Title |
Exploring differential item functioning in the SF-36 by demographic, clinical, psychological and social factors in an osteoarthritis population
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Published in |
BMC Musculoskeletal Disorders, December 2013
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DOI | 10.1186/1471-2474-14-346 |
Pubmed ID | |
Authors |
Beth Pollard, Marie Johnston, Diane Dixon |
Abstract |
The SF-36 is a very commonly used generic measure of health outcome in osteoarthritis (OA). An important, but frequently overlooked, aspect of validating health outcome measures is to establish if items work in the same way across subgroup of a population. That is, if respondents have the same 'true' level of outcome, does the item give the same score in different subgroups or is it biased towards one subgroup or another. Differential item functioning (DIF) can identify items that may be biased for one group or another and has been applied to measuring patient reported outcomes. Items may show DIF for different conditions and between cultures, however the SF-36 has not been specifically examined in an osteoarthritis population nor in a UK population. Hence, the aim of the study was to apply the DIF method to the SF-36 for a UK OA population. |
X Demographics
Geographical breakdown
Country | Count | As % |
---|---|---|
Germany | 1 | 100% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 1 | 100% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
United Kingdom | 1 | 2% |
United States | 1 | 2% |
Nigeria | 1 | 2% |
Unknown | 47 | 94% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Master | 10 | 20% |
Student > Ph. D. Student | 7 | 14% |
Researcher | 6 | 12% |
Student > Doctoral Student | 4 | 8% |
Other | 3 | 6% |
Other | 8 | 16% |
Unknown | 12 | 24% |
Readers by discipline | Count | As % |
---|---|---|
Medicine and Dentistry | 11 | 22% |
Psychology | 8 | 16% |
Nursing and Health Professions | 7 | 14% |
Social Sciences | 5 | 10% |
Economics, Econometrics and Finance | 3 | 6% |
Other | 5 | 10% |
Unknown | 11 | 22% |