Predicting cannabis use moderation among a sample of digital self-help subscribers: A machine learning study
Our study found only modest prediction accuracy when using machine learning models to predict success among individuals who use cannabis and desire to reduce/quit and show interest in digital self-help tools.
Authors
- Marleen I. A. Olthof (ORCID: https://orcid.org/0000-0002-3800-5363)
- Margriet van Laar (ORCID: https://orcid.org/0000-0003-3977-126X)
- Matthijs Blankers (ORCID: https://orcid.org/0000-0002-8821-3312)
- Anna E. Goudriaan (ORCID: https://orcid.org/0000-0001-8670-9384)
- Lucas A. Ramos (ORCID: https://orcid.org/0000-0001-7738-9200)
Institutions
- Trimbos Institute (NL)
- Public Health Service of Amsterdam (NL)
- Amsterdam University of Applied Sciences (NL)
- University of Amsterdam (NL)
Publication Details
- Journal
- Drug and Alcohol Dependence
- Published
- 2024-09-06
- DOI
- https://doi.org/10.1016/j.drugalcdep.2024.112431
- Citations
- 1
- Primary Topic
- Digital Mental Health Interventions
- Type
- article
- Field-Weighted Citation Impact
- 0.41
Funders
- Ministerie van Volksgezondheid, Welzijn en Sport