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Establishing thresholds for meaningful within-individual change using longitudinal item response theory

PURPOSE: Thresholds for meaningful within-individual change (MWIC) are useful for interpreting patient-reported outcome measures (PROM). Transition ratings (TR) have been recommended as anchors to establish MWIC. Traditional statistical methods for analyzing MWIC such as mean change analysis, receiv...

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Autores principales: Bjorner, Jakob Bue, Terluin, Berend, Trigg, Andrew, Hu, Jinxiang, Brady, Keri J. S., Griffiths, Pip
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer International Publishing 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10123029/
https://www.ncbi.nlm.nih.gov/pubmed/35870045
http://dx.doi.org/10.1007/s11136-022-03172-5
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author Bjorner, Jakob Bue
Terluin, Berend
Trigg, Andrew
Hu, Jinxiang
Brady, Keri J. S.
Griffiths, Pip
author_facet Bjorner, Jakob Bue
Terluin, Berend
Trigg, Andrew
Hu, Jinxiang
Brady, Keri J. S.
Griffiths, Pip
author_sort Bjorner, Jakob Bue
collection PubMed
description PURPOSE: Thresholds for meaningful within-individual change (MWIC) are useful for interpreting patient-reported outcome measures (PROM). Transition ratings (TR) have been recommended as anchors to establish MWIC. Traditional statistical methods for analyzing MWIC such as mean change analysis, receiver operating characteristic (ROC) analysis, and predictive modeling ignore problems of floor/ceiling effects and measurement error in the PROM scores and the TR item. We present a novel approach to MWIC estimation for multi-item scales using longitudinal item response theory (LIRT). METHODS: A Graded Response LIRT model for baseline and follow-up PROM data was expanded to include a TR item measuring latent change. The LIRT threshold parameter for the TR established the MWIC threshold on the latent metric, from which the observed PROM score MWIC threshold was estimated. We compared the LIRT approach and traditional methods using an example data set with baseline and three follow-up assessments differing by magnitude of score improvement, variance of score improvement, and baseline-follow-up score correlation. RESULTS: The LIRT model provided good fit to the data. LIRT estimates of observed PROM MWIC varied between 3 and 4 points score improvement. In contrast, results from traditional methods varied from 2 to 10 points—strongly associated with proportion of self-rated improvement. Best agreement between methods was seen when approximately 50% rated their health as improved. CONCLUSION: Results from traditional analyses of anchor-based MWIC are impacted by study conditions. LIRT constitutes a promising and more robust analytic approach to identifying thresholds for MWIC. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s11136-022-03172-5.
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spelling pubmed-101230292023-04-25 Establishing thresholds for meaningful within-individual change using longitudinal item response theory Bjorner, Jakob Bue Terluin, Berend Trigg, Andrew Hu, Jinxiang Brady, Keri J. S. Griffiths, Pip Qual Life Res Special Section: Methodologies for Meaningful Change PURPOSE: Thresholds for meaningful within-individual change (MWIC) are useful for interpreting patient-reported outcome measures (PROM). Transition ratings (TR) have been recommended as anchors to establish MWIC. Traditional statistical methods for analyzing MWIC such as mean change analysis, receiver operating characteristic (ROC) analysis, and predictive modeling ignore problems of floor/ceiling effects and measurement error in the PROM scores and the TR item. We present a novel approach to MWIC estimation for multi-item scales using longitudinal item response theory (LIRT). METHODS: A Graded Response LIRT model for baseline and follow-up PROM data was expanded to include a TR item measuring latent change. The LIRT threshold parameter for the TR established the MWIC threshold on the latent metric, from which the observed PROM score MWIC threshold was estimated. We compared the LIRT approach and traditional methods using an example data set with baseline and three follow-up assessments differing by magnitude of score improvement, variance of score improvement, and baseline-follow-up score correlation. RESULTS: The LIRT model provided good fit to the data. LIRT estimates of observed PROM MWIC varied between 3 and 4 points score improvement. In contrast, results from traditional methods varied from 2 to 10 points—strongly associated with proportion of self-rated improvement. Best agreement between methods was seen when approximately 50% rated their health as improved. CONCLUSION: Results from traditional analyses of anchor-based MWIC are impacted by study conditions. LIRT constitutes a promising and more robust analytic approach to identifying thresholds for MWIC. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s11136-022-03172-5. Springer International Publishing 2022-07-23 2023 /pmc/articles/PMC10123029/ /pubmed/35870045 http://dx.doi.org/10.1007/s11136-022-03172-5 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Special Section: Methodologies for Meaningful Change
Bjorner, Jakob Bue
Terluin, Berend
Trigg, Andrew
Hu, Jinxiang
Brady, Keri J. S.
Griffiths, Pip
Establishing thresholds for meaningful within-individual change using longitudinal item response theory
title Establishing thresholds for meaningful within-individual change using longitudinal item response theory
title_full Establishing thresholds for meaningful within-individual change using longitudinal item response theory
title_fullStr Establishing thresholds for meaningful within-individual change using longitudinal item response theory
title_full_unstemmed Establishing thresholds for meaningful within-individual change using longitudinal item response theory
title_short Establishing thresholds for meaningful within-individual change using longitudinal item response theory
title_sort establishing thresholds for meaningful within-individual change using longitudinal item response theory
topic Special Section: Methodologies for Meaningful Change
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10123029/
https://www.ncbi.nlm.nih.gov/pubmed/35870045
http://dx.doi.org/10.1007/s11136-022-03172-5
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