Primary health care and general practice nurses: What is the nexus?
Bibliographic record
Abstract
This paper presents the findings from three separate qualitative studies that sought to explore the current and potential role of nurses employed in general medical practices in Australia. General practitioners', practice nurses' and consumers' views and perceptions were gathered from individual and group interviews. The data indicate that practice nurses (PNs) are involved in first level or primary care of individuals and engage in some form of preventive health care. Some PNs have a family/community focus in addition to their focus of care on individuals. Engagement in health promotion was found to be opportunistic rather than planned, and focussed on interventions to free individuals from medically defined diseases - the aim being compliance with therapeutic procedures and advice. The broader concept of health promotion, as documented in the Ottawa Charter for Health Promotion, was not pronounced in the PNs' reported practice. Consumers do not articulate confidence in PNs acting autonomously as primary health care practitioners but rather as complementary to general practitioners (GPs), undertaking initial assessment for triage purposes and providing ongoing management, education and support under the GPs' delegation. They would also like them to be family-oriented and holistic in their practice; supporting emotional and social needs in the context of their family lives.
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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 | 0.023 | 0.037 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.008 | 0.017 |
| Scholarly communication | 0.011 | 0.013 |
| Open science | 0.002 | 0.012 |
| Research integrity | 0.006 | 0.004 |
| 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".