Development of a measure of attitude toward nutrition in patient care |
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Authors: | McGaghie W C Van Horn L Fitzgibbon M Telser A Thompson J A Kushner R F Prystowsky J B |
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Affiliation: | Office of Medical Education (McGaghie), Northwestern University Medical School, Chicago, Illinois 60611-3008, USA. wcmc@northwestern.edu |
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Abstract: | BACKGROUND: Development of reliable measures of medical student and resident attitudes about nutrition in patient care is needed before the effects of educational interventions or clinical experience can be gauged. This report describes the systematic development of a measure of attitude toward nutrition in patient care. It presents evidence about scale reliability and the absence of response bias that endorses the trustworthiness of data from the measure. METHODS: An eight-step attitude scale development procedure was used to create the Nutrition In Patient care Survey (NIPS). Data from five samples of first- and second-year medical students and first-year medical residents were subjected to factor analysis (PA2, varimax rotation), reliability analyses, and statistical analyses to test for demographic bias in the attitude data. RESULTS: A 45-item attitude measure was developed that contains five subscales derived from the factor analysis: (1) nutrition in routine care (NRC, 8 items); (2) clinical behavior (CB, 20 items); (3) physician-patient relationship (PPR, 8 items); (4) patient behavior/motivation (PBM, 3 items); and (5) physician efficacy (PE, 6 items). Each subscale yields reliable data in terms of internal consistency (alpha coefficients) and stability (test-retest reliability). Medical student and resident demographic variables have negligible influence on attitude scores. DISCUSSION: The NIPS subscales yield reliable data that can be used to assess outcomes in evaluation research on educational or clinical interventions or to predict patient care practices. Systematic attitude scale development increases the likelihood that the resulting measures will produce useful, trustworthy data. |
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