Unintentional injuries in school-aged children and adolescents: lessons from a systematic review of cohort studies
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
OBJECTIVES: To critically synthesise current knowledge of the patterns of injuries and risk factors for injury in school-aged children, to summarise the evidence and support effective child injury prevention initiatives. DESIGN: Systematic review. Selection criteria and METHODS: Prospective cohort studies reporting unintentional injuries in healthy children aged 5-18 years were identified by searching 15 electronic databases and additional grey literature sources. A narrative synthesis was conducted of papers meeting quality criteria, with risk factors analysed at individual, family and environmental levels. Limitations of existing evidence were considered. RESULTS: 44 papers from 18 different cohort studies met the inclusion criteria. There were broad and consistent patterns of injury across time and place. Male sex, psychological, behavioural and risk-taking behaviour problems, having a large number of siblings, and a young mother were all associated with increased injury occurrence across more than one cohort and setting. CONCLUSIONS: Descriptive epidemiology and risk factors for injury were derived from prospective cohort studies, but few studies used the full potential of their design. Opportunities to use repeated measures to assess temporal changes in injury occurrence, and the exploration of risk factors, particularly those related to the child's environment, have rarely been undertaken. Few studies were conducted in low/middle-income countries where the burden of injury is greatest. These findings should be considered when planning future research and prevention initiatives.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.005 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it