Health Care Experiences of Patients Discontinuing or Reversing Prior Gender-Affirming Treatments
Bibliographic record
Abstract
Importance: Medical education, research, and clinical guidelines are available to support the initiation of gender-affirming care for transgender and nonbinary people. By contrast, little is known about the clinical experiences of those who discontinue or seek to reverse gender-affirming medical or surgical interventions due to a change in gender identity, often referred to as detransition. Objective: To examine the physical and mental health experiences of people who initiated medical or surgical detransition to inform clinical practice. Design, Setting, and Participants: Using constructivist grounded theory as a qualitative approach, data were collected in the form of in-depth interviews. Data were analyzed using an inductive 2-stage coding process to categorize and interpret detransition-related health care experiences to inform clinical practice. Between October 2021 and January 2022, individuals living in Canada who were aged 18 years and older with experience of stopping, shifting, or reversing a gender transition were invited to partake in semistructured virtual interviews. Study advertisements were circulated over social media, to clinicians, and within participants' social networks. A purposive sample of 28 participants who discontinued, shifted, or reversed a gender transition were interviewed. Main Outcomes and Measures: In-depth, narrative descriptions of the physical and mental health experiences of people who discontinued or sought to reverse prior gender-affirming medical and/or surgical interventions. Results: Among the 28 participants, 18 (64%) were assigned female at birth and 10 (36%) were assigned male at birth; 2 (7%) identified as Jewish and White, 5 (18%) identified as having mixed race and ethnicity (which included Arab, Black, Indigenous, Latinx, and South Asian), and 21 (75%) identified as White. Participants initially sought gender-affirmation at a wide range of ages (15 [56%] were between ages 18 and 24 years). Detransition occurred for various reasons, such as an evolving understanding of gender identity or health concerns. Participants reported divergent perspectives about their past gender-affirming medical or surgical treatments. Some participants felt regrets, but a majority were pleased with the results of gender-affirming medical or surgical treatments. Medical detransition was often experienced as physically and psychologically challenging, yet health care avoidance was common. Participants described experiencing stigma and interacting with clinicians who were unprepared to meet their detransition-related medical needs. Conclusions and Relevance: This study's results suggest that further research and clinical guidance is required to address the unmet needs of this population who discontinue or seek to reverse prior gender-affirming interventions.
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 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".