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17-02-2021 | Uitgave 12/2021 Open Access

Quality of Life Research 12/2021

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

Tijdschrift:
Quality of Life Research > Uitgave 12/2021
Auteurs:
Véronique Sébille, Lisa M. Lix, Olawale F. Ayilara, Tolulope T. Sajobi, A. Cecile J. W. Janssens, Richard Sawatzky, Mirjam A. G. Sprangers, Mathilde G. E. Verdam, the Response Shift – in Sync Working Group
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Supplementary Information

The online version of this article (https://​doi.​org/​10.​1007/​s11136-020-02755-4) contains supplementary material, which is available to authorized users.

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Abstract

Purpose

This 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.

Methods

Based 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.

Results

We 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.

Conclusion

No 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.

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