An Empirical Study on the Influencing Factors of Mobile Health Apps Acceptance Among Silver Generation in China: An Extended STAM

Abdollahi, H., Mahoor, M. H., Zandie, R., Siewierski, J., & Qualls, S. H. (2023). Artificial Emotional Intelligence in Socially Assistive Robots for Older Adults: A Pilot Study. IEEE Transactions on Affective Computing, 14(3), 2020-2032. https://doi.org/10.1109/taffc.2022.3143803
Abdollahi, H., Mollahosseini, A., Lane, J. T., & Mahoor, M. H. (2017). A pilot study on using an intelligent life-like robot as a companion for elderly individuals with dementia and depression. 2017 IEEE-RAS 17th International Conference on Humanoid Robotics (Humanoids). https://doi.org/10.1109/humanoids.2017.8246925
Altman, I., & Taylor, D. A. (1973). Social penetration: The development of interpersonal relationships. Holt, Rinehart & Winston.
Ba, S., Whinston, A. B., & Zhang, H. (2003). Building trust in online auction markets through an economic incentive mechanism. Decision Support Systems, 35(3), 273-286.
Bart, Y., Shankar, V., Sultan, F., & Urban, G. L. (2005). Are the drivers and role of online trust the same for all web sites and consumers? A large-scale exploratory empirical study. Journal of marketing, 69(4), 133-152.
Becker, J. M., Klein, K., & Wetzels, M. (2012). Hierarchical latent variable models in PLS-SEM: guidelines for using reflective-formative type models. Long Range Planning, 45(5-6), 359-394.
Belanche, D., Casaló, L. V., & Flavián, C. (2019). Artificial Intelligence in FinTech: understanding robo-advisors adoption among customers. Industrial Management & Data Systems.
Belanche, D., Casaló, L. V., Schepers, J., & Flavián, C. (2021). Examining the effects of robots' physical appearance, warmth, and competence in frontline services: The Humanness?Value?Loyalty model. Psychology & Marketing, 38(12), 2357-2376.
Beldad, A., Hegner, S., & Snippe, J. (2017). The effects of initial trust on user adoption of mobile payment services: A theoretical framework and empirical study. Information & Management, 54(6), 782-797.
Boateng, S. L., & Narteh, B. (2016). Online relationship marketing and affective customer commitment–The mediating role of trust. Journal of Financial Services Marketing, 21, 127-140.
Bott, N., Wexler, S., Drury, L., Pollak, C., Wang, V., Scher, K., & Narducci, S. (2019). A protocol-driven, bedside digital conversational agent to support nurse teams and mitigate risks of hospitalization in older adults: case control pre-post study. Journal of medical Internet research, 21(10), e13440.
Burmester, M., Zeiner, K., Schippert, K., & Platz, A. (2019). Creating positive experiences with digital companions. In Extended Abstracts of the 2019 CHI Conference on Human Factors in Computing Systems (pp. 1-6). https://doi.org/10.1145/3290607.3312821
Carstensen, L. L. (1992). Social and emotional patterns in adulthood: support for socioemotional selectivity theory. Psychology and aging, 7(3), 331-338. https://doi.org/10.1037/0882-7974.7.3.331
Carstensen, L. L., Gottman, J. M., & Levenson, R. W. (1995). Emotional behavior in long-term marriage. Psychology and aging, 10(1), 140-149. https://doi.org/10.1037//0882-7974.10.1.140
Cascio Rizzo, G. L., Berger, J. A., & Villarroel Ordenes, F. (2023). What Drives Virtual Influencer's Impact?. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.4329150
Chandwani, R., De, R., & Dwivedi, Y. K. (2018). Telemedicine for low resource settings: Exploring the generative mechanisms. Technological Forecasting and Social Change, 127, 177-187. https://doi.org/10.1016/j.techfore.2017.06.014
Chen, K., & Chan, A. H. S. (2014). Gerontechnology acceptance by elderly Hong Kong Chinese: a senior technology acceptance model (STAM). Ergonomics , 57(5), 635-652. https://doi.org/10.1080/00140139.2014.895855
