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.
Similar content being viewed by others
References
Ware, J., & Gandek, B. for the IQOLA Project (1998). Overview of the SF-36 Health Survey and the International Quality of Life Assessment (IQOLA) Project. Journal of Clinical Epidemiology, 51(11), 903–912.
Taft, C., Karlsson, J., & Sullivan, M. (2001). Do SF-36 summary component scores accurately summarize subscale scores? Quality of Life Research, 10(5), 395–404.
Ware, J., Kosinski, M., & Keller, S. (1994). SF-36 physical and mental health summary scales: A user manual. Boston, Massachusetts: The Health Institute, New England Medical Center.
Ware, J. (2004). SF-36 Health Survey Update. Retrieved February 17, 2004, from SF-36.org Web site: http://www.sf-36.org/tools/sf36.shtml.
Kiecolt-Glaser, J., McGuire, L., Robles, T., & Glaser, R. (2002). Psychoneuroimmunology and psychosomatic medicine: Back to the future. Psychosomatic Medicine, 64(1), 15–28.
Schattner, A. (2003). The emotional dimension and the biological paradigm of illness: time for a change. Quarterly Journal of Medicine, 96(9), 617–621.
Kiecolt-Glaser, J., McGuire, L., Robles, T., & Glaser, R. (2002). Emotions, morbidity, and mortality: New perspectives from psychoneuroimmunology. Annual Review of Psychology, 53, 83–107.
Polatin, P., Kinney, R., Gatchel, R., Lillo, E., & Mayer, T. (1993). Psychiatric illness and chronic low-back pain. The mind and the spine—which goes first? Spine, 18(1), 66–71.
Dersh, J., Polatin, P., & Gatchel, R. (2002). Chronic pain and psychopathology: Research findings and theoretical considerations. Psychosomatic Medicine, 64(5), 773–786.
Ware, J., Kosinski, M., Gandek, B., Aaronson, N., Apolone, G., Bech, P., Brazier, J., Bullinger, M., Kaasa, S., Leplège, A., Prieto, L., & Sullivan, M. (1998). The factor structure of the SF-36 health survey in 10 countries: Results from the IQOLA project. Journal of Clinical Epidemiology, 51(11), 1,159–1,165.
Ware, J., & Kosinski, M. (2001). Interpreting SF-36 summary health measures: A response. Quality of Life Research, 10(5), 405–413.
Ware, J., & Kosinski, M. Interpreting SF-36 summary health measures: A response —Supplemental documentation. Retrieved from SF-36.org Web site: http://www.sf-36.org/news/responsetotaft.pdf.
Thumboo, J., Fong, K.Y., Machin, D., Chan, S.P., Leong, K.H., Feng, P.H., Thio, S.T., & Boey, M.L. (2001). A community-based study of scaling assumptions and construct validity of the English (UK) and Chinese (HK) SF-36 in Singapore. Quality of Life Research, 10(2), 175–188.
Gandek, B., Sinclair, S., Kosinski, M., & Ware, J. (2004). Psychometric Evaluation of the SF-36 Health Survey in Medicare Managed Care. Health Care Financing Review, 25(4), 5–25.
Jenkinson, C., Layte, R., & Lawrence, K. (1997). Development and testing of the Medical Outcomes Study 36-item short form health survey summary scale scores in the United Kingdom: results from a large-scale survey and a clinical trial. Medical Care, 35(4), 410–416.
Keller, S., Ware, J., Bentler, P., Aaronson, N., Alonso, J., Apolone, G., Bjorner, J., Bullinger, M., Kaasa, S., Leplège, A., Sullivan, M., & Gandek, B. (1998). Use of structural equation modelling to test the construct validity of the SF-36 health survey in ten countries: Results from the IQOLA project. Journal of Clinical Epidemiology, 51(11), 1179–1188.
Peek, M.K., Ray, L., Patel, K., Stoebner-May, D., & Ottenbacher, K. (2004). Reliability and validity of the SF-36 among older Mexican Americans. The Gerontologist, 44(3), 418–425.
Hobart, J., Freeman, J., Lamping, D., Fitzpatrick, R., & Thompson, A. (2001). The SF-36 in multiple sclerosis: Why basic assumptions must be tested. Journal of Neurology, Neurosurgery and Psychiatry, 71(3), 363–370.
