Article
Personalized Prediction of Momentary Affect with Passive Smartphone Sensing Data in a Clinically Heterogeneous Sample: An evaluation of machine learning and mixed effects approaches
2026-02-28
Abstract excerpt
<p>Passive smartphone sensing offers a scalable, low-burden approach to continuous mental health monitoring, yet most studies which use passive sensing features to predict momentary psychological states rely on small, clinically homogeneous samples, limiting generalizability and clinical utility. This study compares methods for personalized prediction of momentary affect, stress, and fatigue using passive sensing...
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Identifiers and source
- Literature Corpus work
- 28ec4739-2744-51f7-9331-b02a4844ac58
- DOI
- 10.31234/osf.io/2g8dp_v1