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Record W4396801414 · doi:10.1080/13561820.2024.2343828

Dissecting through the decade: a 10-year cross-sectional analysis of interprofessional experiences in the anatomy lab

2024· article· en· W4396801414 on OpenAlexafffund
Shirley Quach, Sakshi Sinha, Alexandra Todd, Andrew Palombella, Jasmine Rockarts, Sarah Wojkowski, Bruce Wainman, Yasmeen Mezil

Bibliographic record

VenueJournal of Interprofessional Care · 2024
Typearticle
Languageen
FieldHealth Professions
TopicInterprofessional Education and Collaboration
Canadian institutionsMcMaster University
FundersMcMaster University
KeywordsMedical educationMedicinePsychologyAnatomy

Abstract

fetched live from OpenAlex

Interprofessional education (IPE) is prioritized as a critical component in preparing pre-licensure health professional students for effective teamwork and collaboration in the workplace to facilitate patient-centered care. Knowledge in anatomy is fundamental for healthcare professionals, making interprofessional anatomy education an attractive intervention for IPE and anatomy learning. Since 2009, the Education Program in Anatomy at McMaster University has offered an intensive 10-week IPE Anatomy Dissection elective to seven health professional programs annually. From 2011, students were invited to complete the Readiness for Interprofessional Scale (RIPLS) and Interprofessional Education Perception Scale (IEPS) before and after the elective. A total of 264 students from 2011 to 2020 completed RIPLS and IEPS. There were significant differences before and after the elective in students' total RIPLS scores and three of the four subscales: teamwork and collaboration, positive professional identity, and roles and responsibilities. Similarly, there were statistical differences in the total IEPS scores and two of three subscales: competency and autonomy and perceived actual cooperation. Statistically significant differences in RIPLS and IEPS total scores across several disciplines were also observed. This study demonstrates the elective's impact in improving students' IPE perceptions and attitudes, likely from the extended learning and exposure opportunity with other disciplines.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesResearch integrity, Insufficient 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 score0.287
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.003
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0050.000

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 head0.037
GPT teacher head0.504
Teacher spread0.467 · 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

Citations11
Published2024
Admission routes2
Has abstractyes

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