The experiences of gender diverse and trans children and youth considering and initiating medical interventions in Canadian gender-affirming speciality clinics
Bibliographic record
Abstract
Background: Canadian specialty clinics offering gender-affirming care to trans and gender diverse children and youth have observed a significant increase in referrals in recent years, but there is a lack of information about the experiences of young people receiving care. Furthermore, treatment protocols governing access to gender-affirming medical interventions remain a topic of debate.Aims: This qualitative research aims to develop a deeper understanding of experiences of trans youth seeking and receiving gender-affirming care at Canadian specialty clinics, including their goals in accessing care, feelings about care and medical interventions they have undergone, and whether they have any regrets about these interventions.Methods: The study uses an adapted Grounded Theory methodology from social determinants of health perspective. Thirty-five trans and gender diverse young people aged 9 to 17 years were recruited to participate in semi-structured interviews through the specialty clinics where they had received or were waiting for gender-affirming medical interventions such as puberty blockers, hormone therapy, and surgery.Results: Young people felt positively overall about the care they had received and the medical interventions they had undergone, with many recounting an improvement in their well-being since starting care. Most commonly shared frustrations concerned delays in accessing interventions due to clinic waiting lists or treatment protocols. Some youth described unwanted medication side-effects and others said they had questioned their transition trajectory at certain moments in the past, but none regretted their choice to undergo the interventions.Discussion: The results suggest that trans youth and gender diverse children are benefiting from medical gender-affirming care they receive at specialty clinics, providing valuable insight into their decision-making processes in seeking care and specific interventions. Providers might consider adjusting aspects of treatment protocols (such as age restrictions, puberty stage, or mental health assessments) or applying them on a more flexible, case-by-case basis to reduce barriers to access.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.019 | 0.008 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".