Structural equation modeling-based effect-size indices were used to evaluate and interpret the impact of response shift effects

Abstract

Objectives: The investigation of response shift in patient-reported outcomes (PROs) is important in both clinical practice and research. Insight into the presence and strength of response shift effects is necessary for a valid interpretation of change.

Study design and setting: When response shift is investigated through structural equation modeling (SEM), observed change can be decomposed into change because of recalibration response shift, change because of reprioritization and/or reconceptualization response shift, and change because of change in the construct of interest. Subsequently, calculating effect-size indices of change enables evaluation and interpretation of the clinical significance of these different types of change.

Results: Change was investigated in health-related quality of life data from 170 cancer patients, assessed before surgery and 3 months after surgery. Results indicated that patients deteriorated on general physical health and general fitness and improved on general mental health. The decomposition of change showed that the impact of response shift on the assessment of change was small.

Conclusion: SEM can be used to enable the evaluation and interpretation of the impact of response shift effects on the assessment of change, particularly through calculation of effect-size indices. Insight into the occurrence and clinical significance of possible response shift effects will help to better understand changes in PROs.

Keywords: Change assessment; Clinical significance; Effect size; Health-related quality of life; Patient-reported outcomes; Structural equation modeling.