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The implementation of a municipal indoor ice skating helmet policy: effects on helmet use, participation and attitudes

2015· article· en· W2278746773 on OpenAlexaffabout
Colleen O'Mahony-Menton, Jacqueline Willmore, Katherine Russell

Bibliographic record

VenueInjury Prevention · 2015
Typearticle
Languageen
FieldMedicine
TopicInjury Epidemiology and Prevention
Canadian institutionsOttawa Public Health
Fundersnot available
KeywordsAttendancePoison controlInjury preventionSuicide preventionOccupational safety and healthHuman factors and ergonomicsPublic healthPsychologyMedicineEnvironmental healthPolitical scienceNursing

Abstract

fetched live from OpenAlex

RELEVANT LOCAL INJURY EPIDEMIOLOGY: In Ottawa, between 2005 and 2009 there was an annual average of 47.2 head injuries due to ice skating in children and youth (1-19 years of age) requiring a visit to the emergency department, with the highest rates among those aged 5-14 years. Between 2002 and 2007, only 6% of children were wearing a helmet during ice skating when the head injury occurred. During indoor public skating sessions, 93% of children (<10 years)-57% aged 10-12 years, 20% aged 13-17 years and 9% adults-wore helmets in the absence of a policy. Support for a helmet policy was high from public health, medical, political and community perspectives. BEST PRACTICE: Helmet policies in relation to cycling have demonstrated increases in helmet use and reduction of head injuries without decreasing physical activity. However, no known studies have examined the effect of indoor ice skating helmet policy coupled with education and promotional activities on helmet use, participation and attitudes towards helmet use. IMPLEMENTATION: An ice skating helmet policy for children (<11 years of age) and those with limited skating experience at indoor rinks during public skating sessions was developed, implemented and evaluated. Supportive activities such as discount coupons, promotional materials, a media launch, social marketing and staff training are described. DISCUSSION: The helmet policy was associated with increased helmet use for young children and for older children, youth and adults not included in the policy, without decreasing attendance to public skating sessions.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.439
Threshold uncertainty score0.422

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.061
GPT teacher head0.445
Teacher spread0.384 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations2
Published2015
Admission routes2
Has abstractyes

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