“Coming home to my body”: A qualitative exploration of gender-affirming care-seeking and mental health
Bibliographic record
Abstract
Among transgender, non-binary, and/or gender expansive (TNG) persons, interest in medical and/or surgical forms of gender affirmation is heterogenous, as is access to those forms of medically necessary health care. Yet, the literature characterizing TNG persons' interest in medical and/or surgical gender-affirming care, barriers to accessing that care, and how societal narratives and expectations impact TNG individuals' self-image and mental health, as well as their personal choices regarding gender-affirming care remains sparse. Here we present qualitative research exploring TNG participants' interest in gender-affirming care and how such interventions impact identity formation. We conducted loosely structured interviews with a convenience sample of 54 TNG persons in the U.S. and Canada from Facebook pages used to recruit TNG research participants. One-hour interviews were conducted by an openly TNG researcher; participants were compensated. The most frequently sought gender-affirming care was hormone therapy, followed by chest ("top") surgery, genital ("bottom") surgery, electrolysis, breast augmentation, hysterectomy, and voice training. Less commonly desired interventions included fertility preservation, facial feminization/masculinization, and vocal surgery. Participants described four main categories of access barriers: financial (e.g., cost of medical/surgical care, inadequate insurance), logistical (e.g., no local providers, gatekeeping policies around body size and mental health, pandemic-related delays), personal fears about sub-optimal outcomes (e.g., complications, loss of sensation, undesired aesthetic and/or functional results), and societal discrimination (e.g., familial rejection, job loss, safety concerns). Participants reported primarily seeking this healthcare for social legibility, alleviating dysphoria/pursuing euphoria, and/or gender exploration. All who sought gender-affirming care reported improved mental health-including depression, anxiety, dissociation, and eating disorders-and social relationships, though many struggled to find TNG-competent mental health providers. This work provides key insights into how gender-affirming care can contribute to improving mental health for TNG communities, which will assist health providers in optimally treating TNG patients.
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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 | 0.014 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.015 | 0.018 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.003 | 0.004 |
| 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".