Transgender women’s perspectives on mental health care related to vaginoplasty for gender affirmation
Bibliographic record
Abstract
PURPOSE: This study aimed to describe patient experiences and attitudes about the role of the mental health professional as it relates to pursuing gender affirmation surgery. METHODS: This was a mixed-models study with semi-structured interviews. Participants who presented for gender affirming vaginoplasty and had completed pre-surgical requirements but had not yet had the procedure were invited to participate in the study. Semi-structured phone interviews were conducted from November 2019 and December 2020 until saturation of themes was achieved at a sample size of 14. Interviews were then transcribed verbatim and coded by theme. Qualitative analysis was performed using a grounded theory approach. RESULTS: Almost half of the patients did not identify any barriers to obtaining mental health care, but a majority brought up concerns for less advantaged peers, with less access to resources. Some patients also felt that there was benefit to be obtained from the mental health care required before going through with surgery, while others felt the requirements were discriminatory. Finally, a large proportion of our participants reported concerns with the role of mental health care and the requirements set forth by the World Professional Association for Transgender Health (WPATH), and patients gave suggestions for future improvements including decreasing barriers to care while rethinking how guidelines impact patients. CONCLUSION: There are many competing goals to balance when it comes to the guidelines for gender affirmation surgery, and patients had differing and complex relationships with mental health care and the pre-surgical process.
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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 | 0.005 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.005 | 0.005 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| 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".