Mark Hann1, David Reeves. 1. NPCRDC, The University of Manchester, 5th Floor, Williamson Building, Oxford Road, Manchester M13 9PL, UK. mark.hann@manchester.ac.uk
Abstract
OBJECTIVES: The Short Form 36 Health Status Questionnaire (SF-36) has eight scales that can be condensed into two components: physical component summary (PCS) and mental component summary (MCS). This paper investigates: (1) the assumption that PCS and MCS are orthogonal, (2) the applicability of a single model to different condition-specific subgroups, and (3) a reduced five-scale model. STUDY DESIGN AND SETTING: We performed a secondary analysis of two large-scale data sets that utilised the SF-36: the Health Survey for England 1996 and the Welsh Health Survey 1998. We used confirmatory factor analysis to compare hypothetical orthogonal and oblique factor models, and exploratory factor analysis to derive data-driven models for condition-specific subgroups. RESULTS: Oblique models gave the best fit to the data and indicated a considerable correlation between PCS and MCS. The loadings of the eight scales on the two component summaries varied significantly by disease condition. The choice of model made an important difference to norm-referenced scores for large minorities, particularly patients with a mental illness or mental-physical comorbidity. CONCLUSIONS: We recommend that users of the SF-36 adopt the oblique model for calculating PCS and MCS. An oblique five-scale model provides a more universal factor structure without loss of predictive power or reliability.
OBJECTIVES: The Short Form 36 Health Status Questionnaire (SF-36) has eight scales that can be condensed into two components: physical component summary (PCS) and mental component summary (MCS). This paper investigates: (1) the assumption that PCS and MCS are orthogonal, (2) the applicability of a single model to different condition-specific subgroups, and (3) a reduced five-scale model. STUDY DESIGN AND SETTING: We performed a secondary analysis of two large-scale data sets that utilised the SF-36: the Health Survey for England 1996 and the Welsh Health Survey 1998. We used confirmatory factor analysis to compare hypothetical orthogonal and oblique factor models, and exploratory factor analysis to derive data-driven models for condition-specific subgroups. RESULTS: Oblique models gave the best fit to the data and indicated a considerable correlation between PCS and MCS. The loadings of the eight scales on the two component summaries varied significantly by disease condition. The choice of model made an important difference to norm-referenced scores for large minorities, particularly patients with a mental illness or mental-physical comorbidity. CONCLUSIONS: We recommend that users of the SF-36 adopt the oblique model for calculating PCS and MCS. An oblique five-scale model provides a more universal factor structure without loss of predictive power or reliability.
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