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Activating emotions enhance surgical simulation performance: a cluster analysis
by
Fazlollahi, Ali M
, Yilmaz, Recai
, Harley, Jason M
, Bakhaidar, Mohamad
, Alsayegh, Ahmad
, Maestro, Rolando F Del
, Lau, Clarissa H H
in
Brain cancer
/ Cluster analysis
/ Emotions
/ Regression analysis
/ Simulation
/ Students
2021
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Activating emotions enhance surgical simulation performance: a cluster analysis
by
Fazlollahi, Ali M
, Yilmaz, Recai
, Harley, Jason M
, Bakhaidar, Mohamad
, Alsayegh, Ahmad
, Maestro, Rolando F Del
, Lau, Clarissa H H
in
Brain cancer
/ Cluster analysis
/ Emotions
/ Regression analysis
/ Simulation
/ Students
2021
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Do you wish to request the book?
Activating emotions enhance surgical simulation performance: a cluster analysis
by
Fazlollahi, Ali M
, Yilmaz, Recai
, Harley, Jason M
, Bakhaidar, Mohamad
, Alsayegh, Ahmad
, Maestro, Rolando F Del
, Lau, Clarissa H H
in
Brain cancer
/ Cluster analysis
/ Emotions
/ Regression analysis
/ Simulation
/ Students
2021
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Activating emotions enhance surgical simulation performance: a cluster analysis
Journal Article
Activating emotions enhance surgical simulation performance: a cluster analysis
2021
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Overview
Background: Bimanual psychomotor skills are essential to surgical education, therefore medical trainees require multiple opportunities to master their skills. However, developing these technical skills can be a highly stressful and emotional experience. Therefore, we sought to investigate the impact of emotions on performance outcomes in surgical simulation training through the following research questions. Do emotions measured at baseline group students in a meaningful way? Do students' membership in emotion groups predict students' change in performance? Methods: Participants completed 5 practice simulated brain tumour resections followed by 1 realistic virtual reality simulated brain tumour resection; after each simulation, an expertise score was generated. Students also completed a survey on emotions prior to simulations. We used a multivariate clustering approach to group students by their emotions and then conducted regression analysis to examine the predictive relationship between emotion groups and performance change. Results: Seventy-two medical students participated in the study. Cluster analysis identified 3 distinct emotion groups: high positive- and negative-activating emotions (group 1, n = 31), high positive-activating and -deactivating emotions (group 2, n = 22), and low emotions (group 3, n = 19). Regression analysis revealed membership in group 1 significantly predicted positive performance change from fifth practice expertise score to sixth realistic simulated tumour resection expertise score (R2 = 0.05, T1,70 = 4.023, p = 0.049). Conclusion: Our study showed that students who experienced more activating emotions tended to show positive performance change as they shifted from practice to realistic simulations. Students' emotions should be considered during surgical simulation to promote better learning and transfer of skills.
Publisher
CMA Impact, Inc
Subject
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