Mental Health and Timing of Gender-Affirming Care
Bibliographic record
Abstract
BACKGROUND: Gender-incongruent (GI) youth have high rates of mental health problems. Although gender-affirming medical care (GAMC) provides psychological benefit, some GI youth present to care at older ages. Whether a relationship exists between age of presentation to GAMC and mental health difficulties warrants study. METHODS: A cross-sectional chart review of patients presenting to GAMC. Subjects were classified a priori as younger presenting youth (YPY) (<15 years of age at presentation) or older presenting youth (OPY) (≥15 years of age). Self-reported rates of mental health problems and medication use were compared between groups. Binary logistic regression analysis was used to identify determinants of mental health problems. Covariates included pubertal stage at presentation, social transition status, and assigned sex. RESULTS: Of 300 youth, there were 116 YPY and 184 OPY. After presentation, more OPY than YPY reported a diagnosis of depression (46% vs 30%), had self-harmed (40% vs 28%), had considered suicide (52% vs 40%), had attempted suicide (17% vs 9%), and required psychoactive medications (36% vs 23%), with all P < .05. After controlling for covariates, late puberty (Tanner stage 4 or 5) was associated with depressive disorders (odds ratio 5.49; 95% confidence interval [CI]: 1.14–26.32) and anxiety disorders (odds ratio 4.18 [95% CI: 1.22–14.49]), whereas older age remained associated only with psychoactive medication use (odd ratio 1.31 [95% CI: 1.05–1.63]). CONCLUSIONS: Late pubertal stage and older age are associated with worse mental health among GI youth presenting to GAMC, suggesting that this group may be particularly vulnerable and in need of appropriate care.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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".