mHealth Adoption Among Older Chinese Adults: A Conceptual Model With Design Suggestions

References

• Alam, M. Z., Hu, W., & Barua, Z. (2018). Using the UTAUT model to determine factors affecting acceptance and use of mobile health (mHealth) services in Bangladesh. Journal of Studies in Social Sciences, 17(2), 137–172.
   Google Scholar
• Askari, M., Klaver, N. S., van Gestel, T. J., & van de Klundert, J. (2020). Intention to use medical apps among older adults in the Netherlands: Cross-sectional study. Journal of Medical Internet Research, 22(9), e18080. https://doi.org/10.2196/18080
   PubMed Web of Science ®Google Scholar
• Bashshur, R., Shannon, G., Krupinski, E., & Grigsby, J. (2011). The taxonomy of telemedicine. Telemedicine Journal and e-Health: The Official Journal of the American Telemedicine Association, 17(6), 484–494. https://doi.org/10.1089/tmj.2011.0103
   PubMed Web of Science ®Google Scholar
• Becker, M. H. (1974). The health belief model and personal health behavior. Health Education Monographs, 2(4), 409–473. https://doi.org/10.1177/109019817400200407
   Google Scholar
• Beratarrechea, A., Lee, A. G., Willner, J. M., Jahangir, E., Ciapponi, A., & Rubinstein, A. (2014). The impact of mobile health interventions on chronic disease outcomes in developing countries: A systematic review. Telemedicine Journal and e-Health: The Official Journal of the American Telemedicine Association, 20(1), 75–82. https://doi.org/10.1089/tmj.2012.0328
   PubMed Web of Science ®Google Scholar
• Berkowsky, R. W., Sharit, J., & Czaja, S. J. (2017). Factors predicting decisions about technology adoption among older adults. Innovation in Aging, 1(3), igy002. https://doi.org/10.1093/geroni/igy002
   Web of Science ®Google Scholar
• Braun, V., & Clarke, V. (2006). Using thematic analysis in psychology. Qualitative Research in Psychology, 3(2), 77–101. https://doi.org/10.1191/1478088706qp063oa
   Google Scholar
• Chan, C. V., & Kaufman, D. R. (2011). A framework for characterizing eHealth literacy demands and barriers. Journal of Medical Internet Research, 13(4), e94. https://doi.org/10.2196/jmir.1750
   PubMed Web of Science ®Google Scholar
• Chen, K., & Chan, A. H. S. (2011). A review of technology acceptance by older adults. Gerontechnology, 10(1), 1–12. https://doi.org/10.4017/gt.2011.10.01.006.00
   Google Scholar
• Cho, J., Quinlan, M. M., Park, D., & Noh, G. Y. (2014). Determinants of adoption of smartphone health apps among college students. American Journal of Health Behavior, 38(6), 860–870. https://doi.org/10.5993/AJHB.38.6.8
   PubMed Web of Science ®Google Scholar
• Czaja, S. J., Charness, N., Fisk, A. D., Hertzog, C., Nair, S. N., Rogers, W. A., & Sharit, J. (2006). Factors predicting the use of technology: Findings from the Center for Research and Education on Aging and Technology Enhancement (CREATE). Psychology and Aging, 21(2), 333–352. https://doi.org/10.1037/0882-7974.21.2.333
   PubMed Web of Science ®Google Scholar
• Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319–340. https://doi.org/10.2307/249008
   Web of Science ®Google Scholar
• Deng, Z., Hong, Z., Ren, C., Zhang, W., & Xiang, F. (2018). What predicts patients’ adoption intention toward mHealth services in China: Empirical study. JMIR mHealth and uHealth, 6(8), e172. https://doi.org/10.2196/mhealth.9316
   PubMed Web of Science ®Google Scholar
• Engelsma, T., Jaspers, M. W. M., & Peute, L. W. (2021). Considerate mHealth design for older adults with Alzheimer’s disease and related dementias (ADRD): A scoping review on usability barriers and design suggestions. International Journal of Medical Informatics, 152, 104494. https://doi.org/10.1016/j.ijmedinf.2021.104494
   PubMed Web of Science ®Google Scholar
• Eyal, N. (2014). Hooked: How to build habit-forming products. Penguin.
   Google Scholar
• Fereday, J., & Muir-Cochrane, E. (2006). Demonstrating rigor using thematic analysis: A hybrid approach of inductive and deductive coding and theme development. International Journal of Qualitative Methods, 5(1), 80–92. https://doi.org/10.1177/160940690600500107
   Google Scholar
• Fishbein, M., & Ajzen, I. (1977). Belief, attitude, intention, and behavior: An introduction to theory and research. Addison-Wesley.
