Quality of Life Research

, Volume 16, Issue 4, pp 661–673 | Cite as

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

  • Graeme Hawthorne
  • Richard H. Osborne
  • Anne Taylor
  • Jan Sansoni
Original Paper



The SF36 Version 2 (SF36V2) is a revision of the SF36 Version 1, and is a widely used health status measure. It is important that guidelines for interpreting scores are available.


A population sample of Australians (n = 3015) weighted to achieve representativeness was administered the SF36V2. Comparisons between published US weights and sample derived weights were made, and Australian population norms computed and presented.

Major findings

Significant differences were observed on 7/8 scales and on the mental health summary scale. Possible causes of these findings may include different sampling and data collection procedures, demographic characteristics, differences in data collection time (1998 vs. 2004), differences in health status or differences in cultural perception of the meaning of health. Australian population norms by age cohort, gender and health status are reported by T-score as recommended by the instrument developers. Additionally, the proportions of cases within T-score deciles are presented and show there are important data distribution issues.

Principal conclusions

The procedures reported here may be used by other researchers where local effects are suspected. The population norms presented may be of interest. There are statistical artefacts associated with T-scores that have implications for how SF36V2 data are analysed and interpreted.


SF-36 Population norms Emic effects Health status Cultural differences Scoring weights 



We would like to thank Mr Nick Marosszeky for his valuable comments on the manuscript.

This project was supported by a grant from the Community Care Branch, Australian Commonwealth Department of Health and Ageing, as part of the National Continence Management Strategy. The collection of data was carried out by the Population Research and Outcome Studies Unit, South Australian Department of Health. Dr Richard Osborne is supported in part by the Baker Trust, Buckland Foundation, the Arthritis Foundation of Australia, and by the National Health and Medical Research Council Career Development Award Population Health Fellowship.

Finally, our thanks go to those South Australians who gave their time to complete the questionnaire.


