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Practical guidance on use of TEARS-Q to diagnose post-stroke emotionalism. | LitMetric

AI Article Synopsis

Article Abstract

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.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8552395PMC
http://dx.doi.org/10.1177/02692155211024801DOI Listing

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