Critical examination of current response shift methods and proposal for advancing new methods

Véronique Sébille,A Cecile J W Janssens,Olawale F Ayilara,Richard Sawatzky,Mirjam A G Sprangers,Lisa M Lix,Tolulope T Sajobi,Mathilde G E Verdam

doi:10.1007/s11136-020-02755-4

Abstract

PurposeThis work is part of an international, interdisciplinary initiative to synthesize research on response shift in results of patient-reported outcome measures. The objective is to critically examine current response shift methods. We additionally propose advancing new methods that address the limitations of extant methods.MethodsBased on literature reviews, this critical examination comprises design-based, qualitative, individualized, and preference-based methods, latent variable models, and other statistical methods. We critically appraised their definition, operationalization, the type of response shift they can detect, whether they can adjust for and explain response shift, their assumptions, and alternative explanations. Overall limitations requiring new methods were identified.ResultsWe examined 11 methods that aim to operationalize response shift, by assessing change in the meaning of one’s self-evaluation. Six of these methods distinguish between change in observed measurements (observed change) and change in the construct that was intended to be measured (target change). The methods use either (sub)group-based or individual-level analysis, or a combination. All methods have underlying assumptions to be met and alternative explanations for the inferred response shift effects. We highlighted the need to address the interpretation of the results as response shift and proposed advancing new methods handling individual variation in change over time and multiple time points.ConclusionNo single response shift method is optimal; each method has strengths and limitations. Additionally, extra steps need to be taken to correctly interpret the results. Advancing new methods and conducting computer simulation studies that compare methods are recommended to move response shift research forward.

Highlights

Patient-reported outcome measures (PROMs) are incorporated into clinical practice and research to assess the impact of disease and treatment from the patient’s viewpoint
Oort et al [6, 7] highlighted that when the meaning of selfevaluation changes, the relationship between change in measurement and change in the target construct changes
The current work is part of an international, interdisciplinary collaboration to synthesize extant research on response shift [8, 25, 26].The primary objective of the current paper is to provide a critical examination of response shift methods

Summary

Introduction

Patient-reported outcome measures (PROMs) are incorporated into clinical practice and research to assess the impact of disease and treatment from the patient’s viewpoint. The current work is part of an international, interdisciplinary collaboration (see Appendix for the contributing members) to synthesize extant research on response shift [8, 25, 26].The primary objective of the current paper is to provide a critical examination of response shift methods We compare their implied definitions, how response shift is operationalized in terms of the type of response shift they aim to detect and whether they can adjust for and explain detected response shift, their underlying assumptions, and alternative explanations of response shift results. The former encompasses the definitions proposed by Golembiewski et al [2] and Howard et al [3], while Oort et al adopted a different perspective, which is based on the discrepancy between observed change and target change These definitions can be applied to all methods, whereas the Rapkin and Schwartz [5] definition requires assessing appraisal processes. The ability to recall is an important assumption for the use and interpretation of a number of methods, including the thentest (previous level of functioning), appraisal (previous completion of questionnaire items), qualitative methods (a past reference period), and individualized methods such as the SEIQoL (previous domains or weights)

Method

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