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Record W4281870902 · doi:10.1007/s10459-022-10128-4

The implementation of interprofessional education: a scoping review

2022· review· en· W4281870902 on OpenAlexaff
Fiona Bogossian, Karen New, Kendall George, Nigel Barr, Natalie Dodd, Anita Hamilton, Greg Nash, Nicole Masters, Fiona Pelly, Carol Reid, Rebekah Shakhovskoy, Jane Taylor

Bibliographic record

VenueAdvances in Health Sciences Education · 2022
Typereview
Languageen
FieldHealth Professions
TopicInterprofessional Education and Collaboration
Canadian institutionsCARE Canada
FundersUniversity of the Sunshine Coast
KeywordsInterprofessional educationContext (archaeology)CurriculumThematic analysisGovernment (linguistics)Implementation researchMedical educationProcess managementPsychologyMedicineQualitative researchPolitical scienceHealth careNursingSociologyPedagogyEngineeringPsychological intervention

Abstract

fetched live from OpenAlex

INTRODUCTION: Implementation of interprofessional education (IPE) is recognised as challenging, and well-designed programs can have differing levels of success depending on implementation quality. The aim of this review was to summarise the evidence for implementation of IPE, and identify challenges and key lessons to guide faculty in IPE implementation. METHODS: Five stage scoping review of methodological characteristics, implementation components, challenges and key lessons in primary studies in IPE. Thematic analysis using a framework of micro (teaching), meso (institutional), and macro (systemic) level education factors was used to synthesise challenges and key lessons. RESULTS: Twenty-seven primary studies were included in this review. Studies were predominantly descriptive in design and implementation components inconsistently reported. IPE was mostly integrated into curricula, optional, involved group learning, and used combinations of interactive and didactic approaches. Micro level implementation factors (socialisation issues, learning context, and faculty development), meso level implementation factors (leadership and resources, administrative processes), and macro level implementation factors (education system, government policies, social and cultural values) were extrapolated. Sustainability was identified as an additional factor in IPE implementation. CONCLUSION: Lack of complete detailed reporting limits evidence of IPE implementation, however, this review highlighted challenges and yielded key lessons to guide faculty in the implementation of IPE.

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)0.005
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.881
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.003
Science and technology studies0.0030.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
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 head0.090
GPT teacher head0.644
Teacher spread0.555 · 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 designOther design
Domainnot available
GenreReview

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

Citations140
Published2022
Admission routes1
Has abstractyes

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