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Record W4386989374 · doi:10.1093/pch/pxad055.113

R2 (Resident Advocacy Project) Reducing the Risk of ATV-related Harm in Saskatchewan Children

2023· article· en· W4386989374 on OpenAlexaboutno aff
Alyssa Zucchet, Karen Leis

Bibliographic record

VenuePaediatrics & Child Health · 2023
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAgriculture and Farm Safety
Canadian institutionsnot available
Fundersnot available
KeywordsLegislationOccupational safety and healthPoison controlSuicide preventionInjury preventionEnvironmental healthGovernment (linguistics)MedicineHarmHuman factors and ergonomicsMedical emergencyPsychologyPolitical science

Abstract

fetched live from OpenAlex

Abstract Rationale and Objectives All-terrain vehicles (ATVs) are the second highest cause of transport-related hospitalizations, emergency room visits, and disabilities in Saskatchewan citizens of all ages. Saskatchewan law restricts the use of ATVs by children aged 12-16 and bans the use of ATVs by children under the age of 12 on public land. Previous CPS status reports had found this level of legislation inadequate. Clinically, we certainly see many children enter Saskatchewan hospitals for ATV-related injuries, and previous attempts at education campaigns and government lobbying have not been successful. There is limited Saskatchewan information on this issue, so we first sought to gather data to identify where social and legislative advocacy efforts should be directed. Project Description We partnered with the Saskatchewan Prevention Institute, a non-profit organization working to prevent injuries in children, as they have worked on ATV safety over the years with community partners as well as government. We completed a retrospective chart review to describe the prevalence and outcomes of ATV accidents in children and youth (aged 20 and under) presenting to hospitals in Saskatoon from 2016 to 2021. Armed with this data, we will be able to improve education campaigns as well as share information with key stakeholders, and hopefully effect change. Outcomes During the study period, 354 children presented to hospital after an ATV accident (most aged 12-16 years). Over 90% of children using dirt-bikes were wearing a helmet compared to 48% of children using four-wheeled ATVs (quads, side-by-sides, and other ATVs). Accidents involving quads resulted in an average hospital stay of 10 days, compared to 2 days for cases involving dirt-bikes. Finally, the type of injury was significantly associated with the patient’s health region of residence. For example, children living in the North and Far North Saskatchewan accounted for the highest proportion of moderate/severe head injuries (76.19%) and polytraumas (50%). Discussion/Future Directions This data suggests that there is a potential knowledge gap in public knowledge regarding the risks of children using ATVs; that there may be barriers to helmet use; and, most strikingly, that there is a disproportionate number of severe injuries occurring in northern Saskatchewan. New public education initiatives are now in development based on these findings. There are many stakeholders to consider, and we are aiming to share our data so that evidence-based policy decisions can be made. We are currently drafting a letter to relevant ministries, and hope to have more progress to share in the near future.

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)0.005
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.553
Threshold uncertainty score0.888

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.005
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0040.001
Scholarly communication0.0020.001
Open science0.0030.008
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0170.002

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 head0.012
GPT teacher head0.242
Teacher spread0.230 · 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 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
Published2023
Admission routes1
Has abstractyes

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