Individual Determinants Influencing the Acceptance and Use of Mobile Health Applications for Pandemic Management in the UAE

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The British University in Dubai (BUiD)
Pandemics are among the crises that are challenging to manage and contain because of their unique characteristics, such as high speed of spread, lack of medicine and development of mysterious side effects. In order to efficiently manage and control pandemics, modern technologies are used by governments and health authorities, such as mobile health applications (m-health) applications installed on smartphones that are used by everyone. At the beginning of the COVID-19 pandemic, the UAE realised the severity of the pandemic and the need for technology utilisation to overcome this dilemma; thus, the government developed m-health applications such as the Al Hosn app and the Covid19 DXB smart app to manage, monitor and control the pandemic. The main goal of these applications was to be used by the population in order to manage the pandemic efficiently and contain the disease. It is important to explore what factors determine if the users will use such m-health applications for pandemic management because if users are concerned about their medical security and privacy or if they have any fears regarding using the application, then it might have a negative impact on their intention to use the application. The main aim of this research is to investigate the factors that influence the user adoption of mobile applications for pandemic management and to extract the individual determinants that influence the adoption of the mobile application for pandemic crisis management in the UAE. The study is underpinned by innovation adoption theory and utilises an extended model of the Unified Theory of Acceptance and Use of Technology (UTAUT). The study extends the UTAUT model by testing the significance of the two additional constructs of perceived privacy risk and perceived security risk, as well as testing the moderating role of the fear of social isolation, social discrimination, and technology optimism. The research is underpinned by the positivism research philosophy and employs a deductive research approach. A quantitative questionnaire survey was distributed among the UAE public and a total of 384 complete responses were returned and analysed using SPSS version 25 and SmartPLS 3. Structural Equation Modeling (SEM) analysis was conducted to analyse and evaluate the linkages among the study’s constructs. SEM is a multivariate analysis method which is employed to evaluate structural relationships. The findings highlighted individual determinants such as perceived performance expectancy perceived effort expectancy, social influence, perceived privacy risk, and perceived security risk have a positive impact on the behavioural intention of the users and their adoption of m-health applications in the UAE. The findings also demonstrated a positive mediating effect of behavioural intention between the determinants and the use behaviour and the moderating effect of the fear of social isolation, social discrimination, and technology optimism on the relationship between the determinants and behavioural intention. The research theoretically contributes to an extended UTAUT framework by confirming the significance of the constructs of perceived privacy risk and perceived security risk and testing the moderating role of the fear of social isolation, social discrimination, and technology optimism and their effect on the behavioural intention of users of m-health applications for pandemic management. The research practically contributes to practice by developing recommendations for how m-health applications should be designed and managed to motivate individuals to use them while undergoing a pandemic.
PhD Thesis
M-health, contact tracing, covid-19, pandemic, contact tracing adoption, technology acceptance model, unified theory of acceptance and use of technology