Universidad del Desarrollo

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Developing clinical decision making in stroke through virtual online simulation: automated asynchronous or instructor-led synchronous feedback? A randomized controlled trial
(2023)
Valentina Fuentes Lombardo
;
Javier Palominos Salas
;
María A. Pettersen Correa
;
Patricio Caro Guerra
;
NAVIA GONZALEZ, VICTOR HUGO
<jats:p>Aim: to determine whether asynchronous virtual simulation with automatic feedback enhances learning about clinical decision-making in stroke compared with synchronous simulation with instructor-guided feedback in 4th-year medical students. We hypothesize that instructor-guided feedback drives better learning than automatic feedback. Methodology: a quantitative randomized controlled parallel study was designed using the CONSORT extension to simulation studies. Twenty 4th year undergraduate medical students were divided into two groups. One group performed virtual simulations with instructor-guided feedback, and the other worked autonomously with automatic feedback. We administered a knowledge score test survey before and after applying the intervention bundle and a usefulness perception survey. Two-way repeated measures analysis of variance (ANOVA) was used to compare changes in performance. Results: the results of the two-way ANOVA on the performance level showed no significant changes between groups and between the first and third scenarios (p=0,428). Analysis of the simple main effect showed no significant difference between groups in the post-test (p =0,086) and no significant difference after the third scenario in the Synchronous (p = 0,001) and Asynchronous (p = 0,009) groups. The most remarkable improvement was the International Normalized Ratio that contraindicates thrombolysis (70 % improvement), followed by the first-line drug for hypertension and the platelet value that contraindicates thrombolysis (25 % improvement for both). Conclusion: we did not identify differences in student stroke knowledge gained via virtual simulation with automated v/s instructor-guided feedback. The students learned specific elements linked to the safety of administering thrombolytics in patients with stroke.</jats:p>
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Human Anterior Insula Encodes Performance Feedback and Relays Prediction Error to the Medial Prefrontal Cortex
(2020)
BILLEKE BOBADILLA, PABLO ERNESTO
;
Tomas Ossandon
;
Marcela Perrone-Bertolotti
;
Philippe Kahane
;
Julien Bastin
<jats:title>Abstract</jats:title> <jats:p>Adaptive behavior requires the comparison of outcome predictions with actual outcomes (e.g., performance feedback). This process of performance monitoring is computed by a distributed brain network comprising the medial prefrontal cortex (mPFC) and the anterior insular cortex (AIC). Despite being consistently co-activated during different tasks, the precise neuronal computations of each region and their interactions remain elusive. In order to assess the neural mechanism by which the AIC processes performance feedback, we recorded AIC electrophysiological activity in humans. We found that the AIC beta oscillations amplitude is modulated by the probability of performance feedback valence (positive or negative) given the context (task and condition difficulty). Furthermore, the valence of feedback was encoded by delta waves phase-modulating the power of beta oscillations. Finally, connectivity and causal analysis showed that beta oscillations relay feedback information signals to the mPFC. These results reveal that structured oscillatory activity in the anterior insula encodes performance feedback information, thus coordinating brain circuits related to reward-based learning.</jats:p>
5Scopus© Citations 41

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