A Eysenbach,Gunther %+全球电子健康创新中心，多伦多大学和大学健康网络，190 Elizabeth Street, Toronto ON M5G 2C4, Canada， +1 416 340 4800 ext 6427;geysenba@uhnres.utoronto.ca临床试验纵向研究患者退出生存分析观点在本杂志不断努力发展和进一步发展电子健康研究的理论、模型和最佳实践的过程中，本文认为需要一种“损耗科学”，即:需要为电子保健应用程序的中断和参与者退出电子保健试验的相关现象制定模型。我称之为“消耗定律”的是，在任何电子健康试验中，相当大比例的用户在完成或停止使用应用程序之前就退出了。与药物试验等相比，电子卫生试验的这一特点是一个明显的特点。传统的临床试验和循证医学范式规定，高辍学率会降低试验的可信度。因此，电子健康研究人员倾向于掩盖高辍学率，或者根本不发表他们的研究结果，因为他们认为他们的研究是失败的。然而，对于许多电子保健试验，特别是在互联网上进行的试验，特别是使用自助应用程序的试验，高辍学率可能是一种自然和典型的特征。应该强调、测量、分析和讨论损耗的使用度量和决定因素。这还包括分析和报告应用程序最终“起作用”的亚群的特征，即那些留在试验中并使用它的人。 For the question of what works and what does not, such attrition measures are as important to report as pure efficacy measures from intention-to-treat (ITT) analyses. In cases of high dropout rates efficacy measures underestimate the impact of an application on a population which continues to use it. Methods of analyzing attrition curves can be drawn from survival analysis methods, eg, the Kaplan-Meier analysis and proportional hazards regression analysis (Cox model). Measures to be reported include the relative risk of dropping out or of stopping the use of an application, as well as a “usage half-life”, and models reporting demographic and other factors predicting usage discontinuation in a population. Differential dropout or usage rates between two interventions could be a standard metric for the “usability efficacy” of a system. A “run-in and withdrawal” trial design is suggested as a methodological innovation for Internet-based trials with a high number of initial dropouts/nonusers and a stable group of hardcore users. %M 15829473 %R 10.2196/jmir.7.1.e11 %U //www.mybigtv.com/2005/1/e11/ %U https://doi.org/10.2196/jmir.7.1.e11 %U http://www.ncbi.nlm.nih.gov/pubmed/15829473

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