Skip to main content
Log in

Psychometric properties of the RAND-36 among three chronic disease (multiple sclerosis, rheumatic diseases and COPD) in the Netherlands

  • Published:
Quality of Life Research Aims and scope Submit manuscript

Abstract

Objective: In this article, psychometric properties both of the total RAND-36 and of its subscales, such as unidimensionality, differential item functioning (DIF or item bias), homogeneity and reliabilities, are examined. Methods: The data from populations with three chronic illnesses, multiple sclerosis (n = 448), rheumatism (n = 336) and COPD (n = 259), have been collected in different parts of the Netherlands. The main technique used was Mokken scale analysis for polytomous items. Results: All subscales of the RAND-36 appeared to be unidimensional. For the sub scales ‘mental health’ and ‘general health perceptions’ some minor indications of DIF for the different chronic illnesses were found. Reliabilities of almost all subscales in all subpopulations were higher than 0.80, while the homogeneities of almost all subscales in all subpopulations were higher than 0.50, indicating ‘strong unidimensional, hierarchical scales’. Conclusions: In general, the subscales of the RAND-36 can be used to compare persons with different chronic illnesses. The subscale ‘general health perceptions’ did not function as well as would be preferred.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  1. Ware JE Jr, Sherbourne CD. The MOS 36–item short-from health survey (SF-36) I. Conceptual framework and item selection. Med Care 1992; 30: 473–483.

    PubMed  Google Scholar 

  2. McHorney CA, Ware JE Jr, Raczek AE. The MOS 36–item short-form health survey (SF-36) II. Psychometric and clinical tests of validity in measuring physical and mental health constructs. Med Care 1993; 31(3): 247–263.

    PubMed  CAS  Google Scholar 

  3. McHorney CA, Ware JE Jr, Rachel Lu JF, Sherbourne CD. The MOS 36–item short-form health survey (SF-36) III. Tests of data quality, scaling assumptions, and reliability across diverse patient groups. Med Care 1994; 32(1): 40–66.

    PubMed  CAS  Google Scholar 

  4. Hays RD, Sherbourne CD, Mazel RM. The RAND 36–item health survey 1.0. Health Economics 1993; 2: 217–227.

    PubMed  CAS  Google Scholar 

  5. Aaronson NK, Acquandro C, Alonso J, et al. International quality of life assessment (IQOLA) project. Qual Life Res 1992; 1: 349–351.

    Article  PubMed  CAS  Google Scholar 

  6. Ware JE Jr, Gandek B. Overview of the SF-36 health survey and the international quality of life assessment (IQOLA) project. J Clin Epidemiol 1998; 51(11): 903–912.

    Article  PubMed  Google Scholar 

  7. Ware JE Jr, Gandek B. Methods for testing data quality, scaling assumptions, and reliability: The IQOLA project approach. J Clin Epidemiol 1998; 51(11): 945–952.

    Article  PubMed  Google Scholar 

  8. Gandek B, Ware JE Jr, Aaronson NK, et al. Tests of data quality, scaling assumptions, and reliability of the SF-36 in eleven countries: Results from the IQOLA Project. J Clin Epidemiol 1998; 51(11): 1149–1158.

    Article  PubMed  CAS  Google Scholar 

  9. Sullivan M, Karlsson J, Ware JE Jr. The Swedish SF-36 Health Survey-I. Evaluation of data quality, scaling assumptions, reliability and construct validity across general populations in Sweden. Soc Sci Med 1995; 41: 1349–1358.

    Article  PubMed  CAS  Google Scholar 

  10. Bullinger M. German translation and psychometric testing of the SF-36 health survey: Preliminary results from the IQOLA project. Soc Sci Med 1995; 41(10): 1359–1366.

    Article  PubMed  CAS  Google Scholar 

  11. Lewin-Epstein N, Sagiv-Schifter T, Shabtai EL, Shmueli A. Validation of the 36–item short form health survey (Hebrew version) in the adult population of Israel. Med Care 1998; 36: 1361–1370.

    Article  PubMed  CAS  Google Scholar 

  12. Razavi D, Gandek B. Testing Dutch and French translations of the SF-36 health survey among Belgian Angina patients. J Clin Epidemiol 1998; 51(11): 975–981.

