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Record W2118526018 · doi:10.1136/ip.2007.016782

School-age children’s safety attitudes, cognitions, knowledge, and injury experiences: how do these relate to their safety practices?

2008· article· en· W2118526018 on OpenAlexaff
Barbara A. Morrongiello, Michael D. Cusimano, Erin Orr, Benjamin K. Barton, Mary L. Chipman, Jeffrey Tyberg, Abhaya Kulkarini, Nazilla Khanlou, R Masi, Tsegaye Bekele

Bibliographic record

VenueInjury Prevention · 2008
Typearticle
Languageen
FieldMedicine
TopicInjury Epidemiology and Prevention
Canadian institutionsHealth Sciences CentreSunnybrook Health Science CentreSickKids FoundationUniversity of TorontoSt. Michael's HospitalHospital for Sick ChildrenUniversity of Guelph
Fundersnot available
KeywordsHuman factors and ergonomicsOccupational safety and healthInjury preventionCognitionPoison controlAffect (linguistics)Suicide preventionPsychologySafety behaviorsClinical psychologyDevelopmental psychologyMedicineMedical emergencyPsychiatry

Abstract

fetched live from OpenAlex

BACKGROUND: A variety of factors affect the safety and risk practices of school-age children, but rarely have multiple factors been considered simultaneously. OBJECTIVE: To examine children's safety attitudes and cognitions more thoroughly and assess how these factors, along with children's safety knowledge and injury experiences, relate to children's safety practices. METHODS: Over several classroom sessions, boys and girls in two age groups (7-9, 10-12 years) completed a psychometrically sound questionnaire that indexes their behaviors, attitudes, cognitions, knowledge, and injury experiences. RESULTS: Fewer safety practices were reported by older than younger children and boys than girls. Children's attitudes, cognitions, knowledge, and injury experiences each correlated with safety practices, but only safety attitudes and injury experiences predicted practices in a multivariate model. CONCLUSION: Exploring the relative influence of numerous factors on safety practices highlights the important role that attitudes play in predicting children's safety practices. Implications of these results for injury prevention programming are discussed.

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)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.326
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.036
GPT teacher head0.357
Teacher spread0.321 · 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.

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

Citations18
Published2008
Admission routes1
Has abstractyes

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