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"Best fit" framework synthesis: refining the method.

Christopher Carroll1, Andrew Booth, Joanna Leaviss

  • 1Health Economics and Decision Science, School of Health and Related Research, Regent Court, Regent Street, Sheffield S1 4DA, UK. c.carroll@shef.ac.uk

BMC Medical Research Methodology
|March 19, 2013
PubMed
Summary
This summary is machine-generated.

This study presents a refined "best fit" method for qualitative evidence synthesis, demonstrating its practicality and effectiveness in understanding employee views on workplace smoking cessation interventions. The method aids in developing context-specific models for health behaviors.

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Area of Science:

  • Health Services Research
  • Qualitative Research Methods
  • Evidence Synthesis

Background:

  • The "best fit" method for qualitative evidence synthesis requires further specification.
  • A prior worked example highlighted areas for methodological refinement.

Purpose of the Study:

  • To provide a detailed second worked example of the "best fit" method.
  • To fully define and explain all techniques within the method.
  • To assess the appropriateness of the method's components.

Main Methods:

  • Development of systematic theory identification techniques.
  • Creation of an a priori framework for synthesis.
  • Integration of quality assessment, analysis, and synthesis methods.
  • Application to a qualitative evidence synthesis on employee views of workplace smoking cessation interventions.

Main Results:

  • The "best fit" method was found to be practical and fit for purpose in the worked example.
  • The synthesis successfully generated insights into employee perspectives on smoking cessation interventions.
  • The method facilitated the development of context-specific conceptual models.

Conclusions:

  • The "best fit" method is suitable for generating context-specific models of decision-making and health behaviors.
  • It offers a pragmatic approach for rapid qualitative evidence synthesis.
  • The method can generate program theories relevant to intervention effectiveness for researchers and policymakers.