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Record W2063036263 · doi:10.1001/archpedi.160.6.610

Risk-compensation behavior in children: myth or reality?

2006· article· en· W2063036263 on OpenAlexaffabout
I B Pless, Helen Magdalinos, Brent Hagel

Bibliographic record

VenuePubMed · 2006
Typearticle
Languageen
FieldMedicine
TopicInjury Epidemiology and Prevention
Canadian institutionsMcGill University
Fundersnot available
KeywordsInjury preventionPoison controlPsychologyMedicineOccupational safety and healthClinical psychologyDemographyPediatricsMedical emergency

Abstract

fetched live from OpenAlex

OBJECTIVE: To assess risk compensation and risk homeostasis theory in children. DESIGN: We used a case-control study design in children aged 8 to 18 years who had an injury while participating in an activity that did or could entail the use of protective equipment (PE). SETTING: Montreal Children's Hospital emergency department from December 1, 2001, to November 30, 2002. PARTICIPANTS: We interviewed consenting children and compared the reports of risk-taking behaviors in those who did and those who did not report using PE. MAIN OUTCOME MEASURES: Indicators of risk-taking behavior and injury severity. RESULTS: A total of 674 children presented with injuries during the study, and 394 were interviewed (235 PE users and 159 nonusers). There was no evidence of an association between indicators of risk-taking behavior and PE use after adjusting for age, sex, personality, and type of activity and no relationship between injury severity and PE use. CONCLUSIONS: Results of this study provide no support for hypotheses about risk homeostasis theory among children using PE. The validity of the theory appears highly doubtful for children in this age range.

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)0.002
metaresearch head score (Gemma)0.011
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 score0.022
Threshold uncertainty score0.044

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.003
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.030
GPT teacher head0.296
Teacher spread0.267 · 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

Citations26
Published2006
Admission routes2
Has abstractyes

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