Prevalence and implications of gambling problems among firefighters.

Firefighting is a high-risk occupation that accounts for vulnerability to a range of mental health problems and addictive behaviours. However, no research has addressed whether this vulnerability extends to gambling problems, and the aim of this study was thus to provide new data on frequency and implications of such problems in this occupational context. The sample consisted of n = 566 career and retained firefighters who participated in a cross-sectional survey of an Australian metropolitan fire service. The Problem Gambling Severity Index (PGSI) was used to operationalise both clinically significant levels of problem gambling (PGSI ≥ 5), and 'at-risk' gambling (PGSI 1-4); alongside measures of major depression (PHQ-9), anxiety (GAD-7), Posttraumatic Stress Disorder (PCL-5) and alcohol problems (AUDIT), as well as other addictive behaviours, wellbeing and psychosocial issues. Results indicated 12.3% of firefighters that reported any gambling problems across a continuum of severity (PGSI ≥ 1), including 2.3% that were problems gamblers, and 10.0% reporting at-risk gambling. The weighted prevalence of problem gambling was comparable to other significant mental health conditions including depression and PTSD, while the rate of any gambling problems was high relative to other addictive behaviours. Gambling problems were associated with poor mental health and wellbeing, but not psychosocial indicators (e.g., financial difficulties). The findings suggest that gambling problems across a spectrum of severity may be significant yet hidden issues among emergency service workers, and thus require increased recognition and responses at the organisational level.

Key patterns and predictors of response to treatment for military veterans with post-traumatic stress disorder: a growth mixture modelling approach.

BACKGROUND: To determine the patterns and predictors of treatment response trajectories for veterans with post-traumatic stress disorder (PTSD). METHODS: Conditional latent growth mixture modelling was used to identify classes and predictors of class membership. In total, 2686 veterans treated for PTSD between 2002 and 2015 across 14 hospitals in Australia completed the PTSD Checklist at intake, discharge, and 3 and 9 months follow-up. Predictor variables included co-morbid mental health problems, relationship functioning, employment and compensation status. RESULTS: Five distinct classes were found: those with the most severe PTSD at intake separated into a relatively large class (32.5%) with small change, and a small class (3%) with a large change. Those with slightly less severe PTSD separated into one class comprising 49.9% of the total sample with large change effects, and a second class comprising 7.9% with extremely large treatment effects. The final class (6.7%) with least severe PTSD at intake also showed a large treatment effect. Of the multiple predictor variables, depression and guilt were the only two found to predict differences in response trajectories. CONCLUSIONS: These findings highlight the importance of assessing guilt and depression prior to treatment for PTSD, and for severe cases with co-morbid guilt and depression, considering an approach to trauma-focused therapy that specifically targets guilt and depression-related cognitions.