Examining the extent and factors associated with interprofessional teamwork in primary care settings
Bibliographic record
Abstract
Despite growing emphasis on adopting team-based models of primary care to facilitate patient access to a diverse range of care providers, our understanding of team functioning within primary care teams remains limited. This study examined interprofessional teamwork within primary care practices (Family Health Teams [FHT] and Community Health Centers – [CHC]) in Ontario and explored team-level and organizational factors associated with interprofessional teamwork. Interprofessional teamwork was measured using the Collaborative Practice Assessment Tool (CPAT), which was completed by providers in each participating team. The CPAT responses of 988 providers representing on average 12 professions (sd = 2.1) across 66 teams (44 FHTs and 22 CHCs) were included in the analysis. The average CPAT score was 46.6 (sd = 2.5). CHCs had significantly higher CPAT scores than FHTs (mdiff = 1.7, p = .02). Using diverse communication mechanisms to share information, increasing quality improvement capacities, and age of practice, had a statistically significant positive association with CPAT scores. Increasing team size, using centralized administrative processes, a high level of information exchange, and having a mixed governance board were significantly negatively associated with CPAT score. Findings illustrate factors associated with interprofessional teamwork and offer insight into the comparative performance of two team-based primary care models in Ontario.
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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 | 0.003 | 0.015 |
| 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 | 0.000 | 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".