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Research Articles

Adoption of Wearable Devices by Older People: Changes in Use Behaviors and User Experiences

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Pages 964-987 | Received 03 Aug 2021, Accepted 25 May 2022, Published online: 31 Aug 2022

References

  • AARP. Building a better tracker: Older consumers weigh in on activity and sleep monitoring devices 2015. Retrieved March 1, 2020, https://www.aarp.org/content/dam/aarp/home-and-family/personal-technology/2015-07/innovation-50-project-catalyst-tracker-study-AARP.pdf
  • Abouzahra, M., & Ghasemaghaei, M. (2020). The antecedents and results of seniors’ use of activity tracking wearable devices. Health Policy and Technology, 9(2), 213–217. https://doi.org/10.1016/j.hlpt.2019.11.002
  • Adams, R. (2011). The utility of prestige: Chinese and American hedonic ratings of prestige goods. Journal of Global Marketing, 24(4), 287–304. https://doi.org/10.1080/08911762.2011.602320
  • Adapa, A., Nah, F. F.-H., Hall, R. H., Siau, K., & Smith, S. N. (2018). Factors influencing the adoption of smart wearable devices. International Journal of Human–Computer Interaction, 34(5), 399–409. https://doi.org/10.1080/10447318.2017.1357902
  • Anderson, C., & Robey, D. (2017). Affordance potency: Explaining the actualization of technology affordances. Information and Organization, 27(2), 100–115. https://doi.org/10.1016/j.infoandorg.2017.03.002
  • Arning, K., Ziefle, M., & Arning, J. (2008). Comparing apples and oranges? Exploring users’ acceptance of ICT-and eHealth-applications. Digital Camera, 83(50), 1.
  • Ashraf, R. U., Hou, F., & Ahmad, W. (2019). Understanding continuance intention to use social media in China: The roles of personality drivers, hedonic value, and utilitarian value. International Journal of Human–Computer Interaction, 35(13), 1216–1228. https://doi.org/10.1080/10447318.2018.1519145
  • Attig, C., & Franke, T. (2020). Abandonment of personal quantification: A review and empirical study investigating reasons for wearable activity tracking attrition. Computers in Human Behavior, 102, 223–237. https://doi.org/10.1016/j.chb.2019.08.025
  • Babin, B. J., Darden, W. R., & Griffin, M. (1994). Work and/or fun: Measuring hedonic and utilitarian shopping value. Journal of Consumer Research, 20(4), 644–656. https://doi.org/10.1086/209376
  • Bodine, K., & Gemperle, F. (2003). Effects of functionality on perceived comfort of wearables. Paper presented at the Seventh IEEE International Symposium on Wearable Computers, 2003. Proceedings. https://doi.org/10.1109/ISWC.2003.1241394
  • Chen, L., & Tsoi, H. K. (2011). Privacy concern and trust in using social network sites: A comparison between french and chinese users. Paper presented at the IFIP Conference on Human-Computer Interaction. https://doi.org/10.1007/978-3-642-23765-2_16
  • Choi, J., & Kim, S. (2016). Is the smartwatch an IT product or a fashion product? A study on factors affecting the intention to use smartwatches. Computers in Human Behavior, 63, 777–786. https://doi.org/10.1016/j.chb.2016.06.007
  • Cooper, C., Gross, A., Brinkman, C., Pope, R., Allen, K., Hastings, S., Bogen, B. E., & Goode, A. P. (2018). The impact of wearable motion sensing technology on physical activity in older adults. Experimental Gerontology, 112, 9–19. https://doi.org/10.1016/j.exger.2018.08.002
  • Dai, H., & Palvi, P. C. (2009). Mobile commerce adoption in China and the United States: A cross-cultural study. ACM SIGMIS Database, 40(4), 43–61. https://doi.org/10.1145/1644953.1644958
  • Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1989). User acceptance of computer technology: A comparison of two theoretical models. Management Science, 35(8), 982–1003. https://doi.org/10.1287/mnsc.35.8.982
  • Dehghani, M., Kim, K. J., & Dangelico, R. M. (2018). Will smartwatches last? Factors contributing to intention to keep using smart wearable technology. Telematics and Informatics, 35(2), 480–490. https://doi.org/10.1016/j.tele.2018.01.007
