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Selecting optimal screening items for delirium: an application of item response theory

BACKGROUND: Delirium (acute confusion), is a common, morbid, and costly complication of acute illness in older adults. Yet, researchers and clinicians lack short, efficient, and sensitive case identification tools for delirium. Though the Confusion Assessment Method (CAM) is the most widely used alg...

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Autores principales: Yang, Frances M, Jones, Richard N, Inouye, Sharon K, Tommet, Douglas, Crane, Paul K, Rudolph, James L, Ngo, Long H, Marcantonio, Edward R
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3598414/
https://www.ncbi.nlm.nih.gov/pubmed/23339752
http://dx.doi.org/10.1186/1471-2288-13-8
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author Yang, Frances M
Jones, Richard N
Inouye, Sharon K
Tommet, Douglas
Crane, Paul K
Rudolph, James L
Ngo, Long H
Marcantonio, Edward R
author_facet Yang, Frances M
Jones, Richard N
Inouye, Sharon K
Tommet, Douglas
Crane, Paul K
Rudolph, James L
Ngo, Long H
Marcantonio, Edward R
author_sort Yang, Frances M
collection PubMed
description BACKGROUND: Delirium (acute confusion), is a common, morbid, and costly complication of acute illness in older adults. Yet, researchers and clinicians lack short, efficient, and sensitive case identification tools for delirium. Though the Confusion Assessment Method (CAM) is the most widely used algorithm for delirium, the existing assessments that operationalize the CAM algorithm may be too long or complicated for routine clinical use. Item response theory (IRT) models help facilitate the development of short screening tools for use in clinical applications or research studies. This study utilizes IRT to identify a reduced set of optimally performing screening indicators for the four CAM features of delirium. METHODS: Older adults were screened for enrollment in a large scale delirium study conducted in Boston-area post-acute facilities (n = 4,598). Trained interviewers conducted a structured delirium assessment that culminated in rating the presence or absence of four features of delirium based on the CAM. A pool of 135 indicators from established cognitive testing and delirium assessment tools were assigned by an expert panel into two indicator sets per CAM feature representing (a) direct interview questions, including cognitive testing, and (b) interviewer observations. We used IRT models to identify the best items to screen for each feature of delirium. RESULTS: We identified 10 dimensions and chose up to five indicators per dimension. Preference was given to items with peak psychometric information in the latent trait region relevant for screening for delirium. The final set of 48 indicators, derived from 39 items, maintains fidelity to clinical constructs of delirium and maximizes psychometric information relevant for screening. CONCLUSIONS: We identified optimal indicators from a large item pool to screen for delirium. The selected indicators maintain fidelity to clinical constructs of delirium while maximizing psychometric information important for screening. This reduced item set facilitates development of short screening tools suitable for use in clinical applications or research studies. This study represents the first step in the establishment of an item bank for delirium screening with potential questions for clinical researchers to select from and tailor according to their research objectives.
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spelling pubmed-35984142013-03-20 Selecting optimal screening items for delirium: an application of item response theory Yang, Frances M Jones, Richard N Inouye, Sharon K Tommet, Douglas Crane, Paul K Rudolph, James L Ngo, Long H Marcantonio, Edward R BMC Med Res Methodol Research Article BACKGROUND: Delirium (acute confusion), is a common, morbid, and costly complication of acute illness in older adults. Yet, researchers and clinicians lack short, efficient, and sensitive case identification tools for delirium. Though the Confusion Assessment Method (CAM) is the most widely used algorithm for delirium, the existing assessments that operationalize the CAM algorithm may be too long or complicated for routine clinical use. Item response theory (IRT) models help facilitate the development of short screening tools for use in clinical applications or research studies. This study utilizes IRT to identify a reduced set of optimally performing screening indicators for the four CAM features of delirium. METHODS: Older adults were screened for enrollment in a large scale delirium study conducted in Boston-area post-acute facilities (n = 4,598). Trained interviewers conducted a structured delirium assessment that culminated in rating the presence or absence of four features of delirium based on the CAM. A pool of 135 indicators from established cognitive testing and delirium assessment tools were assigned by an expert panel into two indicator sets per CAM feature representing (a) direct interview questions, including cognitive testing, and (b) interviewer observations. We used IRT models to identify the best items to screen for each feature of delirium. RESULTS: We identified 10 dimensions and chose up to five indicators per dimension. Preference was given to items with peak psychometric information in the latent trait region relevant for screening for delirium. The final set of 48 indicators, derived from 39 items, maintains fidelity to clinical constructs of delirium and maximizes psychometric information relevant for screening. CONCLUSIONS: We identified optimal indicators from a large item pool to screen for delirium. The selected indicators maintain fidelity to clinical constructs of delirium while maximizing psychometric information important for screening. This reduced item set facilitates development of short screening tools suitable for use in clinical applications or research studies. This study represents the first step in the establishment of an item bank for delirium screening with potential questions for clinical researchers to select from and tailor according to their research objectives. BioMed Central 2013-01-22 /pmc/articles/PMC3598414/ /pubmed/23339752 http://dx.doi.org/10.1186/1471-2288-13-8 Text en Copyright ©2013 Yang et al; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Yang, Frances M
Jones, Richard N
Inouye, Sharon K
Tommet, Douglas
Crane, Paul K
Rudolph, James L
Ngo, Long H
Marcantonio, Edward R
Selecting optimal screening items for delirium: an application of item response theory
title Selecting optimal screening items for delirium: an application of item response theory
title_full Selecting optimal screening items for delirium: an application of item response theory
title_fullStr Selecting optimal screening items for delirium: an application of item response theory
title_full_unstemmed Selecting optimal screening items for delirium: an application of item response theory
title_short Selecting optimal screening items for delirium: an application of item response theory
title_sort selecting optimal screening items for delirium: an application of item response theory
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3598414/
https://www.ncbi.nlm.nih.gov/pubmed/23339752
http://dx.doi.org/10.1186/1471-2288-13-8
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