Chen, K., Lou, V. W., & Cheng, C. Y. M. (2023). Intention to use robotic exoskeletons by older people: A fuzzy-set qualitative comparative analysis approach. Computers in Human Behavior, 141, 107610. https://doi.org/10.1016/j.chb.2022.107610
Chen, K., & Lou, V. W. Q. (2020). Measuring senior technology acceptance: development of a brief, 14-item scale. Innovation in aging, 4(3). https://doi.org/10.1093/geroni/igaa016
Cheung, J., Tam, E., Chan, T., Law, T., Mak, A., & Zheng, Y. (2020). Interactive Doll Training System for Elderly with Dementia. Gerontechnology, 19(s), 1-1. https://doi.org/10.4017/gt.2020.19.s.69956
Chua, C. S. W., Lim, W. M., Teh, P.-L., & Pedell, S. (2022). Older Adults’ Evaluations of Mobile Apps: Insights from a Mobility App-based Solution. In 2022 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM) (pp. 1159-1163). IEEE. https://doi.org/10.1109/ieem55944.2022.9989960
Cimperman, M., Makovec Bren?i?, M., & Trkman, P. (2016). Analyzing older users’ home telehealth services acceptance behavior—applying an Extended UTAUT model. International Journal of Medical Informatics, 90, 22-31. https://doi.org/10.1016/j.ijmedinf.2016.03.002
Compeau, D. R., & Higgins, C. A. (1995). Computer self-efficacy: Development of a measure and initial test. MIS quarterly , 19(2), 189. https://doi.org/10.2307/249688
Conor, S. (2020). Share of mHealth apps incorporating advanced and standard AI worldwide 2020. https://www.statista.com/statistics/1180814/mhealth-apps-share-incorporating-ai/
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
Deng, Z., Liu, S., & Hinz, O. (2015). The health information seeking and usage behavior intention of Chinese consumers through mobile phones. Information Technology & People, 28(2), 405-423. https://doi.org/10.1108/itp-03-2014-0053
D'Onofrio, G., Sancarlo, D., Raciti, M., Burke, M., Teare, A., Kovacic, T., Cortis, K., Murphy, K., Barrett, E., Whelan, S., Dolan, A., Russo, A., Ricciardi, F., Pegman, G., Presutti, V., Messervey, T., Cavallo, F., Giuliani, F., Bleaden, A., … Greco, A. (2019). MARIO project: validation and evidence of service robots for older people with dementia. Journal of Alzheimer's Disease, 68(4), 1587-1601. https://doi.org/10.3233/jad-181165
Erel, H., Shem Tov, T., Kessler, Y., & Zuckerman, O. (2019). Robots are Always Social. Extended Abstracts of the 2019 CHI Conference on Human Factors in Computing Systems. https://doi.org/10.1145/3290607.3312758
Fang, E. F., Xie, C., Schenkel, J. A., Wu, C., Long, Q., Cui, H., Aman, Y., Frank, J., Liao, J., Zou, H., Wang, N. Y., Wu, J., Liu, X., Li, T., Fang, Y., Niu, Z., Yang, G., Hong, J., Wang, Q., … Woo, J. (2020). A research agenda for ageing in China in the 21st century (2nd edition): Focusing on basic and translational research, long-term care, policy and social networks. Ageing Research Reviews, 64, 101174. https://doi.org/10.1016/j.arr.2020.101174
Feinberg, J. M., & Aiello, J. R. (2006). Social Facilitation: A Test of Competing Theories. Journal of applied social psychology, 36(5), 1087-1109. https://doi.org/10.1111/j.0021-9029.2006.00032.x
Gambino, A., Fox, J., & Ratan, R. (2020). Building a Stronger CASA: Extending the Computers Are Social Actors Paradigm. Human-Machine Communication, 1, 71-86. https://doi.org/10.30658/hmc.1.5
Gell, N., Hoffman, E., & Patel, K. (2021). Technology support challenges and recommendations for adapting an evidence-based exercise program for remote delivery to older adults: exploratory mixed methods study. JMIR aging, 4(4), e27645. https://doi.org/10.2196/27645
