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Record W2174838472 · doi:10.4278/0890-1171-18.2.168

An Integrative Framework for Community Partnering to Translate Theory into Effective Health Promotion Strategy

2003· review· en· W2174838472 on OpenAlexafffund
Allan Best, Daniel Stokols, Lawrence W. Green, Scott J. Leischow, Bev Holmes, Kaye Buchholz

Bibliographic record

VenueAmerican Journal of Health Promotion · 2003
Typereview
Languageen
FieldHealth Professions
TopicCommunity Health and Development
Canadian institutionsVancouver Hospital and Health Sciences Centre
FundersHealth Canada
KeywordsHealth promotionPromotion (chess)Community healthProcess managementPsychologyManagement scienceMedicinePublic relationsBusinessNursingPublic healthPolitical scienceEngineering

Abstract

fetched live from OpenAlex

INTRODUCTION: Although there is general agreement about the complex interplay among individual-, family-, organizational-, and community-level factors as they influence health outcomes, there is still a gap between health promotion research and practice. The authors suggest that a disjuncture exists between the multiple theories and models of health promotion and the practitioner's need for a more unified set of guidelines for comprehensive planning of programs. Therefore, we put forward in this paper an idea toward closing the gap between research and practice, a case for developing an overarching framework--with several health promotion models that could integrate existing theories--and applying it to comprehensive health promotion strategy. AN INTEGRATIVE FRAMEWORK: We outline a theoretical foundation for future health promotion research and practice that integrates four models: the social ecology; the Life Course Health Development; the Predisposing, Reinforcing, and Enabling Constructs in Educational/Environmental Diagnosis and Evaluation-Policy, Regulatory and Organizational Constructs in Educational and Environmental Development; and the community partnering models. The first three models are well developed and complementary. There is little consensus on the latter model, community partnering. However, we suggest that such a model is a vital part of an overall framework, and we present an approach to reconciling theoretical tensions among researchers and practitioners involved in community health promotion. INTEGRATING THE MODELS: THE NEED FOR SYSTEMS THEORY AND THINKING: Systems theory has been relatively ignored both by the health promotion field and, more generally, by the health services. We make a case for greater use of systems theory in the development of an overall framework, both to improve integration and to incorporate key concepts from the diverse systems literatures of other disciplines. VISION FOR HEALTHY COMMUNITIES: (1) Researchers and practitioners understand the complex interplay among individual-, family-, organizational-, and community-level factors as they influence population health; (2) health promotion researchers and practitioners collaborate effectively with others in the community to create integrated strategies that work as a system to address a wide array of health-related factors; (3) The Healthy People Objectives for the Nation includes balanced indicators to reflect health promotion realities and research-measures effects on all levels; (4) the gap between community health promotion "best practices" guidelines and the way things work in the everyday world of health promotion practice has been substantially closed. CONCLUSIONS AND RECOMMENDATIONS: We suggest critical next steps toward closing the gap between health promotion research and practice: investing in networks that promote, support, and sustain ongoing dialogue and sharing of experience; finding common ground in an approach to community partnering; and gaining consensus on the proposed integrating framework.

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)0.023
metaresearch head score (Gemma)0.012
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.023
Threshold uncertainty score0.123

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0230.012
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0050.004
Science and technology studies0.0050.031
Scholarly communication0.0100.011
Open science0.0040.009
Research integrity0.0050.005
Insufficient payload (model declined to judge)0.0120.001

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 head0.182
GPT teacher head0.570
Teacher spread0.389 · 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 designTheoretical or conceptual
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

Citations192
Published2003
Admission routes2
Has abstractyes

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