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

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 d...

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Bibliographic Details
Main Authors: Bagnell, A. (Author), Bessenyei, K. (Author), Elger, B.S (Author), Huguet, A. (Author), McGrath, P. (Author), Meier, S. (Author), Orji, R. (Author), Suruliraj, B. (Author), Wozney, L. (Author)
Format: Article
Language:English
Published: Elsevier Ltd 2021
Subjects:
Online Access:View Fulltext in Publisher
LEADER 02397nam a2200301Ia 4500
001 10.1016-j.chbr.2021.100134
008 220427s2021 CNT 000 0 und d
020 |a 24519588 (ISSN) 
245 1 0 |a Comfortability with the passive collection of smartphone data for monitoring of mental health: An online survey 
260 0 |b Elsevier Ltd  |c 2021 
856 |z View Fulltext in Publisher  |u https://doi.org/10.1016/j.chbr.2021.100134 
520 3 |a 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. © 2021 The Authors 
650 0 4 |a Comfortability with data sharing 
650 0 4 |a Data privacy 
650 0 4 |a Like of features 
650 0 4 |a Mental health 
650 0 4 |a Mobile sensing 
650 0 4 |a Trust in mobile marketers 
700 1 |a Bagnell, A.  |e author 
700 1 |a Bessenyei, K.  |e author 
700 1 |a Elger, B.S.  |e author 
700 1 |a Huguet, A.  |e author 
700 1 |a McGrath, P.  |e author 
700 1 |a Meier, S.  |e author 
700 1 |a Orji, R.  |e author 
700 1 |a Suruliraj, B.  |e author 
700 1 |a Wozney, L.  |e author 
773 |t Computers in Human Behavior Reports