A group of researchers has published a finding that analyzes user attitudes to eHealth applications in China and eHealth system in Ukraine used to provide insights and suggestions to the development of an eHealth application (eZdorovya) for health information services in general. The award-winning paper was featured in IEEE Access front pages and recognised in all IEEE Access social media. The work was supported in part by the Prodintelligence and Deep Learning Studio, Estonia/Ukraine, with the other part from Faculty of Computing and Information Technology, University of Jeddah, Jeddah, Saudi Arabia.
According to the corresponding author, Dr Iwendi, the study includes a survey conducted by Chinese and Ukrainian users, after which thorough data analyses were conducted. Based on the technology acceptance model (TAM), the framework explores the influence of socio-technical factors affecting user’s adoption of eHealth functionalities, Serial Multiple Mediator Model 6 (SMMM6) and a deep neural network-based approach. The key findings from the data analysis are: 1) if the software application is covering an important service function and is interesting to use, Chinese users will continue using it, 2) given an eHealth software with important or interesting function, it is inconclusive whether Ukrainian users will switch to use the application, and 3) deep neural network shows highly accurate prediction results and was given applied suggestions for Chinese and Ukrainian providers in the case of improving eHealth systems based on a raw prediction.