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Record W2021849786 · doi:10.1080/02699050802070752

Evaluating an in-school injury prevention programme's effect on children's helmet wearing habits

2008· article· en· W2021849786 on OpenAlexaff
Gary Blake, Diana Velikonja, Veronica Pepper, Irene Jilderda, Γεωργία Γεωργίου

Bibliographic record

VenueBrain Injury · 2008
Typearticle
Languageen
FieldMedicine
TopicInjury Epidemiology and Prevention
Canadian institutionsHamilton Health Sciences
Fundersnot available
KeywordsChecklistPhysical therapyMedicineRandomized controlled trialInjury preventionPoison controlPsychologySurgeryMedical emergency

Abstract

fetched live from OpenAlex

PRIMARY OBJECTIVE: To evaluate the effectiveness of the Bikes, Blades and Boards (BB&B) programme. It was hypothesized that children who participated in the BB&B programme would demonstrate greater knowledge of how to wear their helmets safely than a control group who did not participate in the programme and retain their skills when assessed 1 year later. RESEARCH DESIGN: Single blind cluster randomized design. METHODS AND PROCEDURES: Twelve classes of grade 2 students (n = 162) participated; six classes were assigned to an experimental or control group. A blinded research assistant, taking 3-5 minutes per child, completed the Helmet Checklist with each group on two occasions and scores of the experimental group (post-BB&B programme) were compared to the control group. The experimental group was reassessed using the Helmet Checklist, 1 year later. EXPERIMENTAL INTERVENTIONS: The BB&B programme consisted of a presentation, bicycle helmet checklist, demonstration and individual practice and feedback. MAIN OUTCOMES AND RESULTS: Children in the experimental group showed a better knowledge of how to wear their helmets safely compared to the control group (F = 51.84, CI = 9.11-9.71) and retained this knowledge 1 year after participating in the BB&B programme. CONCLUSIONS: The BB&B programme is effective in teaching grade 2 children how to wear their helmets correctly, which is knowledge they retain for at least 1 year.

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)0.004
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.405
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.046
GPT teacher head0.391
Teacher spread0.345 · 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

Citations12
Published2008
Admission routes1
Has abstractyes

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