Knowledge Retention of the NIH Stroke Scale among Stroke Unit Health Care Workers Using Video vs. E-Learning: Protocol for a Web-Based, Randomized Controlled Trial

The National Institutes of Health Stroke Scale (NIHSS) is commonly used to triage and monitor the evolution of stroke victims. Data regarding NIHSS knowledge in nurses and physicians working with stroke patients are scarce, and a progressive decline in specific knowledge regarding this challenging s...

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Autores principales: Avinash Koka, Mélanie Suppan, Emmanuel Carrera, Paula Fraga-Freijeiro, Kiril Massuk, Marie-Eve Imbeault, Nathalie Missilier Perruzzo, Sophia Achab, Alexander Salerno, Davide Strambo, Patrik Michel, Loric Stuby, Laurent Suppan
Formato: article
Lenguaje:EN
Publicado: MDPI AG 2021
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R
Acceso en línea:https://doaj.org/article/f4179fabbf024570a15648cf7e0f936d
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Sumario:The National Institutes of Health Stroke Scale (NIHSS) is commonly used to triage and monitor the evolution of stroke victims. Data regarding NIHSS knowledge in nurses and physicians working with stroke patients are scarce, and a progressive decline in specific knowledge regarding this challenging scale is to be expected even among NIHSS certified personnel. This protocol was designed according to the CONSORT-eHealth (Consolidated Standards of Reporting Trials) guidelines. It describes the design of a randomized controlled trial whose primary objective is to determine if nurses and physicians who work in stroke units improve their NIHSS knowledge more significantly after following a highly interactive e-learning module than after following the traditional didactic video. Univariate and multivariable linear regression will be used to analyze the primary outcome, which will be the difference between the score on a 50-question quiz answered before and immediately after following the allocated learning material. Secondary outcomes will include knowledge retention at one month, assessed using the same 50-question quiz, user satisfaction, user course duration perception, and probability of recommending the allocated learning method. The study is scheduled to begin during the first semester of 2022.