  1. 1.
    Ware, J. E., Snow, K. K., Kosinski, M., & Gandek, B. (1993). SF-36 health survey: Manual and interpretation guide. Boston: The Health Institute, New England Medical Centre.Google Scholar
  2. 2.
    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, 961–67.CrossRefPubMedGoogle Scholar
  3. 3.
    McCallum, J. (1994). The new ‘SF-36–health status measure: Australian validity tests. Canberra: National Centre for Epidemiology and Population Health. 2.Google Scholar
  4. 4.
    McCallum, J. (1995). The SF-36 in an Australian sample: Validating a new, generic health status measure. Australian Journal of Public Health, 19, 160–66.PubMedCrossRefGoogle Scholar
  5. 5.
    Perkins, J. J., & Sanson-Fisher, R. W. (1998). An examination of self- and telephone-administered modes of administration for the Australian SF-36. Journal of Clinical Epidemiology, 51, 969–73.CrossRefPubMedGoogle Scholar
  6. 6.
    Watson, E., Firman, D., Baade, P., & Ring, I. (1996). Telephone administration of the SF-36 health survey: Validation studies and population norms for adults in Queensland. Australian and New Zealand Journal of Public Health, 20, 359–63.CrossRefPubMedGoogle Scholar
  7. 7.
    Ware, J. E., Kosinski, M. A., & Dewey J. E. (2000). How to score version 2 of the SF-36 health survey. Lincoln: Quality Metric Inc.Google Scholar
  8. 8.
    Andresen, E., Patrick, D., Carter, W., & Malmgren, J. (1995). Comparing the performance of health status measures for healthy older adults. Journal of the American Geriatrics Society, 43, 1030–034.PubMedGoogle Scholar
  9. 9.
    Bullinger, M., Alonso, J., Apolone, G., Leplège, A., Sullivan, M., Wood Dauphinee, S., Gandek, B., Wagner, A., Aaronson, N., Bech, P., Fukuhara, S., Kaasa, S., & Ware, J.E. Jr. (1998). Translating health status questionnaires and evaluating their quality: The IQOLA Project approach. International Quality of Life Assessment. Journal of Clinical Epidemiology, 51, 913–23.CrossRefPubMedGoogle Scholar
  10. 10.
    Hayes, V., Morris, J., Wolfe, C., & Morgan, M. (1995). The SF-36 health survey questionnaire: Is it suitable for use with older adults? Age and Ageing, 24, 120–25.CrossRefPubMedGoogle Scholar
  11. 11.
    O’Mahoney, P. G., Rodgers, H., Thomson, R. G., Dobson, R., & James, O. F. W. (1998). Is the SF-36 suitable for assessing health status of older stroke patients? Age and Ageing, 27, 19–4.CrossRefGoogle Scholar
  12. 12.
    Parker, S. G., Peet, S. M., Jagger, C., Farhan, M., & Castleden, C. M. (1998). Measuring health status in older patients. The SF-36 in practice. Age and Ageing, 27, 13–8.CrossRefPubMedGoogle Scholar
  13. 13.
    Jenkinson, C. (1995). Evaluating the efficacy of medical treatment: possibilities and limitations. Social Science & Medicine, 41, 1395–401.CrossRefGoogle Scholar
  14. 14.
    Adamson, J., Gooberman-Hill, R., Woolhead, G., & Donovan, J. (2004). ‘Questerviews– Using questionnaires in qualitative interviews as a method of integrating qualitative and quantitative health services research. Journal of Health Services Research & Policy, 9, 139–45.CrossRefGoogle Scholar
  15. 15.
    Ziebland, S. (1995). The short form 36 health status questionnaire: Clues from the Oxford region’s normative data about its usefulness in measuring health gain in population surveys. Journal of Epidemiology and Community Health, 49, 102–05.CrossRefPubMedGoogle Scholar
  16. 16.
    Wilson, D., Parsons, J., & Tucker, G. (2000). The SF-36 summary scales: Problems and solutions. Sozial- und Präventivmedizin, 45, 239–46.CrossRefPubMedGoogle Scholar
  17. 17.
    Keller, S. D., Ware, J. E. Jr., Gandek, B., Aaronson, N. K., Alonso, J., Apolone, G., Bjorner, J. B., Brazier, J., Bullinger, M., Fukuhara, S., Kaasa, S., Leplège, A., Sanson Fisher, R. W., Sullivan, M., & Wood Dauphinee, S. (1998). Testing the equivalence of translations of widely used response choice labels: Results from the IQOLA Project. International Quality of Life Assessment. Journal of Clinical Epidemiology, 51, 933–44.CrossRefPubMedGoogle Scholar
  18. 18.
    Bjorner, J. B., Damsgaard, M. T., Watt, T., & Groenvold, M. (1998). Tests of data quality, scaling assumptions, and reliability of the Danish SF-36. Journal of Clinical Epidemiology, 51, 1001–011.CrossRefPubMedGoogle Scholar
  19. 19.
    Razavi, D., & Gandek, B. (1998). Testing Dutch and French translations of the SF-36 health survey among Belgian angina patients. Journal of Clinical Epidemiology, 51, 975–81.CrossRefPubMedGoogle Scholar
