A Longitudinal Evaluation of a Multimodal POCUS Curriculum in Pediatric Residents
Bibliographic record
Abstract
Introduction: Pediatric residency programs often do not include a point of care ultrasound (POCUS) curriculum. We analyzed a novel POCUS curriculum for pediatric residents that incorporated an online question bank (QB), in addition to a traditional teaching model of didactic instruction and hands-on learning experience. Methods: Four high-yield POCUS topics were chosen: Focused Assessment by Sonography for Trauma (FAST), soft tissue, lung, and cardiac. Residents completed online multiple-choice quizzes before and after each of four in-person learning sessions, taught by ultrasound faculty and fellows. At the end of the academic year participants completed a knowledge retention quiz. Confidence surveys were administered to participants throughout the course of the study. Differences in means were compared by Student’s t-test. Results: Learners demonstrated post-intervention score improvement for each of the four modules. Retention testing demonstrated retained improvement for the soft tissue and cardiac modules, but not for the FAST module. Self-reported confidence increased across all four topics. Conclusion: A multimodal POCUS curriculum utilizing a combination of an online QB and in-person teaching demonstrated lasting knowledge for pediatric trainees.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".