Beyond Detection: Towards Actionable Sensing Research in Clinical Mental Healthcare
Author(s)
Adler, Daniel
Yang, Yuewen
Viranda, Thalia
Xu, Xuhai
Mohr, David
Van Meter, Anna
Tartaglia, Julia
Jacobson, Nicholas
Wang, Fei
Estrin, Deborah
Date Issued
November 21, 2024
Journal
Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies
Publisher
ACM
Citation
Adler, Daniel, Yang, Yuewen, Viranda, Thalia, Xu, Xuhai, Mohr, David et al. 2024. "Beyond Detection: Towards Actionable Sensing Research in Clinical Mental Healthcare." Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies, 8 (4).
Version
Final published version
Abstract
Researchers in ubiquitous computing have long promised that passive sensing will revolutionize mental health measurement by detecting individuals in a population experiencing a mental health disorder or specific symptoms. Recent work suggests that detection tools do not generalize well when trained and tested in more heterogeneous samples. In this work, we contribute a narrative review and findings from two studies with 41 mental health clinicians to understand these generalization challenges. Our findings motivate research on actionable sensing, as an alternative to detection research, studying how passive sensing can be used alongside traditional mental health measures to support actions in clinical care. Specifically, we identify how passive sensing can support clinical actions by revealing patients' presenting problems for treatment and identifying targets for behavior change and symptom reduction, but passive data needs to be contextualized with patients to be appropriately interpreted and used in care. We conclude by suggesting research at the intersection of actionable sensing and mental healthcare, to align technical research in ubiquitous computing with clinical actions and needs.
MIT Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Terms of Use
Creative Commons Attribution
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1145/3699755
