An Internet Survey with the Technology Acceptance Model for Deploying Masks in Combatting COVID-19: Structural Equation Modeling Analysis of My Health Bank in Taiwan (Preprint)
BACKGROUND In the medical industry, the successful completion of many medical practices often relies on information collection and analysis. Government agencies and medical institutions encourage 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), allowing people to access and manage their PHRs at any time. Facing 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 the 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 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%). Four indicators, i.e., chi-squared value/degree of freedom (X2/df) (2.63), goodness-of-fit index (GFI) (0.85), adjusted goodness-of-fit index (AGFI) (0.81), and root mean square error of approximation (RMSEA) (0.07), were calculated. The results showed that the overall fit and fitness of the model were good. 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 a 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 be helpful for facing future threats of unknown, emerging infectious diseases.