Factors Influencing the Perceived Effectiveness of COVID-19 Risk Assessment Mobile Application "MorChana" in Thailand: UTAUT2 Approach

Int J Environ Res Public Health. 2022 May 6;19(9):5643. doi: 10.3390/ijerph19095643.

Abstract

COVID-19 contact-tracing mobile applications have been some of the most important tools during the COVID-19 pandemic. One preventive measure that has been incorporated to help reduce the virus spread is the strict implementation of utilizing a COVID-19 tracing application, such as the MorChana mobile application of Thailand. This study aimed to evaluate the factors affecting the actual usage of the MorChana mobile application. Through the integration of Protection Motivation Theory (PMT) and Unified Theory of Acceptance and Use of Technology (UTAUT2), latent variables such as performance expectancy (PE), effort expectancy (EE), social influence (SI), facilitating conditions (FC), hedonic motivation (HM), habit (HB), perceived risk (PCR), self-efficacy (SEF), privacy (PR), trust (TR), and understanding COVID-19 (U) were considered to measure the intention to use MorChana (IU) and the actual usage (AU) of the mobile application. This study considered 907 anonymous participants who voluntarily answered an online self-administered survey collected via convenience sampling. The results show that IU presented the highest significant effect on AU, followed by HB, HM, PR, FC, U, SEF, PE, EE, TR, and SI. This is evident due to the strict implementation of using mobile applications upon entering any area of the vicinity. Moreover, PCR was not seen to be a significant latent factor affecting AU. This study is the first to have evaluated mobile contact tracing in Thailand. The integrated framework can be applied and extended to determine factors affecting COVID-19 tracing applications in other countries. Moreover, the findings of this study could be applied to other health-related mobile applications worldwide.

Keywords: COVID-19 contact tracing; MorChana; PMT; UTAUT2; mobile application.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • COVID-19* / epidemiology
  • COVID-19* / prevention & control
  • Contact Tracing / methods
  • Humans
  • Mobile Applications*
  • Pandemics
  • Risk Assessment
  • Thailand / epidemiology

Grants and funding

This research was funded by Mapúa University Directed Research for Innovation and Value Enhancement (DRIVE).