Gynecological Providers' Willingness to Prescribe Gender-Affirming Hormone Therapy for Transgender Patients
Bibliographic record
Abstract
Purpose: Transgender individuals face barriers to accessing gender-affirming hormone therapy, yet little is known about gynecological providers' willingness to provide such care. Methods: We surveyed gynecological providers in one healthcare system to determine their willingness to prescribe hormone therapy (HT) for transgender patients and factors associated with willingness to both initiate and refill HT. Results: = 60), 60.3% and 27.6% were willing to refill and initiate HT for transgender patients, respectively. Willingness to refill HT was associated with having met a transgender person and lower transphobia. Unwillingness was associated with lack of transgender health training, lack of staff knowledge about transgender health, and unfamiliarity with transition guidelines. Willingness to initiate HT was associated with younger age and resident status. Unwillingness was associated with unfamiliarity with transition guidelines. Conclusion: While gynecological providers are qualified to prescribe HT for transgender patients, willingness to do so may be influenced by both personal and educational/training factors. Encouraging and training gynecological providers to provide gender-affirming HT will help to increase access for transgender individuals.
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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 | 0.002 | 0.013 |
| 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) | 0.008 | 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".