Twenty years with the public health intervention wheel: Evidence for practice
Bibliographic record
Abstract
The Public Health Intervention Wheel (PHI Wheel) is a population-based practice model for public health nursing practice that encompasses three levels of practice (community, systems, individual/family) and 17 public health interventions. This article shares the story of how the PHI Wheel was created, disseminated, implemented by public health nurses (PHNs) and educators across the globe, and updated with new evidence published in the second edition of Public Health Interventions: Applications for Public Health Nursing in 2019. Evidence on the relevance of PHI Wheel interventions for public health practice in cultural and international settings supports the model's value in explaining PHN practice. This article highlights the experiences of various countries with the PHI Wheel including Canada, Ireland, New Zealand, Norway, Sweden, the United Kingdom, and the United States. The evidence update confirms the relevance of the model to PHN education and practice and reinforces the conviction that development of new evidence is essential for promoting population health.
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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 | 0.087 | 0.239 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.003 | 0.006 |
| Scholarly communication | 0.011 | 0.013 |
| Open science | 0.003 | 0.009 |
| Research integrity | 0.004 | 0.008 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".