Indices and Indicators Developed to Evaluate the “Strengthening Community Actions” Mechanism of the Ottawa Charter for Health Promotion: A Scoping Review
Bibliographic record
Abstract
Objective To determine 1) the indexes/indicators used for evaluating the “strengthening community actions” mechanism of the Ottawa Charter for Health Promotion and 2) to extract the characteristics and key components of the indexes/indicators using a scoping review. Data Source:In May 2020, the search was conducted across three databases: Medline (via PubMed), Embase, and Scopus. Inclusion and Exclusion Criteria: All primary studies relating to development, identification, and measurement of health promotion indices/indicators associated to the “strengthening community actions” were included. The review articles were excluded. Data Extraction The data were extracted to a data-charting form that was developed by the research team. Two authors reviewed the extracted data. Data Synthesis To summarize and report the data, a descriptive numerical analysis and a narrative descriptive synthesizing approach were used. Results In total, 93 study articles were included. A majority of studies (82%) were conducted in developed countries. Different types of recognized indices were categorized into seven groups: social cohesion (n = 3), community capacity (n = 1), community participation (n = 7), social capital (n = 6), social network (n = 3), social support (n = 1), and others (n = 5). Conclusions Having a collection of “strengthening community actions” indices/indicators in hand, health policymakers and health promotion specialists might be able to do their best in considering, selecting, and applying the most appropriate indices/indicators while evaluating community health promotion interventions in different settings.
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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 | 0.159 | 0.282 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.007 | 0.007 |
| Bibliometrics | 0.060 | 0.053 |
| Science and technology studies | 0.004 | 0.005 |
| Scholarly communication | 0.013 | 0.010 |
| Open science | 0.005 | 0.007 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 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".