Using mobile phone sensor technology for mental health research: Integrated analysis to identify hidden challenges and potential solutions
Tjeerd W Boonstra, Jennifer Nicholas, Quincy JJ Wong, Frances Shaw,, Samuel Townsend, Helen Christensen

TL;DR
This study explores the technical and social challenges of using mobile phone sensors for mental health research, emphasizing data collection, privacy, and acceptability to improve behavioral health markers.
Contribution
It provides an integrated analysis of technical and user acceptability challenges in passive sensor data collection for mental health, based on a feasibility study and literature review.
Findings
Sensor data was obtained for 55% (Android) and 45% (iPhone) of scheduled scans.
Battery life was reduced by 12% with frequent scanning, affecting user experience.
Trust, privacy, and purpose of data collection influence app acceptability.
Abstract
Background: Mobile phone sensor technology has great potential in providing behavioral markers of mental health. However, this promise has not yet been brought to fruition. Objective: The objective of our study was to examine challenges involved in developing an app to extract behavioral markers of mental health from passive sensor data. Methods: Both technical challenges and acceptability of passive data collection for mental health research were assessed based on literature review and results obtained from a feasibility study. Socialise, a mobile phone app developed at the Black Dog Institute, was used to collect sensor data (Bluetooth, global positioning system, and battery status) and investigate views and experiences of a group of people with lived experience of mental health challenges (N=32). Results: On average, sensor data were obtained for 55% (Android) and 45% (iPhone OS) of…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