Hobart, J., Williams, L., Moran, K., & Thompson, A. (2002). Quality of life measurement after stroke: Uses and abuses of the SF-36. Stroke, 33(5), 1348–1356.
Nortvedt, M., Riise, T., Myhr, K-M., & Nyland, H. (2000). Performance of the SF-36, SF-12, and RAND-36 summary scales in a multiple sclerosis population. Medical Care, 38(10), 1,022–1,028.
Farivar, S., Cunningham, W., & Hays, R. (2007). Correlated physical and mental health summary scores for the SF-36 and SF-12 Health Survey, V.1. Health and Quality of Life Outcomes, 5, 54.
Simon, G., Revicki, D., Grothaus, L., & Vonkorff, M. (1998). SF-36 Summary scores—Are physical and mental health truly distinct? Medical Care, 36(4), 567–572.
Anagnostopoulos, F., Niakas, D., & Pappa, E. (2005). Construct validation of the Greek SF-36 health survey. Quality of Life Research, 14(8), 1959–1965.
Guthlin, C., & Walach, H. (2007). MOS SF-36: Structural equation modelling to test the construct validity of the second-order factor structure. European Journal of Psychological Assessment, 23(1), 15–23.
Hurst, N., Ruta, D., & 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(8), 862–869.
Taft, C., Karlsson, J., & Sullivan, M. (2001). Interpreting SF-36 summary health measures: A response—Reply. Quality of Life Research, 10(5), 415–420.
Joint Health Surveys Unit of Social and Community Planning Research and University College London (2001). Health Survey for England 1996 [computer file]. (3rd ed.). Colchester, Essex: UK Data Archive [distributor], SN: 3886.
National Assembly for Wales (2000). Welsh Health Survey 1998 [computer file]. Colchester, Essex: UK Data Archive [distributor], SN: 4176.
Gribbons, B., & Hocevar, D. (1998). Levels of aggregation in higher level confirmatory factor analysis: Application for academic self-concept. Structural Equation Modeling, 5(4), 377–390.
Bentler, P. (1995). EQS structural equations program manual. Encino, CA: Multivariate Software, Inc.
Satorra, A., & Bentler, P. (2001). A scaled difference chi-square test statistic for moment structure analysis. Psychometrika, 66(4), 507–514.
Bentler, P., & Wu, E. (1995). EQS for Windows user’s guide. Encino, CA: Multivariate Software, Inc.
Nunnally, J., & Durham, R. (1975). Validity, reliability, and special problems of measurement in evaluation research. In: E. Struening, &M. Guttentag (Eds.), Handbook of Evaluation Research—Volume 1. (pp. 289–354). Beverly Hills/London: Sage Publications.
Hu, L-T., & Bentler, P. (1998). Fit indices in covariance structure modeling: Sensitivity to underparameterized model misspecification. Psychological Methods, 3(4), 424–453.
Norman, G., Sloan, J., & Wyrwich, K. (2004). The truly remarkable universality of half a standard deviation: Confirmation through another look. Expert Review of Pharmacoeconomics & Outcomes Research, 4(5), 581–585.
Farivar, S., Liu, H., & Hays, R. (2004). Half standard deviation estimate of the minimally important difference in HRQOL scores? Expert Review of Pharmacoeconomics & Outcomes Research, 4(5), 515–523.
Samsa, G., Edelman, D., Rothman, M., Williams, G., Lipscomb J., & Matchar, D. (1999). Determining clinically important differences in health status measures: A general approach with illustration to the health utilities index mark II. Pharmacoeconomics, 15(2), 141–155.
Schmitz, N., & Kruse, J. (2007). The SF-36 summary scores and their relation to mental disorders: Physical functioning may affect performance of the summary scores. Journal of Clinical Epidemiology, 60(2), 163–170.
Acknowledgements
The National Primary Care Research and Development Centre (NPCRDC) receives funding from the UK Department of Health (DoH). The views expressed are those of the authors, not the DoH. The authors would like to thank the UK Data Archive at the University of Essex for providing the Health Survey for England 1996 and the Welsh Health Survey 1998, and Diane Whalley at NPCRDC for her advice in the early stages of this work.
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Hann, M., Reeves, D. The SF-36 scales are not accurately summarised by independent physical and mental component scores. Qual Life Res 17, 413–423 (2008). https://doi.org/10.1007/s11136-008-9310-0
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11136-008-9310-0