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Record W1622139406 · doi:10.1002/pmj.21507

Multi-Level Efficacy Evidence of a Combined Interprofessional Collaboration and Project Management Training Program for Healthcare Project Teams

2015· article· en· W1622139406 on OpenAlexaff
François Chiocchio, François Rabbat, Paule Lebel

Bibliographic record

VenueProject Management Journal · 2015
Typearticle
Languageen
FieldHealth Professions
TopicInterprofessional Education and Collaboration
Canadian institutionsUniversité de MontréalUniversity of Ottawa
Fundersnot available
KeywordsTeamworkHealth careContext (archaeology)Project managementCLARITYTask (project management)Work (physics)Knowledge managementProject teamMedical educationProcess managementEngineeringMedicineComputer scienceManagementPolitical science

Abstract

fetched live from OpenAlex

Project work is essential for the improvement of healthcare organizations; yet, project management and collaboration in the project context are not taught to healthcare professionals. Three half-day training workshops integrating project management and collaboration were designed and delivered to 14 interprofessional healthcare project teams. Multivariate measures were taken over the course of 36 weeks. Individual, team, and project-level results showed high satisfaction and perceptions of utility; improved self-efficacy for project-specific task work and teamwork; increased goal clarity and coordination; and a significant impact on the functional performance of projects. This study provides initial benchmark measures regarding the pertinence of project management and interprofessional collaboration training for healthcare project teams.

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)0.017
metaresearch head score (Gemma)0.044
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 score0.017
Threshold uncertainty score0.092

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0170.044
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.246
GPT teacher head0.536
Teacher spread0.290 · 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

Citations49
Published2015
Admission routes1
Has abstractyes

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