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Quality of Life Research

, Volume 19, Issue 7, pp 1069–1076 | Cite as

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

  • Graeme TuckerEmail author
  • Robert Adams
  • David Wilson
Article

Abstract

Purpose

To compare the relationship of the eight SF-36 v1 subscale scores to the summary scores of the PCS and MCS derived from two different scoring algorithms: one based on the original scoring method (Ware, Kosinski and Keller, SF-36 physical and mental health summary scales: a users manual. The Health Institute, New England Medical Centre, Boston, MA, 1994); and the other based on scoring algorithms that use parameters derived from structural equation modelling. Further, to provide SF-12 scoring algorithms similarly based on structural equation modelling.

Methods

The Australian Bureau of Statistics 1995 Australian National Health Survey dataset was used as the basis for the production of coefficients. There were 18,141 observations with no missing data for all eight SF-36 subscales following imputation of data items, and 17,479 observations with no missing data for the SF-12 data items. Data were analysed in LISREL V8.71. Structural equation models were fit to the data in confirmatory factor analyses producing weighted least squares estimates, which overcame anomalies found in the traditional orthogonal scoring methods.

Results

Models with acceptable fits to the hypothesised factor structure were produced, generating factor score weighting coefficients for use with the SF-36 and SF-12 data items, to produce PCS and MCS summary scores consistent with their underlying subscale scores.

Conclusions

The coefficients generated will score the SF-36 summary PCS and MCS in a manner consistent with their subscales. Previous Australian studies using version 1 of SF-36 or SF-12 can re-score their summary scores using these coefficients.

Keywords

SF-36 summary scores Structural Equation Model PCS MCS 

References

  1. 1.
    Arbuckle, J. L., & Wothke, W. (1999). Amos 4.0 user’s guide. Chicago: Small Waters Corporation.Google Scholar
  2. 2.
    Australian Bureau of Statistics. (1995) National Health Survey. SF-36 Population Norms Australia. Canberra: Australian Bureau of Statistics, Catalogue Number 4399.0.Google Scholar
  3. 3.
    Hawthorne, G., Osborne, R. H., Taylor, A., & Sansoni, J. (2007). The SF-36 Version 2: Critical analysis of population weighting, scoring algorithms and population norms. Quality of Life Res, 16, 661–673.CrossRefGoogle Scholar
  4. 4.
    Hurst, N. P., Ruta, D. A., & Kind, P. (1998). Comparison of the MOS short form-12 (SF-12) health status questionnaire with the SF -36 in patients with rheumatoid arthritis. British Journal of Rheumatology, 37, 862–869.CrossRefPubMedGoogle Scholar
  5. 5.
    McCallum, J. (1995). The new SF-36 health status measure: Australian validity tests. In Paper presented to the Health Outcomes and Quality of Life Measurement Conference. Canberra: National Centre for Epidemiology and Population Health.Google Scholar
  6. 6.
    McCallum, J. (1995). The SF-36 in an Australian sample: Validating a new, generic health status measure. Australian Journal of Public Health, 19, 160–166.CrossRefPubMedGoogle Scholar
  7. 7.
    Morfeld, M., Bullinger, M., Natke, J., & Brahler, E. (2005). Die version 2.0 des SF-36 Health Survey-Ergebnisse einer bevolkerungsreprerasentativen studie. Sozial- und Praventivmedizin, 50, 292–300.CrossRefPubMedGoogle Scholar
  8. 8.
    Nordvedt, M. W., Riise, T., Myhr, K. M., & Nyland, H. I. (2000). Performance of the SF-36, SF-12 and RAND SF36 summary scales in a multiple sclerosis population. Medical Care, 38, 1022–1028.CrossRefGoogle Scholar
  9. 9.
    Quality Metric Incorporated. (2008). SF-36 v2TM and SF-12 v2 TM Health Surveys Offer Substantial Improvements. www.SF-36.org/commnity/SF36V2andSF12V2.shtml. Accessed June 20, 2008.
  10. 10.
    Sanson-Fisher, R. W., & Perkins, J. J. (1998). Adaptation and validation of the SF-36 Health Survey for Use in Australia. Journal of Clinical Epidemiology, 51(11), 961–967.CrossRefPubMedGoogle Scholar
  11. 11.
    Sansoni, J., & Costi, J. (2001). SF-36 Version 1 or Version 2: The need for Australian normative data. In Proceedings of Health Outcomes 2001: The Odyssey Advances Conference. Canberra: Australian Health Outcomes Collaboration.Google Scholar
  12. 12.
    Simon, G. E., Revicki, D. A., Grothaus, L., & Vonkorf, M. (1998). SF-36 summary scores. Are physical and mental health truly distinct? Medical Care, 36, 567–572.CrossRefPubMedGoogle Scholar
  13. 13.
    Sorensen, L., Stokes, J. A., Purdie, D. M., et al. (2004). Medication reviews in the community: Results of a randomized, controlled effectiveness trial. British Journal of Clinical Pharmacology, 58, 648–664.CrossRefPubMedGoogle Scholar
  14. 14.
    Taft, C., Karlson, J., & Sullivan, M. (2001). Do SF-36 summary component scores accurately summarise subscale scores? Quality of Life Research, 10, 395–404.CrossRefPubMedGoogle Scholar
  15. 15.
    Ware, J. E., & Kosinski, M. (2001). Interpreting SF-36 summary health measures: A response. Quality of Life Research, 10, 405–413.CrossRefPubMedGoogle Scholar
  16. 16.
    Ware, J. E., Kosinski, M., & Keller, S. D. (1994). SF-36 physical and mental health summary scales: A users manual. Boston, MA: The Health Institute, New England Medical Centre.Google Scholar
  17. 17.
    Ware, J. E., Snow, K. K., Kosinski, M., & Gandek, B. (1993). The SF-36 health survey manual and interpretation guide. Boston, MA: The Health Institute, New England Medical Centre.Google Scholar
  18. 18.
    Wilson, D., Parsons, J., & Tucker, G. (2000). The SF-36 summary scales: Problems and solutions. Sozial- und Praventivmedizin, 45, 239–246.CrossRefPubMedGoogle Scholar
  19. 19.
    Wilson, D., Tucker, G., & Chittleborough, C. (2002). Rethinking and rescoring the SF = 12. Sozial- und Praventivmedizin, 47, 172–177.CrossRefPubMedGoogle Scholar

Copyright information

© Springer Science+Business Media B.V. 2010

Authors and Affiliations

  1. 1.Department of HealthAdelaideAustralia

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