Balancing Privacy and Utility in Child and Adolescent Mental Health Services Research: Retrospective Cohort Study on Synthetic Data Generation
Synthetic data can be used to build trust and promote collaboration among CAMHS researchers by offering access to extensive, representative samples with a low risk of patient identification. This approach expands the breadth of research while safeguarding patient privacy. Effective implementation of synthetic data generation depends on the model's ability to accurately identify and replicate the complex, sequential patterns present in real data.
Authors
- Roman Koposov (ORCID: https://orcid.org/0000-0002-7393-2920)
- Dipendra Pant (ORCID: https://orcid.org/0000-0001-5643-7541)
- Øystein Nytrø (ORCID: https://orcid.org/0000-0002-8163-2362)
- BENNETT L. LEVENTHAL (ORCID: https://orcid.org/0000-0001-6985-3691)
- Kaban Koochakpour (ORCID: https://orcid.org/0000-0001-7214-8651)
- Norbert Skokauskas (ORCID: https://orcid.org/0000-0002-9352-3489)
- Mounir Haizoune
- Lars Ravn Øhlckers
Institutions
- Norwegian University of Science and Technology (NO)
- Western Norway Regional Health Authority (NO)
- Stavanger University Hospital (NO)
- University of Chicago (US)
- St Olav's University Hospital (NO)
- Center for Child and Adolescent Mental Health, Eastern and Southern Norway (NO)
- UiT The Arctic University of Norway (NO)
Publication Details
- Journal
- JMIR Medical Informatics
- Published
- 2025-10-23
- DOI
- https://doi.org/10.2196/71819
- Primary Topic
- Digital Mental Health Interventions
- Type
- article
- Field-Weighted Citation Impact
- 0.00