  20. 20.
    Kazis, L. E., Lee, A., Spiro, A. 3rd, Rogers, W., Ren, X. S., Miller, D. R., Selim, A., Hamed, A., & Haffer, S. C. (2004). Measurement comparisons of the medical outcomes study and veterans SF-36 health survey. Health Care Financing Review, 25, 43–8.PubMedGoogle Scholar
  21. 21.
    McCall, W. A. (1922). How to measure in education. New York: Macmillan.Google Scholar
  22. 22.
    Taft, C., Karlsson, J., & Sullivan, M. (2004). Performance of the Swedish SF-36 version 2.0. Quality of Life Research, 13, 251–56.CrossRefPubMedGoogle Scholar
  23. 23.
    Jenkinson, C., Stewart-Brown, S., Petersen, S., & Paice, C. (1999). Assessment of the SF-36 version 2 in the United Kingdom. Journal of Epidemiology and Community Health, 53, 46–0.CrossRefPubMedGoogle Scholar
  24. 24.
    Morfeld, M., Bullinger, M., Nantke, J., & Brahler, E. (2005). Die version 2.0 des SF-36 Health Survey–Ergebnisse einer bevölkerungsrepräsentativen studie. Sozial- und Präventivmedizin, 50, 292–00.CrossRefPubMedGoogle Scholar
  25. 25.
    Sansoni, J., & Costi, J. (2001). SF-36: Version 1 or Version 2: The need for Australian normative data. Proceedings of Health Outcomes 2001: The Odyssey Advances Conference. Canberra: Australian Health Outcomes Collaboration.Google Scholar
  26. 26.
    ABS (1997). National Health Survey: SF-36 Population Norms, Australia. Canberra: Australia Bureau of Statistics.Google Scholar
  27. 27.
    Harrison Health Research (2004). Findings from Autumn 2004 Health Omnibus Survey. Adelaide, Harrison Health Research.Google Scholar
  28. 28.
    Wilson, D., Wakefield, M., & Taylor, A. (1992). The South Australian Health Omnibus Survey. Health Promotion Journal of Australia, 2, 47–9.Google Scholar
  29. 29.
    Ware, J., Kosinski, M., & Keller, S. (1994). SF-36 physical and mental health summary scales: A user’s manual Boston: The Health Institute, New England Medical Centre.Google Scholar
  30. 30.
    Feeny, D., Furlong, W., & Torrance, G. (1996). Health Utilities Index Mark 2 and Mark 3 (HUI2/3) 15-item questionnaire for self-administered, self-assessed usual health status. Hamilton: Centre for Health Economics and Policy Analysis, McMaster University.Google Scholar
  31. 31.
    ABS (2005). 3235.4.55.001–Population by age and sex, South Australia Canberra: Australian Bureau of Statistics.Google Scholar
  32. 32.
    ABS (2003). 2001.0–Census of population and housing: Basic community profiles, 2001 Canberra.Google Scholar
  33. 33.
    SPSS (2004). SPSS for Windows, Version 13.0 Chicago: SPSS Inc.Google Scholar
  34. 34.
    Gandek, B., & Ware, J. E. Jr. (1998). Methods for validating and norming translations of health status questionnaires: The IQOLA Project approach. International Quality of Life Assessment. Journal of Clinical Epidemiology, 51, 953–59.CrossRefPubMedGoogle Scholar
  35. 35.
    Patrick, D. L., Bush, J. W., & Chen, M. M. (1973). Toward an operational definition of health. Journal of Health and Social Behavior, 14, 6–3.CrossRefPubMedGoogle Scholar
  36. 36.
    Shaw, J. W., Johnson, J. A., & Coons, S. J. (2005). US valuation of the EQ-5D health states: Development and testing of the D1 valuation model. Medical Care, 43, 203–20.CrossRefPubMedGoogle Scholar
  37. 37.
    Havranek, E. P., & Steiner, J. F. (2005). Valuation of health states in the US versus the UK: Two measures divided by a common language? Medical Care, 43, 201–02.CrossRefPubMedGoogle Scholar
  38. 38.
    Johnson, J. A., Luo, N., Shaw, J. W., Kind, P., & Coons, S. J. (2005). Valuations of EQ-5D health states: Are the United States and United Kingdom different? Medical Care, 43, 221–28.CrossRefPubMedGoogle Scholar
  39. 39.
    Fryback, D. G. (2005). A US valuation of the EQ-5D. Medical Care, 43, 199–00.CrossRefPubMedGoogle Scholar
  40. 40.
    Ware, J., Gandek, B., & Keller, S. (1996). Evaluating instruments used cross-nationally: Methods from the IQOLA project. In B. Spilker (Ed.), Quality of Life and Pharmacoeconomics (pp. 681–92). Philadelphia: Lippincott-Raven Publishers.Google Scholar
  41. 41.
    Skevington, S. M., Sartorius, N., & Amir, M. (2004). Developing methods for assessing quality of life in different cultural settings. The history of the WHOQOL instruments. Social Psychiatry and Psychiatric Epidemiology, 39, 1–.CrossRefPubMedGoogle Scholar
  42. 42.
