People with Psychosis Evaluate Algorithmic Relapse Prediction
Researchers conducted a qualitative study of people with psychosis to assess attitudes toward algorithm-based relapse prediction and data sharing. The study examines views on using digital remote monitoring (DRM) systems and algorithmic tools to prevent relapses, focusing on patient perspectives that can shape DRM design, consent, and data-sharing practices.
Scoring Rationale
Patient perspectives directly inform the design and ethical deployment of algorithmic relapse-prediction and `DRM` systems, making this study moderately important for practitioners building clinical monitoring tools.
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