Do preventative care guidelines emphasize behaviour change? A content analysis of three commonly used Australian general practice guidelines
Bibliographic record
Abstract
RATIONALE: Preventive health is a core part of primary care clinical practice and it is critical for both disease prevention and reducing the consequences of chronic disease. In primary care, the 5As framework is often used to guide behaviour change consultations for smoking, nutrition, alcohol use and physical activity. AIMS AND OBJECTIVES: Our objective was to analyze the emphasis placed on each 5As term in commonly used guidelines in Australian general practice and compare this to behaviour change terms/concepts essential to effective consultations. METHOD: A content analysis was undertaken to explore frequency of 5A terms and key behaviour change concepts/terms chapter-by-chapter across the three most commonly used guidelines in Australian general practice. RESULTS: The prevalence of each 5As term differed in all three guidelines, with 'Arrange' being mentioned the least often. Behaviour change concepts and terms, such as patient-centredness, listening, trust and tailoring, were infrequently used and were often confined to a separate chapter of the guidelines. CONCLUSION: The language and content of the guidelines contrast with known effective components of behaviour change consultations. Future revisions could reconsider emphasis of 5As terms to avoid paternalistic approaches, improve shared language across guidelines and incorporate behavioural science principles to enhance preventative care delivery.
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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 | 0.025 | 0.118 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.009 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| 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".