An application of structural equation modeling to detect response shifts and true change in quality of life data from cancer patients undergoing invasive surgery

Abstract

The objective is to show how structural equation modeling can be used to detect reconceptualization, reprioritization, and recalibration response shifts in quality of life data from cancer patients undergoing invasive surgery. A consecutive series of 170 newly diagnosed cancer patients, heterogeneous to cancer site, were included. Patients were administered the SF-36 and a short version of the multidimensional fatigue inventory prior to surgery, and 3 months following surgery. Indications of response shift effects were found for five SF-36 scales: reconceptualization of 'general health', reprioritization of 'social functioning', and recalibration of 'role-physical', 'bodily pain', and 'vitality'. Accounting for these response shifts, we found deteriorated physical health, deteriorated general fitness, and improved mental health. The sizes of the response shift effects on observed change were only small. Yet, accounting for the recalibration response shifts did change the estimate of true change in physical health from medium to large. The structural equation modeling approach was found to be useful in detecting response shift effects. The extent to which the procedure is guided by subjective decisions is discussed.