Assessing and Optimising the Features of a Mobile Health App for COVID-19: The ‘Tetamman’ Application in Saudi Arabia
Abstract
The COVID-19 pandemic has resulted in significant stress on healthcare and public health institutions around the world. COVID-19 apps are an essential tool for public health officials and local communities to contain the pandemic. This study aims to identify the factors influencing users’ intention to use the Tetamman application in Saudi Arabia. The study’s research methodology was developed based on the technology acceptance model (TAM), with important extra control variables. The empirical experiment was designed through a mixed-methods approach, quantitative data (an online survey), and qualitative data (interviews) collection. The quantitative data were collected from 170 participants, and the quantitative analysis was conducted using structural equation modelling with a partial least squares method. The quantitative findings suggest that perceived usefulness and privacy concerns directly influence users; also, perceived ease of use, trust, and application-specific self-efficiency have an indirect effect. The qualitative data were collected from eight participants, and the qualitative analysis was done with thematic analysis. The qualitative results confirm that users will use the app if it respects their privacy. Finally, using the study’s empirical results, an optimisation prototype was designed.