Advertisement

Social Indicators Research

, Volume 91, Issue 2, pp 141–153 | Cite as

Evaluating Item Discrimination Power of WHOQOL-BREF from an Item Response Model Perspectives

  • Ting Hsiang Lin
  • Grace Yao
Article

Abstract

Quality of life (QOL) has become an important component of health. By using the methodology of psychometric theory, we examine the item properties of the WHOQOL-BRIEF. Samejima’s graded response model with natural metrics of the logistic response function was fitted. The results showed items with negative natures were less discriminating. Items written in a specific way were more suitable to assess certain subgroups. The national items showed variation in discriminatory power. Questions measuring objective and specific issues performed worse than items assessing general aspects of the QOL.

Keywords

WHOQOL-BREF Item response theory Item analysis Quality of life 

Notes

Acknowledgements

The authors thank Bureau of Health Promotion, Department of Health and National Health Research Institute in Taiwan, for providing the data.

References

  1. Allalouf, A., Hambleton, R. K., & Sireci, S. G. (1999). Identifying the causes of DIF in translated verbal items. Journal of Educational Measurement, 36, 185–198. doi: 10.1111/j.1745-3984.1999.tb00553.x.CrossRefGoogle Scholar
  2. Bock, R. D., Gibbons, R., Schilling, S. G., Muraki, E., Wilson, D. T., & Wood, R. (2003). TESTFACT 4.0 [Computer software and manual]. Lincolnwood, IL: Scientific Software International.Google Scholar
  3. Bonomi, A. E., Patrick, D. L., Bushnell, D. M., & Martin, M. (2000). Validation of the United States’ version of the World Health Organization Quality of Life (WHOQOL) instrument. Journal of Clinical Epidemiology, 53, 1–12. doi: 10.1016/S0895-4356(99)00123-7.CrossRefGoogle Scholar
  4. Camilli, G. (1992). A conceptual analysis of differential item functioning in terms of a multidimensional item response model. Applied Psychological Measurement, 16, 129–147. doi: 10.1177/014662169201600203.CrossRefGoogle Scholar
  5. Cole, N. S., & Moss, P. A. (1989). Bias in test use. In R. L. Linn (Ed.), Educational measurement (3rd ed.). New York: American Council on Education.Google Scholar
  6. DeGirolamo, G., Rucci, P., Scocco, P., Becchi, A., Coppa, F., D’Addario, A., et al. (2000). Quality of life assessment: Validation of the Italian version of the WHOQOL-Brief. Epidemiologia e Psichiatria Sociale, 9, 45–55.Google Scholar
  7. Drasgow, F., & Lissak, R. I. (1983). Modified parallel analysis: A procedure for examining the latent dimensionality of dichotomously scored item responses. The Journal of Applied Psychology, 68, 363–373. doi: 10.1037/0021-9010.68.3.363.CrossRefGoogle Scholar
  8. Embretson, S. E., & Reise, S. P. (2000). Item response theory for psychologists. Mahwah, NJ: Lawrence Erlbaum Associates.Google Scholar
  9. Fraser, C. (1988). NOHARM: An IBM PC computer program for fitting both unidimensional and multidimensional normal ogive models of latent trait theory. Armidale, Australia: The University of New England.Google Scholar
  10. Hambleton, R. K., Swaminathan, H., & Rogers, H. J. (1991). Fundamentals of item response theory. Newbury Park, CA: Sage.Google Scholar
  11. Herche, J., & Engelland, B. (1996). Reversed-polarity items and scale unidimensionality. Journal of the Academy of Marketing Science, 24, 366–374. doi: 10.1177/0092070396244007.CrossRefGoogle Scholar
  12. Holland, P. W. (1990). On the sampling theory foundations of item response theory models. Psychometrika, 55, 577–601. doi: 10.1007/BF02294609.CrossRefGoogle Scholar
  13. Holland, P. W., & Thayer, D. T. (1988). Differential item functioning and the Mantel-Haenszel procedure. In H. Wainer & H. I. Braun (Eds.), Test validity. Hillsdale, NJ: Lawrence Erlbaum.Google Scholar
  14. Kim, S. H., Cohen, A. S., & Park, T. H. (1995). Detection of differential item functioning in multiple groups. Journal of Educational Measurement, 32, 261–276. doi: 10.1111/j.1745-3984.1995.tb00466.x.CrossRefGoogle Scholar
