Temperament and fracture risk among preschool children: a target kids! Cross-sectional survey
Bibliographic record
Abstract
Background Previous studies have reported an association between temperament and fracture risk among school-age children; however, few studies have examined this association among preschool children. Aims/Objective/Purpose The purpose of this study was to examine the association between temperament and fracture risk among preschool children (3–5 years). Methods A cross-sectional study with a case-control analytic approach was used to examine the association between temperament and fracture risk among preschool children in Toronto, Canada. Participants were selected from TARGet Kids!—a community-based pediatric primary care research network. Cases were children who had experienced a fracture. Controls were children with no history of fracture. A 1 : 12 ratio of cases: controls was used, with all cases selected and random sampling of controls. Primary exposure variables included three temperament subscales from the Children's Behavior Questionnaire—Surgency, Effortful Control and Negative Affect. Logistic regression was conducted to estimate the ORs and 95% CIs of fractures predicted by temperament, adjusted for sex and daycare status. Models were run for each temperament subscale. Results/Outcomes A total of 48 cases and 600 controls were selected. No significant association between temperament and fracture risk was found. Sex (females vs males, unadjusted OR 2.46, 95% CI 1.29 to 4.68) and daycare attendance (attends vs does not attend, unadjusted OR 0.44, 95% CI 0.24 to 0.80) were the only significant predictors of fracture risk among preschool children. Significance/Contribution to the Field These findings contrast with results among school-age children. The lack of association between temperament and injury may relate to increased supervision of preschool children and developmental stage. Conference theme Safety, Design and Sustainability Conference topic Child safety
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".