Correlates of past year suicidal thoughts among sexual and gender minority young adults: A machine learning analysis

J Psychiatr Res. 2022 Aug:152:269-277. doi: 10.1016/j.jpsychires.2022.06.013. Epub 2022 Jun 12.

Abstract

Sexual and gender minority populations are at elevated risk of experiencing suicidal thoughts and attempting suicide. The COVID-19 pandemic exacerbated mental health and substance use challenges among this population. We aimed to examine the relative importance and effects of intersectional factors and strong interactions associated with the risk of suicidal thoughts among Canadian lesbian, gay, bisexual, transgender, queer, questioning, intersex and Two Spirit (LGBTQI2S+) young adults. A cross-sectional online survey was conducted among LGBTQI2S + participants aged 16-29 years living in two Canadian provinces (Ontario, Quebec). Among 1414 participants (mean age 21.90 years), 61% (n = 857) participants reported suicidal thoughts in last 12 months. We built a random forest model to predict the risk of having past year suicidal thoughts, which achieved high performance with an area under the receiver operating characteristic curve (AUC) of 0.84. The top 10 correlates identified were: seeking help from health professionals for mental health or substance use issues since the start of the pandemic, current self-rated mental health status, insulted by parents or adults in childhood, ever heard that being identifying as LGBTQI2S+ is not normal, age in years, past week feeling depressed, lifetime diagnosis of mental illness, lifetime diagnosis of depressive disorder, past week feeling sad, ever pretended to be straight or cisgender to be accepted. The increase in the risk of suicidal thoughts for those having mental health challenges or facing minority stressors is more pronounced in those living in urban areas or being unemployed than those living in rural areas or being employed.

Keywords: Machine learning; Mental health; Sexual and gender minority; Suicide; Young adult.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adult
  • COVID-19* / epidemiology
  • Cross-Sectional Studies
  • Female
  • Humans
  • Machine Learning
  • Ontario
  • Pandemics
  • Sexual and Gender Minorities*
  • Substance-Related Disorders*
  • Suicidal Ideation
  • Young Adult