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Using framework analysis methods for qualitative research: AMEE Guide No. 164.

Sonja KlingbergRenée E StalmeijerLara Varpio
Published in: Medical teacher (2023)
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.
Keyphrases
  • data analysis
  • healthcare
  • systematic review
  • public health
  • mental health
  • big data
  • electronic health record
  • risk assessment
  • deep learning
  • social media
  • quality improvement