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Ecological Models Revisited: Their Uses and Evolution in Health Promotion Over Two Decades

2011· review· en· W2116190278 on OpenAlexafffund
Lucie Richard, Lise Gauvin, Kim D. Raine

Bibliographic record

VenueAnnual Review of Public Health · 2011
Typereview
Languageen
FieldHealth Professions
TopicCommunity Health and Development
Canadian institutionsCentre Hospitalier de l’Université de MontréalUniversity of AlbertaUniversité de Montréal
FundersCanadian Institutes of Health Research
KeywordsSocial ecological modelEnthusiasmHealth promotionPromotion (chess)Conceptual modelEcologyEcological healthPublic healthEcological psychologyManagement scienceEnvironmental resource managementPolitical scienceComputer sciencePsychologyMedicineEnvironmental scienceBiologyPoliticsEngineeringEcosystemNursing

Abstract

fetched live from OpenAlex

Since the 1980s, ecological models of health promotion have generated a great deal of enthusiasm among researchers and interventionists. These models emerged from conceptual developments in other fields, and only selected elements of the ecological approach have been integrated into them. In this article, we describe the tenets of the ecological approach and highlight those aspects that have been integrated into ecological models used in health promotion. We also analyze how ecological models have been applied to the study of two important public health issues, namely physical activity promotion and the increased consumption of fruits and vegetables, by conducting an archival study of published research. Finally, we make a statement regarding the usefulness of ecological models for research and practice and propose recommendations for future research, program planning, and evaluation.

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)0.013
metaresearch head score (Gemma)0.015
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.019
Threshold uncertainty score0.067

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0130.015
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0040.002
Bibliometrics0.0060.009
Science and technology studies0.0010.015
Scholarly communication0.0060.009
Open science0.0030.004
Research integrity0.0050.010
Insufficient payload (model declined to judge)0.0030.001

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.

Opus teacher head0.358
GPT teacher head0.536
Teacher spread0.178 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations604
Published2011
Admission routes2
Has abstractyes

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