Using mobile phone sensor technology for mental health research: integrated analysis to identify hidden challenges and potential solutions

Tjeerd W. Boonstra, Jennifer Nicholas, Quincy J. J. Wong, Frances Shaw, Samuel Townsend, Helen Christensen

Research output: Contribution to journalArticlepeer-review

50 Citations (Scopus)
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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, location, 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% (iOS) of scheduled scans. Battery life was reduced from 21.3 hours to 18.8 hours when scanning every 5 minutes with a reduction of 2.5 hours or 12%. Despite this relatively small reduction, most participants reported that the app had a noticeable effect on their battery life. In addition to battery life, the purpose of data collection, trust in the organization that collects data, and perceived impact on privacy were identified as main factors for acceptability. CONCLUSIONS: Based on the findings of the feasibility study and literature review, we recommend a commitment to open science and transparent reporting and stronger partnerships and communication with users. Sensing technology has the potential to greatly enhance the delivery and impact of mental health care. Realizing this requires all aspects of mobile phone sensor technology to be rigorously assessed.

Original languageEnglish
Article numbere10131
Number of pages18
JournalJournal of Medical Internet Research
Issue number7
Publication statusPublished - 30 Jul 2018
Externally publishedYes

Bibliographical note

Copyright the Author(s) 2018. Version archived for private and non-commercial use with the permission of the author/s and according to publisher conditions. For further rights please contact the publisher.


  • passive sensing
  • mental health
  • ubiquitous computing
  • ethics
  • depression
  • mobile health
  • smartphone
  • wearable sensors


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