MétaCan
Menu
Back to cohort
Record W4414139825 · doi:10.12688/mep.21183.1

Perceptions of interprofessional collaboration among University of Montreal’s pediatric residents rotating through the Pediatric Intensive Care Unit: Mixed-method analysis of the current situation and recommendations for future innovative teaching-learning activities

2025· article· en· W4414139825 on OpenAlexaboutno aff
Alex Lepage-Farrell, Amélie Richard, Baruch Toledano, Anne-Marie Pinard

Bibliographic record

VenueMedEdPublish · 2025
Typearticle
Languageen
FieldHealth Professions
TopicInterprofessional Education and Collaboration
Canadian institutionsnot available
Fundersnot available
KeywordsPsychological interventionIntensive carePerceptionHealth careInterprofessional educationMEDLINE

Abstract

fetched live from OpenAlex

<ns3:p>Background Interprofessional collaboration is essential for healthcare workers in intensive care units. To collaborate effectively, doctors must be trained in medical schools. Unfortunately, training is uneven across residency programs. The objectives of this project were to explore the collaborative training needs of pediatric residents at the University of Montreal program and then make recommendations for the development of future training activities. Methods This was a mixed-methods study. Results Our study explored perceptions of collaboration between residents and their colleagues (doctors, nurses, respiratory therapists, pharmacists), and the barriers and facilitators to training, particularly during the pediatric intensive care rotation. Conclusions This study provides helpful and insightful suggestions for fostering interprofessional education among pediatric trainees. Interventions must be implemented locally to better clarify the role of the resident within the team, provide more support to physician teachers, and integrate the rest of the professional team into training and assessment.</ns3:p>

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.284
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.004
Science and technology studies0.0020.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.018
GPT teacher head0.410
Teacher spread0.392 · 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 teacher head, not a consensus.

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

Citations0
Published2025
Admission routes1
Has abstractyes

Explore more

Same venueMedEdPublishSame topicInterprofessional Education and CollaborationFrench-language works237,207