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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Autores principales:	Kitti Bessenyei, Banuchitra Suruliraj, Alexa Bagnell, Patrick McGrath, Lori Wozney, Anna Huguet, Bernice Simone Elger, Sandra Meier, Rita Orji
Formato:	article
Lenguaje:	EN
Publicado:	Elsevier 2021
Materias:	Mobile sensing Mental health Data privacy Comfortability with data sharing Like of features Trust in mobile marketers Electronic computers. Computer science QA75.5-76.95 Psychology BF1-990
Acceso en línea:	https://doaj.org/article/cdcab1618cda4872aaed729ceb26cef2
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id	oai:doaj.org-article:cdcab1618cda4872aaed729ceb26cef2
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spelling	oai:doaj.org-article:cdcab1618cda4872aaed729ceb26cef22021-12-01T05:04:46ZComfortability with the passive collection of smartphone data for monitoring of mental health: An online survey2451-958810.1016/j.chbr.2021.100134https://doaj.org/article/cdcab1618cda4872aaed729ceb26cef22021-08-01T00:00:00Zhttp://www.sciencedirect.com/science/article/pii/S2451958821000828https://doaj.org/toc/2451-9588Background: 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.Kitti BessenyeiBanuchitra SurulirajAlexa BagnellPatrick McGrathLori WozneyAnna HuguetBernice Simone ElgerSandra MeierRita OrjiElsevierarticleMobile sensingMental healthData privacyComfortability with data sharingLike of featuresTrust in mobile marketersElectronic computers. Computer scienceQA75.5-76.95PsychologyBF1-990ENComputers in Human Behavior Reports, Vol 4, Iss , Pp 100134- (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Mobile sensing Mental health Data privacy Comfortability with data sharing Like of features Trust in mobile marketers Electronic computers. Computer science QA75.5-76.95 Psychology BF1-990
spellingShingle	Mobile sensing Mental health Data privacy Comfortability with data sharing Like of features Trust in mobile marketers Electronic computers. Computer science QA75.5-76.95 Psychology BF1-990 Kitti Bessenyei Banuchitra Suruliraj Alexa Bagnell Patrick McGrath Lori Wozney Anna Huguet Bernice Simone Elger Sandra Meier Rita Orji Comfortability with the passive collection of smartphone data for monitoring of mental health: An online survey
description	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.
format	article
author	Kitti Bessenyei Banuchitra Suruliraj Alexa Bagnell Patrick McGrath Lori Wozney Anna Huguet Bernice Simone Elger Sandra Meier Rita Orji
author_facet	Kitti Bessenyei Banuchitra Suruliraj Alexa Bagnell Patrick McGrath Lori Wozney Anna Huguet Bernice Simone Elger Sandra Meier Rita Orji
author_sort	Kitti Bessenyei
title	Comfortability with the passive collection of smartphone data for monitoring of mental health: An online survey
title_short	Comfortability with the passive collection of smartphone data for monitoring of mental health: An online survey
title_full	Comfortability with the passive collection of smartphone data for monitoring of mental health: An online survey
title_fullStr	Comfortability with the passive collection of smartphone data for monitoring of mental health: An online survey
title_full_unstemmed	Comfortability with the passive collection of smartphone data for monitoring of mental health: An online survey
title_sort	comfortability with the passive collection of smartphone data for monitoring of mental health: an online survey
publisher	Elsevier
publishDate	2021
url	https://doaj.org/article/cdcab1618cda4872aaed729ceb26cef2
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Comfortability with the passive collection of smartphone data for monitoring of mental health: An online survey

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