Comfortability with the passive collection of smartphone data for monitoring of mental health: An online survey

Abstract

Background: For successful integration of mobile sensing solutions in existing mental health services, patients' comfortability with mobile sensing is crucial. Objective: We thus aimed to investigate people's comfortability with mobile sensing and explore personal, mobile sensing app and data privacy related variables' impact on comfortability. Methods: We conducted an online survey including 491 participants aged >18 and ran three models of linear regression with comfortability with mobile sensing as primary outcome and personal variables as predictors in the 1st model; mobile sensing app related variables as predictors in the 2nd model; and general data privacy related variables as predictors in the 3rd model. Then, we ran an aggregated model of the previous three including all significant predictors. Results: Like of features, perceived control and trust in mobile marketers had the highest impact on comfortability with data sensing and they also predicted intentions to accept app permissions. Conclusions: People are more comfortable with sharing their data and more willing to take the risks of using mobile sensing apps if they find that the features provide them with valuable feedback related to their health. It is highly important for users that they can trust the people they provide access to their data and feel in control of the data they share.

Keywords

• Mobile sensing
• Mental health
• Data privacy
• Comfortability with data sharing
• Like of features
• Trust in mobile marketers