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This study investigates how technology readiness influences intention to use smart healthcare devices among Chinese seniors through technology interactivity, moderated by subjective norms.\n                    <jats:bold>Methods:<\/jats:bold>\n                    A cross-sectional survey involving 552 older participants from Wuxi, China, was analyzed using multiple linear regression and moderated mediation models.\n                    <jats:bold>Results:<\/jats:bold>\n                    The results showed that technology readiness significantly predicted usage intention and was fully mediated by technology interactivity. Subjective norms moderated the relationship between technology interactivity and usage intention, strengthening the indirect effect of technology readiness when subjective norms were high.\n                    <jats:bold>Conclusion:<\/jats:bold>\n                    The findings underscore the crucial role of technology interactivity in linking technology readiness to adoption, while subjective norms further reinforce this mechanism. To promote the adoption of smart healthcare devices, interventions should focus on enhancing technological literacy, fostering interactive user experiences, and leveraging community-driven social support. These findings contribute to resource conservation theory and provide policy insights to reduce digital disparities among aging populations.\n                  <\/jats:p>","DOI":"10.1177\/14604582251344828","type":"journal-article","created":{"date-parts":[[2025,5,23]],"date-time":"2025-05-23T19:25:44Z","timestamp":1748028344000},"update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":0,"title":["Technology readiness and smart healthcare device usage intentions among Chinese elderly: A moderated mediation model of technology interactivity and subjective norms"],"prefix":"10.1177","volume":"31","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-5923-6841","authenticated-orcid":false,"given":"Sheng","family":"Sun","sequence":"first","affiliation":[{"name":"Jiangnan University"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xiaoyang","family":"Lyu","sequence":"additional","affiliation":[{"name":"Jiangnan University"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jian","family":"Chen","sequence":"additional","affiliation":[{"name":"Jiangnan University"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"179","published-online":{"date-parts":[[2025,5,23]]},"reference":[{"key":"e_1_3_5_2_2","doi-asserted-by":"publisher","DOI":"10.3389\/fpsyg.2020.01029"},{"key":"e_1_3_5_3_2","first-page":"100346","article-title":"Artificial intelligence in the field of pharmacy practice: a literature review","volume":"12","author":"Chalasani SH","year":"2023","unstructured":"Chalasani SH, Syed J, Ramesh M, et al. 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