Exploratory factor analysis (EFA) remains one of the standard and most widely used methods for demonstrating construct validity of new instruments.
However, the model for EFA makes assumptions which may not be applicable to all quality of life (QOL) instruments, and as a consequence the results from EFA may be misleading.
In particular, EFA assumes that the underlying construct of QOL (and any postulated subscales or « factors ») may be regarded as being reflected by the items in those factors or subscales.
QOL instruments, however, frequently contain items such as diseases, symptoms or treatment side effects, which are « causal indicators ».
These items may cause reduction in QOL for those patients experiencing them, but the reverse relationship need not apply : not all patients with a poor QOL need be experiencing the same set of symtoms.
Thus a high level of a symptom item may imply that a patient's QOL is likely to be poor, but a poor level of QOL need not imply that the patient probably suffers from that symtom.
This is the reverse of the common EFA model, in which it is implicitly assumed that changes in QOL and any subscales « cause » or are likely to be reflected by corresponding changes in all their constituent items ; thus the items in EFA are called « effect indicators ».
Furthermore, disease-related clusters of symptoms, or treatment-induced side-effects, may result in different studies finding different sets of items being highly correlated. (...)
Mots-clés Pascal : Tumeur maligne, Tumeur, Maladie, Poumon, Appareil respiratoire, Anatomie, Analyse donnée
Mots-clés Pascal anglais : Malignant tumor, Tumor, Disease, Lung, Respiratory system, Anatomy, Data analysis
Notice produite par :
ORS Auvergne - Observatoire Régional de la Santé d'Auvergne
Code Inist : 002B30A11. Création : 16/10/1997.