Accepted for/Published in: Journal of Medical Internet Research
Date Submitted: Jan 18, 2021
Date Accepted: Apr 1, 2021
Date Submitted to PubMed: Apr 22, 2021
An Internet Survey with the Technology Acceptance Model for Deploying Masks in Combating COVID-19: Structural Equation Modeling Analysis of My Health Bank in Taiwan
ABSTRACT
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 to 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 coronavirus disease 2019 (COVID-19) pandemic in 2020, Taiwan has used MIT to effectively prevent the spread of COVID-19 and completed various prevention measures before the outbreak. Using MHB to purchase masks in an efficient and orderly way and thoroughly implement personal protection efforts is highly important.
Objective:
(1) To understand people’s intention to use the electronic PHR platform MHB. (2) To investigate the factors affecting people’s intention to use MHB.
Methods:
From March 31, 2014, to April 9, 2014, in a promotion via email and Facebook, subjects were asked to fill out the 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 IBM SPSS Statistics 21 and AMOS 21.
Results:
This study collected 350 valid questionnaires (female: 219/350, 62.6%; age: 21-30 years: 238/350, 68.0%; education level: university: 228/350, 65.1%; occupation: student: 195/350, 56.6; average monthly income: < NT $30,000: 230/350, 65.7%; residence: northern Taiwan: 236/350, 67.4%; and perceived health status: good: 171/350, 48.9%). Five indicators, i.e., chi-squared value/degree of freedom (?2/??) (2.63), goodness-of-fit index (GFI) (0.85), adjusted goodness-of-fit index (AGFI) (0.81), comparative fit index (CFI) (0.91), and root mean square error of approximation (RMSEA) (0.07), were calculated. The results indicated a good fit. Further analysis indicated that the most important factor affecting the behavioral intention to use was the attitude toward use (0.78), followed by perceived ease of use (0.65), perceived usefulness (0.41), health literacy (0.10), and privacy and security (0.07).
Conclusions:
From the perspective of the populace, this study explored the factors affecting the use of MHB and constructed an interpretation model with strong goodness of fit. The results of our analysis are consistent with the technology acceptance model. Through the diverse value-added services of MHB, Taiwan's experience in pandemic prevention with smart technology can facilitate future responses to unknown, emerging infectious diseases.
Citation
Request queued. Please wait while the file is being generated. It may take some time.
Copyright
© The authors. All rights reserved. This is a privileged document currently under peer-review/community review (or an accepted/rejected manuscript). Authors have provided JMIR Publications with an exclusive license to publish this preprint on it's website for review and ahead-of-print citation purposes only. While the final peer-reviewed paper may be licensed under a cc-by license on publication, at this stage authors and publisher expressively prohibit redistribution of this draft paper other than for review purposes.