Qualitative examination of collaboration in team-based primary care during the COVID-19 pandemic
Bibliographic record
Abstract
OBJECTIVE: The objective of this study was to describe Ontario primary care teams' experiences with collaboration during the COVID-19 pandemic. Descriptive qualitative methods using focus groups conducted virtually for data collection. SETTING: Primary care teams located in Ontario, Canada. PARTICIPANTS: Our study conducted 11 focus groups with 10 primary care teams, with a total of 48 participants reflecting a diverse range of interprofessional healthcare providers and administrators working in primary care. RESULTS: Three themes were identified using thematic analysis: (1) prepandemic team functioning facilitated adaptation, (2) new processes of team interactions and collaboration, and (3) team as a foundation of support. CONCLUSIONS: Results revealed the importance of collaboration for provider well-being, and the challenges of providing collaborative team-based primary care in the pandemic context. Caution against converting primary care collaboration to predominantly virtual modalities postpandemic is recommended. Further research on team functioning during the COVID-19 pandemic in other healthcare organisations will offer additional insight regarding how primary care teams can work collaboratively in a postpandemic environment.
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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 | 0.016 | 0.024 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.014 | 0.012 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".