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Record W2761682905 · doi:10.1093/pch/19.6.e35-138

141: Self-Evaluation of Procedural Skill Competencies By Neonatal Perinatal Medicine Trainees in Canada

2014· article· en· W2761682905 on OpenAlexaffabout
Elsa Fiedrich, Harish Amin, Jonathan White, Chloë Joynt

Bibliographic record

VenuePaediatrics & Child Health · 2014
Typearticle
Languageen
FieldHealth Professions
TopicPrimary Care and Health Outcomes
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsCompetence (human resources)Likert scaleMedicineFamily medicineMedical educationNursingPsychologyDevelopmental psychology

Abstract

fetched live from OpenAlex

Procedural competence is defined as “the ability to perform a procedure independently, without supervision, with a high likelihood of successful completion” (Gaies MG et al. Pediatrics. 2007;120(4):715–22). The Royal College of Physicians and Surgeons of Canada has outlined 19 procedural skills for Neonatal-Perinatal Medicine (NPM) trainees to demonstrate competence by the end of a two-year program. It is unclear how Canadian NPM training programs prepare their residents to acquire these procedural skills. There is no formal way to evaluate which competencies require increased training or exposure. To examine the self-reported attitudes and procedural skill competencies of Neonatal Perinatal Medicine trainees across Canada for 19 procedural skills listed by the Royal College for NPM training. A cross-sectional confidential electronic survey was sent to first and second year NPM trainees in 13 Canadian NPM programs (2012–2013). A five-point Likert scale was used to rate perceived importance (1 = not important to 5 = very important) and competence (1 = not competent to 5 = neonatologist) of each skill before and during their NPM training. Demographic and training data was collected. Two-tailed paired t tests (P<0.05) were used to analyze pre versus current training “competence” for each skill. Only anonymous aggregate data was reported. A total of 47 trainees (68%) completed the survey of which 36 consenting respondents with >6 months Canadian NPM training were analyzed. Only 25% of trainees were FRCPC exam eligible (CMG) (25%), with majority of respondents 12 to 24 months (47.3%) into their training. There were larger changes in pre versus current training perceived competencies in CMG compared to international medical graduates. Most CMG's procedural skills reached competence and improved by >1 during training, with the exception of suprapubic (mean difference 0.55), urinary catheterization (0.67), pericardiocentesis (0.45), and paracentesis (1.00). Pericardiocentesis did not meet competence (1.9/5) despite type and duration of training. Skills performed frequently in NICU (compared to pediatric residencies): umbilical lines (1.3), intubation (1.2), chest tubes (1.7), PICC lines (1.7), and arterial lines (1.5) had a high level of change and competence. Despite training, some NICU procedures rated poorly (x/5) in self-rated competence including paracentesis (2.4), PICC line insertion (3.1), suprapubic tap (2.2) and exchange transfusion (3.1). Observed skills most frequently done by trainees have the greatest change in competence during training for CMG in NPM. Some necessary procedural skills may require changes to instruction methods and these results could help guide curricular improvement.

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)0.002
metaresearch head score (Gemma)0.009
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.054
Threshold uncertainty score0.108

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.020
GPT teacher head0.337
Teacher spread0.316 · 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
Published2014
Admission routes2
Has abstractyes

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