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Practical guidance on use of TEARS-Q to diagnose post-stroke emotionalism
OBJECTIVE: To evaluate, using a classification tree methodology, the ability of the Testing Emotionalism After Recent Stroke – Questionnaire (TEARS-Q) to determine the need for further assessment of post-stroke emotionalism and to identify those whose emotionalism is sufficiently clear that they nee...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
SAGE Publications
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8552395/ https://www.ncbi.nlm.nih.gov/pubmed/34134538 http://dx.doi.org/10.1177/02692155211024801 |
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author | Broomfield, Niall M West, Robert Barber, Mark Gillespie, David C House, Allan Walters, Matthew |
author_facet | Broomfield, Niall M West, Robert Barber, Mark Gillespie, David C House, Allan Walters, Matthew |
author_sort | Broomfield, Niall M |
collection | PubMed |
description | OBJECTIVE: To evaluate, using a classification tree methodology, the ability of the Testing Emotionalism After Recent Stroke – Questionnaire (TEARS-Q) to determine the need for further assessment of post-stroke emotionalism and to identify those whose emotionalism is sufficiently clear that they need assessment for potential intervention. SETTING: Acute stroke units of nine Scottish hospitals in the context of a longitudinal cohort study of post-stroke emotionalism. SUBJECTS: A total of 228 stroke survivors recruited between October 1st 2015 and September 30th 2018, within two weeks of stroke. MEASURES: The measure was the self-report questionnaire TEARS-Q, constructed based on recognised diagnostic features of post-stroke tearful emotionalism. The reference standard was presence/absence of emotionalism on a diagnostic, semi-structured post-stroke emotionalism interview, administered at the same assessment point. RESULTS: Nine of 159 subjects scoring 0 or 1 on TEARS-Q were diagnosed with post-stroke emotionalism on the reference standard, compared to 11 of 21 subjects scoring 2 to 5 on TEARS-Q and 42 of 48 participants scoring 6 and above. Adding age, sex, deprivation, stroke type, stroke severity, mood, cognition, daily functioning and education did not improve the prediction accuracy sufficiently to change the classification tree. CONCLUSION: TEARS-Q reliably identifies those who need no further post-stroke emotionalism assessment, those who need further assessment to clarify diagnosis, and those who almost certainly have post-stroke emotionalism and may benefit from intervention. |
format | Online Article Text |
id | pubmed-8552395 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | SAGE Publications |
record_format | MEDLINE/PubMed |
spelling | pubmed-85523952021-10-29 Practical guidance on use of TEARS-Q to diagnose post-stroke emotionalism Broomfield, Niall M West, Robert Barber, Mark Gillespie, David C House, Allan Walters, Matthew Clin Rehabil Data Collection Tools OBJECTIVE: To evaluate, using a classification tree methodology, the ability of the Testing Emotionalism After Recent Stroke – Questionnaire (TEARS-Q) to determine the need for further assessment of post-stroke emotionalism and to identify those whose emotionalism is sufficiently clear that they need assessment for potential intervention. SETTING: Acute stroke units of nine Scottish hospitals in the context of a longitudinal cohort study of post-stroke emotionalism. SUBJECTS: A total of 228 stroke survivors recruited between October 1st 2015 and September 30th 2018, within two weeks of stroke. MEASURES: The measure was the self-report questionnaire TEARS-Q, constructed based on recognised diagnostic features of post-stroke tearful emotionalism. The reference standard was presence/absence of emotionalism on a diagnostic, semi-structured post-stroke emotionalism interview, administered at the same assessment point. RESULTS: Nine of 159 subjects scoring 0 or 1 on TEARS-Q were diagnosed with post-stroke emotionalism on the reference standard, compared to 11 of 21 subjects scoring 2 to 5 on TEARS-Q and 42 of 48 participants scoring 6 and above. Adding age, sex, deprivation, stroke type, stroke severity, mood, cognition, daily functioning and education did not improve the prediction accuracy sufficiently to change the classification tree. CONCLUSION: TEARS-Q reliably identifies those who need no further post-stroke emotionalism assessment, those who need further assessment to clarify diagnosis, and those who almost certainly have post-stroke emotionalism and may benefit from intervention. SAGE Publications 2021-06-17 2021-12 /pmc/articles/PMC8552395/ /pubmed/34134538 http://dx.doi.org/10.1177/02692155211024801 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/This article is distributed under the terms of the Creative Commons Attribution 4.0 License (https://creativecommons.org/licenses/by/4.0/) which permits any use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access page (https://us.sagepub.com/en-us/nam/open-access-at-sage). |
spellingShingle | Data Collection Tools Broomfield, Niall M West, Robert Barber, Mark Gillespie, David C House, Allan Walters, Matthew Practical guidance on use of TEARS-Q to diagnose post-stroke emotionalism |
title | Practical guidance on use of TEARS-Q to diagnose post-stroke emotionalism |
title_full | Practical guidance on use of TEARS-Q to diagnose post-stroke emotionalism |
title_fullStr | Practical guidance on use of TEARS-Q to diagnose post-stroke emotionalism |
title_full_unstemmed | Practical guidance on use of TEARS-Q to diagnose post-stroke emotionalism |
title_short | Practical guidance on use of TEARS-Q to diagnose post-stroke emotionalism |
title_sort | practical guidance on use of tears-q to diagnose post-stroke emotionalism |
topic | Data Collection Tools |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8552395/ https://www.ncbi.nlm.nih.gov/pubmed/34134538 http://dx.doi.org/10.1177/02692155211024801 |
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