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Record W2794141785 · doi:10.1080/13561820.2018.1433641

Interprofessional education day – an evaluation of an introductory experience for first-year students

2018· article· en· W2794141785 on OpenAlexaffabout
Zachary Singer, Kevin Fung, Elaine Lillie, Jennifer S. McLeod, Grace Scott, Peng You, Krista Helleman

Bibliographic record

VenueJournal of Interprofessional Care · 2018
Typearticle
Languageen
FieldHealth Professions
TopicInterprofessional Education and Collaboration
Canadian institutionsUniversity of WaterlooLondon Health Sciences CentreWestern University
Fundersnot available
KeywordsInterprofessional educationMedical educationCompetence (human resources)PharmacyMedicinePerceptionPsychologyHealth careNursing

Abstract

fetched live from OpenAlex

Interprofessional health care teams have been shown to improve patient safety and reduce medical errors, among other benefits. Introducing interprofessional concepts to students in full day events is an established model that allows students to learn together. Our group developed an academic day for first-year students devoted to an introductory interprofessional education (IPE) experience, 'IPE Day'. In total, 438 students representing medicine, dentistry, pharmacy and optometry gathered together, along with 25 facilitators, for IPE Day. Following the day's program, students completed the evaluation consisting of the Interprofessional Collaborative Competencies Attainment Survey and open-ended questions. Narrative responses were analyzed for content and coded using the Canadian Interprofessional Health Collaborative competency domains. Three hundred and eight evaluations were completed. Students reported increased self-ratings of competency across all 20 items (p < 0.05). Their comments were organized into the six domains: interprofessional communication, collaborative leadership, role clarification, patient-centred care, conflict resolution, and team functioning. Based on these findings, we suggest that this IPE activity may be useful for improving learner perceptions about their interprofessional collaborative practice competence.

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)0.004
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.375
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.047
GPT teacher head0.532
Teacher spread0.486 · 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 designQualitative
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

Citations35
Published2018
Admission routes2
Has abstractyes

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