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Health and Quality of Life Outcomes
Published in: Health and Quality of Life Outcomes 1/2021

Open Access 01-12-2021 | Fatigue | Research

Response shift in health-related quality of life measures in the presence of formative indicators

Authors: Silvia Testa, Daniela Di Cuonzo, Giuliana Ritorto, Laura Fanchini, Sara Bustreo, Patrizia Racca, Rosalba Rosato

Published in: Health and Quality of Life Outcomes | Issue 1/2021

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Abstract

Background

Response shift (RS) has been defined as a change in the meaning of an individual’s self-evaluation that needs to be accounted for when assessing longitudinal changes in health-related quality of life (HRQoL). RS detection through structural equation modeling is accomplished by adopting Oort’s procedure based on a measurement model in which the observed variables are defined as reflective indicators of the HRQoL latent variable; that is, the latent variable causes the variation in the reflective indicators. This study aims to propose a procedure that assesses RS when formative indicators are used in measuring HRQoL; in this last case, the latent variable is considered to be a function of some formative indicators. A secondary aim is to compare the new procedure with Oort’s procedure to highlight similarities and differences.

Methods

The data were retrieved from a consecutive series of 258 patients newly diagnosed with colorectal cancer and undergoing chemotherapy and/or surgery. The European Organisation for Research and Treatment of Cancer Quality of Life Questionnaire (EORTC QOL-C30) was administered twice, once before and once six months after treatment. Structural equation modeling was used to evaluate RS and true change with the newly proposed method (in which fatigue and pain were defined as formative indicators) and with Oort’s procedure (in which fatigue and pain were defined as reflective indicators).

Results

According to the new procedure, there was no measurement bias, and on average, patients’ quality of life improved by 3.53 points (on a scale ranging from 0 to 100) at the 6-month follow-up. With Oort’s procedure, the loading of the pain indicator was not invariant across the two time points, suggesting the presence of reprioritization, whereas the estimation of true change was very similar to the previous one: 3.87.

