

6.0 (1.4, 22.5)

 5.0  7.0  3.1  3.0  5.0

27.5  6.2 10.0 12.5

48.8  0.0  8.0

36.6  0.0

Dependent Personality Disorder (%)

88.24

13.4 (5.9, 27.5)

 5.6 16.0  5.0

37.5

31.7  0.0

ObsessiveCompulsive Personality Disorder (%)

PDQ-R: Personality Disorder Questionnaire-Revised, IPDE: International Personality Disorders Examination, MCMI-II: Millon Clinical Multiaxial Inventory-II, SCID (DSM-IV): Structured Clinical Interview for DSM-IV, PDQ-4: Personality Disorder Questionnaire-4, SCID (DSM-III-R): Structured Clinical Interview for DSM-III-R.

I 2 (%)

Summary effect (95% CI)

Blaszczynski & Steel (1998) Echeburua & Fernandez-Montalvo (2008) Echeburua & Fernandez-Montalvo (2008) Jimenez-Murcia et al. (2009) Kerber et al. (2008) Kroeber (1992) Kruedelbach et al. (2006) Pelletier et al. (2008) Specker et al. (1996)

Study

Avoidant Personality Disorder (%)

TABLE 5. Prevalence of Comorbid Cluster C Personality Disorders in Treatment-Seeking Problem Gambling Samples

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DOWLING ET AL. TABLE 6. Summary of Subgroup Analyses for Antisocial Personality Disorder

Gambling problem severity   Pathological gamblers   Problem and pathological gamblers Measure of comorbidity   Clinician-administered interviews   Self-report questionnaires Study jurisdiction  U.S.  Europe

k

Summary effect (%)

95% CI

9 4

16.3  9.1

12.2, 21.4   4.6, 17.4

9 4

13.4 14.9

  9.3, 18.8   8.2, 25.6

6 5

11.3 16.8

  8.0, 15.9 11.2, 24.4

were smaller in magnitude, suggesting that the findings of the current review were also robust to inclusion of self-selected samples.

DISCUSSION PREVALENCE RATES OF COMORBID PERSONALITY DISORDERS This is the first systematic review and meta-analysis to explore the prevalence rates of comorbid personality disorders in treatment-seeking problem gamblers. Unlike previous narrative reviews, this review used replicable procedures to systematically identify all available evidence and employed meta-analytic techniques to derive reliable prevalence estimates for each personality disorder. The sensitivity analyses also suggested that these prevalence estimates were robust to the inclusion of clinical trials and self-selected samples. The estimates identified for treatment-seeking problem gamblers in this review are much higher than those from the World Health Organization (WHO) World Mental Health Surveys of the general community (6.1% for any personality disorder, 3.6% for Cluster A disorders, 1.5% for Cluster B disorders, and 2.7% for Cluster C disorders) (Huang et al., 2009). In contrast to these surveys, however, treatment-seeking problem gamblers were most likely to display Cluster B and C disorders. It has been argued that the biological, psychological, and social characteristics associated with these disorders may predispose individuals with these disorders to develop gambling problems, particularly in the context of ecologically relevant conditions, such as exposure to gambling, early wins, subjective arousal, substance use, and negative affective states (Blaszczynski & Steel, 1998; Desai & Potenza, 2008; Pelletier et al., 2008; Sacco, Cunningham-Williams, Ostmann, & Spitznagel, 2008; Specker et al., 1996). These characteristics include impulsivity, emotion dysregulation, delayed gratification problems, and affective instability for Cluster B disorders, and isolative behavior, social discomfort, sensitivity to criticism, and perfectionism for Cluster C disorders. Alternatively, the presence of these disorders may influence decisions to engage in or persist in gambling, thereby increasing

