A Technology Acceptance Model for Deploying Masks to Combat the COVID-19 Pandemic in Taiwan (My Health Bank): Web-Based Cross-sectional Survey Study

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 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 <NT $30,000 [<US $1054.89]: 230/350, 65.7%; residence in northern Taiwan: 236/350, 67.4%; and health status perceived as “good”: 171/350, 48.9%). Five indicators, including chi-square test (X2310=2.63), goodness-of-fit index (0.85), adjusted goodness-of-fit index (0.81), comparative fit index (0.91), and root mean square error of approximation (0.07), were calculated. The results indicated a good fit. Further analysis indicated that the most important factor affecting respondents’ behavioral intention to use MHB was their 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 facilitate future responses to unknown, emerging infectious diseases.

An Empirical Study of Technology Acceptance in Higher Education During Covid-19 Pandemic

“…may have affected their perceptions of the system's usefulness and ease of use (Syahruddin et al, 2021). It was observed that self-efficacy has different effects on individual behaviours during the Covid-19 period (Aguilera-Hermida et al, 2021;Pressley & Ha, 2021;Talsma et al, 2021;Tsai et al, 2021).…”

Technology Acceptance Among Patients With Hemophilia in Hong Kong and Their Expectations of a Mobile Health App to Promote Self-management: Survey Study

“…Other than conducting an exploratory analysis on the internal consistency of the items, we did not evaluate the other psychometric properties of the survey tool. However, the items were adapted from the Technology Acceptance Model, which is one of the most popular theoretical frameworks among similar studies conducted in other patient populations [ 19 - 21 ]. As this is a preintervention survey, we do expect the users’ perceptions and preference to change after we launch the mobile app.…”

Determinants of intention to use e-wallet in Generation Z

“…Several previous studies have shown that perceived ease of use influences perceived usefulness (Chandra & Hartono, 2018;Daragmeh et. al., 2021;Schmitz et al, 2022;Tsai et al, 2021;Wu & Chen, 2017). The easier a system is to use, the more people will think it is functional (Lai, 2017).…”

“…People will think that a system is functional when it is easy to use (Lai, 2017). Previous studies have shown that perceived ease of use influences perceived usefulness (Chandra & Hartono, 2018;Daragmeh et al, 2021;Schmitz et al, 2022;Tsai et al, 2021;Wu & Chen, 2017). Thus, this study formulates the following hypothesis.…”