    Szabo, S., Orley, J., Saxena, S., & The WHOQOL Group. (1997). An approach to response scale development for cross-cultural questionnaires. European Psychologist, 2, 270–76.Google Scholar
  43. 43.
    WHOQoL Group (1995). The World Health Organization Quality of Life Assessment (WHOQOL): Position paper from the World Health Organization. Social Science & Medicine, 41, 1403–409.CrossRefGoogle Scholar
  44. 44.
    Wee, H. L., Li, S. C., Cheung, Y. B., Fong, K. Y., & Thumboo, J. (2006). The influence of ethnicity on health-related quality of life in diabetes mellitus: A population-based, multiethnic study. Journal of Diabetes and its Complications, 20, 170–78.CrossRefPubMedGoogle Scholar
  45. 45.
    Ware, J. E. Jr., Gandek, B., Kosinski, M., Aaronson, N. K., Apolone, G., Brazier, J., Bullinger, M., Kaasa, S., Leplege, A., Prieto, L., Sullivan, M., & Thunedborg K. (1998). The equivalence of SF-36 summary health scores estimated using standard and country-specific algorithms in 10 countries: Results from the IQOLA Project. International Quality of Life Assessment. Journal of Clinical Epidemiology, 51, 1167–170.CrossRefPubMedGoogle Scholar
  46. 46.
    Angst, F., Aeschlimann, A., & Stucki, G. (2001). Smallest detectable and minimal clinically important differences of rehabilitation intervention with their implications for required sample sizes using WOMAC and SF-36 quality of life measurement instruments in patients with osteoarthritis of the lower extremities. Arthritis Care and Research, 45, 384–91.CrossRefPubMedGoogle Scholar
  47. 47.
    Kosinski, M., Zhao, S. Z., Dedhiya, S., Osterhaus, J. T., & Ware, J.,E. Jr. (2000). Determining minimally important changes in generic and disease-specific health-related quality of life questionnaires in clinical trials of rheumatoid arthritis. Arthritis and Rheumatism 43, 1478–487.CrossRefPubMedGoogle Scholar
  48. 48.
    Ahroni, J. H., & Boyko, E. J. (2000). Responsiveness of the SF-36 among veterans with diabetes mellitus. Journal of Diabetes and its Complications, 14, 31–9.CrossRefPubMedGoogle Scholar
  49. 49.
    Spiegel, B. M., Younossi, Z. M., Hays, R. D., Revicki, D., Robbins, S., & Kanwal, F. (2005). Impact of hepatitis C on health related quality of life: A systematic review and quantitative assessment. Hepatology, 41, 790–00.CrossRefPubMedGoogle Scholar
  50. 50.
    Wiebe, S., Matijevic, S., Eliasziw, M., & Derry, P. A. (2002). Clinically important change in quality of life in epilepsy. Journal of Neurology, Neurosurgery, and Psychiatry 73, 116–20.CrossRefPubMedGoogle Scholar
  51. 51.
    Quintana, J. M., Escobar, A., Bilbao, A., Arostegui, I., Lafuente, I., & Vidaurreta, I. (2005). Responsiveness and clinically important differences for the WOMAC and SF-36 after hip joint replacement. Osteoarthritis and Cartilage, 13, 1076–083.CrossRefPubMedGoogle Scholar
  52. 52.
    Bessette, L., Sangha, O., Kuntz, K. M., Keller, R. B., Lew, R. A., Fossel, A. H., & Katz, J. N. (1998). Comparative responsiveness of generic versus disease-specific and weighted versus unweighted health status measures in carpal tunnel syndrome. Medical Care, 36, 491–02.CrossRefPubMedGoogle Scholar
  53. 53.
    Hawthorne, G., Herrman, H., & Murphy, B. (2006). Interpreting the WHOQOL-Brèf: Preliminary population norms and effect sizes. Social Indicators Research, 77, 37–9.CrossRefGoogle Scholar
  54. 54.
    Hawthorne, G., & Osborne, R. (2005). Population norms and meaningful differences for the Assessment of Quality of Life (AQoL) measure. Australian and New Zealand Journal of Public Health, 29, 136–42.CrossRefPubMedGoogle Scholar
  55. 55.
    ABS (2002). Year Book Australia. Canberra: Australian Bureau of Statistics.Google Scholar

Copyright information

© Springer Science+Business Media B.V. 2007

Authors and Affiliations

  • Graeme Hawthorne
    • 1
  • Richard H. Osborne
    • 2
  • Anne Taylor
    • 3
  • Jan Sansoni
    • 4
  1. 1.Department of Psychiatry, Royal Melbourne HospitalThe University of MelbourneParkvilleAustralia
  2. 2.AFV Centre for Rheumatic Diseases, Department of Medicine, Royal Melbourne HospitalThe University of MelbourneParkvilleAustralia
  3. 3.Population Research & Outcome Studies Unit, Department of HealthAdelaideAustralia
  4. 4.Australian Health Outcomes Collaboration, Centre for Health Services DevelopmentUniversity of WollongongWollongongAustralia

Personalised recommendations