    Article  PubMed  CAS  Google Scholar 

  13. Bjorner JB, Damsgaard MT, Watt T, Groenvold M. Tests of data quality, scaling assumptions, and reliability of the Danish SF-36. J Clin Epidemiol 1998; 51(11): 1000–1011.

    Google Scholar 

  14. Leplège A, Ecosse E, Verdier A, Perneger TV. The French SF-36 health survey: Translation, cultural adaptation and preliminary psychometric evaluation. J Clin Epidemiol 1998; 51(11): 1013–1023.

    Article  PubMed  Google Scholar 

  15. Apolone G, Mosconi P. The Italian SF-36 Health Survey: Translation, validation and norming. J Clin Epidemiol 1998; 51(11): 1025–1036.

    Article  PubMed  CAS  Google Scholar 

  16. Fukuhara S, Ware JE Jr, Kosinski M, Wada S, Gandek B. Psychometric and clinical tests of validity of the Japanese health survey. J Clin Epidemiol 1998; 51(11): 1045–1053.

    Article  PubMed  CAS  Google Scholar 

  17. Aaronson NK, Muller M, Cohen PDA, et al. Translation, validation, and norming or the Dutch language version of the SF-36 Health Survey in community and chronic disease populations. J Clin Epidemiol 1998; 51(11): 1055–1068.

    Article  PubMed  CAS  Google Scholar 

  18. Bjorner JB, Kreiner S, Ware JE Jr, Damsgaard MT, Bech P. Differential item functioning in the Danish translation of the SF-36. J Clin Epidemiol 1998; 51(11): 1189–1202.

    Article  PubMed  CAS  Google Scholar 

  19. Green SB, Lissitz RW, Mulaik SA. Limitations of coefficient Alpha as an index of test unidimensionality. Educ Psychol Measur 1977; 37: 827–838.

    Google Scholar 

  20. Miller MB. Coefficient alpha: A basic introduction from the perspectives of classical test theory and structural equation modelling. Structural Equation Modeling 1995; 2: 255–273.

    Article  Google Scholar 

  21. Niemoller K, Van Schuur W. Stochastic models for unidimensional scaling: Mokken and Rasch. In: McKay D, Schofield N, Whiteley P (eds), Data Analysis and the Social Sciences, London: Frances Pinter, 1983; 120–170.

    Google Scholar 

  22. Molenaar IW, Sijtsma K. MSP5 for Windows, A program for Mokken Scale Analysis for Polytomous Items, version 5.0 (User's manual) Groningen, The Netherlands: iecProGAMMA, 2000.

    Google Scholar 

  23. Molenaar IW. Nonparametric models for polytomous responses. In: Van de Linden WJ, Hambleton RK (eds), Handbook of Modern Item Response Theory, New York: Springer Verlag, 1997; 369–380.

    Google Scholar 

  24. Van der Zee K, Sanderman R. Het meten van de algemene gezondheidstoestand met de RAND-36: een handleiding. [The measument of the general health situation with the RAND-36: A manual]. Northern Centre for Health Care, University of Groningen, 1993.

  25. Grayson DA. Two-group classification in latent trait theory: Scores with monotone likelihood ratio. Psychometrika 1988; 53: 383–392.

    Article  Google Scholar 

  26. Hemker BA, Sijtsma K. Selection of unidimensional scales from a multidimensional item bank in the polytomous Mokken IRT model. Appl Psychol Measur 1995; 19(4): 337–352.

    Google Scholar 

  27. Ware JE Jr, Keller SD, Gandek B, et al. Evaluating translations of health status questionnaires. Methods from the IQOLA project. Int J Technol Assess Health Care 1995; 11: 525–551.

    Article  PubMed  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Rights and permissions

Reprints and permissions

About this article

Cite this article

Moorer, P., Suurmeijer, T., Foets, M. et al. Psychometric properties of the RAND-36 among three chronic disease (multiple sclerosis, rheumatic diseases and COPD) in the Netherlands. Qual Life Res 10, 637–645 (2001). https://doi.org/10.1023/A:1013131617125

Download citation

  • Issue Date:

  • DOI: https://doi.org/10.1023/A:1013131617125

Navigation