{"title":"Using framework analysis methods for qualitative research: AMEE Guide No. 164.","authors":"Sonja Klingberg, Renée E Stalmeijer, Lara Varpio","doi":"10.1080/0142159X.2023.2259073","DOIUrl":null,"url":null,"abstract":"<p><p>Framework analysis methods (FAMs) are structured approaches to qualitative data analysis that originally stem from large-scale policy research. A defining feature of FAMs is the development and application of a matrix-based analytical framework. These methods can be used across research paradigms and are thus particularly useful tools in the health professions education (HPE) researcher's toolbox. Despite their utility, FAMs are not frequently used in HPE research. In this AMEE Guide, we provide an overview of FAMs and their applications, situating them within specific qualitative research approaches. We also report the specific characteristics, advantages, and disadvantages of FAMs in relation to other popular qualitative analysis methods. Using a specific type of FAM-i.e. the framework method-we illustrate the stages typically involved in doing data analysis with an FAM. Drawing on Sandelowski and Barroso's continuum of data transformation, we argue that FAMs tend to remain close to raw data and be descriptive or exploratory in nature. However, we also illustrate how FAMs can be harnessed for more interpretive analyses. We propose that FAMs are valuable resources for HPE researchers and demonstrate their utility with specific examples from the HPE literature.</p>","PeriodicalId":18643,"journal":{"name":"Medical Teacher","volume":" ","pages":"603-610"},"PeriodicalIF":3.3000,"publicationDate":"2024-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Medical Teacher","FirstCategoryId":"95","ListUrlMain":"https://doi.org/10.1080/0142159X.2023.2259073","RegionNum":2,"RegionCategory":"教育学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2023/9/21 0:00:00","PubModel":"Epub","JCR":"Q1","JCRName":"EDUCATION, SCIENTIFIC DISCIPLINES","Score":null,"Total":0}
引用次数: 0
Abstract
Framework analysis methods (FAMs) are structured approaches to qualitative data analysis that originally stem from large-scale policy research. A defining feature of FAMs is the development and application of a matrix-based analytical framework. These methods can be used across research paradigms and are thus particularly useful tools in the health professions education (HPE) researcher's toolbox. Despite their utility, FAMs are not frequently used in HPE research. In this AMEE Guide, we provide an overview of FAMs and their applications, situating them within specific qualitative research approaches. We also report the specific characteristics, advantages, and disadvantages of FAMs in relation to other popular qualitative analysis methods. Using a specific type of FAM-i.e. the framework method-we illustrate the stages typically involved in doing data analysis with an FAM. Drawing on Sandelowski and Barroso's continuum of data transformation, we argue that FAMs tend to remain close to raw data and be descriptive or exploratory in nature. However, we also illustrate how FAMs can be harnessed for more interpretive analyses. We propose that FAMs are valuable resources for HPE researchers and demonstrate their utility with specific examples from the HPE literature.
期刊介绍:
Medical Teacher provides accounts of new teaching methods, guidance on structuring courses and assessing achievement, and serves as a forum for communication between medical teachers and those involved in general education. In particular, the journal recognizes the problems teachers have in keeping up-to-date with the developments in educational methods that lead to more effective teaching and learning at a time when the content of the curriculum—from medical procedures to policy changes in health care provision—is also changing. The journal features reports of innovation and research in medical education, case studies, survey articles, practical guidelines, reviews of current literature and book reviews. All articles are peer reviewed.