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

Keywords: Mobile apps, Privacy, User experience

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.

  

Author Biographies

Leming Zhou, University of Pittsburgh
Associate Professor, Department of Health Inforamtion Management
Bambang Parmanto, University of Pittsburgh
Professor, Department of Health Information Management

References

Atienza, A. A., Zarcadoolas, C., Vaughon, W., Hughes, P., Patel, V., Chou, W. Y., & Pritts, J. (2015). Consumer attitudes and perceptions on mhealth privacy and security: Findings from a mixed-methods study. Journal of Health Communication, 20(6), 673-679. https://doi.org/10.1080/10810730.2015.1018560

Beck, A. T., Steer, R. A., & Carbin, M. G. (1988). Psychometric properties of the Beck Depression Inventory: Twenty-five years of evaluation. Clinical Psychology Review, 8(1), 77-100. https://doi.org/10.1016/0272-7358(88)90050-5

Bendixen, R. M., Fairman, A. D., Karavolis, M., Sullivan, C., & Parmanto, B. (2017). A user-centered approach: Understanding client and caregiver needs and preferences in the development of mhealth apps for self-management. JMIR Mhealth and Uhealth, 5(9), e141. https://doi.org/10.2196/mhealth.7136

Boyles, J. L., Smith, A., & Madden, M. (2012). Privacy and data management on mobile devices. https://www.pewresearch.org/internet/.

Crookston, B. T., West, J. H., Hall, P. C., Dahle, K. M., Heaton, T. L., Beck, R. N., & Muralidharan, C. (2017). Mental and emotional self-help technology apps: Cross-sectional study of theory, technology, and mental health behaviors. JMIR Mental Health, 4(4), e45. https://doi.org/10.2196/mental.7262

Di Matteo, D., Fine, A., Fotinos, K., Rose, J., & Katzman, M. (2018). Patient willingness to consent to mobile phone data collection for mental health apps: Structured questionnaire. JMIR Mental Health, 5(3), e56. https://doi.org/10.2196/mental.9539

Feinberg, J., & Keeshin, S. (2017). Management of newly diagnosed HIV infection. Annals of Internal Medicine, 167(1), ITC1-ITC16. https://doi.org/10.7326/aitc201707040

Goedel, W. C., Mitchell, J. W., Krebs, P., & Duncan, D. T. (2017). Willingness to use mobile phone apps for HIV prevention among men who have sex with men in London: Web-based survey. JMIR Mhealth and Uhealth, 5(10), e153. https://doi.org/10.2196/mhealth.8143

Goldenberg, T., McDougal, S. J., Sullivan, P. S., Stekler, J. D., & Stephenson, R. (2014). Preferences for a mobile HIV prevention app for men who have sex with men. JMIR mHealth and uHealth, 2(4), e47. https://doi.org/10.2196/mhealth.3745

Goldenberg, T., McDougal, S. J., Sullivan, P. S., Stekler, J. D., & Stephenson, R. (2015). Building a mobile HIV prevention app for men who have sex with men: An iterative and community-driven process. JMIR Public Health Surveillance, 1(2), e18. https://doi.org/10.2196/publichealth.4449

Grundy, Q., Chiu, K., Held, F., Continella, A., Bero, L., & Holz, R. (2019). Data sharing practices of medicines related apps and the mobile ecosystem: Traffic, content, and network analysis. British Medical Journal, 364, l920. https://doi.org/10.1136/bmj.l920

Kao, C. K., & Liebovitz, D. M. (2017). Consumer mobile health apps: Current state, barriers, and future directions. Physical Medicine & Rehabilitation, 9(5S), S106-S115. https://doi.org/10.1016/j.pmrj.2017.02.018

Kenny, R., Dooley, B., & Fitzgerald, A. (2016). Developing mental health mobile apps: Exploring adolescents' perspectives. Health Informatics Journal, 22(2), 265-275. https://doi.org/10.1177/1460458214555041

Krebs, P., & Duncan, D. T. (2015). Health app use among us mobile phone owners: A national survey. JMIR Mhealth and Uhealth, 3(4), e101. https://doi.org/10.2196/mhealth.4924

Kroenke, K., Spitzer, R. L., & Williams, J. B. (2001). The PHQ-9: Validity of a brief depression severity measure. Journal of General Internal Medicine, 16(9), 606-613.

