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Record W2153854526 · doi:10.1136/jech.57.9.668

Bicycle helmet campaigns and head injuries among children. Does poverty matter?

2003· article· en· W2153854526 on OpenAlexaff
Céline Farley

Bibliographic record

VenueJournal of Epidemiology & Community Health · 2003
Typearticle
Languageen
FieldMedicine
TopicInjury Epidemiology and Prevention
Canadian institutionsInstitut National de Santé Publique du Québec
Fundersnot available
KeywordsMedicinePovertyEnvironmental healthInjury preventionOccupational safety and healthPoison controlSuicide preventionPopulationHead injuryDemographySurgeryEconomic growth

Abstract

fetched live from OpenAlex

OBJECTIVES: To assess the impact of a community based bicycle helmet programme aimed at children aged 5-12 years (about 140,000) from poor and well off municipalities. METHODS: A quasi-experimental design, including a control group, was used. Changes in the risk of bicycle related head injuries leading to hospitalisation were measured, using rates ratios. RESULTS: Reductions in bicycle related head injuries were registered in both categories of municipalities. Compared with the pre-programme period, the protective effect of the programme during the post-programme period was as significant among children from poor municipalities (RR= 0.45 95%CI 0.26 to 0.78) as among those from richer municipalities (RR=0.55 95%CI 0.41 to 0.75). CONCLUSION: Population based educational programmes may have a favourable impact on injury risks in poor areas despite lower adoption of protective behaviours.

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)0.024
metaresearch head score (Gemma)0.008
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesResearch integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.025
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0240.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.003
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 head0.048
GPT teacher head0.394
Teacher spread0.347 · 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

Citations9
Published2003
Admission routes1
Has abstractyes

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