Prevalence of comorbid disorders in problem and pathological gambling: systematic review and meta‐analysis of population surveys
Abstract
Aims This paper reviews evidence pertaining to the prevalence of common comorbid disorders, including alcohol use disorder, depression, substance use disorders, nicotine dependence, anxiety disorders and antisocial personality disorder, in population‐representative samples of problem and pathological gamblers. Methods A systematic search was conducted for peer‐reviewed and unpublished articles reported between 1 January 1998 and 20 September 2010. Only studies which examined the prevalence of comorbid conditions in problem and/or pathological gamblers from a general population sample using randomized sampling methods and standardized measurement tools were included. Meta‐analysis techniques were then performed to synthesize the included studies and estimate the weighted mean effect size and heterogeneity across studies. Results Eleven eligible studies were identified from the literature. Results from across the studies indicated that problem and pathological gamblers had high rates of other comorbid disorders. The highest mean prevalence was for nicotine dependence (60.1%), followed by a substance use disorder (57.5%), any type of mood disorder (37.9%) and any type of anxiety disorder (37.4%). However, there was evidence of moderate heterogeneity across studies, suggesting that rate estimates do not necessarily converge around a single population figure, and that weighted means should be interpreted with caution. Conclusions Problem and pathological gamblers experience high levels of other comorbid mental health disorders and screening for comorbid disorders upon entering treatment for gambling problems is recommended. Further research is required to explore the underlying causes of variability observed in the prevalence estimates.
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Approximately 37% of subthreshold and clinical gamblers suffer from an anxiety disorder.
“Approximately 37% (range: 14.0% −60.3%) of subthreshold and clinical gamblers suffer from an anxiety disorder (Kessler et al., 2008; Lorains et al., 2011; Petry et al., 2005)”
From Cued for Risk: Evidence for an Incentive Sensitization Framework to Explain the Interplay between Stress and Anxiety, Substance Abuse, and Reward Uncertainty in Disordered Gambling Behavior (2019) · cites this paper as Lorains et al., 2011
Substance use disorders are one of the most frequently comorbid conditions in gambling disorder.
“Substance use disorders are one of the most frequently comorbid conditions in gambling disorder (K.-L. Chou & Afifi, 2011; Lorains et al., 2011; Walther, Morgenstern, & Hanewinkel, 2012).”
From Cued for Risk: Evidence for an Incentive Sensitization Framework to Explain the Interplay between Stress and Anxiety, Substance Abuse, and Reward Uncertainty in Disordered Gambling Behavior (2019) · cites this paper as Lorains et al., 2011
A meta-analysis including 11 studies reported an average comorbidity rate of 28.1% for alcohol use disorders and 60.1% for nicotine dependence in individuals with subthreshold or clinical gambling severity.
“A recent meta-analysis including 11 studies conducted between 1998-2010 reported an average comorbidity rate of 28.1% (range: 9.9% - 73.2%) for alcohol use disorders and 60.1% (range: 34.9% - 76.3%) for nicotine dependence in individuals with subthreshold or clinical gambling severity (Lorains et al., 2011; Petry et al., 2005).”
From Cued for Risk: Evidence for an Incentive Sensitization Framework to Explain the Interplay between Stress and Anxiety, Substance Abuse, and Reward Uncertainty in Disordered Gambling Behavior (2019) · cites this paper as Lorains et al., 2011
Gambling disorder often co-occurs with psychiatric disorders, particularly substance use and anxiety disorders.
“Gambling disorder often co-occurs with psychiatric disorders, particularly substance use and anxiety disorders (el-Guebaly et al., 2006; Kessler et al., 2008; Lorains, Cowlishaw, & Thomas, 2011; Parhami, Mojtabai, Rosenthal, Afifi, & Fong, 2014).”
From Cued for Risk: Evidence for an Incentive Sensitization Framework to Explain the Interplay between Stress and Anxiety, Substance Abuse, and Reward Uncertainty in Disordered Gambling Behavior (2019) · cites this paper as Lorains, Cowlishaw, & Thomas, 2011
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- Authors
- Lorains, F. K., Cowlishaw, S., & Thomas, S. A.
- Affiliations
- Monash University (AU)
- University of Bristol (GB)
- Corresponding author
- Lorains, Felicity K.
- Venue
- Addiction
- Publisher
- Wiley
- Published
- 2011-02-07
- Volume
- 106
- Issue
- 3
- Pages
- 490-498
- ISSN
- 0965-2140 (ISSN-L)
- 1360-0443
- OpenAlex
- W1939808128
- Cited by
- 1,006
- References
- 56
- Citations by year
- 2026: 45 · 2025: 58 · 2024: 49 · 2023: 60 · 2022: 73 · 2021: 67 · 2020: 103 · 2019: 87 · 2018: 85 · 2017: 67 · 2016: 74 · 2015: 72 · 2014: 66 · 2013: 49 · 2012: 32
- FWCI
- 4.43
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Addiction (publishedVersion)
- PubMed (publishedVersion)
- Lancaster EPrints (Lancaster University) (submittedVersion)
- Bristol Research (University of Bristol) (submittedVersion)
- Topics
- Social Sciences › Psychology › Clinical Psychology › Gambling Behavior and Treatments
- Health Sciences › Medicine › Epidemiology › Substance Abuse Treatment and Outcomes
- Social Sciences › Psychology › Clinical Psychology › Personality Disorders and Psychopathology
- Keywords
- problem gambling, gambling addiction, comorbidities, prevalence, nicotine dependence, substance use disorders, alcoholism, depression, anxiety disorders, antisocial personality disorder, mental illness
- MeSH terms
- Adult, Mental Disorders, Data Interpretation, Statistical, Gambling, Humans, Patient Acceptance of Health Care, Population Surveillance, Smoking, Comorbidity, Prevalence, Behavior, Addictive, Substance-Related Disorders
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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