A 5-year longitudinal examination of the co-occurring patterns of gambling and other addictive behaviors

ADDICTIVE BEHAVIORS(2024)

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摘要
Objective: We examined the co-occurring patterns of problem gambling and substance/behavioral addiction severity over a fiveyear period and the predictors of the different co-occurring patterns of problem gambling and addiction severity.Methods: We conducted a secondary analysis of the Quinte Longitudinal Study (QLS) data. The QLS is a 5-year prospective longitudinal study of gambling and problem gambling in the Quinte Region in Southern Ontario. The QLS consists of a total of 4,121 participants, including a sample of participants at risk of developing problem gambling. Severity of problem gambling, substance use, and behavioral addictions were used to examine their co-occurring patterns over time. Predictors of the co-occurring patterns included the presence of mental health disorders, personality, stress, happiness, lifesatisfaction, social support, family history, and demographics. Results: Six co-occurring patterns of problem gambling and addiction severity were identified. The largest cooccurring pattern was characterized by concurrent decrease in gambling and other addictive behaviors. Several co-occurring patterns were characterized by moderate-to-severe problem gambling and other addiction severity that remained stable over time. No co-occurring pattern represented a decrease in gambling followed by increase in other addictive behaviors (e.g., addiction substitution). The presence of mental health disorders, stress, and lifesatisfaction significantly predicted the different co-occurring patterns. Conclusions: Taken together, the results suggest that in a non-clinical sample, gambling and other co-occurring addictive behaviors are likely to simultaneously decrease over time. Comorbidity of mental health disorders significantly influences co-occurring patterns of gambling and other addictive behaviors.
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关键词
Co-occurring pattern of addictive behavior,Addiction substitution,Quinte Longitudinal Study,Latent class growth analyses,Dual-process model
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