Effectiveness of Machine Learning-Based Adjustments to an eHealth Intervention Targeting Mild Alcohol Use
Strong correlates as indicated by machine learning analyses were found to affect goal setting and use of an eHealth program for alcohol use problems.
Authors
- Nick M. Lommerse
- Marloes E. Derksen (ORCID: https://orcid.org/0000-0003-0372-7021)
- Matthijs Blankers (ORCID: https://orcid.org/0000-0002-8821-3312)
- Tamara de Bruijn
- Anna E. Goudriaan (ORCID: https://orcid.org/0000-0001-8670-9384)
- Hamid Nasri
- Guido van Wingen (ORCID: https://orcid.org/0000-0003-3076-5891)
- Max van Beek (ORCID: https://orcid.org/0000-0002-6188-4984)
- Steffen Pauws (ORCID: https://orcid.org/0000-0003-2257-9239)
Institutions
- Tilburg University (NL)
- Amsterdam Institute for Addiction Research (NL)
- Trimbos Institute (NL)
- Jellinek (NL)
- Arkin (NL)
- Public Health Service of Amsterdam (NL)
- Reinier van Arkel (NL)
- Amsterdam University Medical Centers (NL)
Publication Details
- Journal
- European Addiction Research
- Published
- 2024-12-20
- DOI
- https://doi.org/10.1159/000543252
- Citations
- 2
- Primary Topic
- Digital Mental Health Interventions
- Type
- article
- Field-Weighted Citation Impact
- 0.82
Funders
- ZonMw