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Record W2016303085 · doi:10.12927/cjnl.2010.21727

Different Roles, Same Goal: Students Learn about Interprofessional Practice in a Clinical Setting

2010· article· en· W2016303085 on OpenAlexafffundvenueabout
Susan Glover Takahashi, Sharon Brissette, Kelly Thorstad

Bibliographic record

VenueNursing leadership · 2010
Typearticle
Languageen
FieldHealth Professions
TopicInterprofessional Education and Collaboration
Canadian institutionsShriners Hospitals for Children - Canada
FundersToronto Rehabilitation InstituteShriners Hospitals for Children
KeywordsNursingInterprofessional educationHealth careWork (physics)Medical educationMedicinePsychology

Abstract

fetched live from OpenAlex

The Shriners Hospitals for Children-Canada has developed an innovative Interprofessional Education Program to help tomorrow's healthcare professionals gain the skills and knowledge they need to work effectively in teams to provide efficient, collaborative and family-centred care. Undergraduate students in nursing, physiotherapy and occupational therapy participated in group discussions, seminars by staff members and group presentations. Students reported increased understanding of their own and others' roles and a more holistic view of patients and families, and demonstrated their ability to work in teams to create collaborative care plans. Facilitating factors were a strong existing interprofessional team, administrative buy-in and support, consistent clinical nurse specialist involvement and strong, enthusiastic students. Challenges included logistics, time taken away from students' regular clinical time, time required of staff for program planning and implementation, and the difficulty of evaluating effects on patient care. The program shows promise as a way of introducing students to interprofessional practice and giving them a chance to practise their newly acquired skills in a clinical setting. It also has the potential to enhance staff awareness of interprofessional issues and facilitate staff development.

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)0.003
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesResearch integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.103
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.005
Insufficient payload (model declined to judge)0.0010.001

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 head0.152
GPT teacher head0.531
Teacher spread0.380 · 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

Citations13
Published2010
Admission routes4
Has abstractyes

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