Identifying Psychosocial and Ecological Determinants of Enthusiasm In Youth: Integrative Cross-Sectional Analysis Using Machine Learning.

Journal: JMIR public health and surveillance
PMID: 39264706

Abstract

BACKGROUND: Understanding the factors contributing to mental well-being in youth is a public health priority. Self-reported enthusiasm for the future may be a useful indicator of well-being and has been shown to forecast social and educational success. Typically, cross-domain measures of ecological and health-related factors with relevance to public policy and programming are analyzed either in isolation or in targeted models assessing bivariate interactions. Here, we capitalize on a large provincial data set and machine learning to identify the sociodemographic, experiential, behavioral, and other health-related factors most strongly associated with levels of subjective enthusiasm for the future in a large sample of elementary and secondary school students.

Authors

  • Roberta M Dolling-Boreham
    Temerty Faculty of Medicine, University of Toronto, Toronto, ON, Canada.
  • Akshay Mohan
    Krembil Centre for Neuroinformatics, Centre for Addiction and Mental Health, Toronto, ON, Canada.
  • Mohamed Abdelhack
    Graduate School of Informatics, Kyoto University, Yoshida-Honmachi, Sakyo-Ku, Kyoto 606-8501, Japan.
  • Tara Elton-Marshall
    School of Epidemiology and Public Health, Faculty of Medicine, University of Ottawa, Ottawa, ON, Canada.
  • Hayley A Hamilton
    Institute for Mental Health Policy Research, Centre for Addiction and Mental Health, Toronto, ON, Canada.
  • Angela Boak
    Institute for Mental Health Policy Research, Centre for Addiction and Mental Health, Toronto, ON, Canada.
  • Daniel Felsky
    Krembil Centre for Neuroinformatics, Centre for Addiction and Mental Health, Toronto, ON, Canada.

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