Lipschitz, J., Miller, C. J., Hogan, T. P., Burdick, K. E., Lippin-Foster, R., Simon, S. R., & Burgess, J. (2019). Adoption of mobile apps for depression and anxiety: Cross-sectional survey study on patient interest and barriers to engagement. JMIR Mental Health, 6(1), e11334. https://doi.org/10.2196/11334

Maglogiannis, I., Kazatzopoulos, L., Delakouridis, K., & Hadjiefthymiades, S. (2009). Enabling location privacy and medical data encryption in patient telemonitoring systems. IEEE Transactions on Information Technology and Biomedicine, 13(6), 946-954. https://doi.org/10.1109/TITB.2008.2011155

Martinez-Perez, B., de la Torre-Diez, I., & Lopez-Coronado, M. (2015). Privacy and security in mobile health apps: A review and recommendations. Journal of Medical Systems, 39(1), 181. https://doi.org/10.1007/s10916-014-0181-3

Mitchell, J. W., Torres, M. B., Joe, J., Danh, T., Gass, B., & Horvath, K. J. (2016). Formative work to develop a tailored HIV testing smartphone app for diverse, at-risk, HIV-negative men who have sex with men: A focus group study. JMIR Mhealth and Uhealth, 4(4), e128. https://doi.org/10.2196/mhealth.6178

Morera, E. P., de la Torre Diez, I., Garcia-Zapirain, B., Lopez-Coronado, M., & Arambarri, J. (2016). Security recommendations for mhealth apps: Elaboration of a developer's guide. Journal of Medical Systems, 40(6), 152. https://doi.org/10.1007/s10916-016-0513-6

Nussbaum, R., Kelly, C., Quinby, E., Mac, A., Parmanto, B., & Dicianno, B. E. (2019). Systematic review of mobile health applications in rehabilitation. Archives of Physical Medicine and Rehabilitation, 100(1), 115-127.

https://doi.org/10.1016/j.apmr.2018.07.439

Office for Civil Rights - United States Department of State, (2019). Breach portal: Notice to the Secretary of HHS breach of unsecured protected health information: Cases currently under investigation. https://ocrportal.hhs.gov/ocr/breach/breach_report.jsf

Olmstead, K., & Smith, A. (2017). American and cybersecurity. http://www.pewinternet.org/2017/1/26/americans-and-cybersecurity/

Parmanto, B., Pramana, G., Yu, D. X., Fairman, A. D., & Dicianno, B. E. (2015). Development of mhealth system for supporting self-management and remote consultation of skincare. BMC Medical Informatics and Decision Making, 15, 114. https://doi.org/10.1186/s12911-015-0237-4

Parmanto, B., Pramana, G., Yu, D. X., Fairman, A. D., Dicianno, B. E., & McCue, M. P. (2013). Imhere: A novel mhealth system for supporting self-care in management of complex and chronic conditions. JMIR Mhealth Uhealth, 1(2), e10. https://doi.org/10.2196/mhealth.2391

Pew Research Center. (2019). Mobile fact sheet. https://www.pewinternet.org/fact-sheet/mobile/

Proudfoot, J., Parker, G., Hadzi Pavlovic, D., Manicavasagar, V., Adler, E., & Whitton, A. (2010). Community attitudes to the appropriation of mobile phones for monitoring and managing depression, anxiety, and stress. Journal of Medical Internet Research, 12(5), e64. https://doi.org/10.2196/jmir.1475

Radloff, L. S. (1977). The CES-D scale: A self-report depression scale for research in the general population. Applied Psychological Measurement, 1, 385-401.