  • Dhar, R., & Wertenbroch, K. (2000). Consumer choice between hedonic and utilitarian goods. Journal of Marketing Research, 37(1), 60–71. https://doi.org/10.1509/jmkr.37.1.60.18718
  • Ehmen, H., Haesner, M., Steinke, I., Dorn, M., Gövercin, M., & Steinhagen-Thiessen, E. (2012). Comparison of four different mobile devices for measuring heart rate and ECG with respect to aspects of usability and acceptance by older people. Applied Ergonomics, 43(3), 582–587. https://doi.org/10.1016/j.apergo.2011.09.003
  • Farina, N., & Lowry, R. G. (2017). Older adults’ satisfaction of wearing consumer-level activity monitors. Journal of Rehabilitation and Assistive Technologies Engineering, 4, 1–6. https://doi.org/10.1177/2055668317733258
  • Farivar, S., Abouzahra, M., & Ghasemaghaei, M. (2020). Wearable device adoption among older adults: A mixed-methods study. International Journal of Information Management, 55, 102209. https://doi.org/10.1016/j.ijinfomgt.2020.102209
  • Gao, W., Emaminejad, S., Nyein, H. Y. Y., Challa, S., Chen, K., Peck, A., Fahad, H. M., Ota, H., Shiraki, H., Kiriya, D., Lien, D.-H., Brooks, G. A., Davis, R. W., & Javey, A. (2016). Fully integrated wearable sensor arrays for multiplexed in situ perspiration analysis. Nature, 529(7587), 509–514. https://doi.org/10.1038/nature16521
  • Gaver, W. W. (1991). Technology affordances. Paper presented at the Proceedings of the SIGCHI conference on Human factors in computing systems.
  • Gibson, J. J. (1977). The theory of affordances. In S. Robert & J. Bransford (Eds.), Perceiving, acting, and knowing: Toward an ecological psychology (pp. 67–82). Erlbaum.
  • Hart, J., & Sutcliffe, A. (2019). Is it all about the Apps or the Device?: User experience and technology acceptance among iPad users. International Journal of Human-Computer Studies, 130, 93–112. https://doi.org/10.1016/j.ijhcs.2019.05.002
  • Hassenzahl, M., & Tractinsky, N. (2006). User experience – A research agenda. Behaviour & Information Technology, 25(2), 91–97. https://doi.org/10.1080/01449290500330331
  • Holdack, E., Lurie-Stoyanov, K., & Fromme, H. F. (2022). The role of perceived enjoyment and perceived informativeness in assessing the acceptance of AR wearables. Journal of Retailing and Consumer Services, 65, 102259. https://doi.org/10.1016/j.jretconser.2020.102259
  • Hong, J.-C., Lin, P.-H., & Hsieh, P.-C. (2017). The effect of consumer innovativeness on perceived value and continuance intention to use smartwatch. Computers in Human Behavior, 67, 264–272. https://doi.org/10.1016/j.chb.2016.11.001
  • Hsiao, K.-L. (2017). What drives smartwatch adoption intention? Comparing apple and non-apple watches. Library Hi Tech, 35(1), 186–206. https://doi.org/10.1108/LHT-09-2016-0105
  • Hsiao, K.-L., & Chen, C.-C. (2018). What drives smartwatch purchase intention? Perspectives from hardware, software, design, and value. Telematics and Informatics, 35(1), 103–113. https://doi.org/10.1016/j.tele.2017.10.002
  • Hui, W. (2016). Population Aging and Long-Term Care Policy in China and the United States [Master dissertation]. St. Cloud State University.
  • Hutchby, I. (2001). Technologies, texts and affordances. Sociology, 35(2), 441–456. https://doi.org/10.1017/S0038038501000219
  • Hwang, C., Chung, T.-L., & Sanders, E. A. (2016). Attitudes and purchase intentions for smart clothing: Examining US consumers’ functional, expressive, and aesthetic needs for solar-powered clothing. Clothing and Textiles Research Journal, 34(3), 207–222. https://doi.org/10.1177/0887302X16646447
  • IDC. (2020). China’s wearable device market tracking report for the fourth quarter of 2019. Retrieved from https://www.idc.com/promo/wearablevendor
  • Jiang, X., Ji, S. (2009). Consumer online privacy concern and behaviour intention: Cultural and institutional aspects. Paper presented at the Proceedings of the International Conference on Information Resources Management (CONF-IRM).
