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Record W2135428518 · doi:10.1177/1524839905278955

Understanding Facilitators of and Barriers to Health Promotion Practice

2006· article· en· W2135428518 on OpenAlexaffabout
Kerry Robinson, S. Michelle Driedger, Susan J. Elliott, John Eyles

Bibliographic record

VenueHealth Promotion Practice · 2006
Typearticle
Languageen
FieldHealth Professions
TopicCommunity Health and Development
Canadian institutionsUniversity of ManitobaMcMaster UniversityCanadian Heart Research Centre
Fundersnot available
KeywordsHealth promotionPublic relationsPromotion (chess)Health carePublic healthMedicineNursingHealth educationPopulation healthHealth policyPolitical sciencePolitics

Abstract

fetched live from OpenAlex

The health promotion best practices literature is imbued with hope for knowledge mobilization, enhanced practice, and improved population health. Given constrained medical care systems, health promotion is key to reducing the significant burden of chronic disease. However, we have seen little evidence of change. This article investigates facilitators of, and barriers to, three stages of health promotion practice in public health organizations, interagency coalitions, and volunteer committees. The article focuses not on what works but why it does or does not, drawing on five case studies within the Canadian Heart Health Initiative. Results indicate that the presence or absence of appropriately committed and/or skilled people, funds and/or resources, and priority and/or interest are the most common factors affecting all stages of health promotion practice. The article extends the literature on internal and external factors affecting health promotion and highlights strategic influences to consider in support of effective health promotion practice.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.026
metaresearch head score (Gemma)0.067
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.026
Threshold uncertainty score0.139

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0260.067
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0050.005
Scholarly communication0.0050.002
Open science0.0010.005
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0030.000

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.

Opus teacher head0.248
GPT teacher head0.496
Teacher spread0.248 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

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".

Quick stats

Citations58
Published2006
Admission routes2
Has abstractyes

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