  15. Kristjansson, E. A., Desrochers, A., & Zumbo, B. D. (2003). Translating and adapting measurement instruments for cross-cultural research: A guide for practitioners. Canadian Journal of Nursing Research, 35, 127–142.Google Scholar
  16. Lord, F. M. (1980). Applications of item response theory to practical testing problems. Lawrence Erlbaum: Hillsdale.Google Scholar
  17. Lord, F. M., & Novick, M. R. (1968). Statistical theories of mental test scores (with contributions by A. Birnbaum). Reading, MA: Addison-Wesley.Google Scholar
  18. McDonald, R. P. (1967). Nonlinear factor analysis. Psychometric monographs, no. 15.Google Scholar
  19. McDonald, R. P. (1997). Normal-ogive multidimensional model. In W. J. van der Linden & R. K. Hambleton (Eds.), Handbook of modern item response theory. New York: Springer.Google Scholar
  20. McDonald, R. P. (1999). Test theory: A unified treatment. Mahwah, NJ: Erlbaum.Google Scholar
  21. Min, S. K., Kim, K. I., Lee, C. I., Jung, Y. C., Suh, S. Y., & Kim, D. K. (2002). Development of the Korean versions of WHO quality of life scale and WHOQOL-BREF. Quality of Life Research, 11, 593–600. doi: 10.1023/A:1016351406336.CrossRefGoogle Scholar
  22. Muraki, E., & Bock, R. D. (1996). PARSCALE: IRT based test scoring and item analysis for graded open-ended exercises and performance tasks. Version 3. Chicago: Scientific Software International Inc.Google Scholar
  23. Norholm, V., & Bech, P. (2001). The WHO Quality of Life (WHOQOL) questionnaire: Danish validation study. Nordic Journal of Psychiatry, 55, 229–235. doi: 10.1080/080394801681019075.CrossRefGoogle Scholar
  24. Roskam, E. E. (1985). Current issues in item response theory. In E. E. Roskam (Ed.), Measurement and personality assessment (pp. 3–19). Amsteerdam: North Holland.Google Scholar
  25. Samejima, F. (1967). Estimation of latent ability using a response pattern of graded scores. Psychometrika Monograph, 34(Supplement), 100–114.Google Scholar
  26. Skevington, S. M., Bradshawa, J., & Saxenab, S. (1999). Selecting national items for the WHOQOL: Conceptual and psychometric considerations. Social Science & Medicine, 48, 473–487. doi: 10.1016/S0277-9536(98)00355-4.CrossRefGoogle Scholar
  27. Stout, W. (1987). A nonparametric approach for assessing latent trait unidimensionality. Psychometrika, 52, 589–617. doi: 10.1007/BF02294821.CrossRefGoogle Scholar
  28. van der Linden, W. J., & Hambleton, R. K. (1996). Handbook of modern item response theory. New York: Springer.Google Scholar
  29. World Health Organization. (1980). International classification of impairments, disabilities and handicaps. Geneva: WHO.Google Scholar
  30. World Health Organization. (1993). WHOQOL study protocol. Geneva: WHO (MNH/PSF/93.9).Google Scholar
  31. World Health Organization. (1994). WHOQOL protocol for new centers. Geneva: WHO (MNH/PSF/94.4).Google Scholar
  32. Wu, A. D., & Zumbo, B. D. (2007). Thinking about item response theory from a logistic regression perspective: A focus on polytomous models. In S. S. Sawilowsky (Ed.), Real data analysis. AERA, Educational Statisicians Book Series (pp. 241–269). Greenwich, CT: Information Age Publishing, Inc.Google Scholar
  33. Yao, G., Chung, C. W., Yu, C. F., & Wang, J. D. (2002). Development and verification of validity and reliability of the WHOQOL-BREF Taiwan version. Journal of the Formosan Medical Association, 101, 342–351.Google Scholar
  34. Zumbo, B. D. (2007). Three generations of differential item functioning (DIF) analyses: Considering where it has been, where it is now, and where it is going. Language Assessment Quarterly, 4, 223–233.Google Scholar
  35. Zumbo, B. D., Pope, G. A., Watson, J. E., & Hubley, A. M. (1997). An empirical test of Roskam's conjecture about the interpretation of an ICC parameter in personality inventories. Educational and Psychological Measurement, 57, 963–969.CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media B.V. 2008

Authors and Affiliations

  1. 1.Department of StatisticsNational Taipei UniversityTaipeiTaiwan, ROC
  2. 2.National Taiwan UniversityTaipeiTaiwan, ROC

Personalised recommendations