User Preferences for Privacy Protection Methods in Mobile Health Apps: A Mixed-Methods Study.

Leming Zhou,Bambang Parmanto

doi:10.5195/ijt.2020.6319

Leming Zhou, Bambang Parmanto

Open Access

https://doi.org/10.5195/ijt.2020.6319

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Abstract

Background:Mobile health (mHealth) apps have the potential to facilitate convenient health care delivery and self-management of health. However, many users have concerns about their privacy when they use mHealth apps. Different apps provide different solutions for protecting users' privacy.Objective:The purpose of this study was to determine user preferences among the several privacy protection methods used in current mHealth apps and the reasons behind their preferences.Methods:Five privacy protection methods currently used in mHealth apps were presented to a group of study participants who had mild or moderate depression and expressed concerns about privacy of information when they used mental health apps. After a demonstration of the methods, study participants were asked to fill out a questionnaire and indicate their perceived privacy protection level (PPPL) of each method, their preference rating for each method, and the privacy protection methods they had used in the past. A brief interview was then conducted to collect study participants' comments on these methods and elicit the reasons for their preference ratings. Statistical analysis was performed to determine the statistical significance of differences in participants' preference ratings and in the PPPLs obtained for the five methods. Study participants' comments on the privacy protection methods and suggestions were noted and summarized.Results:Forty (40) study participants were selected from a large candidate pool using the IRB approved selection criteria. All study participants viewed the app demonstration and understood the five privacy protection methods properly, which was indicated by their correct sorting of the PPPL of the five methods in their answers to the questionnaire. All study participants specified their preferences with respect to these methods and provided the rationale behind their selections on the questionnaire and during the brief interview. The results indicate that the users preferred privacy protection methods with customizable modules in multi-purpose apps because of their convenience and strong privacy protection, where the customization can be done either in the app or via a Web portal.Conclusions:This study identified user preferred privacy protection methods. These identified privacy protection methods may be used in many types of apps that perform sensitive health information management to better protect users' privacy and encourage more users to adopt these mHealth apps.

Highlights

OF PARTICIPANTS TO THE STUDYAt the beginning of the study, the investigators explained the purpose of the study, the procedure to be followed, and what data would be collected in the study.STEP 5
After a demonstration of the methods, study participants were asked to fill out a questionnaire and indicate their perceived privacy protection level (PPPL) of each method, their preference rating for each method, and the privacy protection methods they had used in the past
Local privacy violations are committed by people around a person; these are accomplished in various ways, including asking private questions, using personal items without authorization, viewing the person’s internet browsing history on his or her personal computer or mobile device, and observing a person during private activities such as using a mobile health app (Boyles et al, 2012)

Summary

Introduction

OF PARTICIPANTS TO THE STUDYAt the beginning of the study, the investigators explained the purpose of the study, the procedure to be followed, and what data would be collected in the study.STEP 5. The study participants were asked to fill out a questionnaire that elicited demographic information, their perceived privacy protection level (PPPL) for the five presented privacy protection methods, their preference rating for each method, and the methods they typically used to protect their local privacy. Objective: The purpose of this study was to determine user preferences among the several privacy protection methods used in current mHealth apps and the reasons behind their preferences. After a demonstration of the methods, study participants were asked to fill out a questionnaire and indicate their perceived privacy protection level (PPPL) of each method, their preference rating for each method, and the privacy protection methods they had used in the past. All study participants viewed the app demonstration and understood the five privacy protection methods properly, which was indicated by their correct sorting of the PPPL of the five methods in their answers to the questionnaire.

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