Knowledge flow and exchange in interdisciplinary primary health care teams (PHCTs): an exploratory study
Bibliographic record
Abstract
OBJECTIVE: Improving the process of evidence-based practice in primary health care requires an understanding of information exchange among colleagues. This study explored how clinically oriented research knowledge flows through multidisciplinary primary health care teams (PHCTs) and influences clinical decisions. METHODS: This was an exploratory mixed-methods study with members of six PHCTs in Ontario, Canada. Quantitative data were collected using a questionnaire and analyzed with social network analysis (SNA) using UCINet. Qualitative data were collected using semi-structured interviews and analyzed with content analysis procedures using NVivo8. RESULTS: It was found that obtaining research knowledge was perceived to be a shared responsibility among team members, whereas its application in patient care was seen as the responsibility of the team leader, usually the senior physician. PHCT members acknowledged the need for resources for information access, synthesis, interpretation, or management. CONCLUSION: Information sharing in interdisciplinary teams is a complex and multifaceted process. Specific interventions need to be improved such as formalizing modes of communication, better organizing knowledge-sharing activities, and improving the active use of allied health professionals. Despite movement toward team-based models, senior physicians are often gatekeepers of uptake of new evidence and changes in practice.
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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 | 0.013 | 0.035 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.007 | 0.003 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.005 |
| 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".