Title |
Using framework-based synthesis for conducting reviews of qualitative studies
|
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Published in |
BMC Medicine, April 2011
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DOI | 10.1186/1741-7015-9-39 |
Pubmed ID | |
Authors |
Mary Dixon-Woods |
Abstract |
Framework analysis is a technique used for data analysis in primary qualitative research. Recent years have seen its being adapted to conduct syntheses of qualitative studies. Framework-based synthesis shows considerable promise in addressing applied policy questions. An innovation in the approach, known as 'best fit' framework synthesis, has been published in BMC Medical Research Methodology this month. It involves reviewers in choosing a conceptual model likely to be suitable for the question of the review, and using it as the basis of their initial coding framework. This framework is then modified in response to the evidence reported in the studies in the reviews, so that the final product is a revised framework that may include both modified factors and new factors that were not anticipated in the original model. 'Best fit' framework-based synthesis may be especially suitable in addressing urgent policy questions where the need for a more fully developed synthesis is balanced by the need for a quick answer. Please see related article: http://www.biomedcentral.com/1471-2288/11/29. |
X Demographics
Geographical breakdown
Country | Count | As % |
---|---|---|
United Kingdom | 2 | 29% |
South Africa | 1 | 14% |
Unknown | 4 | 57% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 4 | 57% |
Scientists | 3 | 43% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
United Kingdom | 14 | 3% |
Australia | 2 | <1% |
United States | 2 | <1% |
India | 1 | <1% |
Spain | 1 | <1% |
Canada | 1 | <1% |
Unknown | 454 | 96% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Master | 97 | 20% |
Student > Ph. D. Student | 95 | 20% |
Researcher | 75 | 16% |
Student > Doctoral Student | 27 | 6% |
Student > Bachelor | 23 | 5% |
Other | 79 | 17% |
Unknown | 79 | 17% |
Readers by discipline | Count | As % |
---|---|---|
Medicine and Dentistry | 87 | 18% |
Social Sciences | 81 | 17% |
Nursing and Health Professions | 48 | 10% |
Psychology | 39 | 8% |
Business, Management and Accounting | 33 | 7% |
Other | 85 | 18% |
Unknown | 102 | 21% |