A fuzzy-set qualitative comparative analysis exploration of multiple paths to users' continuous use behavior of diabetes self-management apps. (April 2023)

• Record Type: Journal Article
• Authors: Gao, Chenchen; Shen, Yucong; Xu, Wenxian; Zhang, Yongjie; Tu, Qiongyao; Zhu, Xingjie; Lu, Zhongqiu; Yang, Yeqin
• Is Part Of: International journal of medical informatics. Volume 172(2023)
• Publication Date: 2023-04
• Subjects: Continuous use behavior -- Diabetes self-management applications -- Fuzzy-set qualitative comparative analysis -- Information ecologies; Medical informatics -- Periodicals; Information science -- Periodicals; Computers -- Periodicals; Medical technology -- Periodicals; Medical Informatics -- Periodicals; Technology, Medical -- Periodicals; Computers; Information science; Medical informatics; Medical technology; Electronic journals; Periodicals; Electronic journals; 610.285
• DOI: 10.1016/j.ijmedinf.2023.105000
• Languages: English
• ISSNs: 1386-5056

Abstract

Abstract: Background: Despite the obvious potential benefits of diabetes self-management apps, users' continuous use of diabetes self-management apps is still not widespread. Influential factors coexisted in information ecologies are likely to have a synthetic effect on users' continuous use behavior. However, it is less clear how factors in information ecologies combine to influence users' continuous use behavior. Objective: The objectives of this study are to explore combinations of factors (perceived severity, information quality, service quality, system quality, and social influence) in information ecologies that lead to users' continuous use behavior of diabetes self-management apps and which combination is the most important. Methods: Purpose sampling was used to recruit diabetes self-management app users from July 1, 2021 to January 31, 2022. Fuzzy-set qualitative comparative analysis (fsQCA) was then employed by conducting necessity and sufficiency analysis. Results: In total 280 diabetes self-management app users participated. The necessity analysis indicated that no single factor was necessary to cause users' continuous use behavior, and the sufficiency analysis identified five different combinations of factors that lead to users' continuous use behavior. Of these five, the combination of high information quality, high service quality, and high social influence was found to be the most important path. Conclusions: Users' continuous use behavior of diabetes self-management apps results from the synergistic effects of factors in information ecologies. The five paths that directly contribute to users' continuous use, as well as the four user types preliminarily identified in this study may provide a reference for healthcare providers and app developers.