  • Kalantari, M. (2017). Consumers’ adoption of wearable technologies: Literature review, synthesis, and future research agenda. International Journal of Technology Marketing, 12(3), 274–307. https://doi.org/10.1504/IJTMKT.2017.089665
  • Kaptelinin, V., & Nardi, B. (2012). Affordances in HCI: Toward a mediated action perspective. Paper presented at the CHI '12 Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, Austin, TX. https://doi.org/10.1145/2207676.2208541
  • Karahanna, E., Xu, S. X., Xu, Y., & Zhang, N. A. (2018). The needs–Affordances–Features perspective for the use of social media. MIS Quarterly, 42(3), 737–756. https://doi.org/10.25300/MISQ/2018/11492
  • Kekade, S., Hseieh, C.-H., Islam, M. M., Atique, S., Khalfan, A. M., Li, Y.-C., & Abdul, S. S. (2018). The usefulness and actual use of wearable devices among the elderly population. Computer Methods and Programs in Biomedicine, 153, 137–159. https://doi.org/10.1016/j.cmpb.2017.10.008
  • Keogh, A., Dorn, J. F., Walsh, L., Calvo, F., & Caulfield, B. (2020). Comparing the usability and acceptability of wearable sensors among older Irish adults in a real-world context: Observational study. JMIR mHealth and uHealth, 8(4), e15704. https://doi.org/10.2196/15704
  • Kianmehr, H., Sabounchi, N. S., Seyedzadeh Sabounchi, S., & Cosler, L. E. (2019). Patient expectation trends on receiving antibiotic prescriptions for respiratory tract infections: A systematic review and meta‐regression analysis. International Journal of Clinical Practice, 73(7), e13360. https://doi.org/10.1111/ijcp.13360
  • Kim, J., & Park, E. (2019). Beyond coolness: Predicting the technology adoption of interactive wearable devices. Journal of Retailing and Consumer Services, 49, 114–119. https://doi.org/10.1016/j.jretconser.2019.03.013
  • Kim, K. J., & Shin, D. H. (2015). An acceptance model for smart watches. Internet Research, 25(4), 527–541. https://doi.org/10.1108/IntR-05-2014-0126
  • Kim, T., & Chiu, W. (2019). Consumer acceptance of sports wearable technology: The role of technology readiness. International Journal of Sports Marketing and Sponsorship, 20(1), 109–126. https://doi.org/10.1108/IJSMS-06-2017-0050
  • Kononova, A., Li, L., Kamp, K., Bowen, M., Rikard, R., Cotten, S., & Peng, W. (2019). The use of wearable activity trackers among older people: Focus group study of tracker perceptions, motivators, and barriers in the maintenance stage of behavior change. JMIR mHealth and uHealth, 7(4), e9832. https://doi.org/10.2196/mhealth.9832
  • Law, E. L. C., Van Schaik, P., & Roto, V. (2014). Attitudes towards user experience (UX) measurement. International Journal of Human-Computer Studies, 72(6), 526–541. https://doi.org/10.1016/j.ijhcs.2013.09.006
  • Ledger, D., McCaffrey, D. (2014). Inside wearables: How the science of human behavior change offers the secret. Endeavour Partners. https://medium.com/@endeavourprtnrs/inside-wearable-how-the-science-of-human-behavior-change-offers-the-secret-to-long-term-engagement-a15b3c7d4cf3
  • Lee, B. C., Xie, J., Ajisafe, T., & Kim, S.-H. (2020). How are wearable activity trackers adopted in older people? Comparison between subjective adoption attitudes and physical activity performance. International Journal of Environmental Research and Public Health, 17(10), 3461. https://doi.org/10.3390/ijerph17103461
  • Leonardi, P. (2011). When flexible routines meet flexible technologies: Affordance, constraint, and the imbrication of human and material agencies. MIS Quarterly, 35(1), 147–167. https://doi.org/10.2307/23043493
  • Leonardi, P. M. (2013). When does technology use enable network change in organizations? A comparative study of feature use and shared affordances. MIS Quarterly, 37(3), 749–775. https://doi.org/10.25300/MISQ/2013/37.3.04
  • Li, J., Ma, Q., Chan, A. H., & Man, S. (2019). Health monitoring through wearable technologies for older people: Smart wearables acceptance model. Applied Ergonomics, 75, 162–169. https://doi.org/10.1016/j.apergo.2018.10.006
