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Best Fit Framework Synthesis

Page history last edited by Andrew Booth 4 years, 3 months ago

In a Nutshell - Best fit framework synthesis

 

Best fit framework synthesis – what is it?

Best fit framework synthesis seeks to capitalise on the inherent advantages of both frame­work synthesis and thematic synthesis to derive a methodology that is particularly suited to pragmatic situations, such as the production of health technology assessments. It does this by starting with a ‘good enough’ framework, populating it with as much of the data as possible without forcing the data to fit. Following this initial deductive phase, you can handle the remaining data inductively, creating new themes until all the data are processed. While framework synthesis described above, and its primary data predeces­sor framework analysis, have always accommodated the subsequent inductive addition of data, the best fit framework approach is characterised by the conscious and explicit engineering of a distinct two-stage process. This ensures that there is a clear audit trail for themes derived from the original framework and those subsequently identified by the inductive process of thematic synthesis. In addition to added transparency the method also facilitates project management and version control by keeping the two stages phased and sequential, rather than iterative.

 

What can I use it for?

Best fit framework synthesis is most suitable where you are unable to identify a model or framework that represents a close match to the data being extracted. For example, in its original application a review team were unable to identify a conceptual model that suf­ficiently depicted the phenomenon of taking substances such as aspirin to prevent bowel cancer. However, they identified a model that looked at factors influencing women who were taking dietary supplements. Despite differences in age group, and between a single gender issue and a problem affecting both genders, factors influencing their behaviour, such as the effect of friends and family and the media and fears of adverse effects, were common to both health issues. As a general rule of thumb, a match of between 60% and 80% of the data to the chosen framework offers a relative advantage over thematic synthesis. Subsequent variants merge several competing frameworks for a well-theorised area (workplace smok­ing prevention) to create a more comprehensive meta-framework for data extraction (Carroll et al., 2013). Logic models and policy frameworks (Walt and Gilson, 2014) are also suggested as potential structures for data extraction (Booth and Carroll, 2015) where theoretical frame­works do not exist.

 

How has it been used?

Examples of the best fit framework synthesis approach are not yet plentiful although increas­ing rapidly. As Dixon-Woods (2011) comments:

 

Framework-based synthesis is an important advance in conducting reviews of qualita­tive synthesis. The ‘best fit’ strategy is a variant of this approach that may be very help­ful when policy makers, practitioners or other decision makers need answers quickly, and are able to tolerate some ambiguity about whether the answer is the very best that could be given.

 

References

Booth A, Carroll C. How to build up the actionable knowledge base: the role of ‘best fit’ framework synthesis for studies of improvement in healthcare. BMJ quality & safety. 2015 Aug 25:bmjqs-2014.

Carroll C, Booth A, Cooper K. A worked example of" best fit" framework synthesis: A systematic review of views concerning the taking of some potential chemopreventive agents. BMC Medical Research Methodology. 2011 Dec 1;11(1):1-9.

Carroll C, Booth A, Leaviss J, Rick J. “Best fit” framework synthesis: refining the method. BMC medical research methodology. 2013 Mar 13;13(1):1.

Dixon-Woods M. Using framework-based synthesis for conducting reviews of qualitative studies. BMC Medicine. 2011 Apr 14;9(1):1.

Walt G, Gilson L. Can frameworks inform knowledge about health policy processes? Reviewing health policy papers on agenda setting and testing them against a specific priority-setting framework. Health policy and planning. 2014 Dec 1;29(suppl 3):iii6-22.

 

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