Quality of Life Research

, Volume 6, Issue 5, pp 393–406 | Cite as

Causal indicators in quality of life research

  • P. M. Fayers
  • D. J. Hand
  • K. Bjordal
  • M. Groenvold


Quality of Life (QOL) questionnaires contain two different types of items. Some items, such as assessments of symptoms of disease, may be called causal indicators because the occurrence of these symptoms can cause a change in QOL. A severe state of even a single symptom may suffice to cause impairment of QOL, although a poor QOL need not necessarily imply that a patient suffers from all the symptoms. Other items, for example anxiety and depression, can be regarded as effect indicators which reflect the level of QOL. These indicators usually have a more uniform relationship with QOL, and therefore a patient with poor QOL is likely to have low scores on all effect indicators. In extreme cases it may seem intuitively obvious which items are causal and which are effect indicators, but often it is less clear. We propose a model which includes these two types of indicators and show that they behave in markedly different ways. Formal quantitative methods are developed for distinguishing them. We also discuss the impact of this distinction upon instrument validation and the design and analysis of summary subscales.

Quality of life instruments construct validity multi-item scales composite scales causal indicators 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Fayers PM, Hand D. Factor analysis, causal indicators, and quality of life. Qual Life Res 1997; 6: 139–150.Google Scholar
  2. 2.
    Feinstein AR. Clinimetrics. New Haven: Yale University Press, 1987.Google Scholar
  3. 3.
    Zigmond AS, Snaith RP. The Hospital Anxiety and Depression Scale. Acta Psychiatr Scand 1983; 67: 361–370.Google Scholar
  4. 4.
    Aaronson NK, Bakker W, Stewart AL, et al. Multidimensional approach to the measurement of quality of life in lung cancer clinical trials. In: Aaronson NK, Beckmann J, eds. The Quality of Life of Cancer Patients. New York: Raven Press, 1987:63–82.Google Scholar
  5. 5.
    Fitzpatrick R, Fletcher A, Gore S et al. Quality of life measures in health care. I: Applications and issues in assessment. BMJ 1992; 305: 1074–1077.Google Scholar
  6. 6.
    Bollen KA. Structural Equations with Latent Variables. New York: J Wiley & Sons, 1989.Google Scholar
  7. 7.
    MacCallum RC, Wegener DT, Uchino BN, Fabrigar LR. The problem of equivalent models in applications of covariance structure-analysis. Psychol Bull 1993; 114: 185–299.Google Scholar
  8. 8.
    Hume D. A Treatise of Human Nature []. New York: Dutton, 1976.Google Scholar
  9. 9.
    Rothman KJ. Causes. Am J Epidemiol 1976; 104: 587–592.Google Scholar
  10. 10.
    Aaronson NK, Ahmedzai S, Bergman B, et al. The European Organization for Research and Treatment of Cancer QLQ-C30: a quality-of-life instrument for use in international clinical trials in oncology. J Natl Cancer Inst 1993; 85: 365–376.Google Scholar
  11. 11.
    Fayers PM, Aaronson NK, Bjordal K, Sullivan M. EORTC QLQ-C30 Scoring Manual. Brussels: EORTC, 1995.Google Scholar
  12. 12.
    Bjordal K. Quality of Life in Patients Treated for Head and Neck Cancer: Methodological and Clinical Issues. Oslo: University of Oslo, 1996.Google Scholar
  13. 13.
    Spector PE. Summated Rating Scale Construction: An Introduction. London: Sage Publications Ltd, 1992.Google Scholar
  14. 14.
    Fletcher A, Gore S, Jones D et al. Quality of life measures in health care. II: Design, analysis, and interpretation. BMJ 1992; 305: 1145–1148.Google Scholar
  15. 15.
    de Haes JCJM, Olschewski M, Fayers PM et al. The Rotterdam Symptom Checklist (RSCL): A Manual. Groningen: Northern Centre for Healthcare Research, 1996.Google Scholar
  16. 16.
    Agresti A. Modelling patterns of agreement and disagreement. Stat Methods Med Res 1992; 1: 201–218.Google Scholar
  17. 17.
    Agresti A, Lang JB. Quasi-symmetrical latent class models, with application to rater agreement. Biometrics 1993; 49: 131–139.Google Scholar
  18. 18.
    Stasny EA, Bauer HR. Symmetry and quasi-symmetry: an example in modelling pairs of sounds from children's early speech. Stat Med 1990; 9: 1143–1155.Google Scholar
  19. 19.
    Nunnally JC, Bernstein IH. Psychometric Theory, 3rd edn. New York: McGraw-Hill, 1994.Google Scholar

Copyright information

© Chapman and Hall 1997

Authors and Affiliations

  • P. M. Fayers
    • 1
    • 2
  • D. J. Hand
    • 3
  • K. Bjordal
    • 4
  • M. Groenvold
    • 5
  1. 1.Unit for Epidemiology and Clinical Research, Faculty of MedicineNorwegian University of Science and TechnologyTrondheimNorway
  2. 2.Cancer Trials OfficeMedical Research CouncilCambridgeUK
  3. 3.Department of StatisticsOpen UniversityMilton KeynesUK
  4. 4.Department of OncologyTrondheim University HospitalNorway
  5. 5.Department of Health Services ResearchUniversity of CopenhagenDenmark

Personalised recommendations