Advancing a theoretical model for public health and health promotion indicator development: Proposal from the EUHPID consortium
Bibliographic record
Abstract
This paper discusses the work of the EUHPID Project to develop a European Health Promotion Monitoring System based on a common set of health promotion indicators. The Project has established three working groups to progress this task - health promotion policy and practice-driven, data-driven and theory-driven. The work of the latter group is reviewed in particular. EUHPID has taken a systems theory approach in order to develop a model as a common frame of reference and a rational basis for the selection, organization and interpretation of health promotion indicators. After reviewing the strengths and weaknesses of those health promotion models currently proposed for indicator development, the paper proposes a general systems model of health development, and specific analytical, socio-ecological models related to public health and health promotion. These are described and discussed in detail. Taking the Ottawa Charter as the preferred framework for health promotion, the socio-ecological model for health promotion adopts its five action areas to form five types of systems. The structure and processes for each of these five systems are proposed to form the basis of a classification system for health promotion indicators. The paper goes on to illustrate such a system with reference to indicators in the workplace setting. The EUHPID Consortium suggest that their socio-ecological model could become a common reference point for the public health field generally, and offer an invitation to interested readers to contribute to this development.
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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 | 0.088 | 0.060 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.012 | 0.010 |
| Science and technology studies | 0.007 | 0.036 |
| Scholarly communication | 0.021 | 0.022 |
| Open science | 0.009 | 0.016 |
| Research integrity | 0.011 | 0.009 |
| Insufficient payload (model declined to judge) | 0.005 | 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".