Ethical aspects and user preferences in applying machine learning to adjust eHealth addressing substance use: A mixed-methods study.

Journal: International journal of medical informatics
PMID: 40157245

Abstract

BACKGROUND: Digital health interventions targeting substance use disorders are being increasingly implemented. Data science methodology has the potential to enhance involvement and efficacy of these interventions, though application may raise ethical considerations. This study aimed to explore possible ethical aspects and preferences among users of an online digital intervention for substance use and gambling disorder regarding the application of supervised machine learning (ML) methodology.

Authors

  • Marloes E Derksen
    Arkin Mental Health Care and Amsterdam Institute for Addiction Research, Amsterdam, Netherlands; Amsterdam UMC, location University of Amsterdam, Department of Medical Informatics, eHealth Living & Learning Lab Amsterdam, Meibergdreef 9, Amsterdam, Netherlands; Amsterdam Public Health, Digital Health & Mental Health, Amsterdam, Netherlands. Electronic address: m.e.derksen@amsterdamumc.nl.
  • Max van Beek
    Arkin Mental Health Care, Amsterdam, The Netherlands.
  • Tamara de Bruijn
    Jellinek Prevention, Amsterdam, The Netherlands.
  • Floor Stuit
    Arkin Mental Health Care and Amsterdam Institute for Addiction Research, Amsterdam, Netherlands.
  • Matthijs Blankers
    Department of Research, Arkin Mental Health Care, Klaprozenweg 111, 1033NN, Amsterdam, The Netherlands. matthijs.blankers@arkin.nl.
  • Anneke E Goudriaan
    Arkin Mental Health Care and Amsterdam Institute for Addiction Research, Amsterdam, Netherlands; Amsterdam Public Health, Digital Health & Mental Health, Amsterdam, Netherlands; Amsterdam UMC, location University of Amsterdam, Department of Psychiatry, Meibergdreef 9, Amsterdam, the Netherlands.

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