Ashley L Buchanan, Raúl U Hernández-Ramírez, Judith J Lok, Sten H Vermund, Samuel R Friedman, Laura Forastiere, Donna Spiegelman
{"title":"在网络随机研究中评估一揽子干预措施的直接效应和溢出效应。","authors":"Ashley L Buchanan, Raúl U Hernández-Ramírez, Judith J Lok, Sten H Vermund, Samuel R Friedman, Laura Forastiere, Donna Spiegelman","doi":"10.1097/EDE.0000000000001742","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>Intervention packages may result in a greater public health impact than single interventions. Understanding the separate impact of each component on the overall package effectiveness can improve intervention delivery.</p><p><strong>Methods: </strong>We adapted an approach to evaluate the effects of a time-varying intervention package in a network-randomized study. In some network-randomized studies, only a subset of participants in exposed networks receive the intervention themselves. The spillover effect contrasts average potential outcomes if a person was not exposed to themselves under intervention in the network versus no intervention in a control network. We estimated the effects of components of the intervention package in HIV Prevention Trials Network 037, a Phase III network-randomized HIV prevention trial among people who inject drugs and their risk networks using marginal structural models to adjust for time-varying confounding. The index participant in an intervention network received a peer education intervention initially at baseline, then boosters at 6 and 12 months. All participants were followed to ascertain HIV risk behaviors.</p><p><strong>Results: </strong>There were 560 participants with at least one follow-up visit, 48% of whom were randomized to the intervention, and 1,598 participant visits were observed. The spillover effect of the boosters in the presence of initial peer education training was a 39% rate reduction (rate ratio = 0.61; 95% confidence interval = 0.43, 0.87).</p><p><strong>Conclusions: </strong>These methods will be useful for evaluating intervention packages in studies with network features.</p>","PeriodicalId":11779,"journal":{"name":"Epidemiology","volume":" ","pages":"481-488"},"PeriodicalIF":4.7000,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Assessing Direct and Spillover Effects of Intervention Packages in Network-randomized Studies.\",\"authors\":\"Ashley L Buchanan, Raúl U Hernández-Ramírez, Judith J Lok, Sten H Vermund, Samuel R Friedman, Laura Forastiere, Donna Spiegelman\",\"doi\":\"10.1097/EDE.0000000000001742\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>Intervention packages may result in a greater public health impact than single interventions. Understanding the separate impact of each component on the overall package effectiveness can improve intervention delivery.</p><p><strong>Methods: </strong>We adapted an approach to evaluate the effects of a time-varying intervention package in a network-randomized study. In some network-randomized studies, only a subset of participants in exposed networks receive the intervention themselves. The spillover effect contrasts average potential outcomes if a person was not exposed to themselves under intervention in the network versus no intervention in a control network. We estimated the effects of components of the intervention package in HIV Prevention Trials Network 037, a Phase III network-randomized HIV prevention trial among people who inject drugs and their risk networks using marginal structural models to adjust for time-varying confounding. The index participant in an intervention network received a peer education intervention initially at baseline, then boosters at 6 and 12 months. All participants were followed to ascertain HIV risk behaviors.</p><p><strong>Results: </strong>There were 560 participants with at least one follow-up visit, 48% of whom were randomized to the intervention, and 1,598 participant visits were observed. The spillover effect of the boosters in the presence of initial peer education training was a 39% rate reduction (rate ratio = 0.61; 95% confidence interval = 0.43, 0.87).</p><p><strong>Conclusions: </strong>These methods will be useful for evaluating intervention packages in studies with network features.</p>\",\"PeriodicalId\":11779,\"journal\":{\"name\":\"Epidemiology\",\"volume\":\" \",\"pages\":\"481-488\"},\"PeriodicalIF\":4.7000,\"publicationDate\":\"2024-07-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Epidemiology\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1097/EDE.0000000000001742\",\"RegionNum\":2,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2024/5/6 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"Q1\",\"JCRName\":\"PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Epidemiology","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1097/EDE.0000000000001742","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/5/6 0:00:00","PubModel":"Epub","JCR":"Q1","JCRName":"PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH","Score":null,"Total":0}
Assessing Direct and Spillover Effects of Intervention Packages in Network-randomized Studies.
Background: Intervention packages may result in a greater public health impact than single interventions. Understanding the separate impact of each component on the overall package effectiveness can improve intervention delivery.
Methods: We adapted an approach to evaluate the effects of a time-varying intervention package in a network-randomized study. In some network-randomized studies, only a subset of participants in exposed networks receive the intervention themselves. The spillover effect contrasts average potential outcomes if a person was not exposed to themselves under intervention in the network versus no intervention in a control network. We estimated the effects of components of the intervention package in HIV Prevention Trials Network 037, a Phase III network-randomized HIV prevention trial among people who inject drugs and their risk networks using marginal structural models to adjust for time-varying confounding. The index participant in an intervention network received a peer education intervention initially at baseline, then boosters at 6 and 12 months. All participants were followed to ascertain HIV risk behaviors.
Results: There were 560 participants with at least one follow-up visit, 48% of whom were randomized to the intervention, and 1,598 participant visits were observed. The spillover effect of the boosters in the presence of initial peer education training was a 39% rate reduction (rate ratio = 0.61; 95% confidence interval = 0.43, 0.87).
Conclusions: These methods will be useful for evaluating intervention packages in studies with network features.
期刊介绍:
Epidemiology publishes original research from all fields of epidemiology. The journal also welcomes review articles and meta-analyses, novel hypotheses, descriptions and applications of new methods, and discussions of research theory or public health policy. We give special consideration to papers from developing countries.