Elena D Staguhn, Tricia Kirkhart, Lauren Allen, Claudia M Campbell, Stephen T Wegener, Renan C Castillo
{"title":"在线自我管理项目参与的预测因素:一项纵向观察研究。","authors":"Elena D Staguhn, Tricia Kirkhart, Lauren Allen, Claudia M Campbell, Stephen T Wegener, Renan C Castillo","doi":"10.1037/rep0000521","DOIUrl":null,"url":null,"abstract":"<p><strong>Purpose/objective: </strong>Lack of patient participation and engagement remains a barrier to implementing effective online self-management and behavioral health interventions. Identifying patient characteristics associated with engagement rates may lead to interventions that improve engagement in traditional and online self-management programs. In this study, two online self-management and recovery programs were evaluated to identify factors that predict patient engagement.</p><p><strong>Research method/design: </strong>Predictors were collected in a questionnaire at baseline before 435 participants started either of the two interventions. One or two online lessons were completed per week with seven or eight total lessons to complete in each program, and each lesson took about 20-30 min to finish. Full patient engagement was defined as completing all lessons and assessments in the program and partial engagement as attempting at least one lesson or assessment.</p><p><strong>Results: </strong>Predictors of full patient engagement were self-rated confidence in completing the program or being over 60 years of age. Predictors of at least partial patient engagement were experienced ordering online or being over 50 years of age.</p><p><strong>Conclusions/implications: </strong>Identifying profiles of individuals who predict poor engagement may improve implementation and the health outcomes of intervention programs. (PsycInfo Database Record (c) 2024 APA, all rights reserved).</p>","PeriodicalId":1,"journal":{"name":"Accounts of Chemical Research","volume":null,"pages":null},"PeriodicalIF":16.4000,"publicationDate":"2024-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11059776/pdf/","citationCount":"0","resultStr":"{\"title\":\"Predictors of participation in online self-management programs: A longitudinal observational study.\",\"authors\":\"Elena D Staguhn, Tricia Kirkhart, Lauren Allen, Claudia M Campbell, Stephen T Wegener, Renan C Castillo\",\"doi\":\"10.1037/rep0000521\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Purpose/objective: </strong>Lack of patient participation and engagement remains a barrier to implementing effective online self-management and behavioral health interventions. Identifying patient characteristics associated with engagement rates may lead to interventions that improve engagement in traditional and online self-management programs. In this study, two online self-management and recovery programs were evaluated to identify factors that predict patient engagement.</p><p><strong>Research method/design: </strong>Predictors were collected in a questionnaire at baseline before 435 participants started either of the two interventions. One or two online lessons were completed per week with seven or eight total lessons to complete in each program, and each lesson took about 20-30 min to finish. Full patient engagement was defined as completing all lessons and assessments in the program and partial engagement as attempting at least one lesson or assessment.</p><p><strong>Results: </strong>Predictors of full patient engagement were self-rated confidence in completing the program or being over 60 years of age. Predictors of at least partial patient engagement were experienced ordering online or being over 50 years of age.</p><p><strong>Conclusions/implications: </strong>Identifying profiles of individuals who predict poor engagement may improve implementation and the health outcomes of intervention programs. (PsycInfo Database Record (c) 2024 APA, all rights reserved).</p>\",\"PeriodicalId\":1,\"journal\":{\"name\":\"Accounts of Chemical Research\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":16.4000,\"publicationDate\":\"2024-05-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11059776/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Accounts of Chemical Research\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1037/rep0000521\",\"RegionNum\":1,\"RegionCategory\":\"化学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2023/11/13 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"Q1\",\"JCRName\":\"CHEMISTRY, MULTIDISCIPLINARY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Accounts of Chemical Research","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1037/rep0000521","RegionNum":1,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2023/11/13 0:00:00","PubModel":"Epub","JCR":"Q1","JCRName":"CHEMISTRY, MULTIDISCIPLINARY","Score":null,"Total":0}
Predictors of participation in online self-management programs: A longitudinal observational study.
Purpose/objective: Lack of patient participation and engagement remains a barrier to implementing effective online self-management and behavioral health interventions. Identifying patient characteristics associated with engagement rates may lead to interventions that improve engagement in traditional and online self-management programs. In this study, two online self-management and recovery programs were evaluated to identify factors that predict patient engagement.
Research method/design: Predictors were collected in a questionnaire at baseline before 435 participants started either of the two interventions. One or two online lessons were completed per week with seven or eight total lessons to complete in each program, and each lesson took about 20-30 min to finish. Full patient engagement was defined as completing all lessons and assessments in the program and partial engagement as attempting at least one lesson or assessment.
Results: Predictors of full patient engagement were self-rated confidence in completing the program or being over 60 years of age. Predictors of at least partial patient engagement were experienced ordering online or being over 50 years of age.
Conclusions/implications: Identifying profiles of individuals who predict poor engagement may improve implementation and the health outcomes of intervention programs. (PsycInfo Database Record (c) 2024 APA, all rights reserved).
期刊介绍：
Accounts of Chemical Research presents short, concise and critical articles offering easy-to-read overviews of basic research and applications in all areas of chemistry and biochemistry. These short reviews focus on research from the author’s own laboratory and are designed to teach the reader about a research project. In addition, Accounts of Chemical Research publishes commentaries that give an informed opinion on a current research problem. Special Issues online are devoted to a single topic of unusual activity and significance.
Accounts of Chemical Research replaces the traditional article abstract with an article "Conspectus." These entries synopsize the research affording the reader a closer look at the content and significance of an article. Through this provision of a more detailed description of the article contents, the Conspectus enhances the article's discoverability by search engines and the exposure for the research.
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