Ghafurian, M., Ellard, C., & Dautenhahn, K. (2021). Social companion robots to reduce isolation: A perception change due to COVID-19. Human-Computer Interaction - INTERACT 2021, 43-63. https://doi.org/10.1007/978-3-030-85616-8_4
Guendelman, S., Broderick, A., Mlo, H., Gemmill, A., & Lindeman, D. (2017). Listening to communities: mixed-method study of the engagement of disadvantaged mothers and pregnant women with digital health technologies. Journal of medical Internet research, 19(7), e240. https://doi.org/10.2196/jmir.7736
Hall, M. A. (2006). Researching medical trust in the United States. Journal of health organization and management, 20(5), 456-467. https://doi.org/10.1108/14777260610701812
Huppertz, C., Forbrig, T. A., Lengert-Brzozowski, S., & Gräske, J. (2023). Associations Between Older Adults' Loneliness and Acceptance of Socially Assistive Robots: A Cross-Sectional Study. Journal of Gerontological Nursing, 49(4), 21-26. https://doi.org/10.3928/00989134-20230309-04
iMedia Research. (2023). Data on the Operational Status and Consumer Behavior of the Chinese Internet Healthcare Industry Survey.
Junglas, I., Goel, L., Abraham, C., & Ives, B. (2013). The Social component of information systems—How sociability contributes to technology acceptance. Journal of the Association for Information Systems, 14(10), 585-616. https://doi.org/10.17705/1jais.00344
Khan, T., Khan, K. D., Azhar, M. S., Shah, S. N. A., Uddin, M. M., & Khan, T. H. (2022). Mobile health services and the elderly: Assessing the determinants of technology adoption readiness in Pakistan. Journal of Public Affairs, 22(4). https://doi.org/10.1002/pa.2685
Kim, E., & Tadisina, S. (2003). Customers' initial trust in e-businesses: How to measure customers' initial trust.
Kim, G., Shin, B., & Lee, H. G. (2009). Understanding dynamics between initial trust and usage intentions of mobile banking. Information Systems Journal, 19(3), 283-311. https://doi.org/10.1111/j.1365-2575.2007.00269.x
Kim, H., Choi, H., Jung, Y.-I., Kim, E., Lee, W., & Yi, J. Y. (2023). Evaluation of a technology-enhanced, integrated community health and wellness program for seniors (HWePS): protocol of a non-randomized comparison trial. BMC Public Health, 23(1). https://doi.org/10.1186/s12889-022-14921-z
Kimiagari, S., & Baei, F. (2022). Promoting e-banking actual usage: mix of technology acceptance model and technology-organisation-environment framework. Enterprise Information Systems , 16(8-9). https://doi.org/10.1080/17517575.2021.1894356
Krämer, N. C., Eimler, S., von der Pütten, A., & Payr, S. (2011). THEORY OF COMPANIONS: WHAT CAN THEORETICAL MODELS CONTRIBUTE TO APPLICATIONS AND UNDERSTANDING OF HUMAN-ROBOT INTERACTION? Applied Artificial Intelligence, 25(6), 474-502. https://doi.org/10.1080/08839514.2011.587153
Lazard, A. J., Brennen, J. S., Troutman Adams, E., & Love, B. (2020). Cues for Increasing Social Presence for Mobile Health App Adoption. Journal of Health Communication, 25(2), 136-149. https://doi.org/10.1080/10810730.2020.1719241
Liang, A., Piroth, I., Robinson, H., MacDonald, B., Fisher, M., Nater, U. M., Skoluda, N., & Broadbent, E. (2017). A Pilot Randomized Trial of a Companion Robot for People With Dementia Living in the Community. Journal of the American Medical Directors Association, 18(10), 871-878. https://doi.org/10.1016/j.jamda.2017.05.019
Liu, F., Ngai, E., & Ju, X. (2019). Understanding mobile health service use: An investigation of routine and emergency use intentions. International Journal of Information Management, 45, 107-117. https://doi.org/10.1016/j.ijinfomgt.2018.09.004
Lu, H.-L., Liang, A.-R., & Li, Z.-J. (2018). Study on the effect of socialized online learning platform on undergraduates' continuous intention. Journal of Higher Education Finance, 021(002), 19-27.