Conclusions

RS and true change in HRQoL can be evaluated in the presence of formative indicators. Defining a measurement model by formative or reflective indicators can lead to different results.
Literature
1.
Crosby RD, Kolotkin RL, Williams GR. Defining clinically meaningful change in health-related quality of life. J Clin Epidemiol. 2003;56(5):395–407.PubMedCrossRef
2.
Sajobi TT, et al. Scoping review of response shift methods: current reporting practices and recommendations. Qual Life Res. 2018;27(5):1133–46.PubMedCrossRef
3.
Vanier A, et al. Overall performance of Oort’s procedure for response shift detection at item level: a pilot simulation study. Qual Life Res. 2015;24(8):1799–807.PubMedCrossRef
4.
Sprangers MA, Schwartz CE. Integrating response shift into health-related quality of life research: a theoretical model. Soc Sci Med. 1999;48(11):1507–15.PubMedCrossRef
5.
Rapkin BD, Schwartz CE. Toward a theoretical model of quality-of-life appraisal: implications of findings from studies of response shift. Health Qual Life Outcomes. 2004;2:14.PubMedPubMedCentralCrossRef
6.
Oort FJ. Using structural equation modeling to detect response shifts and true change. Qual Life Res. 2005;14(3):587–98.PubMedCrossRef
7.
Rapkin BD, Schwartz CE. Advancing quality-of-life research by deepening our understanding of response shift: a unifying theory of appraisal. Qual Life Res. 2019;28(10):2623–30.PubMedCrossRef
8.
Schwartz CE, Sprangers MA. Reflections on genes and sustainable change: toward a trait and state conceptualization of response shift. J Clin Epidemiol. 2009;62(11):1118–23.PubMedCrossRef
9.
Fleuren BP, et al. Handling the reflective-formative measurement conundrum: a practical illustration based on sustainable employability. J Clin Epidemiol. 2018;103:71–81.PubMedCrossRef
10.
Bollen KA, Diamantopoulos A. In defense of causal-formative indicators: a minority report. Psychol Methods. 2017;22(3):581.PubMedCrossRef
11.
Jarvis CB, MacKenzie SB, Podsakoff PM. A critical review of construct indicators and measurement model misspecification in marketing and consumer research. J Consum Res. 2003;30(2):199–218.CrossRef
12.
Oort FJ. Towards a formal definition of response shift (in reply to GW Donaldson). Qual Life Res. 2005;14:2353–5.PubMedCrossRef
13.
Donaldson GW. Structural equation models for quality of life response shifts: promises and pitfalls. Qual Life Res. 2005;14(10):2345–51.PubMedCrossRef
14.
Bollen KA, Davis WR. Causal indicator models: Identification, estimation, and testing. Struct Equ Model Multidiscip J. 2009;16(3):498–522.CrossRef
15.
Bollen K. Structural equations with latent variables. New York: Wiley; 1989.CrossRef
16.
Boehmer S, Luszczynska A. Two kinds of items in quality of life instruments: “indicator and causal variables” in the EORTC qlq-c30. Qual Life Res. 2006;15(1):131–41.PubMedCrossRef
17.
Bollen K, Lennox R. Conventional wisdom on measurement: a structural equation perspective. Psychol Bull. 1991;110(2):305–14.CrossRef
18.
Fayers PM, Hand DJ. Factor analysis, causal indicators and quality of life. Qual Life Res. 1997;6(2):139–50.PubMedCrossRef
19.
Traa MJ, et al. Evaluating quality of life and response shift from a couple-based perspective: a study among patients with colorectal cancer and their partners. Qual Life Res. 2015;24(6):1431–41.PubMedCrossRef
20.
Bernhard J, et al. Quality of life as subjective experience: Reframing of perception in patients with colon cancer undergoing radical resection with or without adjuvant chemotherapy. Ann Oncol. 1999;10(7):775–82.PubMedCrossRef
21.
Ito N, et al. Response shift in quality-of-life assessment in patients undergoing curative surgery with permanent colostomy: a preliminary study. Gastroenterol Nurs. 2010;33(6):408–12.PubMedCrossRef
22.
Neuman HB, et al. Rectal cancer patients’ quality of life with a temporary stoma: shifting perspectives. Dis Colon Rectum. 2012;55(11):1117–24.PubMedCrossRef
23.
Fayers PM, et al. Causal indicators in quality of life research. Qual Life Res. 1997;6(5):393–406.PubMedCrossRef
24.
Giesinger JM, et al. Replication and validation of higher order models demonstrated that a summary score for the EORTC QLQ-C30 is robust. J Clin Epidemiol. 2016;69:79–88.PubMedCrossRef
25.
Bollen KA. Evaluating effect, composite, and causal indicators in structural equation models. Mis Q. 2011;32:359–72.CrossRef
26.
27.
Aaronson NK, et al. The European Organization for Research and Treatment of Cancer QLQ-C30: a quality-of-life instrument for use in international clinical trials in oncology. JNCI J Natl Cancer Inst. 1993;85(5):365–76.PubMedCrossRef
28.
Vickrey B, et al. A health-related quality of life measure for multiple sclerosis. Qual Life Res. 1995;4(3):187–206.PubMedCrossRef
29.
Ware JE Jr, Sherbourne CD. The MOS 36-item short-form health survey (SF-36): I. Conceptual framework and item selection. Med Care. 1992;30:473–83.PubMedCrossRef
30.
Hu LT, Bentler PM. Cutoff criteria for fit indexes in covariance structure analysis: conventional criteria versus new alternatives. Struct Equ Model Multidiscip J. 1999;6(1):1–55.CrossRef
31.
Browne MW, Cudeck R. Alternative ways of assessing model fit. In: Bollen KA, Long JS, editors. Testing structural equation models. Newbury Park: Sage; 1993. p. 136–92.
32.
33.
Costa DS. Reflective, causal, and composite indicators of quality of life: a conceptual or an empirical distinction? Qual Life Res. 2015;24(9):2057–65.PubMedCrossRef
34.
Oort FJ, Visser MR, Sprangers MA. Formal definitions of measurement bias and explanation bias clarify measurement and conceptual perspectives on response shift. J Clin Epidemiol. 2009;62(11):1126–37.PubMedCrossRef
35.
King-Kallimanis BL, et al. Structural equation modeling of health-related quality-of-life data illustrates the measurement and conceptual perspectives on response shift. J Clin Epidemiol. 2009;62(11):1157–64.PubMedCrossRef
Metadata
Title
Response shift in health-related quality of life measures in the presence of formative indicators
Authors
Silvia Testa
Daniela Di Cuonzo
Giuliana Ritorto
Laura Fanchini
Sara Bustreo
Patrizia Racca
Rosalba Rosato
Publication date
01-12-2021
Publisher
BioMed Central
Keyword
Fatigue
Published in
Health and Quality of Life Outcomes / Issue 1/2021
Electronic ISSN: 1477-7525
DOI
https://doi.org/10.1186/s12955-020-01663-y

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