Toward a Better Understanding of the Intention to Use mHealth Apps: Exploratory Study (Preprint)

Abstract

BACKGROUND An increasing number of Mobile Health Applications (m-Health apps) are becoming available to download and use on mobile devices. Even with the increase in availability and use of m-Health apps, there has still not been a lot of research into understanding the Intention to Use this kind of applications. Therefore, the purpose of this paper is to investigate a technology acceptance model that has been specially designed for primary health care applications. The proposed model is an extension of the Technology Acceptance Model (TAM), and it was empirically tested using data obtained from a survey of m-Health apps users (n = 310). The research analyzed two additional external factors: Promotion of Health and Health Benefits. The data was analyzed with PLS-SEM software and confirmed that gender moderates the adoption of m-Health apps in Spain and the explanatory capacity of the proposed model was R2 BIU =76.4%. Likewise, the relationships of the external constructs of the extended TAM model were found to be significant. The results show the importance of healthy habits developed in m-Health apps. In addition, communication campaigns for these apps should be aimed at transferring the usefulness of e-health as an agent for transforming attitudes, and as more health benefits are obtained, ease of use is greater. Also, m-Health apps could be used to predict what the behavior of patients would be in the face of recommendations to prevent pandemics, such as COVID-19 or SARS and to track users’ symptoms while they stay at home. Gender is a determining factor in how it influences the intention to use m-Health apps, so perhaps different interfaces and utilities could be designed according to gender. OBJECTIVE The purpose of this paper is to investigate a technology acceptance model that has been specially designed for primary health care applications. METHODS The proposed model is an extension of the Technology Acceptance Model (TAM), and it was empirically tested using data obtained from a survey of m-Health apps users (n = 310). The research analyzed two additional external factors: Promotion of Health and Health Benefits. The data was analyzed with PLS-SEM analysis. RESULTS The results confirmed that gender moderates the adoption of m-Health apps in Spain and the explanatory capacity of the proposed model was R2 BIU =76.4%. Likewise, the relationships of the external constructs of the extended TAM model were found to be significant. The results show the importance of healthy habits developed in m-Health apps. In addition, communication campaigns for these apps should be aimed at transferring the usefulness of e-health as an agent for transforming attitudes, and as more health benefits are obtained, ease of use is greater. CONCLUSIONS Also, m-Health apps could be used to predict what the behavior of patients would be in the face of recommendations to prevent pandemics, such as COVID-19 or SARS and to track users’ symptoms while they stay at home. Gender is a determining factor in how it influences the intention to use m-Health apps, so perhaps different interfaces and utilities could be designed according to gender. CLINICALTRIAL _