The Law of Attrition Gunther Eysenbach, MD, MPH Abstract This paper argues for the need for a "science of attrition" in eHealth research, focusing on the discontinuation of eHealth applications and participant dropout from trials. The "law of attrition" refers to the observation that a significant proportion of users drop out of eHealth trials before completion. Unlike traditional clinical trials, high dropout rates in eHealth trials are not necessarily indicative of failure. Instead, they may be a natural and typical feature, especially in Internet-based trials with self-help applications. Usage metrics and attrition determinants should be measured, analyzed, and discussed. This includes analyzing the characteristics of the subpopulation that continues to use the application. Attrition measures are as important as efficacy measures from intention-to-treat (ITT) analyses. Methods of analyzing attrition curves can be drawn from survival analysis methods, such as Kaplan-Meier analysis and proportional hazards regression analysis (Cox model). Measures to be reported include the relative risk of dropping out or stopping use, a "usage half-life," and models predicting usage discontinuation. Differential dropout rates between interventions could be a standard metric for "usability efficacy." A "run-in and withdrawal" trial design is suggested for Internet-based trials with high initial dropouts and a stable group of users. The Law of Attrition (Or: Why Do eHealth Users Discontinue Usage?) In this issue of the Journal, several papers discuss the methodology of Internet-based trials. These papers highlight the high dropout rates in eHealth trials, which are a fundamental challenge in evaluating eHealth applications. The "law of attrition" refers to the phenomenon of participants stopping usage or being lost to follow-up. This is a common issue in eHealth trials, where participants often discontinue use or drop out of the trial. The paper argues for the need to develop a "science of attrition" to better understand and address this issue. It also discusses the importance of analyzing attrition curves and the factors influencing attrition, such as the characteristics of the innovation and the environment in which it is used. The paper concludes that a "run-in and withdrawal" trial design could be a methodological innovation for Internet-based trials with high initial dropouts and a stable group of users.The Law of Attrition Gunther Eysenbach, MD, MPH Abstract This paper argues for the need for a "science of attrition" in eHealth research, focusing on the discontinuation of eHealth applications and participant dropout from trials. The "law of attrition" refers to the observation that a significant proportion of users drop out of eHealth trials before completion. Unlike traditional clinical trials, high dropout rates in eHealth trials are not necessarily indicative of failure. Instead, they may be a natural and typical feature, especially in Internet-based trials with self-help applications. Usage metrics and attrition determinants should be measured, analyzed, and discussed. This includes analyzing the characteristics of the subpopulation that continues to use the application. Attrition measures are as important as efficacy measures from intention-to-treat (ITT) analyses. Methods of analyzing attrition curves can be drawn from survival analysis methods, such as Kaplan-Meier analysis and proportional hazards regression analysis (Cox model). Measures to be reported include the relative risk of dropping out or stopping use, a "usage half-life," and models predicting usage discontinuation. Differential dropout rates between interventions could be a standard metric for "usability efficacy." A "run-in and withdrawal" trial design is suggested for Internet-based trials with high initial dropouts and a stable group of users. The Law of Attrition (Or: Why Do eHealth Users Discontinue Usage?) In this issue of the Journal, several papers discuss the methodology of Internet-based trials. These papers highlight the high dropout rates in eHealth trials, which are a fundamental challenge in evaluating eHealth applications. The "law of attrition" refers to the phenomenon of participants stopping usage or being lost to follow-up. This is a common issue in eHealth trials, where participants often discontinue use or drop out of the trial. The paper argues for the need to develop a "science of attrition" to better understand and address this issue. It also discusses the importance of analyzing attrition curves and the factors influencing attrition, such as the characteristics of the innovation and the environment in which it is used. The paper concludes that a "run-in and withdrawal" trial design could be a methodological innovation for Internet-based trials with high initial dropouts and a stable group of users.