  • Li, L., Peng, W., Kamp, K., Bowen, M., Cotten, S. R., Rikard, R., & Kononova, A. (2017). Poster: Understanding long-term adoption of wearable activity trackers among older people. Paper presented at the Proceedings of the 2017 Workshop on Wearable Systems and Applications. http://dx.doi.org/10.1145/3089351.3089360
  • Li, L., Peng, W., Kononova, A., Bowen, M., & Cotten, S. R. (2020). Factors associated with older Adults' Long-Term Use of Wearable Activity Trackers. Telemedicine Journal and e-Health, 26(6), 769–775. https://doi.org/10.1089/tmj.2019.0052
  • Lili, W., & Min, D. (2014). Effect of cultural factors on online privacy concern: Korea vs. China. Journal of Information Technology Applications and Management, 21(2), 149–165. https://doi.org/10.21219/jitam.2014.21.2.149
  • Lim, E. A. C., & Ang, S. H. (2008). Hedonic vs. utilitarian consumption: A cross-cultural perspective based on cultural conditioning. Journal of Business Research, 61(3), 225–232. https://doi.org/10.1016/j.jbusres.2007.06.004
  • Liu, J. Y.-W., Kor, P. P.-K., Chan, C. P.-Y., Kwan, R. Y.-C., & Sze-Ki, D. (2020). The effectiveness of a wearable activity tracker (WAT)-based intervention to improve physical activity levels in sedentary older people: A systematic review and meta-analysis. Archives of Gerontology and Geriatrics, 91, 104211. https://doi.org/10.1016/j.archger.2020.104211
  • Liu, S., Zhang, W., Wu, L-h., & Wu, B. J. S. S, Medicine. (2019). Contributory behaviors and life satisfaction among Chinese older people: Exploring variations by gender and living arrangements. Social Science & Medicine, 229, 70–78. https://doi.org/10.1016/j.socscimed.2018.06.015
  • Liu, X., & Chen, Y. (2012). Information Ethics: A Cross-Cultural Study of Ethical Decision-Making between US and Chinese Business Students, 16, 25–28.
  • Lu, H., Hsu, C., & Hsu, H. (2005). An empirical study of the effect of perceived risk upon intention to use online applications. Information Management & Computer Security, 13(2), 106–120. https://doi.org/10.1108/09685220510589299
  • Lu, Y., Zhou, T., & Wang, B. (2009). Exploring Chinese users’ acceptance of instant messaging using the theory of planned behavior, the technology acceptance model, and the flow theory. Computers in Human Behavior, 25(1), 29–39. https://doi.org/10.1016/j.chb.2008.06.002
  • Lueg, C., Banks, B., Michalek, J., Dimsey, J., & Oswin, D. (2019). Close encounters of the Fifth kind: Recognizing system‐initiated engagement as interaction type. Journal of the Association for Information Science and Technology, 70(6), 634–637. https://doi.org/10.1002/asi.24136
  • Markus, M. L., & Silver, M. S. (2008). A foundation for the study of IT effects: A new look at DeSanctis and Poole’s concepts of structural features and spirit. Journal of the Association for Information Systems, 9(10), 609–632. https://doi.org/10.17705/1jais.00176
  • McMahon, S. K., Lewis, B., Oakes, M., Guan, W., Wyman, J. F., & Rothman, A. J. (2016). Older people’ experiences using a commercially available monitor to self-track their physical activity. JMIR mHealth and uHealth, 4(2), e5120. https://doi.org/10.2196/mhealth.5120
  • Mercer, K., Giangregorio, L., Schneider, E., Chilana, P., Li, M., & Grindrod, K. (2016). Acceptance of commercially available wearable activity trackers among adults aged Over 50 and with chronic illness: A mixed-methods evaluation. JMIR mHealth and uHealth, 4(1), e4225. https://doi.org/10.2196/mhealth.4225
  • Mercer, K., Giangregorio, L., Schneider, E., Chilana, P., Li, M., & Grindrod, K. (2016). Acceptance of commercially available wearable activity trackers among adults aged over 50 and with chronic illness: A mixed-methods evaluation. JMIR mHealth and uHealth, 4(1), e7. https://doi.org/10.2196/mhealth.4225
  • Niknejad, N., Ismail, W. B., Mardani, A., Liao, H., & Ghani, I. (2020). A comprehensive overview of smart wearables: The state of the art literature, recent advances, and future challenges. Engineering Applications of Artificial Intelligence, 90, 103529. https://doi.org/10.1016/j.engappai.2020.103529
  • Norman, D. A. (1988). The psychology of everyday things, New York Basic Book. paperback as the Design of Everyday Things, 1990.
