Sexual Health of Adolescent Patients Admitted to a Psychiatric Unit.
Bibliographic record
Abstract
OBJECTIVE: To review sexual health screening practices during admission to an adolescent psychiatry unit. METHOD: Retrospective chart review of randomly selected youth admitted over a one-year period (2013). Data extracted included demographics, reasons for admission, sexual health history, as well as any comorbid behaviours noted. The main outcome measure was whether sexual health details were documented at any time during admission; if so, this information was extracted for analysis. Statistical analysis was done using univariate associations and logistic association. RESULTS: Mean age of subjects (n=99, 79 females and 20 males) was 15.24 years (SD = 1.30). Most common reasons for admission were suicidal gestures/self harm (n=57, 58%) and mood disorders (n=53, 54%). Thirty-seven patients (37%) had sexual health information documented in their charts. No demographic variables were significantly associated with being asked sexual health questions. Patients who had mood disorder diagnoses had 6 times the odds (95%CI: 1.18 to 29.96, P=0.03) of sexual health questions being documented compared to those not diagnosed with mood disorders. CONCLUSIONS: Screening for sexual health concerns is not being documented in the majority of adolescent psychiatry inpatients. Omitting sexual health screening during hospitalizations represents a missed opportunity for investigation and management of sexual health issues in this high-risk group. As many adolescents, particular those struggling with mental illness, do not attend preventative health visits, screening for pregnancy risk and other reproductive health needs is recommended at every adolescent encounter and in all settings.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".