   Google Scholar
• Fisk, A. D., Czaja, S. J., Rogers, W. A., Charness, N., & Sharit, J. (2020). Designing for older adults: Principles and creative human factors approaches. CRC Press.
   Google Scholar
• Fogg, B. J. (2009). A behavior model for persuasive design [Paper presentation]. Proceedings of the 4th international Conference on Persuasive Technology. Persuasive, Claremont, California, USA. https://doi.org/10.1145/1541948.1541999
   Google Scholar
• Foong, P. S. (2016). The value of the life course perspective in the design of mobile technologies for older adults. In S. S. Lim (Ed.), Mobile communication and the family (pp. 165–181). Springer. https://doi.org/10.1007/978-94-017-7441-3_10
   Google Scholar
• Free, C., Phillips, G., Galli, L., Watson, L., Felix, L., Edwards, P., Patel, V., & Haines, A. (2013). The effectiveness of mobile-health technology-based health behaviour change or disease management interventions for health care consumers: A systematic review. PLoS Medicine, 10(1), e1001362. https://doi.org/10.1371/journal.pmed.1001362
   PubMed Web of Science ®Google Scholar
• Georgsson, M., & Staggers, N. (2016). An evaluation of patients’ experienced usability of a diabetes mHealth system using a multi-method approach. Journal of Biomedical Informatics, 59, 115–129. https://doi.org/10.1016/j.jbi.2015.11.008
   PubMed Web of Science ®Google Scholar
• Guo, X., Han, X., Zhang, X., Dang, Y., & Chen, C. (2015). Investigating m-health acceptance from a protection motivation theory perspective: gender and age differences. Telemedicine Journal and e-Health: The Official Journal of the American Telemedicine Association, 21(8), 661–669. https://doi.org/10.1089/tmj.2014.0166
   PubMed Web of Science ®Google Scholar
• iResearch. (2020). 2020 white paper of Chinese artificial intelligence mobile phone (in Chinese). https://www.iresearch.com.cn/Detail/report?id=3704&isfree=0
   Google Scholar
• Klasnja, P., & Pratt, W. (2012). Healthcare in the pocket: Mapping the space of mobile-phone health interventions. Journal of Biomedical Informatics, 45(1), 184–198. https://doi.org/10.1016/j.jbi.2011.08.017
   PubMed Web of Science ®Google Scholar
• Klaver, N. S., van de Klundert, J., van den Broek, R., & Askari, M. (2021). Relationship between perceived risks of using mHealth applications and the intention to use them among older adults in the Netherlands: Cross-sectional study. JMIR mHealth and uHealth, 9(8), e26845. https://doi.org/10.2196/26845
   PubMed Web of Science ®Google Scholar
• Kumar, S., Nilsen, W. J., Abernethy, A., Atienza, A., Patrick, K., Pavel, M., Riley, W. T., Shar, A., Spring, B., Spruijt-Metz, D., Hedeker, D., Honavar, V., Kravitz, R., Lefebvre, R. C., Mohr, D. C., Murphy, S. A., Quinn, C., Shusterman, V., & Swendeman, D. (2013). Mobile health technology evaluation: The mHealth evidence workshop. American Journal of Preventive Medicine, 45(2), 228–236. https://doi.org/10.1016/j.amepre.2013.03.017
   PubMed Web of Science ®Google Scholar
• Kuruvilla, S., Sadana, R., Montesinos, A. V., Beard, J., Vasdeki, J. F., de Carvalho, I. A., Thomas, R. B., Drisse, M.-N. B., Daelmans, B., & Goodman, T. (2018). A life-course approach to health: synergy with sustainable development goals. Bulletin of the World Health Organization, 96(1), 42. https://doi.org/10.2471/BLT.17.198358
   PubMed Web of Science ®Google Scholar
• Leung, L., & Chen, C. (2019). E-health/m-health adoption and lifestyle improvements: Exploring the roles of technology readiness, the expectation-confirmation model, and health-related information activities. Telecommunications Policy, 43(6), 563–575. https://doi.org/10.1016/j.telpol.2019.01.005
   Web of Science ®Google Scholar
• Limayem, M., Hirt, S. G., & Cheung, C. M. (2007). How habit limits the predictive power of intention: The case of information systems continuance. MIS Quarterly, 31(4), 705–737. https://doi.org/10.2307/25148817
   Web of Science ®Google Scholar
• Lv, X., Guo, X., Xu, Y., Yuan, J., & Yu, X. (2012). Explaining the mobile health services acceptance from different age groups: a protection motivation theory perspective. International Journal of Advancements in Computing Technology, 4(3), 1–9. https://doi.org/10.4156/ijact.vol4.issue3.1
   Google Scholar
• Miao, R., Wu, Q., Wang, Z., Zhang, X., Song, Y., Zhang, H., Sun, Q., & Jiang, Z. (2017). Factors that influence users’ adoption intention of mobile health: A structural equation modeling approach. International Journal of Production Research, 55(19), 5801–5815. https://doi.org/10.1080/00207543.2017.1336681
   Web of Science ®Google Scholar
• Mitzner, T. L., Rogers, W. A., Fisk, A. D., Boot, W. R., Charness, N., Czaja, S. J., & Sharit, J. (2014). Predicting older adults’ perceptions about a computer system designed for seniors. Universal Access in the Information Society, 15, 271–280. https://doi.org/10.1007/s10209-014-0383-y
   PubMed Web of Science ®Google Scholar
• Perry, K., Shearer, E., Sylvers, P., Carlile, J., & Felker, B. (2019). mHealth 101: An introductory guide for mobile apps in clinical practice. Journal of Technology in Behavioral Science, 4(2), 162–169. https://doi.org/10.1007/s41347-019-00108-8
   Google Scholar
• Plaza, I., Martín, L., Martin, S., & Medrano, C. (2011). Mobile applications in an aging society: Status and trends. Journal of Systems and Software, 84(11), 1977–1988. https://doi.org/10.1016/j.jss.2011.05.035
   Web of Science ®Google Scholar
• Ritchie, J., Lewis, J., Nicholls, C. M., & Ormston, R. (2013). Qualitative research practice: A guide for social science students and researchers. Sage.
