The role of data type and recipient in individuals’ perspectives on sharing passively collected smartphone data for mental health: Cross-sectional questionnaire study

Jennifer Nicholas*, Katie Shilton, Stephen M. Schueller, Elizabeth L. Gray, Mary J. Kwasny, David C. Mohr

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

44 Scopus citations


Background: The growing field of personal sensing harnesses sensor data collected from individuals’ smartphones to understand their behaviors and experiences. Such data could be a powerful tool within mental health care. However, it is important to note that the nature of these data differs from the information usually available to, or discussed with, health care professionals. To design digital mental health tools that are acceptable to users, understanding how personal sensing data can be used and shared is critical. Objective: This study aimed to investigate individuals’ perspectives about sharing different types of sensor data beyond the research context, specifically with doctors, electronic health record (EHR) systems, and family members. Methods: A questionnaire assessed participants’ comfort with sharing six types of sensed data: physical activity, mood, sleep, communication logs, location, and social activity. Participants were asked about their comfort with sharing these data with three different recipients: doctors, EHR systems, and family members. A series of principal component analyses (one for each data recipient) was performed to identify clusters of sensor data types according to participants’ comfort with sharing them. Relationships between recipients and sensor clusters were then explored using generalized estimating equation logistic regression models. Results: A total of 211 participants completed the questionnaire. The majority were female (171/211, 81.0%), and the mean age was 38 years (SD 10.32). Principal component analyses consistently identified two clusters of sensed data across the three data recipients: “health information,” including sleep, mood, and physical activity, and “personal data,” including communication logs, location, and social activity. Overall, participants were significantly more comfortable sharing any type of sensed data with their doctor than with the EHR system or family members (P<.001) and more comfortable sharing “health information” than “personal data” (P<.001). Participant characteristics such as age or presence of depression or anxiety did not influence participants’ comfort with sharing sensed data. Conclusions: The comfort level in sharing sensed data was dependent on both data type and recipient, but not individual characteristics. Given the identified differences in comfort with sensed data sharing, contextual factors of data type and recipient appear to be critically important as we design systems that harness sensor data for mental health treatment and support.

Original languageEnglish (US)
Article numbere12578
JournalJMIR mHealth and uHealth
Issue number4
StatePublished - Apr 2019


  • Anxiety
  • Depression
  • Digital mental health
  • MHealth
  • Mobile phone
  • Personal sensing
  • Privacy

ASJC Scopus subject areas

  • Health Informatics


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