TY - JOUR AU - Pham, Quynh AU - Graham, Gary AU - Carrion, Carme AU - Morita, Plinio P AU - Seto, Emily AU - Stinson, Jennifer N AU - Cafazzo, Joseph A PY - 2019 DA - 2019/01/18 TI -一个分析指标库来评估慢性病消费者移动健康应用程序的有效参与:范围审查JO - JMIR移动健康Uhealth SP - e11941 VL - 7 IS - 1 KW -分析KW -有效参与KW -参与KW -依从KW -日志数据KW -移动健康KW -移动应用KW -慢性疾病KW -范围审查AB -背景:有各种证据支持当前移动健康(Mhealth)应用程序改善慢性健康和福祉的雄心。对于这种变化效应的一种解释是，用户没有像预期的那样参与到应用程序中。分析的应用，定义为使用数据产生新的见解，是研究和解释参与移动医疗干预的一种新兴方法。目的:本研究旨在巩固参与的分析指标如何在临床和技术背景下应用，并告知它们如何在未来的评估中得到最佳应用。方法:我们进行了范围审查，对用于慢性病消费者移动健康应用程序评估的分析指标范围进行了分类。我们根据应用程序结构和用户粘性数据的应用对研究进行分类，并计算每个类别的描述性数据。采用卡方检验和Fisher精确独立性检验来计算编码变量之间的差异。结果:共有41项研究符合我们的纳入标准。纳入审查的平均移动健康评估是一项针对心理健康自我管理的混合结构应用程序的两组前测后随机对照试验，有103名参与者，持续5个月，不提供医疗保健提供者服务，测量3个参与度分析指标，根据参与度数据对用户进行细分，应用参与度数据进行描述性分析，并且不报告人员流失。 Across the reviewed studies, engagement was measured using the following 7 analytic indicators: the number of measures recorded (76%, 31/41), the frequency of interactions logged (73%, 30/41), the number of features accessed (49%, 20/41), the number of log-ins or sessions logged (46%, 19/41), the number of modules or lessons started or completed (29%, 12/41), time spent engaging with the app (27%, 11/41), and the number or content of pages accessed (17%, 7/41). Engagement with unstructured apps was mostly measured by the number of features accessed (8/10, P=.04), and engagement with hybrid apps was mostly measured by the number of measures recorded (21/24, P=.03). A total of 24 studies presented, described, or summarized the data generated from applying analytic indicators to measure engagement. The remaining 17 studies used or planned to use these data to infer a relationship between engagement patterns and intended outcomes. Conclusions: Although researchers measured on average 3 indicators in a single study, the majority reported findings descriptively and did not further investigate how engagement with an app contributed to its impact on health and well-being. Researchers are gaining nuanced insights into engagement but are not yet characterizing effective engagement for improved outcomes. Raising the standard of mHealth app efficacy through measuring analytic indicators of engagement may enable greater confidence in the causal impact of apps on improved chronic health and well-being. SN - 2291-5222 UR - http://mhealth.www.mybigtv.com/2019/1/e11941/ UR - https://doi.org/10.2196/11941 UR - http://www.ncbi.nlm.nih.gov/pubmed/30664463 DO - 10.2196/11941 ID - info:doi/10.2196/11941 ER -