A multi-method analytical approach to predicting young adults' intention to invest in mHealth during the COVID-19 pandemic.

ABSTRACT: Mobile-based health (mHealth) systems are proving to be a popular alternative to the traditional visits to healthcare providers. They can also be useful and effective in fighting the spread of infectious diseases, such as the COVID-19 pandemic. Even though young adults are the most prevalent mHealth user group, the relevant literature has overlooked their intention to invest in and use mHealth services. This study aims to investigate the predictors that influence young adults' intention to invest in mHealth (IINmH), particularly during the COVID-19 crisis, by designing a research methodology that incorporates both the health belief model (HBM) and the expectation-confirmation model (ECM). As an expansion of the integrated HBM-ECM model, this study proposes two additional predictors: mobile

SUBMITTER: Hasan N 

PROVIDER: S-EPMC8693780 | biostudies-literature | 2022 Mar

REPOSITORIES: biostudies-literature