Evaluation of perceived collaborative behaviour amongst stakeholders and clinicians of a continuing education programme in arthritis care
Bibliographic record
Abstract
Successful implementation of new extended practice roles which transcend conventional boundaries of practice entails strong collaboration with other healthcare providers. This study describes interprofessional collaborative behaviour perceived by advanced clinician practitioner in arthritis care (ACPAC) graduates at 1 year beyond training, and relevant stakeholders, across urban, community and remote clinical settings in Canada. A mixed-method approach involved a quantitative (survey) and qualitative (focus group/interview) evaluation issued across a 4-month period. ACPAC graduates work across heterogeneous settings and are on teams of diverse size and composition. Seventy per cent perceived their team as actively working in an interprofessional care model. Mean scores on the Bruyère Clinical Team Self-Assessment on Interprofessional Practice subjective subscales were high (range: 3.66-4.26, scale: 1-5 = better perception of team's interprofessional practice), whereas the objective scale was lower (mean: 4.6, scale: 0-9 = more interprofessional team practices). Data from focus groups (ACPAC graduates) and interviews (stakeholders) provided further illumination of these results at individual, group and system levels. Issues relating to ACPAC graduate role recognition, as well as their deployment, integration and institutional support, including access to medical directives, limitation of scope of practice, remuneration conflicts and tenuous funding arrangements were barriers perceived to affect role implementation and interprofessional working. This study offers the opportunity to reflect on newly introduced roles for health professionals with expectations of collaboration that will challenge traditional healthcare delivery.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.015 | 0.035 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".