Detection of response shift in health-related quality of life studies: a systematic review.

Background: Response Shift (RS) refers to the idea that an individual may undergo changes in its health-related quality of life (HRQOL). If internal standard, values, or reconceptualization of HRQOL change over time, then answer to the same items by the same individuals may not be comparable over time. Traditional measures to evaluate RS is prone to bias and strong methodologies to study the existence of this phenomenon is required. The objective is to systematically identify, analyze, and synthesize the existing and recent evidence of statistical methods used for RS detection in HRQOL studies.

Methods: The analysis of selected studies between January 2010 and July 2020 was performed through a systematic review in MEDLINE/PubMed, Scopus, Web of Science, PsycINFO and Google Scholar databases. The search strategy used the terms "Health-Related Quality of Life" and "Response Shift" using the filters "Humans", "Journal Article", "English" and "2010/01/01-2020/07/31". The search was made in August 2020.

Results: After considering the inclusion and exclusion criteria, from the total selected articles (675), 107 (15.9%) of the publications were included in the analysis. From these, 79 (71.0%) detected the existence of RS and 86 (80.4%) only used one detection method. The most used methods were Then Test (n = 41) and Oort's Structural Equation Models (SEM) (n = 35). Other method used were Multiple Lineal Regression (n = 7), Mixed-Effect Regression (n = 6), Latent Trajectory Analysis (n = 6), Item Response Theory (n = 6), Logistics Regression (n = 5), Regression and Classification Trees (n = 4) and Relative Importance Method (n = 4). Most of these detected recalibration, including Then Test (n = 27), followed by Oort's SEM that detected the higher combination of RS types: recalibration (n = 24), reprioritization (n = 13) and reconceptualization (n = 7).

Conclusions: There is a continuous interest of studying RS detection. Oort's SEM becomes the most versatile method in its capability for detecting RS in all different types. Despite results from previous systematic reviews, same methods have been used during the last years. We observed the need to explore other alternative methods allowing same detection capacity with robust and highly precise methodology. The investigation on RS detection and types requires more study, therefore new opportunity grows to continue attending this phenomenon through a multidisciplinary perspective.