Lu, X., Zhang, R., Wu, W., Shang, X., & Liu, M. (2018). Relationship between internet health information and patient compliance based on trust: Empirical study. Journal of Medical Internet Research, 20(8), e253. https://doi.org/10.2196/jmir.9364
Mehrabian, A., & Russell, J. A. (1974). An approach to environmental psychology. the MIT Press.
Melumad, S., & Pham, M. T. (2020). The smartphone as a pacifying technology. Journal of Consumer Research, 47(2), 237-255. https://doi.org/10.1093/jcr/ucaa005
Merrill, K., Jr., Kim, J., & Collins, C. (2022). AI companions for lonely individuals and the role of social presence. Communication Research Reports, 39(2), 93-103. https://doi.org/10.1080/08824096.2022.2045929
Metallo, C., Agrifoglio, R., Lepore, L., & Landriani, L. (2022). Explaing users’ technology acceptance through national cultural values in the hospital context. BMC health services research, 22(1). https://doi.org/10.1186/s12913-022-07488-3
Nass, C., Steuer, J., & Tauber, E. R. (1994). Computers are social actors. Proceedings of the SIGCHI conference on Human factors in computing systems celebrating interdependence - CHI '94. https://doi.org/10.1145/191666.191703
Nie, J., Wang, P., & Lei, L. (2020). Why can't we be separated from our smartphones? The vital roles of smartphone activity in smartphone separation anxiety. Computers in Human Behavior, 109, 106351. https://doi.org/10.1016/j.chb.2020.106351
Ou, C. X., Pavlou, P. A., & Davison, R. M. (2014). Swift guanxi in online marketplaces: The role of computer-mediated communication technologies. MIS quarterly, 38(1), 209-230. https://doi.org/10.25300/misq/2014/38.1.10
Ozkan-Yildirim, S., & Pancar, T. (2021). Smart Wearable Technology for Health Tracking: What Are the Factors that Affect Their Use?. IoT in Healthcare and Ambient Assisted Living, 165-199. https://doi.org/10.1007/978-981-15-9897-5_9
Pal, D., Funilkul, S., Charoenkitkarn, N., & Kanthamanon, P. (2018). Internet-of-things and smart homes for elderly healthcare: An end user perspective. IEEE Access, 6, 10483-10496. https://doi.org/10.1109/access.2018.2808472
Pappas, N. (2016). Marketing strategies, perceived risks, and consumer trust in online buying behaviour. Journal of retailing and consumer services, 29, 92-103. https://doi.org/10.1016/j.jretconser.2015.11.007
Park, H. K., Chung, J., & Ha, J. (2023). Acceptance of technology related to healthcare among older Korean adults in rural areas: A mixed-method study. Technology in Society, 72, 102182. https://doi.org/10.1016/j.techsoc.2022.102182
Park, S. M. (2015). The influence on self-esteem for skin & health care behavior according to the lifestyle of new silver generation. Kor J Aesthet Cosmetol, 13(1), 123-133.
