Barriers and facilitators in gender-affirming hormone therapy: Scoping review of healthcare providers’ and transgender patients’ perspectives
Bibliographic record
Abstract
Introduction: Gender-affirming hormone therapy is a critical component of healthcare for transgender individuals. However, barriers in access and provision persist, impacting both patients and healthcare providers. This study aimed to explore the literature on gender-affirming hormone therapy provision from the perspectives of transgender adult patients and healthcare practitioners to identify facilitators and barriers to care. Methods: A scoping review was conducted using the JBI methodology and guided by the PRISMA extension for scoping reviews. A systematic search was performed in PubMed, CINAHL, and Scopus databases. Inclusion criteria focused both healthcare providers’ and transgender adults’ experiences with gender-affirming hormone therapy. The search, conducted on July 23, 2022, and updated on March 1, 2023, identified 12 studies meeting the inclusion criteria for the final analysis. Results: Facilitators for gender-affirming hormone therapy included regular access to primary care providers, multidisciplinary care approaches, and strong patient-provider relationships. Barriers identified were the lack of knowledgeable providers, denial or refusal of care, and inappropriate treatment. Both patients and providers emphasized the need for improved training and competence in transgender healthcare. Conclusion: Significant gaps in provider competence and systemic issues in accessing gender-affirming hormone therapy was identified. Addressing these barriers through targeted education and improved care systems is essential for ensuring affirming, patient-centered care and better health outcomes for transgender adults.
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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 | 0.036 | 0.099 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.004 |
| Bibliometrics | 0.013 | 0.013 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.002 |
| 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".