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the likelihood of developing more severe gambling problems (Blaszczynski & Steel, 1998; Desai & Potenza, 2008; Pelletier et al., 2008). These explanations assume that the personality traits precede the development of gambling problems. Because the diagnostic criteria locate personality disorder traits in late adolescence or early adulthood, it is often presumed that they precede the onset of gambling problems (Bagby et al., 2008). However, it is possible that personality disorder traits emerge in response to the consequences of problem gambling behavior, such as personal distress, decreased quality of life, repeated attempts at concealment, and financial difficulties, rather than acting as causative factors in their own right (Bagby et al., 2008; Blaszczynski & McConaghy, 1994; Crockford & El-Guebaly, 1998). Alternatively, problem gambling and personality disorders may be manifestations of a common underlying etiology, such as common genetic or biological mechanisms (Bagby et al., 2008; Desai & Potenza, 2008), or are independent disturbances that each affect the manifestation, course, and treatment of the other (Bagby et al., 2008; Blaszczynski & McConaghy, 1994). Prospective studies are required to address this issue. The prevalence estimates identified in this review must be interpreted in the context of an emerging literature indicating that a substantial proportion of treatment-seeking problem gamblers have multiple comorbid psychopathological disorders (Blaszczynski & Steel, 1998; Echeburua & Fernandez-Montalvo, 2008; Fernandez-Montalvo & Echeburua, 2004; Ibanez et al., 2001; Kerber, Black, & Buckwalter, 2008; Kruedelbach et al., 2006; Pelletier et al., 2008; Westphal & Johnson, 2007). Failure to control for other disorders may therefore produce inflated rates of personality disorder comorbidity for problem gamblers (Bagby et al., 2008). The available evidence (Bagby et al., 2008; Blaszczynski & Steel, 1998; Sacco et al., 2008) suggests that the co-occurrence of problem gambling and personality disorders generally decreases once the presence of other disorders is statistically removed, that some personality disorders (such as Cluster B disorders) may be uniquely associated with problem gambling, and that the presence of some disorders (such as depression) may account for the co-occurrence of the disorders more than others (such as substance use disorders). Further research controlling for multiple co-occurring disorders or using multimorbidity coefficients is required (Batstra, Bos, & Neeleman, 2002). The findings of this review should not be generalized to non-treatmentseeking problem gamblers. Treatment seekers are not representative of the broader population of problem gamblers (Slutske, 2006). Moreover, the act of seeking treatment is more associated with certain personality disorders, such as borderline, narcissistic, or histrionic personality disorders (Bagby et al., 2008). Treatment-seeking problem gamblers may therefore systematically exhibit different patterns of personality disorder comorbidity than their non-treatment-seeking counterparts (Bagby et al., 2008). Interestingly, the prevalence estimate for antisocial personality dis-

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order in a meta-analysis of population-representative samples of problem gamblers (Lorains et al., 2011) was double that found in the current review. Consistent with the diagnosis of antisocial personality disorder (APA, 2000), this finding suggests that problem gamblers with this comorbidity are unlikely to voluntarily seek treatment.

HETEROGENEITY IN PREVALENCE ESTIMATES OF COMORBID PERSONALITY DISORDERS A notable feature of the data was significant variability in the rates of comorbid personality disorders in the primary studies. In contrast to expectations from previous literature (Bagby et al., 2008; Blaszczynski & Steel, 1998; Lorains et al., 2011; Specker et al., 1996), the subgroup analyses in this review revealed no significant differences in estimates for antisocial personality disorder according to gambling problem severity, measure of comorbidity, or study jurisdiction. However, only antisocial personality disorder had sufficient primary studies available to conduct subgroup analyses. Future updates of this review may consider the effect of these methodological and clinical factors for other personality disorders, as more studies become available.

