This systematic review aimed to identify early risk and protective factors (in childhood, adolescence or young adulthood) longitudinally associated with the subsequent development of gambling problems. A systematic search of peer-reviewed and grey literature from 1990 to 2015 identified 15 studies published in 23 articles. Meta-analyses quantified the effect size of 13 individual risk factors (alcohol use frequency, antisocial behaviours, depression, male gender, cannabis use, illicit drug use, impulsivity, number of gambling activities, problem gambling severity, sensation seeking, tobacco use, violence, undercontrolled temperament), one relationship risk factor (peer antisocial behaviours), one community risk factor (poor academic performance), one individual protective factor (socio-economic status) and two relationship protective factors (parent supervision, social problems). Effect sizes were on average small to medium and sensitivity analyses revealed that the results were generally robust to the quality of methodological approaches of the included articles. These findings highlight the need for global prevention efforts that reduce risk factors and screen young people with high-risk profiles. There is insufficient investigation of protective factors to adequately guide prevention initiatives. Future longitudinal research is required to identify additional risk and protective factors associated with problem gambling, particularly within the relationship, community, and societal levels of the socio-ecological model.

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.

Background: Data analysis approaches such as qualitative content analysis are notoriously time and labor intensive because of the time to detect, assess, and code a large amount of data. Tools such as ChatGPT may have tremendous potential in automating at least some of the analysis. Objective: The aim of this study was to explore the utility of ChatGPT in conducting qualitative content analysis through the analysis of forum posts from people sharing their experiences on reducing their sugar consumption. Methods: Inductive and deductive content analysis were performed on 537 forum posts to detect mechanisms of behavior change. Thorough prompt engineering provided appropriate instructions for ChatGPT to execute data analysis tasks. Data identification involved extracting change mechanisms from a subset of forum posts. The precision of the extracted data was assessed through comparison with human coding. On the basis of the identified change mechanisms, coding schemes were developed with ChatGPT using data-driven (inductive) and theory-driven (deductive) content analysis approaches. The deductive approach was informed by the Theoretical Domains Framework using both an unconstrained coding scheme and a structured coding matrix. In total, 10 coding schemes were created from a subset of data and then applied to the full data set in 10 new conversations, resulting in 100 conversations each for inductive and unconstrained deductive analysis. A total of 10 further conversations coded the full data set into the structured coding matrix. Intercoder agreement was evaluated across and within coding schemes. ChatGPT output was also evaluated by the researchers to assess whether it reflected prompt instructions. Results: The precision of detecting change mechanisms in the data subset ranged from 66% to 88%. Overall κ scores for intercoder agreement ranged from 0.72 to 0.82 across inductive coding schemes and from 0.58 to 0.73 across unconstrained coding schemes and structured coding matrix. Coding into the best-performing coding scheme resulted in category-specific κ scores ranging from 0.67 to 0.95 for the inductive approach and from 0.13 to 0.87 for the deductive approaches. ChatGPT largely followed prompt instructions in producing a description of each coding scheme, although the wording for the inductively developed coding schemes was lengthier than specified. Conclusions: ChatGPT appears fairly reliable in assisting with qualitative analysis. ChatGPT performed better in developing an inductive coding scheme that emerged from the data than adapting an existing framework into an unconstrained coding scheme or coding directly into a structured matrix. The potential for ChatGPT to act as a second coder also appears promising, with almost perfect agreement in at least 1 coding scheme. The findings suggest that ChatGPT could prove useful as a tool to assist in each phase of qualitative content analysis, but multiple iterations are required to determine the reliability of each stage of analysis.

This study provides a systematic review of the empirical evidence related to the association between problem gambling and intimate partner violence (IPV). We identified 14 available studies in the systematic search (8 for victimisation only, 4 for perpetration only and 2 for both victimisation and perpetration). Although there were some equivocal findings, we found that most of the available research suggests that there is a significant relationship between problem gambling and being a victim of IPV. There was more consistent evidence that there is a significant relationship between problem gambling and perpetration of IPV. Meta-analyses revealed that over one third of problem gamblers report being victims of physical IPV (38.1%) or perpetrators of physical IPV (36.5%) and that the prevalence of problem gambling in IPV perpetrators is 11.3%. Although the exact nature of the relationships between problem gambling and IPV is yet to be determined, the findings suggest that less than full employment and clinical anger problems are implicated in the relationship between problem gambling and IPV victimization and that younger age, less than full employment, clinical anger problems, impulsivity, and alcohol and substance use are implicated in the relationship between problem gambling and IPV perpetration. The findings highlight the need for treatment services to undertake routine screening and assessment of problem gambling, IPV, alcohol and substance use problems, and mental health issues and provide interventions designed to manage this cluster of comorbid conditions. Further research is also required to investigate the relationship between problem gambling and violence that extends into the family beyond intimate partners.