Community engagement in general practice: a qualitative study
Bibliographic record
Abstract
BACKGROUND Community engagement is believed to be an important component of quality primary health care. We aimed to capture specific examples of community engagement by general practices, and to understand the barriers that prevent engagement. METHODS We conducted 20 distinct interviews with 31 key informants from general practice and the wider community. The interviews were semi-structured around key relevant topics and were analysed thematically. RESULTS Key themes identified from the interview transcripts included an understanding of 'community', examples of community engagement and the perceived benefits and barriers to community-engaged general practice. We particularly explored aspects of community engagement with Māori. CONCLUSIONS General practices in the study do not think in terms of communities, and they do not have a systematic framework for engagement. Although local champions have generated some great initiatives, most practices seemed to lack a conceptual framework for engagement: who to engage with, how to engage with them, and how to evaluate the results of the engagement.
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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 | 0.021 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.011 | 0.009 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".