Predicting anorexia nervosa treatment efficacy: an explainable machine learning approach
Results encouraged interventions focused on body-self experience in addition to interpersonal relationships, including body-swapping experiences and metaverse activities, respectively. This could maximize treatment efficacy, effectively allocating limited resources to achieve clinically relevant outcomes.
Authors
- Elena Sajno (ORCID: https://orcid.org/0000-0002-9621-8981)
- Giulia Brizzi (ORCID: https://orcid.org/0009-0000-7472-742X)
- Margherita Boltri (ORCID: https://orcid.org/0000-0002-6742-8541)
- Leonardo Mendolicchio (ORCID: https://orcid.org/0000-0002-0225-1407)
- Federico Brusa (ORCID: https://orcid.org/0000-0002-5353-7296)
- Federica Scarpina (ORCID: https://orcid.org/0000-0003-4326-1596)
- Chiara Pupillo (ORCID: https://orcid.org/0009-0007-5764-1211)
- Giuseppe Riva (ORCID: https://orcid.org/0000-0002-1825-7635)
Institutions
- Università Cattolica del Sacro Cuore (IT)
- University of Pisa (IT)
- IRCCS Istituto Auxologico Italiano (IT)
- Ospedale San Giuseppe (IT)
- University of Turin (IT)
Publication Details
- Journal
- Journal of Eating Disorders
- Published
- 2025-06-02
- DOI
- https://doi.org/10.1186/s40337-025-01265-3
- Citations
- 2
- Primary Topic
- Eating Disorders and Behaviors
- Type
- article
- Field-Weighted Citation Impact
- 4.61
Funders
- Ministero della Salute