   Google Scholar
• Rogers, E. M. (2010). Diffusion of innovations. Simon and Schuster.
   Google Scholar
• Rogers, R. W. (1975). A protection motivation theory of fear appeals and attitude change. The Journal of Psychology, 91(1), 93–114. https://doi.org/10.1080/00223980.1975.9915803
   PubMed Web of Science ®Google Scholar
• Salgado, T., Tavares, J., & Oliveira, T. (2020). Drivers of mobile health acceptance and use from the patient perspective: Survey study and quantitative model development. JMIR mHealth and uHealth, 8(7), e17588. https://doi.org/10.2196/17588
   PubMed Web of Science ®Google Scholar
• Schnall, R., Higgins, T., Brown, W., Carballo-Dieguez, A., & Bakken, S. (2015). Trust, perceived risk, perceived ease of use and perceived usefulness as factors related to mHealth technology use. Studies in Health Technology and Informatics, 216, 467–471.
   PubMedGoogle Scholar
• Shen, C., Wang, M. P., Chu, J. T., Wan, A., Viswanath, K., Chan, S. S. C., & Lam, T. H. (2017). Health app possession among smartphone or tablet owners in Hong Kong: Population-based survey. JMIR mHealth and uHealth, 5(6), e7628. https://doi.org/10.2196/mhealth.7628
   Web of Science ®Google Scholar
• Sun, J., Guo, Y., Wang, X., & Zeng, Q. (2016). mHealth for aging China: opportunities and challenges. Aging and disease, 7(1), 53. https://doi.org/10.14336/AD.2015.1011
   PubMed Web of Science ®Google Scholar
• Tajudeen, F. P. B., Maw Pin, N., Saedon, T., & Izzati, N. (2021). Mobile technologies and healthy ageing: A bibliometric analysis on publication trends and knowledge structure of mHealth research for older adults. International Journal of Human–Computer Interaction, 38(2), 1–13. https://doi.org/10.1080/10447318.2021.1926115
   Web of Science ®Google Scholar
• Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 27(3), 425–478. https://doi.org/10.2307/30036540
   Web of Science ®Google Scholar
• Venkatesh, V., Thong, J. Y., & Xu, X. (2012). Consumer acceptance and use of information technology: extending the unified theory of acceptance and use of technology. MIS Quarterly, 36(1), 157–178. https://doi.org/10.2307/41410412
   Web of Science ®Google Scholar
• Wang, K. H., Chen, G., & Chen, H.-G. (2017). A model of technology adoption by older adults. Social Behavior and Personality: An International Journal, 45(4), 563–572. https://doi.org/10.2224/sbp.5778
   Web of Science ®Google Scholar
• WHO. (2011). mHealth: New horizons for health through mobile technologies: Based on the findings of second global survey on eHealth. WHO. https://apps.who.int/iris/handle/10665/44607
   Google Scholar
• WHO. (2020). Decade of healthy ageing: Baseline report. https://www.who.int/publications/m/item/decade-of-healthy-ageing-baseline-report
   Google Scholar
• Wildenbos, G. A., Peute, L., & Jaspers, M. (2018). Aging barriers influencing mobile health usability for older adults: A literature based framework (MOLD-US). International Journal of Medical Informatics, 114, 66–75. https://doi.org/10.1016/j.ijmedinf.2018.03.012
   PubMed Web of Science ®Google Scholar