期刊
JOURNAL OF MEDICAL INTERNET RESEARCH
卷 23, 期 4, 页码 -出版社
JMIR PUBLICATIONS, INC
DOI: 10.2196/27069
关键词
personal health record; electronic medical record; my health bank; technology acceptance model; structural equation model; electronic health record; COVID-19; protection; survey; model; intention; usage; literacy; privacy; security
The successful completion of medical practices often depends on information collection and analysis. Taiwan's electronic personal health record platform "My Health Bank" has played a key role in managing personal health and preventing the spread of diseases like COVID-19. This study aims to understand people's intention to use the platform and investigate the factors influencing their decision.
Background: The successful completion of medical practices often relies on information collection and analysis. Government agencies and medical institutions have encouraged people to use medical information technology (MIT) to manage their conditions and promote personal health. In 2014, Taiwan established the first electronic personal health record (PHR) platform, My Health Bank (MHB), which allows people to access and manage their PHRs at any time. In the face of the COVID-19 pandemic in 2020, Taiwan has used MIT to effectively prevent the spread of COVID-19 and undertaken various prevention measures before the onset of the outbreak. Using MHB to purchase masks in an efficient and orderly way and thoroughly implementing personal protection efforts is highly important to contain disease spread. Objective: This study aims to understand people's intention to use the electronic PHR platform MHB and to investigate the factors affecting their intention to use this platform. Methods: From March 31 to April 9, 2014, in a promotion via email and Facebook, participants were asked to fill out a structured questionnaire after watching an introductory video about MHB on YouTube. The questionnaire included seven dimensions: perceived usefulness, perceived ease of use, health literacy, privacy and security, computer self-efficacy, attitude toward use, and behavioral intention to use. Each question was measured on a 5-point Likert scale ranging from strongly disagree (1 point) to strongly agree (5 points). Descriptive statistics and structural equation analysis were performed using SPSS 21 and AMOS 21 software. Results: A total of 350 valid questionnaire responses were collected (female: 219/350, 62.6%; age: 21-30 years: 238/350, 68.0%; university-level education: 228/350, 65.1%; occupation as student: 195/350, 56.6%; average monthly income
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