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Using Task-Evoked Pupillary Response to Predict Clinical Performance during a Simulation Training.
Mauriz, Elba; Caloca-Amber, Sandra; Vázquez-Casares, Ana M.
Afiliação
  • Mauriz E; Department of Nursing and Physiotherapy, Universidad de León, Campus de Vegazana, s/n, 24071 León, Spain.
  • Caloca-Amber S; Institute of Food Science and Technology (ICTAL), La Serna 58, 24007 León, Spain.
  • Vázquez-Casares AM; Department of Nursing and Physiotherapy, Universidad de León, Campus de Vegazana, s/n, 24071 León, Spain.
Healthcare (Basel) ; 11(4)2023 Feb 04.
Article em En | MEDLINE | ID: mdl-36832990
ABSTRACT
Training in healthcare skills can be affected by trainees' workload when completing a task. Due to cognitive processing demands being negatively correlated to clinical performance, assessing mental workload through objective measures is crucial. This study aimed to investigate task-evoked changes in pupil size as reliable markers of mental workload and clinical performance. A sample of 49 nursing students participated in a cardiac arrest simulation-based practice. Measurements of cognitive demands (NASA-Task Load Index), physiological parameters (blood pressure, oxygen saturation, and heart rate), and pupil responses (minimum, maximum, and difference diameters) throughout revealed statistically significant differences according to performance scores. The analysis of a multiple regression model produced a statistically significant pattern between pupil diameter differences and heart rate, systolic blood pressure, workload, and performance (R2 = 0.280; F (6, 41) = 2.660; p < 0.028; d = 2.042). Findings suggest that pupil variations are promising markers to complement physiological metrics for predicting mental workload and clinical performance in medical practice.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies / Risk_factors_studies Idioma: En Ano de publicação: 2023 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies / Risk_factors_studies Idioma: En Ano de publicação: 2023 Tipo de documento: Article