Recognition is growing that gambling, although highly profitable for corporations and governments, is a source of serious and unevenly distributed harm. This recognition has led to demands for public health strategies at the local, national, and international levels. We aimed to identify review-level evidence for interventions to address or prevent gambling-related harms and explore policy implications, using stakeholder consultation to assess the evidence base, identify gaps, and suggest key research questions. We opted for a systematic mapping review and narrative synthesis for all forms of gambling in any setting. We included participants from the whole population, identified gamblers including self-defined, and specific populations at risk (eg, children and young people). We included all outcome measures relating to prevention or treatment of gambling-related harms that were reported by review authors. After duplication, the searches generated 1080 records.

Of 43 potential papers, 13 were excluded at the full paper stage and 30 papers were included in the Review. We identified whole-population preventive interventions, such as demand reduction (n=3) and supply reduction (n=4) interventions, and targeted treatment interventions for individuals addicted to gambling, such as therapeutic (n=12), pharmacological (n=5), and self-help or mutual support (n=4) interventions. We also reviewed studies (n=2) comparing these approaches. Interventions to screen, identify, and support individuals at risk of gambling-related harms and interventions to support ongoing recovery and prevent relapse for individuals with a gambling addiction were not represented in the review-level evidence. A public health approach suggests that there are opportunities to reduce gambling-related harms by intervening across the whole gambling pathway, from regulation of access to gambling to screening for individuals at risk and services for individuals with an identified gambling problem. The dearth of evidence for some interventions means that implementation must be accompanied by robust evaluation.