Sarstedt, M., Hair, J. F., Jr., Cheah, J.-H., Becker, J.-M., & Ringle, C. M. (2019). How to Specify, Estimate, and Validate Higher-Order Constructs in PLS-SEM. Australasian Marketing Journal, 27(3), 197-211. https://doi.org/10.1016/j.ausmj.2019.05.003
Skjuve, M., Følstad, A., Fostervold, K. I., & Brandtzaeg, P. B. (2021). My chatbot companion - a Study of Human-Chatbot Relationships. International Journal of Human-Computer Studies, 149, 102601. https://doi.org/10.1016/j.ijhcs.2021.102601
Sohn, K., & Kwon, O. (2020). Technology acceptance theories and factors influencing artificial Intelligence-based intelligent products. Telematics and Informatics, 47, 101324. https://doi.org/10.1016/j.tele.2019.101324
Strohmann, T., Siemon, D., Khosrawi-Rad, B., & Robra-Bissantz, S. (2023). Toward a design theory for virtual companionship. Human–Computer Interaction, 38(3-4), 194-234. https://doi.org/10.1080/07370024.2022.2084620
Su, L., Cheng, J., & Swanson, S. R. (2020). The impact of tourism activity type on emotion and storytelling: The moderating roles of travel companion presence and relative ability. Tourism Management, 81, 104138. https://doi.org/10.1016/j.tourman.2020.104138
Ta, V., Griffith, C., Boatfield, C., Wang, X., Civitello, M., Bader, H., DeCero, E., & Loggarakis, A. (2020). User Experiences of Social Support From Companion Chatbots in Everyday Contexts: Thematic Analysis. Journal of Medical Internet Research, 22(3), e16235. https://doi.org/10.2196/16235
Takahashi, T. D. (2019). The Inspiring Possibilities and Sobering Realities of Making Virtual Beings. Venture Beat. Available online: https://venturebeat. Com/2019/07/26/the-deanbeat-the-inspiring-possibilities-and-sobering-realities-of-makingvirtual-beings/(accessed on 2 February 2022).
Talukder, M. S., Sorwar, G., Bao, Y., Ahmed, J. U., & Palash, M. A. S. (2020). Predicting antecedents of wearable healthcare technology acceptance by elderly: A combined SEM-Neural Network approach. Technological Forecasting and Social Change, 150, 119793. https://doi.org/10.1016/j.techfore.2019.119793
Triplett, N. (1898). The dynamogenic factors in pacemaking and competition. The American journal of psychology, 9(4), 507-533.
Urban, G. L., Amyx, C., & Lorenzon, A. (2009). Online trust: state of the art, new frontiers, and research potential. Journal of interactive marketing, 23(2), 179-190.
Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS quarterly, 425-478.
Wei, H., & Long, L. (2008). Interpersonal initial trust within organizations. Advances in Psychological Science, 16(02), 328.
World Health Organisation. (2011). mHealth New horizon for health through mobile technologies based on the findings of the second global survey on eHealth. Global observatory for eHealth series, Vol. 3.
World Health Organisation. (2016). China country assessment report on ageing and health. World Health Organization. https://www.who.int/ageing/publications/china-country-assessment/en/
Wulfert, T. (2019). Mobile app service quality dimensions and requirements for mobile shopping companion apps. Junior Management Science, 4(3), 339-391.
Xiao, F., Miao, Q., Xie, X., Sun, L., & Wang, R. (2018). SHMO: A seniors health monitoring system based on energy-free sensing. Computer Networks, 132, 108-117. https://doi.org/10.1016/j.comnet.2018.01.003
Ye, Q., Deng, Z., Chen, Y., Liao, J., Li, G., & Lu, Y. (2019). How Resource Scarcity and Accessibility Affect Patients ’ Usage of Mobile Health in China?: Resource Competition Perspective Corresponding Author?: 7, 1–14.
Zavoyskiy, S. (2023). Smartphones and Emotional Transfer: An Investigation of Smartphone-To-Human Emotional Contagion (Doctoral dissertation, State University of New York at Albany).
Zickuhr, K. A. T. H. R. Y. N., & Smith, A. (2012). Digital differences. Pew Internet & American Life Project. Pew Internet Research Project, April, 13.