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Record W2116086294 · doi:10.3109/0142159x.2012.737966

Patients as educators: Interprofessional learning for patient-centred care

2013· article· en· W2116086294 on OpenAlexaff
Angela Towle, William Godolphin

Bibliographic record

VenueMedical Teacher · 2013
Typearticle
Languageen
FieldHealth Professions
TopicInterprofessional Education and Collaboration
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsInterprofessional educationMedical educationMedicineMEDLINEPsychologyPatient careNursingHealth carePolitical science

Abstract

fetched live from OpenAlex

BACKGROUND: Patients with chronic conditions have unique expertise that enhances interprofessional education. Although their active involvement in education is increasing, patients have minimal roles in key educational tasks. A model that brings patients and students together for patient-centred learning, with faculty playing a supportive role, has been described in theory but not yet implemented. AIMS: To identify issues involved in creating an educational intervention designed and delivered by patients and document outcomes. METHOD: An advisory group of community members, students and faculty guided development of the intervention (interprofessional workshops). Community educators (CEs) were recruited through community organizations with a healthcare mandate. Workshops were planned by teams of key stakeholders, delivered by CEs, and evaluated by post-workshop student questionnaires. RESULTS: Workshops were delivered by CEs with epilepsy, arthritis, HIV/AIDS and two groups with mental health problems. Roles and responsibilities of planning team members that facilitated control by CEs were identified. Ten workshops attended by 142 students from 15 different disciplines were all highly rated. Workshop objectives defined by CEs and student learning both closely matched dimensions of patient-centredness. CONCLUSIONS: Our work demonstrates feasibility and impact of an educational intervention led by patient educators facilitated but not controlled by faculty.

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)0.000
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.381
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.003
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 integrity0.0000.001
Insufficient payload (model declined to judge)0.0710.004

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 head0.019
GPT teacher head0.399
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; both teacher heads agree on what is shown here.

Study designNot applicable
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

Citations105
Published2013
Admission routes1
Has abstractyes

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