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The Long‐Term Effects of an Interprofessional Education Dissection Course on Healthcare Professional Students

2017· article· en· W2970847603 on OpenAlexaff
Yu Hang Zheng, Andrew Palombella, Jenn Salfi, Ilana Bayer, Bruce Wainman

Bibliographic record

VenueThe FASEB Journal · 2017
Typearticle
Languageen
FieldHealth Professions
TopicInterprofessional Education and Collaboration
Canadian institutionsBrock UniversityMcMaster University
Fundersnot available
KeywordsCourse (navigation)Health professionalsTerm (time)Interprofessional educationDissection (medical)Medical educationPsychologyMedicineHealth carePolitical scienceSurgeryEngineering

Abstract

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An intensive interprofessional gross anatomy dissection course was created in 2009 to facilitate interprofessional education (IPE) at McMaster University. First year students from Medicine, Nursing, Midwifery, Physician Assistant, Occupational Therapy, and Physiotherapy programs were randomly assigned into four interprofessional teams for this 10‐week course. Previously, data was collected from 2011 to 2016 using a before/after design to measure differences in attitudes and perceptions towards IPE and collaboration using the revised Readiness for Interprofessional Learning Scale (RIPLS) and Interdisciplinary Education Perception Scale (IEPS), while focus group data elaborated on the student experience with the course. Pre‐ and post‐matched data revealed significant improvements in positive professional identity, competency and autonomy, role clarity, and attitudes toward other health professions. Qualitative analysis of intraprofessional focus group interviews revealed meaningful improvements in a number of areas including learning anatomy, role clarity, and attitudes towards other health professions. The purpose of this study is to assess the long‐term effects of our IPE gross anatomy dissection course on past participants by quantitatively and qualitatively evaluating how their attitudes and perceptions have changed now that they have started working with other health care professionals outside of the IPE course setting. Past students were contacted via email and asked to fill out a follow‐up questionnaire consisting of a modified RIPLS and open‐ended questions to measure both quantitative and qualitative change, respectively. Thirty‐four past participants who have clinical experience working in an interprofessional setting or who are working in the healthcare field responded to the survey. Post‐course and follow‐up subscale score mean differences were analyzed using the Wilcoxon Signed‐Rank Test. Quantitative analysis revealed a significant decrease in teamwork and collaboration, and positive professional identity, but a significant improvement in their understanding of roles and responsibilities compared to their time in the course. Qualitative analysis of open‐ended questions revealed a number of themes including development of interprofessional competencies, anatomy learning through dissection, relationship building, and appreciation of the gross anatomy dissection course. Our results indicate that the IPE experience in anatomy was highly valued by the students and that past participants maintain a clear understanding of their scope of practice, but the reality of clinical practice may have eroded gains made in the program.

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)0.004
metaresearch head score (Gemma)0.011
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0010.001
Open science0.0010.002
Research integrity0.0010.001
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 head0.024
GPT teacher head0.495
Teacher spread0.471 · 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".

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Citations0
Published2017
Admission routes1
Has abstractyes

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