Reid, S. C., Kauer, S. D., Hearps, S. J., Crooke, A. H., Khor, A. S., Sanci, L. A., & Patton, G. C. (2013). A mobile phone application for the assessment and management of youth mental health problems in primary care: Health service outcomes from a randomised controlled trial of mobiletype. BMC Family Practice, 14, 84. https://doi.org/10.1186/1471-2296-14-84

Rendina, H. J., & Mustanski, B. (2018). Privacy, trust, and data sharing in web-based and mobile research: Participant perspectives in a large nationwide sample of men who have sex with men in the United States. Journal of Medical Internet Research, 20(7), e233. https://doi.org/10.2196/jmir.9019

Schueller, S. M., Neary, M., O'Loughlin, K., & Adkins, E. C. (2018). Discovery of and interest in health apps among those with mental health needs: Survey and focus group study. Journal of Medical Internet Research, 20(6), e10141. https://doi.org/10.2196/10141

Setiawan, I. M. A., Zhou, L., Alfikri, Z., Saptono, A., Fairman, A. D., Dicianno, B., & Parmanto, B. (2019). An adaptive mhealth system to support self-management for persons with chronic conditions and disabilities: Usability and feasibility studies. JMIR Formative Research, 3(2), e12982. https://doi.org/10.2196/12982

Shafique, U., Khan, H., Waqar, S., Sher, A., Zeb, A., Shafi, U., . . . Ullah, R. (2017). Modern authentication techniques in smart phones: Security and usability perspective. (IJACSA) International Journal of Advanced Computer Science and Applications, 8(1), 331-340.

Smith, K. A., Zhou, L., & Watzlaf, V. J. M. (2017). User authentication in smartphones for telehealth. International Journal of Telerehabilitation, 9(2), 3-12. https://doi.org/10.5195/ijt.2017.6226

Switsers, L., Dauwe, A., Vanhoudt, A., Van Dyck, H., Lombaerts, K., & Oldenburg, J. (2018). Users' perspectives on mhealth self-management of bipolar disorder: Qualitative focus group study. JMIR Mhealth Uhealth, 6(5), e108. https://doi.org/10.2196/mhealth.9529

Wang, H., & Chow, S.-C. (2007). Sample size calculation for comparing means. Wiley Encyclopedia of Clinical Trials. https://doi.org/10.1002/9780471462422.eoct006

Xu, H., Gupta, S., Rosson, M. B., & Caroll, J. M. (2012). Measuring mobile users' concerns for information privacy. Paper presented at the International Conference on Information Systems, ICIS 2012, Orlando, FL. .

Zhang, A., Reynolds, N. R., Farley, J. E., Wang, X., Tan, S., & Yan, J. (2019). Preferences for an HIV prevention mobile phone app: A qualitative study among men who have sex with men in China. BMC Public Health, 19(1), 297. https://doi.org/10.1186/s12889-019-6617-4

Zhou, L., Bao, J., Watzlaf, V., & Parmanto, B. (2019). Barriers to and facilitators of the use of mobile health apps from a security perspective: Mixed-methods study. JMIR Mhealth and Uhealth, 7(4), e11223. https://doi.org/10.2196/11223

Zhou, L., Parmanto, B., Alfikri, Z., & Bao, J. (2018). A mobile app for assisting users to make informed selections in security settings for protecting personal health data: Development and feasibility study. JMIR Mhealth and Uhealth, 6(12), e11210. https://doi.org/10.2196/11210

Published
2020-12-08
How to Cite
Zhou, L., & Parmanto, B. (2020). User Preferences for Privacy Protection Methods in Mobile Health Apps: A Mixed-Methods Study. International Journal of Telerehabilitation, 12(2), 13–26. https://doi.org/10.5195/ijt.2020.6319
Section
Original Research