Teaching Ultrasound Early: Outcomes from a Student-Led POCUS Elective Course
Suri, I.; Parkas, N.; Solazzo, E.; Yu, R.; Moehrle, N.
Show abstract
BackgroundPoint-of-care ultrasound (POCUS) utilization across specialties continues to grow, making it a valuable skill for medical students. Early exposure to ultrasound may enhance students clinical reasoning, anatomical understanding, and integration of POCUS into the physical exam. This study evaluates the impact of a student-organized, physician-taught POCUS elective course on pre-clinical medical students competence in foundational ultrasound skills. MethodsFifteen students were enrolled in the course. Students attended four weekly 90-minute sessions focused on a unique organ system. Students took a 19-question test before and after the course to assess overall learning. Five-question quizzes were conducted before and after each session to evaluate immediate learning. Fishers exact test was used to compare correct vs. incorrect quiz answers before and after each session. ResultsOverall knowledge of POCUS, determined by the 19-question quiz, improved from 61.5% to 76.8% (p = 0.01). FAST and cardiac ultrasound quiz scores improved from 54.2% to 91.4% (p < 0.01) and 57.7% to 85.7% (p < 0.01), respectively. The pre- and post-quiz score for the abdominal ultrasound exam remained the same at 80.0% (p = 1). The gynecologic ultrasound exam score improved from 45.0% to 66.7% (p = 0.3). ConclusionsThis elective course significantly increased pre-clinical medical students knowledge of ultrasound. No statistically significant difference was noted for the abdominal or gynecologic sessions.
Matching journals
The top 1 journal accounts for 50% of the predicted probability mass.
Similar papers in this journal
- Improving capacity for advanced training in obstetric surgery: Evaluation of a blended learning approach 95%
- Team-Based Learning Versus Lecture-Based Instruction for Chest Radiograph Interpretation in Physician Associate Education: A Quasi-Experimental Study 95%
- Medical student residency preferences and motivational factors: a longitudinal, single-institution perspective 94%
Similar papers in this journal
- Introducing the 4Ps Model of Transitioning to Distance Learning: a convergent mixed methods study conducted during the COVID-19 pandemic 94%
- Evaluating user experience with immersive technology in simulation-based education: a modified Delphi study with qualitative analysis 93%
- Environmental influences and individual characteristics that affect learner-centered teaching practices 92%
Similar papers in this journal
- Evaluation of Self-Directed Learning Activities at King Abdulaziz University: A Qualitative Study of Faculty Perceptions 94%
- Factors determining success of the chronically instrumented unanesthetized fetal sheep model of human development: a retrospective cohort study 90%
- Effects of contrast-medium and vertebral measurement level on computed tomography-based body composition parameters of skeletal muscle and adipose tissue 88%
Similar papers in this journal
- Emotional Distress, Stress, Anxiety and the Impact of the COVID-19 Pandemic on Early Career Women in Healthcare Sciences Research 91%
- Data-driven hypothesis generation among junior clinical researchers: A comparison of a secondary data analysis with visualization (VIADS) and other tools 91%
- A Retrospective Case Study of Successful Translational Research: Cardiovascular Disease Risk Assessment, Experiences in Community Engagement 89%
Similar papers in this journal
- Virtual Recruitment is Here to Stay: 2020 ID Fellowship Program and Matched Applicant Recruitment Experiences 92%
- Characterization of prolonged COVID-19 symptoms and patient comorbidities in an outpatient telemedicine cohort 87%
- High proportion of post-acute sequelae of SARS-CoV-2 infection in individuals 1-6 months after illness and association with disease severity in an outpatient telemedicine population 87%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.