  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 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.
