Intentional Hand Fractures are Associated with Future Psychiatric Conditions in Youth
Bibliographic record
Abstract
INTRODUCTION: Hand fractures are a common complaint in pediatric patients. The association between pediatric hand fractures and subsequent engagement with mental health and addictions (MHA) services remains unstudied. This study investigated the relationship between hand injury mechanisms and future presentation to MHA services. METHODS: A retrospective cohort study was conducted off all patients presenting to a pediatric plastic surgery clinic from 2012 to 2017. Data collected included demographics, fracture mechanism and location, and subsequent presentation to MHA services. Stepwise logistic regression models were employed to assess risk factors for future presentation to MHA and diagnosis of psychiatric illnesses. RESULTS: A total of 1184 patients presented with pediatric hand fractures. Most injuries were accidental (87.9%), with sports being the most common cause (52.4%). Intentional injuries accounted for 12.2% of cases, primarily due to punching a solid object (53.5%) or another individual (45.1%). Patients with intentional injuries were significantly older (14.1 vs 11.8 years, p<0.001) and predominantly male (93.1% vs 66.2%, p <0.001) compared to patients with accidental injuries. Overall, 12.2% of patients were assessed by MHA services, with a relative risk of 5.59 for those with intentional injuries. The most diagnosed psychiatric illness was ADHD (56.7%). Intentional injury mechanism was significantly associated with a future diagnosis of ADHD (p<0.001), generalized anxiety disorder (p=0.022), major depressive disorder (p=0.012), and substance use disorder (p<0.001). CONCLUSIONS: Intentional hand fractures in the pediatric population are strongly associated with future MHA assessment. These findings support early screening and referral to MHA services when intentional injury mechanism is identified.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".