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Record W3212167108 · doi:10.1136/bmjopen-2021-053859

Firearm injury epidemiology in children and youth in Ontario, Canada: a population-based study

2021· article· en· W3212167108 on OpenAlexafffundabout
Natasha Saunders, Charlotte Moore Hepburn, Anjie Huang, Claire de Oliveira, Rachel Strauss, Lisa Fıksenbaum, Paul Pageau, Ning Liu, David Gómez, Alison Macpherson

Bibliographic record

VenueBMJ Open · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicGun Ownership and Violence Research
Canadian institutionsUniversity of OttawaInstitute for Clinical Evaluative SciencesSickKids FoundationYork UniversityUniversity of Toronto
FundersCanadian Institutes of Health Research
KeywordsMedicineEpidemiologyInjury preventionPoison controlOccupational safety and healthSuicide preventionHuman factors and ergonomicsPublic healthPopulationMedical emergencyFamily medicinePopulation based studyEnvironmental healthNursingPathology

Abstract

fetched live from OpenAlex

BACKGROUND AND OBJECTIVE: Despite firearms contributing to significant morbidity and mortality globally, firearm injury epidemiology is seldom described outside of the USA. We examined firearm injuries among youth in Canada, including weapon type, and intent. DESIGN: Population-based, pooled cross-sectional study using linked health administrative and demographic databases. SETTING: Ontario, Canada. PARTICIPANTS: All children and youth from birth to 24 years, residing in Ontario from 1 April 2003 to 31 March 2018. EXPOSURE: Firearm injury intent and weapon type using the International Classification of Disease-10 CM codes with Canadian enhancements. Secondary exposures were sociodemographics including age, sex, rurality and income. MAIN OUTCOMES: Any hospital or death record of a firearm injury with counts and rates of firearm injuries described overall and stratified by weapon type and injury intent. Multivariable Poisson regression stratified by injury intent was used to calculate rate ratios of firearm injuries by weapon type. RESULTS: Of 5486 children and youth with a firearm injury (annual rate: 8.8/100 000 population), 90.7% survived. Most injuries occurred in males (90.1%, 15.5/100 000 population). 62.3% (3416) of injuries were unintentional (5.5/100 000 population) of which 1.9% were deaths, whereas 26.5% (1452) were assault related (2.3/100 00 population) of which 18.7% were deaths. Self-injury accounted for 3.7% (204) of cases of which 72.0% were deaths. Across all intents, adjusted regression models showed males were at an increased risk of injury. Non-powdered firearms accounted for half (48.6%, 3.9/100 000 population) of all injuries. Compared with handguns, non-powdered firearms had a higher risk of causing unintentional injuries (adjusted rate ratio (aRR) 14.75, 95% CI 12.01 to 18.12) but not assault (aRR 0.84, 95% CI 0.70 to 1.00). CONCLUSIONS: Firearm injuries are a preventable public health problem among youth in Ontario, Canada. Unintentional injuries and those caused by non-powdered firearms were most common and assault and self-injury contributed to substantial firearm-related deaths and should be a focus of prevention efforts.

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)0.001
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 score0.006
Threshold uncertainty score0.903

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
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 head0.160
GPT teacher head0.456
Teacher spread0.296 · 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

Citations17
Published2021
Admission routes3
Has abstractyes

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