Scoping review of response shift methods: current reporting practices and recommendations

Background Response shift (RS) has been defined as a change in the meaning of an individual's self-evaluation of his/her health status and quality of life. Several statistical model- and design-based methods have been developed to test for RS in longitudinal data. We reviewed the uptake of thes...

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Bibliographic Details
Published inQuality of life research Vol. 27; no. 5; pp. 1133 - 1146
Main Authors Sajobi, Tolulope T., Brahmbatt, Ronak, Lix, Lisa M., Zumbo, Bruno D., Sawatzky, Richard
Format Journal Article
LanguageEnglish
Published Cham Springer 01.05.2018
Springer International Publishing
Springer Nature B.V
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Summary:Background Response shift (RS) has been defined as a change in the meaning of an individual's self-evaluation of his/her health status and quality of life. Several statistical model- and design-based methods have been developed to test for RS in longitudinal data. We reviewed the uptake of these methods in patient-reported outcomes (PRO) literature. Methods CINHAHL, EMBASE, Medline, ProQuest, PsycINFO, and Web of Science were searched to identify English-language articles about RS published until 2016. Data on year and country of publication, PRO measure adopted, RS detection method, type of RS detected, and testing of underlying model assumptions were extracted from the included articles. Results Of the 1032 articles identified, 101 (9.8%) articles were included in the study. While 54.5 of the articles reported on the Then-test, 30.7% of the articles reported on Oort's or Schmitt's structural equation modeling (SEM) procedure. Newer RS detection methods, such as relative importance analysis and random forest regression, have been used less frequently. Less than 25% reported on testing the assumptions underlying the adopted RS detection method(s). Conclusions Despite rapid methodological advancements in RS research, this review highlights the need for further research about RS detection methods for complex longitudinal data and standardized reporting guidelines.
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ISSN:0962-9343
1573-2649
DOI:10.1007/s11136-017-1751-x