Gender Affirmation Is Associated with Transgender and Gender Nonbinary Youth Mental Health Improvement
Bibliographic record
Abstract
Purpose: The present study aimed to evaluate the impact of each domain of gender affirmation (social, legal, and medical/surgical) on the mental health of transgender and gender nonbinary youth. Methods: Three hundred fifty transgender boys, transgender girls, and gender nonbinary Brazilian youth, from 16 to 24 years old, answered an online survey. Results: The final sample consisted of 350 youth who participated in this study. A total of 149 (42.64%) youth identified as transgender boys, 85 (24.28%) identified as transgender girls, and 116 (33.14%) identified as gender nonbinary youth. The mean age was 18.61 (95% confidence interval 18.34–18.88) years. Having accessed multiple steps of gender affirmation (social, legal, and medical/surgical) was associated with fewer symptoms of depression and less anxiety. Furthermore, engaging in gender affirmation processes helped youth to develop a sense of pride and positivity about their gender identity and a feeling of being socially accepted. Conclusion: Enabling transgender and gender nonbinary youth to access gender affirmation processes more easily should be considered as a strategy to reduce depression and anxiety symptoms, as well as to improve gender positivity.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".