Quality of life in the Danish general population--normative data and validity of WHOQOL-BREF using Rasch and item response theory models

Qual Life Res. 2004 Mar;13(2):531-40. doi: 10.1023/B:QURE.0000018485.05372.d6.


Background: The main objective of this study was to investigate the construct validity of the WHOQOL-BREF by use of Rasch and Item Response Theory models and to examine the stability of the model across high/low scoring individuals, gender, education, and depressive illness. Furthermore, the objective of the study was to estimate the reference data for the quality of life questionnaire WHOQOL-BREF in the general Danish population and in subgroups defined by age, gender, and education.

Methods: Mail-out-mail-back questionnaires were sent to a randomly selected sample of the Danish general population. The response rate was 68.5%, and the sample reported here contained 1101 respondents: 578 women and 519 men (four respondents did not indicate their genders).

Results: Each of the four domains of the WHOQOL-BREF scale fitted a two-parameter IRT model, but did not fit the Rasch model. Due to multidimensionality, the total score of 26 items fitted neither model. Regression analysis was carried out, showing a level of explained variance of between 10 and 14%. The mean scores of the WHOQOL-BREF are reported as normative data for the general Danish population.

Conclusion: The profile of the four WHOQOL-BREF domains is a more adequate expression of quality of life than the total score of all 26 items. Although none of the subscales are statistically sufficient measures of their domains, the profile scores seem to be adequate approximations to the optimal score.

Publication types

  • Research Support, Non-U.S. Gov't
  • Validation Study

MeSH terms

  • Adult
  • Age Factors
  • Aged
  • Attitude to Health*
  • Denmark
  • Educational Status
  • Female
  • Health Status Indicators*
  • Humans
  • Male
  • Mental Disorders / psychology
  • Middle Aged
  • Psychometrics / instrumentation*
  • Quality of Life*
  • Registries
  • Regression Analysis
  • Sex Factors
  • Surveys and Questionnaires
  • World Health Organization