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Substance Use and Minority Stress in a Population of Lesbian, Gay and Bisexual Nurses.

Shannon L Avery-DesmaraisKristen A SetharesCaitlin StoverAbigail BatchelderMary K McCurry
Published in: Substance use & misuse (2020)
The aim of this study was to explore the incidence of problematic substance use (PSU) and the relationship between level of substance use, minority stress, and general stressors in a population of lesbian, gay and bisexual (LGB) identified nurses. Methods: A national, convenience sample of 394 self-identified LGB nurses completed an online survey in March 2019. Using data from the ASSIST V3.1 measurement tool, the incidence of problematic and non-problematic tobacco, alcohol and illicit substance use was described as a percentage of respondents in each group. Hierarchical regression assessed the impact of demographic variables, sexual orientation, gender identity, race/ethnicity, and level of substance use. Multiple regression assessed the impact of general stressors, minority stress processes, including coping and social support and internalized homophobia, on level of substance use. Results: The incidence of PSU was higher in this population of LGB-identified nurses than previously described in either the general population of nurses or the general LGB population. Demographic variables and minority status had variable associations with level of tobacco, alcohol and illicit substance use. Components of Meyer's minority stress model had a stronger and more consistent association with level of tobacco, alcohol and illicit substance use than general stress. Predictors of level of substance use across groups suggest community involvement may be significant. These results have potential implications for public health and the prevention and treatment of substance use in LGB-identified nurses.
Keyphrases
  • mental health
  • healthcare
  • social support
  • public health
  • men who have sex with men
  • depressive symptoms
  • risk factors
  • hiv positive
  • cross sectional
  • quality improvement
  • big data
  • hepatitis c virus