Interprofessional education for students of the health professions: The “Seamless Care” model
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
"Seamless Care" was one of 21 grants awarded by Health Canada to inform policymakers of the effectiveness of interprofessional education in promoting collaborative patient-centred practice among health professionals. The "Seamless Care" model of interprofessional education was designed with input from three Faculties at Dalhousie University (Medicine, Dentistry and Health Professions). The design was grounded in relevant learning theories--Social Cognitive Theory, Self-efficacy, Situated Learning theory and Constructivism. The intervention was informed by principles of active learning, problem-based learning, reflection and role modeling. The primary goal of Seamless Care was to develop students' interprofessional patient-centred collaborative skills through experiential learning. Fourteen student teams, each including one student from medicine, nursing, pharmacy, dentistry and dental hygiene, learned with, from and about each other while they were mentored in the collaborative care of patients transitioning from acute care to the community. Student teams providing collaborative care assisted patients experiencing a chronic illness to become more active in managing their health through development of self-management and decision-making skills. This paper describes the Seamless Care model of interprofessional education and discusses the theoretical underpinnings of this experiential model of interprofessional education designed to extend classroom-based interprofessional education to the clinical setting.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it