The effect of internet-based psychological treatment for gambling problems has not been previously investigated by meta-analysis. The present study is therefore a quantitative synthesis of studies on the effects of internet-based treatment for gambling problems. Given that effects may vary according to the presence of therapist support and control conditions, it was presumed that subgroup analyses would elucidate such effects.
A systematic search with no time constraints was conducted in PsycINFO, MEDLINE, Web of Science, and the Cochrane Library. Two authors independently extracted data using a predefined form, including study quality assessment based on the Cochrane risk of bias tool. Effect sizes were calculated using random-effects models. Heterogeneity was indexed by Cochran’s Q and the I2 statistics. Publication bias was investigated using trim and fill.
Thirteen studies were included in the analysis. Random effects models at post-treatment showed significant effects for general gambling symptoms (g = 0.73; 95% CI = 0.43–1.03), gambling frequency (g = 0.29; 95% CI = 0.14–0.45), and amount of money lost gambling (g = 0.19; 95% CI = 0.11–0.27). The corresponding findings at follow-up were g = 1.20 (95% CI = 0.79–1.61), g = 0.36 (95% CI = 0.12–0.60), and g = 0.20 (95% CI = 0.12–0.29) respectively. Subgroup analyses showed that for general gambling symptoms, studies with therapist support yield larger effects than studies without, both post-treatment and at follow-up. Additionally, on general gambling symptoms and gambling frequency, there were lower effect sizes for studies with a control group compared to studies without a control group at follow-up. Studies with higher baseline severity of gambling problems were associated with larger effect sizes at both posttreatment and follow-up than studies with more lenient inclusion criteria concerning gambling problems.
Discussion and conclusions
Internet-based treatment has the potential to reach a large proportion of persons with gambling problems. Results of the meta-analysis suggest that such treatments hold promise as an effective approach. Future studies are encouraged to examine moderators of treatment outcomes, validate treatment effects cross-culturally, and investigate the effects of novel developments such as ecological momentary interventions.
Although alcohol intake and gambling often co-occur in related venues, there is conflicting evidence regarding the effects of alcohol expectancy and intake on gambling behavior. We therefore conducted an experimental investigation of the effects of alcohol expectancy and intake on slot machine gambling behavior.
Participants were 184 (females = 94) individuals [age range: 18–40 (mean = 21.9) years] randomized to four independent conditions differing in information/expectancy about beverage (told they received either alcohol or placebo) and beverage intake [actually ingesting low (target blood alcohol concentration [BAC] < 0.40 mg/L) vs. moderate (target BAC > 0.40 mg/L; ≈0.80 mg/L) amounts of alcohol]. All participants completed self-report questionnaires assessing demographic variables, subjective intoxication, alcohol effects (stimulant and sedative), and gambling factors (behavior and problems, evaluation, and beliefs). Participants also gambled on a simulated slot machine.
A significant main effect of beverage intake on subjective intoxication and alcohol effects was detected as expected. No significant main or interaction effects were detected for number of gambling sessions, bet size and variation, remaining credits at termination, reaction time, and game evaluation.
Alcohol expectancy and intake do not affect gambling persistence, dissipation of funds, reaction time, or gambling enjoyment.