Inserm UMR1246 SPHERE

Universities of Nantes and Tours


SPHERE is a multidisciplinary unit that seeks to develop and validate methods that can be used in clinical or epidemiological studies.

The philosophy that drives the SPHERE unit is that the patient must be considered as a whole, i.e. taking into account his/her environment, and integrating his/her perceptions, experience, and wishes.

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4 axes of research

Axis 1

Cluster Randomized Trials and Complex Interventions

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Axis 2

Definition, selection, validation, and assessment of outcomes

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Axis 3

Methods for the measurement and interpretation of Self-Reported Outcomes

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Axis 4

Prediction and Causality

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A revised model of response shift phenomenon
04/05/2021 04/2021

Response shift in patient‑reported outcomes: definition, theory, and a revised model

Author(s) of the publication: Antoine Vanier, Frans J Oort, Leah McClimans, Nikki Ow, Bernice G Gulek, Jan R Böhnke, Mirjam Sprangers, Véronique Sébille, Nancy Mayo, the Response Shift - in Sync Working Group

This work is part of an international initiative: the Response Shift - in Sync Working Group.

Purpose The extant response shift definitions and theoretical response shift models, while helpful, also introduce predicaments
and theoretical debates continue. To address these predicaments and stimulate empirical research, we propose a more
specific formal definition of response shift and a revised theoretical model.
Methods This work is an international collaborative effort and involved a critical assessment of the literature.
Results Three main predicaments were identified. First, the formal definitions of response shift need further specification
and clarification. Second, previous models were focused on explaining change in the construct intended to be measured
rather than explaining the construct at multiple time points and neglected the importance of using at least two time points
to investigate response shift. Third, extant models do not explicitly distinguish the measure from the construct. Here we
define response shift as an effect occurring whenever observed change (e.g., change in patient-reported outcome measures
(PROM) scores) is not fully explained by target change (i.e., change in the construct intended to be measured). The revised
model distinguishes the measure (e.g., PROM) from the underlying target construct (e.g., quality of life) at two time points.
The major plausible paths are delineated, and the underlying assumptions of this model are explicated.
Conclusion It is our hope that this refined definition and model are useful in the further development of response shift theory.
The model with its explicit list of assumptions and hypothesized relationships lends itself for critical, empirical examination.
Future studies are needed to empirically test the assumptions and hypothesized relationships.

Response Shift, Theory
Quality of Life Resarch
Critical examination of current response shift methods and proposal for advancing new methods
04/05/2021 02/01/20

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

Author(s) of the publication: Véronique Sébille, Lisa M Lix, Olawale F Ayilara, Tolulope T Sajobi, A.Cecile JW Janssens, Richard Sawatzky, Mirjam AG Sprangers, Mathilde GE Verdam - the Response Shift - in Sync Working Group

This work is part of an international initiative : The Response Shift - in Sync Working Group.

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.

Patient-Reported Outcomes, Response shift
Quality of Life Resarch
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Two pages on SPHERE in the latest issue of Inserm, Le magazine!

Public Health: Consider the entire patient sphere

pages 12-13