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Abstract
The mobile health (mHealth) industry is an enormous global market; however, the dropout or continuance of mHealth is a major challenge that is affecting its positive outcomes. To date, the results of studies on the impact factors have been inconsistent. Consequently, research on the pooled effects of impact factors on the continuance intention of mHealth is limited. Therefore, this study aims to systematically analyze quantitative studies on the continuance intention of mHealth and explore the pooled effect of each direct and indirect impact factor. Until October 2021, eight literature databases were searched. Fifty-eight peer-reviewed studies on the impact factors and effects on continuance intention of mHealth were included. Out of the 19 direct impact factors of continuance intention, 15 are significant, with attitude (β = 0.450; 95% CI: 0.135, 0.683), satisfaction (β = 0.406; 95% CI: 0.292, 0.509), health empowerment (β = 0.359; 95% CI: 0.204, 0.497), perceived usefulness (β = 0.343; 95% CI: 0.280, 0.403), and perceived quality of health life (β = 0.315, 95% CI: 0.211, 0.412) having the largest pooled effect coefficients on continuance intention. There is high heterogeneity between the studies; thus, we conducted a subgroup analysis to explore the moderating effect of different characteristics on the impact effects. The geographic region, user type, mHealth type, user age, and publication year significantly moderate influential relationships, such as trust and continuance intention. Thus, mHealth developers should develop personalized continuous use promotion strategies based on user characteristics.
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1 Jilin University, Department of Medical Informatics, School of Public Health, Changchun, China (GRID:grid.64924.3d) (ISNI:0000 0004 1760 5735)
2 Zhejiang University, IT Center, Second Affiliated Hospital, School of Medicine, Hangzhou, China (GRID:grid.13402.34) (ISNI:0000 0004 1759 700X); Zhejiang University, School of Public Health, Hangzhou, China (GRID:grid.13402.34) (ISNI:0000 0004 1759 700X); Zhejiang University, Key Laboratory of Cancer Prevention and Intervention, China National Ministry of Education, School of Medicine, Hangzhou, China (GRID:grid.13402.34) (ISNI:0000 0004 1759 700X)
3 Peking University, Institute of Medical Technology, Health Science Center, Beijing, China (GRID:grid.11135.37) (ISNI:0000 0001 2256 9319)
4 The Affiliated Hospital of Southwest Medical University, Department of Oncology, Luzhou, China (GRID:grid.488387.8)
5 Wangjing hospital, Department of Gastroenterology, Beijing, China (GRID:grid.416935.c); Chinese Academy of Medical Sciences, Key Laboratory of Traditional Chinese Medicine Treatment of Functional Gastrointestinal Diseases, Beijing, China (GRID:grid.506261.6) (ISNI:0000 0001 0706 7839)
6 Peking University, Institute of Medical Technology, Health Science Center, Beijing, China (GRID:grid.11135.37) (ISNI:0000 0001 2256 9319); Peking University, Center for Medical Informatics, Health Science Center, Beijing, China (GRID:grid.11135.37) (ISNI:0000 0001 2256 9319); Southwest Medical University, School of Medical Informatics and Engineering, Luzhou, China (GRID:grid.410578.f) (ISNI:0000 0001 1114 4286)