Comparison of characteristics of children and adolescents with and without a history of abuse assessed in an urgent psychiatric clinic
Bibliographic record
Abstract
PURPOSE: The objective was 1) to describe the clinical characteristics of children referred for an urgent psychiatric consult with and without, a history of abuse; 2) to study differences in demographic and clinical variables between the groups; and 3) to examine the relationship between different types of abuse and disposition after assessment. METHODS: This is a 2-year retrospective cohort study of all patients aged 12 to 17 years referred to a hospital urgent psychiatric clinic. Patients were divided into two groups, those with a history of abuse and those without. Study variables included demographics, reason for referral, history of emotional, physical, sexual abuse, substance use, bullying victimization, DSM-5 diagnoses, and disposition. The study population was described using means, frequencies, and percentages, while relationships between types of abuse and clinical and demographic variables were assessed using Mann-Whitney U statistics, Spearman correlations, and logistic regression. RESULTS: The prevalence of any type of abuse was 30.4% (227 of 746 referrals). The abused group were older, more likely to be female, to have a history of substance use, bullying victimization, diagnosis of an externalizing disorder, and more likely to be admitted. Among the abused group, males were significantly more likely to report physical/emotional abuse, and female sexual abuse. There was no difference between different kinds of abuse and final diagnoses. CONCLUSIONS: Almost one-third of children and adolescents referred for urgent psychiatric consultation reported a history of abuse. Awareness of the association between abuse and emergency visits may assist physicians in triaging for urgent psychiatric assessment.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".