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Record W4410285792 · doi:10.1177/17579759251332968

Health promotion in French national sports federations: the challenge of settings-based approach implementation

2025· article· en· W4410285792 on OpenAlexaboutno aff
Aurélie Van Hoye, Mathieu Winand, Laurianne Crochet, Florence Rostan, Fabienne Lemonnier, Stacey Johnson, Benjamin Tézier, Anne Vuillemin

Bibliographic record

VenueGlobal Health Promotion · 2025
Typearticle
Languageen
FieldHealth Professions
TopicSchool Health and Nursing Education
Canadian institutionsnot available
FundersUniversité Côte d’AzurUniversité de Lorraine
KeywordsHealth promotionPromotion (chess)Political sciencePublic relationsMedicineNursingPublic healthPolitics

Abstract

fetched live from OpenAlex

Research has shown that sports clubs call upon support from national sports federations (NSFs) to develop into a setting to promote health. The present study investigates how French NSFs themselves promote health. A two-step case study design was undertaken. A website analysis of 51 NSFs recognized as health promoting by the French National Olympic Committee was executed to examine health promotion (HP) visibility, and presence in strategic plans, committees and programs. Based on this search, four NSFs were chosen for an in-depth study, including interviews with representatives and a document analysis. Data were analyzed based on the Ottawa Charter strategies for HP. Results across all studied NSFs confirmed that NSFs are committed to HP, but HP is not mentioned directly, not visible, nor properly understood. Rather, a health topic approach is adopted, specifically focusing on strategies to enhance social and physical health. HP implementation lacks coordination, where resource investment is based on the sports ministry's focus on specific health topics, in a reactive manner, to implement national policies. NSFs' implementation of HP is very similar to that of a sports club, demonstrating that sports federations' vision and actions towards HP have to quit the silo and health topics approach in order to better support HP in their affiliated clubs. Future research should investigate determinants of HP implementation among NSFs. Practical implications include a recognition of HP beyond health topics, an integration of health as a transversal aim in NSFs' policies and programs, and a governance system to coordinate HP activities.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.006
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.802
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.080
GPT teacher head0.512
Teacher spread0.432 · 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 teacher head, not a consensus.

Study designObservational
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

Citations0
Published2025
Admission routes1
Has abstractyes

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