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Abstract 15181: The National Pediatric Cardiology Boot Camp Training Program - Five Years’ Evidence of Consistent Educational Benefit

2020· article· en· W3162085453 on OpenAlexaboutno aff
Loren D. Sacks, Kara S. Motonaga, Catherine D. Krawczeski, David M. Axelrod, Lillian Su, Robert Bishop, Alisa Arunamata, David M. Kwiatkowski, Inger Olson, Shiraz A. Maskatia, Alaina K. Kipps, Leo Lopez, Rajesh Shenoy, Paul Grossfeld, Michael Weidenbach, Angela M. Kelle, Sonali S. Patel, Robert H. Pass, Lupe Romero-Villanueva, Holly Lewin, Scott R. Ceresnak

Bibliographic record

VenueCirculation · 2020
Typearticle
Languageen
FieldMedicine
TopicCardiac, Anesthesia and Surgical Outcomes
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineSubspecialtyPhysical therapyFamily medicine

Abstract

fetched live from OpenAlex

Introduction: The transition from residency to subspecialty fellowship in pediatric cardiology is challenging, with the daunting requirement to rapidly acquire a broad scope of knowledge and skill. In 2015, a pediatric cardiology boot camp was designed as an educational tool to help prepare trainees for this transition. Hypothesis: A national pediatric cardiology boot camp consistently improves knowledge and decreases anxiety for prospective fellows. Methods: In late spring each year (2015-2019), a 2.5-day intensive program was provided for trainees prior to beginning fellowship in July. Hands-on, simulation-based experiences were provided on topics including anatomy, auscultation, echocardiography, catheterization, cardiovascular intensive care, electrophysiology, heart failure, pulmonary hypertension, and cardiac surgery. Knowledge based exams and surveys were completed by each participant pre- and post-training. Pre- and post-training exam results were compared via paired t-tests and survey results were compared via Wilcoxon rank sum. Results: Over 5 years 144 participants (72 female, 50%) completed the course, representing 40 fellowship programs in the United States and Canada. In aggregate, significant improvement was seen in participants’ knowledge assessment (pre 45 ± 11% vs. post 71 ± 9%; p<0.0001). Post-intervention tests showed significant increases in knowledge every year, with a similar mean rate of improvement from year to year (25±10%; p=0.15). Participants in 2015 did score higher on both pre and post testing (pre 55±10%, post 85±7%; p<0.0001), but the improvement rate remained consistent. Pre- and post-program surveys showed significant improvement in 38 of 38 domains assessing comfort and anxiety (p<0.001 for each domain). All participants strongly agreed (97%) or agreed (3%) that the boot camp was a valuable learning experience and 98% strongly agreed (66%) or agreed (32%) that boot camp alleviated anxieties about starting fellowship. Conclusions: The Pediatric Cardiology Boot Camp provides a significant and reproducible educational benefit to participants nationwide. This intensive program simultaneously improves learners’ knowledge and alleviates anxiety as they transition to subspecialty training.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.011
metaresearch head score (Gemma)0.031
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.014
Threshold uncertainty score0.057

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.031
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0070.001

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.

Opus teacher head0.100
GPT teacher head0.337
Teacher spread0.237 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2020
Admission routes1
Has abstractyes

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