Identifying major impact factors affecting the continuance intention of mHealth: a systematic review and multi-subgroup meta-analysis.
Identifying major impact factors affecting the continuance intention of mHealth: a systematic review and multi-subgroup meta-analysis.
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确定影响移动医疗持续意图的主要影响因素：系统评价和多亚组荟萃分析
DOI：
10.1038/s41746-022-00692-9
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发表时间：
2022-09-15
影响因子：
15.2
通讯作者：
中科院分区：
文献类型：
--
作者：
移动医疗（mHealth）行业是一个巨大的全球市场；然而，移动医疗的退出或继续是一个重大挑战，正在影响其积极成果。迄今为止，对影响因素的研究结果并不一致。因此，对影响因素对移动医疗继续意愿的综合影响的研究是有限的。因此，本研究旨在系统分析移动医疗持续意愿的定量研究，探讨各直接和间接影响因素的综合效应。截至2021年10月，共检索了8个文献数据库。纳入了58项关于移动健康的影响因素和对继续使用意愿的影响的同行评议研究。在19个直接影响延续意愿的因素中，有15个具有显著性，其中态度（β = 0.450, 95% CI: 0.135, 0.683）、满意度（β = 0.406, 95% CI: 0.292, 0.509）、健康赋权（β = 0.359, 95% CI: 0.204, 0.497）、感知有用性（β = 0.343, 95% CI: 0.280, 0.403）和感知健康生活质量（β = 0.315, 95% CI: 0.211, 0.412）对延续意愿的综合影响系数最大。研究之间存在高度异质性；因此，我们进行亚组分析，探讨不同特征对冲击效应的调节作用。地理区域、用户类型、移动健康类型、用户年龄和出版年份显著调节信任和继续意愿等影响关系。因此，移动健康开发者应该根据用户特点制定个性化的持续使用推广策略。
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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影响因子：
5
作者：
Esmaeilzadeh P
通讯作者：
Esmaeilzadeh P
DOI：
10.1016/j.ijinfomgt.2021.102351
发表时间：
2021-08
影响因子：
21
作者：
Birkmeyer S;Wirtz BW;Langer PF
通讯作者：
Langer PF
DOI：
10.1016/j.ijmedinf.2018.04.008
发表时间：
2018-08-01
影响因子：
4.9
作者：
Chen, Yuan;Yang, Lvle;Yang, Jun
通讯作者：
Yang, Jun
影响因子：
5.3
作者：
Chen, Shih-Chih;Jong, Din;Lai, Min-Tsai
通讯作者：
Lai, Min-Tsai
影响因子：
3.7
作者：
Akter, Shahriar;D'Ambra, John;Hani, Umme
通讯作者：
Hani, Umme