  • Nunnally, J. C. (1978). Psychometric theory. 2nd ed. Mcgraw Hill Book Company.
  • Pal, D., Funilkul, S., & Vanijja, V. (2020). The future of smartwatches: Assessing the end-users’ continued use using an extended expectation-confirmation model. Universal Access in the Information Society, 19(2), 261–281. https://doi.org/10.1007/s10209-018-0639-z
  • Pan, S., & Jordan-Marsh, M. (2010). Internet use intention and adoption among Chinese older adults: From the expanded technology acceptance model perspective. Computers in Human Behavior, 26(5), 1111–1119. https://doi.org/10.1016/j.chb.2010.03.015
  • Park, E. (2020). User acceptance of smart wearable devices: An expectation-confirmation model approach. Telematics and Informatics, 47, 101318. https://doi.org/10.1016/j.tele.2019.101318
  • Preusse, K. C., Mitzner, T. L., Fausset, C. B., & Rogers, W. A. (2017). Older adults’ acceptance of activity trackers. Journal of Applied Gerontology, 36(2), 127–155. https://doi.org/10.1177/0733464815624151
  • Puri, A., Kim, B., Nguyen, O., Stolee, P., Tung, J., & Lee, J. (2017). User acceptance of wrist-worn activity trackers among community-dwelling older adults: Mixed method study. JMIR mHealth and uHealth, 5(11), e8211. https://doi.org/10.2196/mhealth.8211
  • Puri, A., Kim, B., Nguyen, O., Stolee, P., Tung, J., & Lee, J. (2017). User acceptance of wrist-worn activity trackers among community-dwelling older people: Mixed method study. JMIR mHealth and uHealth, 5(11), e173. https://doi.org/10.2196/mhealth.8211
  • Rasche, P., Wille, M., Theis, S., Schäefer, K., Schlick, C. M., & Mertens, A. (2015). Activity tracker and elderly. Paper presented at the 2015 IEEE International Conference on Computer and Information Technology; Ubiquitous Computing and Communications; Dependable, Autonomic and Secure Computing; Pervasive Intelligence and Computing. https://doi.org/10.1109/CIT/IUCC/DASC/PICOM.2015.211
  • Ridgers, N. D., McNarry, M. A., & Mackintosh, K. A. J. J. (2016). Feasibility and effectiveness of using wearable activity trackers in youth: A systematic review. JMIR Mhealth Uhealth, 4(4), e6540. https://doi.org/10.2196/mhealth.6540
  • Rupp, M. A., Michaelis, J. R., McConnell, D. S., & Smither, J. A. (2018). The role of individual differences on perceptions of wearable fitness device trust, usability, and motivational impact. Applied Ergonomics, 70, 77–87. https://doi.org/10.1016/j.apergo.2018.02.005
  • Schlomann, A. (2017). A case study on older people’ long-term use of an activity tracker. Gerontechnology, 16(2), 115–124. https://doi.org/10.4017/gt.2017.16.2.007.00
  • Shan, G., & Bohn, C. (2003). Anthropometrical data and coefficients of regression related to gender and race. Applied Ergonomics, 34(4), 327–337. https://doi.org/10.1016/S0003-6870(03)00040-1
  • Statistics, C. N. B. o. (2021). Seventh national census. Statistics, C. N. B. o.
