Skip to main content
SpringerLink
Log in

Identifying Optimal Items in Quality of Life Assessment

  • Published:
Quality & Quantity Aims and scope Submit manuscript

Abstract

Quality of life has drawn increasing attention in health science and more efforts have been devoted to develop instruments that are valid and reliable to assess quality of life. The World Health Organization (WHO) has devised an instrument World Health Organization Quality of Life Survey- Abbreviated Version (WHOQOL-BREF) to assess quality of life, but the psychometric property of each individual item has not been studied yet. Using item response theory, we examine the properties of the WHOQOL-BRIEF Taiwan version. Samejima’s graded response model was fitted, and item parameters were calculated. The items were ranked base on their discrimination power, and the best items are identified. Several data with subset of items (22, 20, 18, 16 and 14 items) were created by omitting items with lower discrimination power. The test information function of the full questionnaire and the subsets were compared. The results showed there were significant positive correlations between the full questionnaire and the subsets of items and the distributions are similar. The test information function showed the maximum amount of test information spaced over two ends of the theta continuum, and this suggested that the WHOQOL-BREF provided more information for groups with either lower or higher satisfaction of quality of life, while it is less discriminating for individuals in the middle range.

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

Access this article

Log in via an institution

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

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  • Baker F.B. (1992). Item Response Theory: Parameter Estimation Techniques. M. Dekker, New York

    Google Scholar 

  • Bock R.D., Aitken M. (1981). Marginal maximum likelihood estimation of item parameters: application of an EM algorithm. Psychometrika 46: 443–445

    Article  Google Scholar 

  • 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

    Article  PubMed  Google Scholar 

  • DeGirolamo G., Rucci P., Scocco P., Becchi A., Coppa F., D’Addario A., Daru E., De Leo D., Galassi L., Mangelli L., Marson C., Neri G., Soldani L. (2000). Quality of life assessment: validation of the Italian version of the WHOQOL-Brief. Epidemiology Psichiatry Society 9: 45–55

    Google Scholar 

  • DeLeeuw J., Verhelst N. (1986). Maximum likelihood estimation in generalized Rasch models. Journal of Educational Statistics 11: 183–196

    Article  Google Scholar 

  • Dempster A.P., Laird N.M., Rubin D.B. (1977). Maximum likelihood from incomplete data via the EM algorithm (with discussion). Journal of the Royal Statistical Society, Series B 39: 1–38

    Google Scholar 

  • Hambleton R.K., Swaminathan H., Rogers H.J. (1991). Fundamentals of Item Response Theory. Sage, Newbury Park, CA

    Google Scholar 

  • Herche J., Engelland B. (1996). Reversed-polarity items and scale uni-dimensionality. Journal of the Academy of Marketing Science 24: 366–374

    Article  Google Scholar 

  • Holland P.W. (1990). On the sampling theory foundations of item response theory models. Psychometrika 55: 577–601

    Article  MathSciNet  Google Scholar 

  • 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

    Article  PubMed  Google Scholar 

  • Muraki E., Bock R.D. (1996). PARSCALE: IRT based Test Scoring and Item Analysis for Graded Open-ended Exercises and Performance Tasks, Version 3. Scientific Software International Inc, Chicago

    Google Scholar 

  • Norholm V., Bech P. (2001). The WHO Quality of Life (WHOQOL) Questionnaire: Danish validation study. Nordic Journal of Psychiatry 55: 229–235

    Article  PubMed  Google Scholar 

  • Samejima F. (1967). Estimation of latent ability using a response pattern of graded scores. Psychometrika Monograph Supplement 34: 100–114

    Google Scholar 

  • Skevington S.M., Bradshawa J., Saxenab S. (1999). Selecting national items for the WHOQOL: conceptual and psychometric considerations. Social Science and Medicine 48: 473–487

    Article  PubMed  Google Scholar 

  • Thissen D. (1981). MULTILOGTM User’s Guide. Multiple Categorical Item Analysis and Test Scoring Using Item Response Theory, Version 6.0. Scientific Software, Chicago, Illinois

    Google Scholar 

  • World Health Organization (1993). WHOQOL Study Protocol. WHO, Geneva, (MNH/PSF/93.9)

    Google Scholar 

  • World Health Organization (1994). WHOQOL Protocol for New Centers. WHO, Geneva

    Google Scholar 

  • 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

    PubMed  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Statistics, National Taipei University, 67, Section 3, Ming-Sheng East Road, Taipei, 10433, Taiwan, ROC

    Ting Hsiang Lin

Authors
  1. Ting Hsiang Lin
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Ting Hsiang Lin.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Lin, T.H. Identifying Optimal Items in Quality of Life Assessment. Qual Quant 41, 661–672 (2007). https://doi.org/10.1007/s11135-006-9017-7

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11135-006-9017-7

Keywords

Search

Navigation