Justin Knox , Kara Portier , Christopher Magana , Maggie Denning , Christopher M. Ferraris , Emily Dove-Medows , Cho-Hee Shrader , Ohemaa Poku , Phil Kreniske , Robert Remien , Efrat Aharonovich , Jennifer C. Elliott , Denis Nash , Kathryn Lancaster , Till Baernighausen , Kayo Fujimoto , Adam Carrico , John A. Schneider , Alida Bouris , D. Scott Batey , Stefan D. Baral
{"title":"COMBINE EBIs: A novel COllaborative Method for Building INterventions from Existing Evidence-Based Interventions","authors":"Justin Knox , Kara Portier , Christopher Magana , Maggie Denning , Christopher M. Ferraris , Emily Dove-Medows , Cho-Hee Shrader , Ohemaa Poku , Phil Kreniske , Robert Remien , Efrat Aharonovich , Jennifer C. Elliott , Denis Nash , Kathryn Lancaster , Till Baernighausen , Kayo Fujimoto , Adam Carrico , John A. Schneider , Alida Bouris , D. Scott Batey , Stefan D. Baral","doi":"10.1016/j.annepidem.2025.10.018","DOIUrl":null,"url":null,"abstract":"<div><h3>Purpose</h3><div>Combining evidence-based interventions (EBIs) is a discrete process from adapting EBIs, and specific guidance for how to combine EBIs could be helpful amidst the proliferation of frameworks that combine and stage EBIs and calls for services to be combined or bundled. To address this gap, we developed and applied the <strong>CO</strong>llaborative <strong>M</strong>ethod for <strong>B</strong>uilding <strong>IN</strong>terventions from <strong>E</strong>xisting <strong>E</strong>vidence-<strong>B</strong>ased <strong>I</strong>nterventions (<strong>COMBINE-EBIs</strong>) approach, a five-step process for combining EBIs.</div></div><div><h3>Methods</h3><div>The five steps of COMBINE-EBIs are: (1) Identify and Select EBIs, (2) Develop a Shared Conceptual Model, (3) Evaluate the Conceptual Model, (4) Create a Single Combined Protocol, and (5) Refine through Further Input.</div></div><div><h3>Results</h3><div>We developed and applied the 5-step COMBINE-EBIs process to build a fully refined, pre-tested, combined multi-component intervention that leverages intrinsic social network support and mHealth technology to support people with HIV who drink heavily improve HIV care outcomes and reduce alcohol use.</div></div><div><h3>Conclusions</h3><div>COMBINE-EBIs is a rigorous, systematic and efficient approach for building multi-component, multi-modal interventions to address multiple, co-occurring health behaviors simultaneously. COMBINE-EBIs is a resource efficient approach that could facilitate the creation of additional multi-component interventions to address complex, co-occurring health conditions synergistically. Future research should evaluate the feasibility and utility of COMBINE-EBIs, including where adaptations are needed to maximize utility.</div></div>","PeriodicalId":50767,"journal":{"name":"Annals of Epidemiology","volume":"112 ","pages":"Pages 64-75"},"PeriodicalIF":3.6000,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Annals of Epidemiology","FirstCategoryId":"3","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1047279725003151","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/11/6 0:00:00","PubModel":"Epub","JCR":"Q1","JCRName":"PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH","Score":null,"Total":0}
引用次数: 0
Abstract
Purpose
Combining evidence-based interventions (EBIs) is a discrete process from adapting EBIs, and specific guidance for how to combine EBIs could be helpful amidst the proliferation of frameworks that combine and stage EBIs and calls for services to be combined or bundled. To address this gap, we developed and applied the COllaborative Method for Building INterventions from Existing Evidence-Based Interventions (COMBINE-EBIs) approach, a five-step process for combining EBIs.
Methods
The five steps of COMBINE-EBIs are: (1) Identify and Select EBIs, (2) Develop a Shared Conceptual Model, (3) Evaluate the Conceptual Model, (4) Create a Single Combined Protocol, and (5) Refine through Further Input.
Results
We developed and applied the 5-step COMBINE-EBIs process to build a fully refined, pre-tested, combined multi-component intervention that leverages intrinsic social network support and mHealth technology to support people with HIV who drink heavily improve HIV care outcomes and reduce alcohol use.
Conclusions
COMBINE-EBIs is a rigorous, systematic and efficient approach for building multi-component, multi-modal interventions to address multiple, co-occurring health behaviors simultaneously. COMBINE-EBIs is a resource efficient approach that could facilitate the creation of additional multi-component interventions to address complex, co-occurring health conditions synergistically. Future research should evaluate the feasibility and utility of COMBINE-EBIs, including where adaptations are needed to maximize utility.
期刊介绍:
The journal emphasizes the application of epidemiologic methods to issues that affect the distribution and determinants of human illness in diverse contexts. Its primary focus is on chronic and acute conditions of diverse etiologies and of major importance to clinical medicine, public health, and health care delivery.