  • Steele, R., Lo, A., Secombe, C., & Wong, Y. K. (2009). Elderly persons’ perception and acceptance of using wireless sensor networks to assist healthcare. International Journal of Medical Informatics, 78(12), 788–801. https://doi.org/10.1016/j.ijmedinf.2009.08.001
  • Steinert, A., Haesner, M., & Steinhagen-Thiessen, E. (2018). Activity-tracking devices for older people: Comparison and preferences. Universal Access in the Information Society, 17(2), 411–419. https://doi.org/10.1007/s10209-017-0539-7
  • Sundar, S. S., Go, E., Kim, H. S., & Zhang, B. (2015). Communicating art, virtually! Psychological effects of technological affordances in a virtual museum. International Journal of Human–Computer Interaction, 31(6), 385–401. https://doi.org/10.1080/10447318.2015.1033912
  • Talukder, M. S., Sorwar, G., Bao, Y., Ahmed, J. U., & Palash, M. A. (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
  • 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. JSTOR 30036540. https://doi.org/10.2307/30036540
  • 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
  • Venkatesh, V., & Zhang, X. (2010). Unified theory of acceptance and use of technology: U.S. Vs. China. Journal of Global Information Technology Management, 13(1), 5–27. https://doi.org/10.1080/1097198X.2010.10856507
  • Voss, K. E., Spangenberg, E. R., & Grohmann, B. (2003). Measuring the hedonic and utilitarian dimensions of consumer attitude. Journal of Marketing Research, 40(3), 310–320. https://doi.org/10.1509/jmkr.40.3.310.19238
  • Wang, L., Rau, P.-L P., & Salvendy, G. (2011). A cross-culture study on older adults’ information technology acceptance. International Journal of Mobile Communications, 9(5), 421–440. https://doi.org/10.1504/IJMC.2011.042452
  • Wang, Z., Yang, Z., & Dong, T. (2017). A review of wearable technologies for elderly care that can accurately track indoor position, recognize physical activities and monitor vital signs in real time. Sensors, 17(2), 341. https://doi.org/10.3390/s17020341
  • Wen, D., Zhang, X., & Lei, J. (2017). Consumers’ perceived attitudes to wearable devices in health monitoring in China: A survey study. Computer Methods and Programs in Biomedicine, 140, 131–137. https://doi.org/10.1016/j.cmpb.2016.12.009
  • Wilcox, S., Sharkey, J. R., Mathews, A. E., Laditka, J. N., Laditka, S. B., Logsdon, R. G., … Liu, R. J. T. g. (2009). Perceptions and beliefs about the role of physical activity and nutrition on brain health in older people. Gerontologist.49(S1), S61–S71. https://doi.org/10.1093/geront/gnp078
  • World Health Organization. (2015). World report on ageing and health.
  • Wu, L.-H., Wu, L.-C., & Chang, S.-C. (2016). Exploring consumers’ intention to accept smartwatch. Computers in Human Behavior, 64, 383–392. https://doi.org/10.1016/j.chb.2016.07.005
  • Yang, H., Yu, J., Zo, H., & Choi, M. (2016). User acceptance of wearable devices: An extended perspective of perceived value. Telematics and Informatics, 33(2), 256–269. https://doi.org/10.1016/j.tele.2015.08.007
  • Zhang, M., Luo, M., Nie, R., & Zhang, Y. (2017). Technical attributes, health attribute, consumer attributes and their roles in adoption intention of healthcare wearable technology. International Journal of Medical Informatics, 108, 97–109. https://doi.org/10.1016/j.ijmedinf.2017.09.016
  • Zhang, Y., Xu, L., Nevitt, M. C., Aliabadi, P., Yu, W., Qin, M., Lui, L.-Y., & Felson, D. T. (2001). Comparison of the prevalence of knee osteoarthritis between the elderly Chinese population in Beijing and whites in the United States. Arthritis & Rheumatism, 44(9), 2065–2071. https://doi.org/10.1002/1529-0131(200109)44:9<2065::AID-ART356>3.0.CO;2-Z
  • Zhou, J. (2019). Let us meet online! Examining the factors influencing older Chinese’s social networking site use. Journal of Cross-Cultural Gerontology, 34(1), 35–49. https://doi.org/10.1007/s10823-019-09365-9
  • Zhou, J., Rau, P.-L P., & Salvendy, G. (2014). Older adults’ use of smart phones: An investigation of the factors influencing the acceptance of new functions. Behaviour & Information Technology, 33(6), 552–560. https://doi.org/10.1080/0144929X.2013.780637

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