Characteristics of Adolescents Referred to a Gender Clinic: Are Youth Seen Now Different from Those in Initial Reports?
Bibliographic record
Abstract
BACKGROUND/AIMS: To examine characteristics, including mental health comorbidities, among adolescents presenting to a transgender clinic and to compare these data to previous reports. METHODS: Retrospective chart review among youth seen at The Hospital for Sick Children between January 2014 and June 2016. Demographic data, clinical characteristics, and mental health comorbidities were assessed. Baseline and repeat blood work were also examined. RESULTS: Charts from 203 adolescents aged 12-18 years were reviewed (156 assigned female at birth [AFAB] (77%) aged 16.3 ± 1.63 years, 47 assigned male at birth [AMAB] aged 16.1 ± 1.70 years). There was no statistically significant difference between gender groups except for Tanner stage (AFAB, mean 4.42 ± 0.8 and AMAB, mean 4.03 ± 1.1, p = 0.040). Individuals from racial/ethnic minority populations were under-represented compared to the background population. Self-report and baseline psychological questionnaires showed high levels of gender dysphoria, mood disorders, and suicidal ideation, with higher levels of anxiety detected on questionnaires among AFAB (p = 0.03). Laboratory abnormalities identified on baseline and repeat testing were minor; on cross-sex hormones, hemoglobin levels increased slightly in AFAB (p = 0.002, highest = 166 g/L) and decreased among AMAB (p = 0.02, lowest = 132 g/L). CONCLUSION: Our study supports an evolving demographic trend with more AFAB than AMAB youth now presenting to gender clinics. The data also corroborate studies indicating that extensive laboratory testing may not be a necessary part of caring for these youths. Why more AFAB are now presenting to clinic and racial/ethnic minorities are underrepresented is not clear, but these trends have important implications for clinical care and warrant further study.
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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 | 0.002 |
| 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".