{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,7]],"date-time":"2026-10-07T13:52:55Z","timestamp":1791381175463,"version":"4.3.3"},"reference-count":94,"publisher":"JMIR Publications Inc.","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["J Med Internet Res"],"abstract":"<jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>The COVID-19 pandemic has shifted health care toward virtual and online models, impacting both users and providers. Numerous user concerns and perceived risks related to telemedicine are continually evolving and adjusting in response to the pandemic. In many countries, there has been a substantial increase in the use of virtual health care visits, which offers a unique opportunity for researchers to explore these user concerns.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Objective<\/jats:title>\n                    <jats:p>This study aimed to first reconstruct the risk dimensions associated with telemedicine, then identify the risk factors affecting users\u2019 adoption, and finally propose effective solutions to mitigate these concerns. By integrating the newly constructed perceived risk with the technology acceptance model (TAM), we scrutinized various dimensions of perceived risk and their influence on users\u2019 perceptions of ease of use, perceived usefulness, and use intention (UI).<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>Our target population consists of adults aged \u226518 years who have used or may use telemedicine services, recruited through an anonymous, voluntary, open, web-based survey. We collected responses and used part of them to reconstruct risk dimensions using exploratory factor analysis. Subsequently, we analyzed the intricate relationship between perceived risk, the TAM, and the acceptance of telemedicine using structural equation modeling with another part of the responses.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>A total of 1600 valid responses were collected. Eight distinct risk dimensions were reconstructed, revealing a substantial negative impact of performance risk on UI. The psychological and social risk was the strongest barrier to the ease of using telemedicine. Time risk, provider risk, and privacy risk were not statistically significant to the TAM. The resulting model elucidates a remarkable 66% variance in UI for telemedicine services.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>This study substantially advances the field of telemedicine research by reconstructing and redefining 8 risk dimensions and confirming the statistical significance of 5 perceived risks on the adoption of telemedicine services. These insights are poised to facilitate the promotion and enhancement of telemedicine services in the health care sector.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.2196\/53306","type":"journal-article","created":{"date-parts":[[2024,11,25]],"date-time":"2024-11-25T22:06:01Z","timestamp":1732572361000},"page":"e53306","source":"Crossref","is-referenced-by-count":5,"title":["Reconstructing Risk Dimensions in Telemedicine: Investigating Technology Adoption and Barriers During the COVID-19 Pandemic in 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