Investigating Smartphone-Based Sensing Features for Depression Severity Prediction: Observation Study
Our findings underline the potential of smart sensing and EMA to infer depression severity as isolated paradigms and when combined. Although these could become important parts of clinical decision support systems for depression diagnostics and treatment in the future, confirmatory studies are needed before they can be applied to routine care. Furthermore, privacy, ethical, and acceptance issues need to be addressed.
Authors
- Eva-Maria Meßner (ORCID: https://orcid.org/0000-0001-6100-8354)
- Kennedy Opoku Asare (ORCID: https://orcid.org/0000-0003-1986-1006)
- Christian Montag (ORCID: https://orcid.org/0000-0001-8112-0837)
- Christopher Kannen (ORCID: https://orcid.org/0000-0003-4242-0233)
- Harald Baumeister (ORCID: https://orcid.org/0000-0002-2040-661X)
- Yannik Terhorst (ORCID: https://orcid.org/0000-0003-4091-5048)
Institutions
- Universität Ulm (DE)
- LMU Klinikum (DE)
- Ludwig-Maximilians-Universität München (DE)
- University of Oulu (FI)
Publication Details
- Journal
- Journal of Medical Internet Research
- Published
- 2024-10-18
- DOI
- https://doi.org/10.2196/55308
- Citations
- 5
- Primary Topic
- Digital Mental Health Interventions
- Type
- article
- Field-Weighted Citation Impact
- 2.05