Quality of Life Research

, Volume 11, Issue 1, pp 19–26 | Cite as

A comparison of an electronic version of the SF-36 General Health Questionnaire to the standard paper version

  • Judy M. Ryan
  • John R. Corry
  • Robyn Attewell
  • Michael J. Smithson

Abstract

Because of its sound psychometric properties the SF-36 General Health Questionnaire is used throughout the world, yet it is difficult to analyse and score. Using a newly developed software package, onto which any questionnaire can be loaded, we developed an electronic version of the SF-36 General Health Questionnaire. The purpose of this study is test the effect of the electronic mode of administration on the measurement properties of the SF-36. In a randomised cross-over design study 79 healthy individuals and 36 chronic pain patients completed both electronic and paper versions of the SF-36. Seventy-one percent preferred the electronic SF-36, 7% stated no preference, and 22% preferred the paper version. Completion time for the electronic SF-36 was slightly less, and there were no missing or problematical responses, whereas 44% of participants had at least one missing or problematical response in the paper version. Data entry and auditing time was 8 hours. There was less than 4% inter-version difference for any of the SF-36 sub-scales. The electronic SF-36 was well accepted and slightly quicker to complete than the paper version. We conclude that the electronic SF-36 is equivalent in performance and more effective than the paper version.

Data quality Electronic administration mode SF-36 

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References

  1. 1.
    Lohr KN. Advances in health status assessment. Overview ofthe conference. Med Care 1989; 27(Suppl 3): S1-S11.Google Scholar
  2. 2.
    Drummond HE, et al. Electronic quality of life questionnaires: A comparison ofpen-based electronic questionnaires with conventional paper in a gastrointestinal study. Qual Life Res 1995; 4: 21–26.Google Scholar
  3. 3.
    Pouwer FJ, et al. A comparison ofthe standard and the computerized versions ofthe Well-being Questionnaire (WBQ) and the Diabetics Treatment Satisfaction Questionnaire (DTSQ). Qual Life Res 1998; 7: 33–38.Google Scholar
  4. 4.
    Velikova G, et al. Automated collection ofquality-of-life data: A comparison ofpaper and computer touch-screen questionnaires. J Clin Oncol 1999; 17(3): 998–1007.Google Scholar
  5. 5.
    Bloom DE. Technology, experimentation, and the quality of survey data. Science 1998; 280 (May).Google Scholar
  6. 6.
    Ware JE, et al. SF-36 Health Survey; Manual and Interpretation Guide. Boston: 1993.Google Scholar
  7. 7.
    McHorney CA, Ware JE, Jr, Raczek AE. The MOS 36-item short-form health survey (SF-36): II. Psychometric and clinical tests ofvalidity in measuring physical and mental health constructs. Med Care 1993; 31(3): 247–263.Google Scholar
  8. 8.
    Ware JE, Jr, Sherbourne CD. The MOS 36-item short-form health survey (SF-36). I. Conceptual framework and item selection. Med Care 1992; 30(6): 473–483.Google Scholar
  9. 9.
    Bowling A. Measuring Disease. Philadelphia: Open University Press, 1995.Google Scholar
  10. 10.
    Statistical Package for Social Sciences, Chicago.Google Scholar
  11. 11.
    Burke JD, et al. Test-retest reliability in psychiatric patients ofthe SF-36 Health Survey. Int J Methods Psychiatr Res 1994; 5: 189–194.Google Scholar
  12. 12.
    American PA. Guidlines for Computer Based Tests and Interpretation. 1986.Google Scholar
  13. 13.
    Pocock SJ. Clinical Trials: A Practical Approach. London: Wiley, 1983.Google Scholar
  14. 14.
    Altman D. Some common problems in medical research. In: Armitage P, Berry G (eds), Statistical Methods in Medical Research, Oxford: Blackwell.Google Scholar
  15. 15.
    Brenner H, KU. Dependence of weighted j coefficients on the number of categories. Epidemiology 1995; 7(2): 199–202.Google Scholar
  16. 16.
    Landis JR, Koch GG. The measurement ofobserver agreement for categorical data. Biometrics 1977; 33(1): 159–174.Google Scholar
  17. 17.
    Maitland ME, Mandel AR. A client-computer interface for questionnaire data. Arch Phys Med Rehabil 1994; 75(6): 639–642.Google Scholar

Copyright information

© Kluwer Academic Publishers 2002

Authors and Affiliations

  • Judy M. Ryan
    • 1
  • John R. Corry
    • 2
  • Robyn Attewell
    • 3
  • Michael J. Smithson
    • 1
  1. 1.School of PsychologyAustralian National UniversityAustralia
  2. 2.Occupational Health and Rehabilitation ServicesAustralia
  3. 3.Covance Pty LtdCanberraAustralia

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