Modeling the predictors of mobile health adoption by Rohingya Refugees in Bangladesh: An extension of UTAUT2 using combined SEM-Neural network approach.

ABSTRACT: While the healthcare facilities for the people is questionable in Bangladesh, Rohingya refugees is a burning issue for both Bangladesh and global community. Integrating Rohingya refugees into the framework of mHealth could be beneficial for both Bangladesh and Rohingya refugees in general, and in specific situation like COVID-19 outbreak. However, no research has been found on what motivates Rohingya refugees to accept mHealth in Bangladesh. Drawing on the UTAUT2 model, this study investigates the predictors of acceptance of mHealth services technologies among Rohingya refugees. The study also seeks to clarify the roles of mHealth developers, the Bangladesh government, and non-governmental organizations working with the 1.1 million Rohingya refugees in Bangladesh. Quantitative data

SUBMITTER: Barua Z 

PROVIDER: S-EPMC10407243 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature