Cargando…
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...
Autores principales: | , , , , , , , |
---|---|
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 |
_version_ | 1782262761059778560 |
---|---|
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. |
format | Online Article Text |
id | pubmed-3598414 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2013 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
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 |
work_keys_str_mv | AT yangfrancesm selectingoptimalscreeningitemsfordeliriumanapplicationofitemresponsetheory AT jonesrichardn selectingoptimalscreeningitemsfordeliriumanapplicationofitemresponsetheory AT inouyesharonk selectingoptimalscreeningitemsfordeliriumanapplicationofitemresponsetheory AT tommetdouglas selectingoptimalscreeningitemsfordeliriumanapplicationofitemresponsetheory AT cranepaulk selectingoptimalscreeningitemsfordeliriumanapplicationofitemresponsetheory AT rudolphjamesl selectingoptimalscreeningitemsfordeliriumanapplicationofitemresponsetheory AT ngolongh selectingoptimalscreeningitemsfordeliriumanapplicationofitemresponsetheory AT marcantonioedwardr selectingoptimalscreeningitemsfordeliriumanapplicationofitemresponsetheory |