Background: Focused transthoracic echocardiography (FOTE) is crucial for patients' bedside management. However, limited opportunities exist for practical FOTE training, prompting the use of simulation and self-learning videos to overcome this constraint. This study aimed to evaluate the impact of incorporating self-learning videos into a simulation FOTE training course.
Approach: This was a prospective, randomized study involving University of Toronto internal medicine residents, who participated in a 2-h didactic and simulation FOTE training course before being randomized to a control group receiving written learning materials or an intervention group with additional self-directed learning videos.
Evaluation: Twenty-eight participants were randomized, and twenty-one (75%) completed the 1-month follow-up. Participants were assessed using a written test on image acquisition techniques and structure identification, scanning time and image quality on a simulator and self-reported scanning comfort, both pre-intervention and 1-month post-intervention. The groups had no significant difference in the time spent reviewing the material (1.5 vs. 1.4 h, p = 0.76). A significant increase in post-course scores was observed in all evaluations except for the control group's written test (p = 0.07). There were no significant between-group differences across the written test (p = 0.7), image quality (p = 0.6) and comfort level (p = 0.7). Compared to the control group, the intervention group exhibited a greater reduction in the scanning time (38 vs. 72 s, p = 0.02).
Implications: FOTE training effectively increases theoretical knowledge and practical skills in a simulated setting. However, limited video utilization by participants precluded the inference of definitive conclusions on the impact of self-learning videos.
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http://dx.doi.org/10.1111/tct.70014 | DOI Listing |
Clin Teach
February 2025
Interdepartmental Division of Critical Care Medicine, Toronto General Hospital, University of Toronto, Toronto, Ontario, Canada.
Background: Focused transthoracic echocardiography (FOTE) is crucial for patients' bedside management. However, limited opportunities exist for practical FOTE training, prompting the use of simulation and self-learning videos to overcome this constraint. This study aimed to evaluate the impact of incorporating self-learning videos into a simulation FOTE training course.
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The automatic video recognition of depression is becoming increasingly important in clinical applications. However, traditional depression recognition models still face challenges in practical applications, such as high computational costs, the poor application effectiveness of facial movement features, and spatial feature degradation due to model stitching. To overcome these challenges, this work proposes a lightweight Time-Context Enhanced Depression Detection Network (TCEDN).
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