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Abstracto

Variables Associated with Drug and Alcohol Abuse among Male and Female users with Severe Mental Disorders

Marie-Josée Fleury, Guy Grenier and Jean-Marie Bamvita

Objectives: According to current literature, the most reliable variables associated with substance abuse are sociodemographic variables, mainly gender. Based on longitudinal research and a comprehensive framework, this study aimed to determine variables associated with substance abuse among users with severe mental disorders and between males and females of this general sample.

Methods: A cohort of 297 users with severe mental disorders was interviewed after an 18-month follow-up period. A hierarchical linear regression analysis was carried out using five blocks of independent variables at baseline (sociodemographic, clinical, needs and functionality, negative life events, social support). Two additional models were built to separately assess variables associated with substance abuse in males and females, using multiple linear regression analysis.

Results: Drug and alcohol abuse among users with severe mental disorders was associated with being non-French speaking, younger, male, a resident in autonomous housing, or an individual with less functionality and high severity of needs. Seven variables were associated with substance abuse among females while nine variables were independently associated with substance abuse among males.

Conclusion: The results confirm that socio-demographic variables are the most important variables associated with substance abuse among users with severe mental disorders. Language (being non-French-speaking) was the most important variable associated with substance abuse among users with severe mental disorders, and the only variable common to both males and females. These results suggest that mental health services need to pay special attention to certain linguistic minorities that are more likely to experience substance abuse issues.

Descargo de responsabilidad: este resumen se tradujo utilizando herramientas de inteligencia artificial y aún no ha sido revisado ni verificado.