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Record W2624003318 · doi:10.22230/jripe.2017v6n2a235

The Impact of Hidden Curriculum in Wilderness-Based Educational Events on Interprofessional Competencies: A Mixed-Method Study

2017· article· en· W2624003318 on OpenAlexafffundvenue
Maurianne Reade, Marion Maar, Nicole Cardinal, Lisa Boesch, Sara Lacarte, Tara Rollins, Nicholas Jeeves

Bibliographic record

VenueJournal of Research in Interprofessional Practice and Education · 2017
Typearticle
Languageen
FieldHealth Professions
TopicInterprofessional Education and Collaboration
Canadian institutionsNOSM UniversityLaurentian University
FundersNorthern Ontario Academic Medicine Association
KeywordsCurriculumInterprofessional educationMedical educationMedicineTest (biology)Event (particle physics)PsychologyNursingPedagogyHealth care

Abstract

fetched live from OpenAlex

Background: The purpose of this study was to determine if interprofessional skills, attitudes, and behaviours could be learned during an austere medicine educational activity where interprofessionalism remained within the informal and hidden curriculum.Methods and Findings: We used a mixed-methods approach to examine the potential acquisition of interprofessional competencies during wilderness medicine educational events. Thirty-four participants, over two events, completed interprofessional learner contracts, audio diary entries between patient scenarios, and the Interprofessional Collaborative Competency Attainment Survey (ICCAS) using a retrospective pre-test/post-test design. Audio diary entries showed the reflection that took place between scenarios during the orienteering portion of the event and the adjustments toward interprofessionalism that took place. Both the survey and audio diaries confirmed that participants perceived an improvement of their interprofessional competencies after the WildER Med event.Conclusions: The outcomes confirm that interprofessional competencies can be developed during a learning event such as WildER Med, where the interprofessional curriculum is hidden. Austere medicine, which is at the base of this learning event, represents an opportunity for the further understanding and exploration of interprofessional education.

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)0.014
metaresearch head score (Gemma)0.013
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies, Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.129
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0140.013
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.003
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 head0.084
GPT teacher head0.620
Teacher spread0.535 · 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

Citations3
Published2017
Admission routes3
Has abstractyes

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