90 Effectiveness of “Pediatric Developmental Screening Days” on Resident Knowledge and Skills
Bibliographic record
Abstract
Canadian graduates of Pediatrics (GenPeds) residency programs report receiving inadequate training in child development in preparation for clinical practice. Developmental screening instruments allow early detection of childhood developmental disorders. Needs assessment indicated that clinical preceptors did not use screens, and residents’ primary personal learning objectives were red flags and referrals. We then developed a new curriculum to allow GenPeds residents to make experience-based decisions regarding screening in their future independent practice. (1) To determine whether this curriculum resulted in greater knowledge and skills (k+s) than controls (medical students and fourth year GenPeds residents). (2) To discover whether exam scores for k+s in screen scoring and management were greater after high volume practice Screening Days (SD) compared to scores immediately after the first year (R1) summer orientation teaching sessions (workshop). Forty-four R1, second (R2), and third (R3) year residents participated in the curriculum (2016–2018). Interventions included a SD in R1 and R3 Developmental Pediatrics (DevPeds) rotations following the interactive, case-based, hands-on workshop on scoring PEDS (Parents’ Evaluation of Developmental Status) + PEDS:DM (Developmental Milestones) and managing results of positive screens. Five different Short Answer Question exams were given on a variety of common parent concerns, at a total of 8 timepoints. One exam was repeated: immediately post-workshop and at R1, 2, and 3 end-year (during blocks 9 and 10 of 13-block year) in program OSCE. Four other exams were given at start (pre-) and end (post-) of DevPeds rotations. T-tests and Pearson’s chi-squared test were used to compare residents’ versus control group’s (n=14) mean total scores and percentage of passing. ANOVA and Pearson’s chi-squared test were used to compare R1, R2, and R3s’ mean total scores and percentage of passing. Results were significantly better than controls, at post-workshop, R2 R3 end-year, and R1 R3 post-rotation, for screen scoring and management of positive screen results which are moderately and highly predictive of developmental disorders; at R1 pre-rotation, scoring but not management was better; R1 end-year management was better, when most have had their SD; lack of difference at R3 pre-rotation suggests that k+s were not consolidated in absence of R2 practice. Screen scoring on the repeated exam was significantly better following SD (R2 R3 end-year) than post-workshop. Application of knowledge through screening experience effectively increased knowledge and skills in GenPeds residents. High volume practice Screening Days fostered greater results than hands-on workshop.
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".