Faculty of Education - Research Publications

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Author: Cowlishaw, Sean × Author: Dowling, Nicole × Start date: 2005 × Type: Journal Article ×

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    Prevalence of psychiatric co-morbidity in treatment-seeking problem gamblers: A systematic review and meta-analysis
    Dowling, NA ; Cowlishaw, S ; Jackson, AC ; Merkouris, SS ; Francis, KL ; Christensen, DR (SAGE PUBLICATIONS LTD, 2015-06)
    OBJECTIVE: The aim of this paper was to systematically review and meta-analyse the prevalence of co-morbid psychiatric disorders (DSM-IV Axis I disorders) among treatment-seeking problem gamblers. METHODS: A systematic search was conducted for peer-reviewed studies that provided prevalence estimates of Axis I psychiatric disorders in individuals seeking psychological or pharmacological treatment for problem gambling (including pathological gambling). Meta-analytic techniques were performed to estimate the weighted mean effect size and heterogeneity across studies. RESULTS: Results from 36 studies identified high rates of co-morbid current (74.8%, 95% CI 36.5-93.9) and lifetime (75.5%, 95% CI 46.5-91.8) Axis I disorders. There were high rates of current mood disorders (23.1%, 95% CI 14.9-34.0), alcohol use disorders (21.2%, 95% CI 15.6-28.1), anxiety disorders (17.6%, 95% CI 10.8-27.3) and substance (non-alcohol) use disorders (7.0%, 95% CI 1.7-24.9). Specifically, the highest mean prevalence of current psychiatric disorders was for nicotine dependence (56.4%, 95% CI 35.7-75.2) and major depressive disorder (29.9%, 95% CI 20.5-41.3), with smaller estimates for alcohol abuse (18.2%, 95% CI 13.4-24.2), alcohol dependence (15.2%, 95% CI 10.2-22.0), social phobia (14.9%, 95% CI 2.0-59.8), generalised anxiety disorder (14.4%, 95% CI 3.9-40.8), panic disorder (13.7%, 95% CI 6.7-26.0), post-traumatic stress disorder (12.3%, 95% CI 3.4-35.7), cannabis use disorder (11.5%, 95% CI 4.8-25.0), attention-deficit hyperactivity disorder (9.3%, 95% CI 4.1-19.6), adjustment disorder (9.2%, 95% CI 4.8-17.2), bipolar disorder (8.8%, 95% CI 4.4-17.1) and obsessive-compulsive disorder (8.2%, 95% CI 3.4-18.6). There were no consistent patterns according to gambling problem severity, type of treatment facility and study jurisdiction. Although these estimates were robust to the inclusion of studies with non-representative sampling biases, they should be interpreted with caution as they were highly variable across studies. CONCLUSIONS: The findings highlight the need for gambling treatment services to undertake routine screening and assessment of psychiatric co-morbidity and provide treatment approaches that adequately manage these co-morbid disorders. Further research is required to explore the reasons for the variability observed in the prevalence estimates.
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    Therapist-delivered and self-help interventions for gambling problems: A review of contents
    Rodda, S ; Merkouris, SS ; Abraham, C ; Hodgins, DC ; Cowlishaw, S ; Dowling, NA (AKADEMIAI KIADO ZRT, 2018-06)
    Background and aims To date, no systematic approach to identifying the content and characteristics of psychological interventions used to reduce gambling or problem gambling has been developed. This study aimed to develop a reliable classification system capable of identifying intervention characteristics that could, potentially, account for greater or lesser effectiveness. Methods Intervention descriptions were content analyzed to identify common and differentiating characteristics. A coder manual was developed and applied by three independent coders to identify the presence or absence of defined characteristics in 46 psychological and self-help gambling interventions. Results The final classification taxonomy, entitled Gambling Intervention System of CharacTerization (GIST), included 35 categories of intervention characteristics. These were assigned to four groups: (a) types of change techniques (18 categories; e.g., cognitive restructuring and relapse prevention), (b) participant and study characteristics (6 categories; e.g., recruitment strategy and remuneration policy), and (c) characteristics of the delivery and conduct of interventions (11 categories; e.g., modality of delivery and therapist involvement), and (d) evaluation characteristics (e.g., type of control group). Interrater reliability of identification of defined characteristics was high (κ = 0.80-1.00). Discussion This research provides a tool that allows systematic identification of intervention characteristics, thereby enabling consideration, not only of whether interventions are effective or not, but also of which domain-relevant characteristics account for greater or lesser effectiveness. The taxonomy also facilitates standardized description of intervention content in a field in which many diverse interventions have been evaluated. Conclusion Application of this coding tool has the potential to accelerate the development of more efficient and effective therapist-delivered and self-directed interventions to reduce gambling problems.