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Record W2053936225 · doi:10.1080/15389588.2012.711498

Child and Youth Traffic-Related Injuries: Use of a Trauma Registry to Identify Priorities for Prevention in the United Arab Emirates

2013· article· en· W2053936225 on OpenAlexaff
Michal Grivna, Peter Barss, Cristina Stănculescu, Hani O. Eid, Fikri M. Abu‐Zidan

Bibliographic record

VenueTraffic Injury Prevention · 2013
Typearticle
Languageen
FieldEngineering
TopicTraffic and Road Safety
Canadian institutionsMcGill UniversityUniversity of British ColumbiaInterior Health
FundersUtah Agricultural Experiment Station
KeywordsMedicineInjury preventionOccupational safety and healthAbbreviated Injury ScalePoison controlSuicide preventionIncidence (geometry)Human factors and ergonomicsMedical emergencyInjury Severity ScorePediatrics

Abstract

fetched live from OpenAlex

OBJECTIVE: Traffic-related injuries are the main cause of death during childhood and youth in the United Arab Emirates (UAE), use of safety restraints by citizens is uncommon, rollovers are frequent, and current legislation does not protect rear-seat occupants. Because little was known about the circumstances of hospitalizations for traffic injuries to guide prevention, a trauma registry was used to assess causes and determinants for traffic-related injuries during childhood and youth (<19 years) and its value for prevention. METHODS: One hundred ninety-three children and youth with traffic injuries were admitted for more than 24 h at surgical wards of the main trauma hospital in the Al-Ain region during a 36-month period (2003-2006). Injuries were analyzed by age, nationality, road user and vehicle types, severity, anatomical region, and the presence of head injury using Injury Severity Scores (ISS) and the Abbreviated Injury Scale (AIS). RESULTS: Traffic injuries represented 40 percent (n = 193) of injuries to 0- to 19-year-olds, followed by falls (39 percent). Among 15- to 19-year-olds, who accounted for 46 percent of child and youth victims, the incidence was 150/100,000 person years, compared to an incidence of 15 to 51 for younger age groups. Overall, 53 percent were vehicle occupants, 23 percent were pedestrians, 14 percent were bicyclists, 6 percent were motorcyclists, with 4 percent other. The ratio of male-to-female victims was 6.7:1; for drivers it was 33:0; and for pedestrians, bicyclists, and motorcyclists it was between 10:1 and 12:1; injured females were mainly rear-seat passengers and the male: female ratio was 1.4:1. Seventy-one percent of pedestrians were ≤9 years old. Although the ratio of UAE children to foreign children was estimated at 0.7:1 in the community, 58 percent of the injured were UAE citizens. The ratio of injured UAE: non-UAE citizens was 1.4:1 overall but 5.6:1 for drivers and 4.5:1 for motorcyclists. Forty-one percent of citizens were injured in 4-wheel drive sport utility vehicles compared to 13 percent of non-citizens. Head injuries occurred in 68 percent of vehicle occupants and 51 percent of nonoccupants, with AIS ≥ 3 injuries in 23 percent of occupants and 26 percent of nonoccupants. Sixty-seven percent of rear occupants had head injuries. CONCLUSIONS: Male drivers and vulnerable road users were at an unusually high risk relative to females. A relatively high frequency of traffic-related head injuries among UAE children and youth, including rear-seat passengers and other vehicle occupants, suggests that considerable preventable morbidity is associated with nonuse of safety restraints and/or other factors such as excess speed and rollovers of 4-wheel drive vehicles. Trauma registries can be useful for prevention; inclusion of data on safety restraints and helmet use by road user type is essential.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.657
Threshold uncertainty score0.906

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.022
GPT teacher head0.267
Teacher spread0.245 · 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 designSimulation or modeling
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

Citations26
Published2013
Admission routes1
Has abstractyes

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