CLINICAL IMPLICATIONS FOR PRACTICE AND RESEARCH The findings of this review highlight the need to undertake systematic and routine screening and comprehensive assessment of co-occurring personality disorders of people seeking treatment for gambling problems (Pelletier et al., 2008; Petry, 2005; Westphal & Johnson, 2007). This can be achieved through comprehensive screening for multiple personality disorders or targeted screening for specific personality disorders (Westphal & Johnson, 2007). Although comprehensive screening is appropriate given the broad range of potentially comorbid personality disorders, many comprehensive measures have long administration times and are only commercially available. Alternatively, targeted screening instruments for prevalent specific personality disorders, such as narcissistic and antisocial personality disorders, may be employed. The findings of this review also underscore the need to develop individually tailored case formulations, treatment plans, treatment objectives, and individualized intervention approaches for problem gamblers with comorbid personality disorders. The presence of some personality disorders may alert clinicians to potential obstacles and difficulties in therapy, thereby guiding treatment decisions (Echeburua & Fernandez-Montalvo, 2008). Clinicians may need to set stringent behavioral limits and expectations, expect lower treatment motivation and higher resistance, be more tolerant of poor compliance, promote treatment adherence, and expect longer term treatment (Blaszczynski & Steel, 1998; Echeburua & Fernandez-Montalvo, 2008; Pelletier et al., 2008). Such recognition of personality disorder

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comorbidity could therefore serve to maximize treatment response, enhance client satisfaction, reduce attrition, and lower treatment costs (Ladouceur et al., 2006). There is also a need for an appropriate clinical response by specialist gambling agencies. Services either require appropriate referral pathways or a workforce with adequate skills to appropriately manage personality disorders (Westphal & Johnson, 2007). The presence of considerable personality disorder comorbidity suggests that a multimodal, stepped care approach to gambling treatment may be appropriate, whereby treatment intensity increases with increasing client needs. Such a stepped care approach involves a treatment network that encompasses a continuum of integrated services delivering a broad spectrum of treatment from minimally restrictive to increasingly intensive approaches (Marotta, 2003). Despite their obvious importance, the implications of comorbid personality disorders for problem gambling treatment have received little research attention. Further research is required to explore the clinical profiles of treatment-seeking problem gamblers with specific comorbid personality disorders and to explore the influence of comorbid personality disorders on treatment motivation and compliance, treatment success, likelihood of relapse, and number of treatment attempts. Research has also yet to identify the most appropriate interventions for subgroups of problem gamblers with co-occurring personality disorders. Intensive and prolonged CBT and contingency management may be effective for problem gamblers with comorbid antisocial personality disorder (Blaszczynski & Nower, 2002; Gibbon et al., 2010), while dialectical behavior therapy, schema-focused therapy, mentalization-based treatment, and interpersonal therapy may be effective for problem gamblers with comorbid borderline personality disorder (Christensen et al., 2013; Stoffers et al., 2012). Future research is required to evaluate the efficacy of interventions specifically designed for problem gamblers with comorbid personality disorders. Appendix 1: Detailed Search Strategy Medline and PsycInfo  1. pathological gambl$  2. problem gambl$  3. disordered gambl$   4.  1 or 2 or 3  5. intervention  6. medication  7. help  8. helpline  9. online 10.  gamblers anonymous 11. pharmaco$ 12. therap$ 13. treat$ 14. counsel$ 15.  5 OR 6 OR 7 OR 8 OR 9 OR 10 OR 11 OR 12 OR 13 OR 14 16. 4 AND 15

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EMBASE   1.  pathological NEAR/1 gambl*   2.  problem NEAR/1 gambl*   3.  disordered NEAR/1 gambl*   4.  1 OR 2 OR 3  5. intervention  6. counsel*  7. medication  8. help  9. ‘gamblers anonymous’ 10. therap* 11. pharmaco* 12. helpline 13. online 14. treat* 15.  5 OR 6 OR 7 OR 8 OR 9 OR 10 OR 11 OR 12 OR 13 OR 14 OR 15 16.  4 AND 15 CINAHL 1.  TX “pathological gambl*” OR TX “problem gambl*” OR TX “disordered gambl*”  2. TX treat* OR TX intervention OR TX counsel* OR TX medication OR TX help OR TX “gamblers anonymous” OR TX therap* OR TX pharmaco* OR TX helpline OR TX online 3.  1 AND 2

REVIEW OF PERSONALITY DISORDERS IN PROBLEM GAMBLERS751 Appendix 2: PRISMA flow diagram: Flow of information through the different phases of the systematic review

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