Literature DB >> 11210594

The SF-36 summary scales: problems and solutions.

D Wilson, J Parsons, G Tucker.   

Abstract

To determine the accuracy of the SF-36 summary mental and physical health scales in reflecting their underlying subscales using the traditional method of scoring based on factor coefficients derived through principle components analysis and orthogonal rotation. A representative Australian population survey containing the SF-36 was used to obtain factor coefficients from principle components analysis and orthogonal rotation for scoring the physical component summary (PCS) and the mental component summary (MCS) of the SF-36 in the traditional way. In addition two other methods were used to produce coefficients. The first method used maximum likelihood extraction and oblique rotation. The second method fit a structural equation model to the data in a confirmatory factor analysis. The coefficients derived by each of the methods were applied to the data of a second representative population survey. This survey also provided data on physical and mental health status which allowed comparison of the summary scores and underlying subscales according to various health states. Neither of the scoring methods based on the exploratory factor analyses methods (orthogonal and oblique) produced summary scale scores, by age group, that adequately reflected the underlying subscales. When coefficients derived using structural equation modeling were fit to the data in a confirmatory factor analysis the MCS and PCS accurately reflected their underlying subscale scores. They also produced MCS and PCS scores for the various health states as would be expected from the underlying subscales. The traditional methods of scoring the SF-36 summary scales produce results that would not be expected from the underlying subscales. The problem was only corrected by fitting a structural equation model to the data in a confirmatory factor analysis. The results advise caution in the use of the SF-36 summary scales and suggests that alternative methods of developing factor coefficients need to be employed in studies using the SF-36 summary scales.

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Year:  2000        PMID: 11210594     DOI: 10.1007/bf01591686

Source DB:  PubMed          Journal:  Soz Praventivmed        ISSN: 0303-8408


  21 in total

1.  Rethinking and rescoring the SF-12.

Authors:  David Wilson; Graeme Tucker; Catherine Chittleborough
Journal:  Soz Praventivmed       Date:  2002

2.  Performance of the RAND-12 and SF-12 summary scores in type 2 diabetes.

Authors:  Jeffrey A Johnson; Sheri L Maddigan
Journal:  Qual Life Res       Date:  2004-03       Impact factor: 4.147

3.  New Australian population scoring coefficients for the old version of the SF-36 and SF-12 health status questionnaires.

Authors:  Graeme Tucker; Robert Adams; David Wilson
Journal:  Qual Life Res       Date:  2010-05-04       Impact factor: 4.147

4.  The case for using country-specific scoring coefficients for scoring the SF-12, with scoring implications for the SF-36.

Authors:  Graeme Tucker; Robert Adams; David Wilson
Journal:  Qual Life Res       Date:  2015-09-28       Impact factor: 4.147

Review 5.  Are factor analytical techniques used appropriately in the validation of health status questionnaires? A systematic review on the quality of factor analysis of the SF-36.

Authors:  Henrica C W de Vet; Herman J Adèr; Caroline B Terwee; François Pouwer
Journal:  Qual Life Res       Date:  2005-06       Impact factor: 4.147

6.  The SF36 Version 2: critical analyses of population weights, scoring algorithms and population norms.

Authors:  Graeme Hawthorne; Richard H Osborne; Anne Taylor; Jan Sansoni
Journal:  Qual Life Res       Date:  2007-02-01       Impact factor: 4.147

7.  Comparison between exploratory factor-analytic and SEM-based approaches to constructing SF-36 summary scores.

Authors:  Fotios Anagnostopoulos; Dimitris Niakas; Yannis Tountas
Journal:  Qual Life Res       Date:  2008-11-26       Impact factor: 4.147

8.  Deriving SF-12v2 physical and mental health summary scores: a comparison of different scoring algorithms.

Authors:  John A Fleishman; Alfredo J Selim; Lewis E Kazis
Journal:  Qual Life Res       Date:  2010-01-22       Impact factor: 4.147

9.  A comparison of SF-36 summary measures of physical and mental health for women across the life course.

Authors:  Gita D Mishra; Richard Hockey; Annette J Dobson
Journal:  Qual Life Res       Date:  2013-12-03       Impact factor: 4.147

10.  Associations of physical and mental health problems with chronic cough in a representative population cohort.

Authors:  Robert J Adams; Sarah L Appleton; David H Wilson; Anne W Taylor; Richard E Ruffin
Journal:  Cough       Date:  2009-12-16
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