Gaps in Developmental Pediatrics training: A Canadian resident physician perspective
Bibliographic record
Abstract
This article was migrated. The article was marked as recommended. Introduction: Postgraduate medical training worldwide has recently experienced a transition to Competency-Based Medical Education (CBME). This provides a timely opportunity to critically evaluate the postgraduate medical curriculum, particularly from a trainee perspective. Studies reveal that Canadian residents and recent graduates in pediatrics and family medicine are uncomfortable with their proficiency in child development. However, little is known about residents' perceptions of their training, nor where specific needs lie. We therefore sought to identify gaps in developmental pediatrics training, with the goal of informing the development of a new CBME curriculum. Methods: An online cross sectional needs assessment survey was administered to current pediatrics and family medicine residents at our institution. A total of 63 residents participated, 43 pediatrics and 20 family medicine. Results: Four key themes emerged from analysis of survey results: 1. Residents agree that developmental pediatrics is relevant to future practice and competency; 2. Residents feel they lack competency in the assessment and management of patients with developmental issues; 3. Residents' feelings of insufficient and inadequate training increase over time; 4. Residents recommend changes to developmental pediatrics training. Conclusion: As we prepare to transition to CBME, curriculum should be purposefully developed to meet resident identified need and reflect appropriate competencies required for clinical practice.
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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 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.012 | 0.005 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.007 | 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".