Lived Experiences of Rural Elderly Using Mobile Health Applications for Chronic Disease Management in Indonesia
Main Article Content
Abstract
Digital health technologies, particularly mobile health (mHealth) applications, are increasingly used for chronic disease management among aging populations. Yet, little is known about how elderly individuals in rural Indonesia experience and interpret these technologies in daily life. Prior studies often adopt quantitative methods, overlooking the emotional and subjective aspects of mHealth use. This study employed a descriptive phenomenological approach to explore the lived experiences of elderly patients using mHealth for chronic disease management in rural Indonesia. Data were collected between March and May 2024 through in-depth, semi-structured interviews with eight participants. Thematic analysis was conducted to uncover patterns of meaning. Five central themes emerged: initial apprehension, evolving trust, digital isolation, intergenerational learning, and sustained routine. These findings reflect not only how participants interact with mHealth but also how their engagement is shaped by socio-emotional and cultural factors. The study underscores the need for digital health interventions to incorporate emotional, relational, and contextual dimensions to support elderly users more effectively. These insights inform the development of inclusive and empathetic mHealth systems tailored to aging populations in rural settings.
Article Details
Section

This work is licensed under a Creative Commons Attribution 4.0 International License.
References
Alessa, T., Hawley, M. S., Hock, E. S., & de Witte, L. (2019). Smartphone apps to support self-management of hypertension: Review and content analysis. JMIR mHealth and uHealth, 7(5). Scopus. https://doi.org/10.2196/13645
Baldwin, J. L., Singh, H., Sittig, D. F., & Giardina, T. D. (2017). Patient portals and health apps: Pitfalls, promises, and what one might learn from the other. Healthcare, 5(3), 81–85. Scopus. https://doi.org/10.1016/j.hjdsi.2016.08.004
Berg, B. L. (2001). Qualitative research methods for the social sciences (4th ed). Allyn and Bacon.
Bonoto, B. C., de Araújo, V. E., Godói, I. P., de Lemos, L. L. P., Godman, B., Bennie, M., Diniz, L. M., & Guerra, A. A. (2017). Efficacy of mobile apps to support the care of patients with diabetes mellitus: A systematic review and meta-analysis of randomized controlled trials. JMIR mHealth and uHealth, 5(3). Scopus. https://doi.org/10.2196/mhealth.6309
Brzan, P. P., Rotman, E., Pajnkihar, M., & Klanjsek, P. (2016). Mobile Applications for Control and Self Management of Diabetes: A Systematic Review. Journal of Medical Systems, 40(9). Scopus. https://doi.org/10.1007/s10916-016-0564-8
Chhabra, H. S., Sharma, S., & Verma, S. (2018). Smartphone app in self-management of chronic low back pain: A randomized controlled trial. European Spine Journal, 27(11), 2862–2874. Scopus. https://doi.org/10.1007/s00586-018-5788-5
Chung, C.-F., Cook, J., Bales, E., Zia, J., & Munson, S. A. (2015). More than telemonitoring: Health provider use and nonuse of life-log data in irritable bowel syndrome and weight management. Journal of Medical Internet Research, 17(8). Scopus. https://doi.org/10.2196/jmir.4364
Grainger, R., Townsley, H., White, B., Langlotz, T., & Taylor, W. J. (2017). Apps for people with rheumatoid arthritis to monitor their disease activity: A review of apps for best practice and quality. JMIR mHealth and uHealth, 5(2). Scopus. https://doi.org/10.2196/mhealth.6956
Jeffrey, B., Bagala, M., Creighton, A., Leavey, T., Nicholls, S., Wood, C., Longman, J., Barker, J., & Pit, S. (2019). Mobile phone applications and their use in the self-management of Type 2 Diabetes Mellitus: A qualitative study among app users and non-app users. Diabetology and Metabolic Syndrome, 11(1). Scopus. https://doi.org/10.1186/s13098-019-0480-4
Lee, J.-A., Choi, M., Lee, S. A., & Jiang, N. (2018). Effective behavioral intervention strategies using mobile health applications for chronic disease management: A systematic review. BMC Medical Informatics and Decision Making, 18(1). Scopus. https://doi.org/10.1186/s12911-018-0591-0
Majeed-Ariss, R., Baildam, E., Campbell, M., Chieng, A., Fallon, D., Hall, A., McDonagh, J. E., Stones, S. R., Thomson, W., & Swallow, V. (2015). Apps and adolescents: A systematic review of adolescents’ use of mobile phone and tablet apps that support personal management of their chronic or long-term physical conditions. Journal of Medical Internet Research, 17(12). Scopus. https://doi.org/10.2196/jmir.5043
Miller, A. S., Cafazzo, J. A., & Seto, E. (2016). A game plan: Gamification design principles in mHealth applications for chronic disease management. Health Informatics Journal, 22(2), 184–193. Scopus. https://doi.org/10.1177/1460458214537511
Nicholas, J., Larsen, M. E., Proudfoot, J., & Christensen, H. (2015). Mobile apps for bipolar disorder: A systematic review of features and content quality. Journal of Medical Internet Research, 17(8). Scopus. https://doi.org/10.2196/jmir.4581
Riegel, B., Moser, D. K., Buck, H. G., VaughanDickson, V., B.Dunbar, S., Lee, C. S., Lennie, T. A., Lindenfeld, J., Mitchell, J. E., Treat-Jacobson, D. J., & Webber, D. E. (2017). Self-care for the prevention and management of cardiovascular disease and stroke: A scientific statement for healthcare professionals from the American heart association. Journal of the American Heart Association, 6(9). Scopus. https://doi.org/10.1161/JAHA.117.006997
Sallis, R., Franklin, B., Joy, L., Ross, R., Sabgir, D., & Stone, J. (2015). Strategies for Promoting Physical Activity in Clinical Practice. Progress in Cardiovascular Diseases, 57(4), 375–386. Scopus. https://doi.org/10.1016/j.pcad.2014.10.003
Stein, N., & Brooks, K. (2017). A fully automated conversational artificial intelligence for weight loss: Longitudinal observational study among overweight and obese adults. JMIR Diabetes, 2(2). Scopus. https://doi.org/10.2196/diabetes.8590
Wildenbos, G. A., Jaspers, M. W. M., Schijven, M. P., & Dusseljee-Peute, L. W. (2019). Mobile health for older adult patients: Using an aging barriers framework to classify usability problems. International Journal of Medical Informatics, 124, 68–77. Scopus. https://doi.org/10.1016/j.ijmedinf.2019.01.006