医学
随机对照试验
系统回顾
多样性(控制论)
报告审判综合标准
协议(科学)
医疗保健
梅德林
替代医学
医学教育
应用心理学
心理学
计算机科学
外科
人工智能
法学
经济
病理
经济增长
政治学
作者
Susan Armijo‐Olivo,Jordana Barbosa da Silva,Ester Moreira de Castro‐Carletti,Ana Izabela Sobral de Oliveira‐Souza,Elisa Bizetti Pelai,Norazlin Mohamad,Fatemeh Baghbaninaghadehi,Liz Dennett,Jeremy Steen,Dinesh Kumbhare,Nikolaus Ballenberger
标识
DOI:10.1097/phm.0000000000002444
摘要
ABSTRACT: This review presents a comprehensive summary and critical evaluation of intention-to-treat analysis, with a particular focus on its application to randomized controlled trials within the field of rehabilitation. Adhering to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines, we conducted a methodological review that encompassed electronic and manual search strategies to identify relevant studies. Our selection process involved two independent reviewers who initially screened titles and abstracts and subsequently performed full-text screening based on established eligibility criteria. In addition, we included studies from manual searches that were already cataloged within the first author's personal database. The findings are synthesized through a narrative approach, covering fundamental aspects of intention to treat, including its definition, common misconceptions, advantages, disadvantages, and key recommendations. Notably, the health literature offers a variety of definitions for intention to treat, which can lead to misinterpretations and inappropriate application when analyzing randomized controlled trial results, potentially resulting in misleading findings with significant implications for healthcare decision making. Authors should clearly report the specific intention-to-treat definition used in their analysis, provide details on participant dropouts, and explain upon their approach to managing missing data. Adherence to reporting guidelines, such as the Consolidated Standards of Reporting Trials for randomized controlled trials, is essential to standardize intention-to-treat information, ensuring the delivery of accurate and informative results for healthcare decision making.
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