Interprofessionalism and shared decision-making in primary care: a stepwise approach towards a new 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
Most shared decision-making (SDM) models within healthcare have been limited to the patient-physician dyad. As a first step towards promoting an interprofessional approach to SDM in primary care, this article reports how an interprofessional and interdisciplinary group developed and achieved consensus on a new interprofessional SDM model. The key concepts within published reviews of SDM models and interprofessionalism were identified, analysed, and discussed by the group in order to reach consensus on the new interprofessional SDM (IP-SDM) model. The IP-SDM model comprises three levels: the individual (micro) level and two healthcare system (meso and macro) levels. At the individual level, the patient presents with a health condition that requires decision-making and follows a structured process to make an informed, value-based decision in concert with a team of healthcare professionals. The model acknowledges (at the meso level) the influence of individual team members' professional roles including the decision coach and organizational routines. At the macro level it acknowledges the influence of system level factors (i.e. health policies, professional organisations, and social context) on the meso and individual levels. Subsequently, the IP-SDM model will be validated with other stakeholders.
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.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.006 |
| 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