Experiences of Gender-Diverse Youth Living With Chronic Pain
Bibliographic record
Abstract
BACKGROUND: Although sex differences in pain are well documented, little is known regarding the relationship between gender and pain. Gender-diverse youth experience unique pain risk factors, including minority stress exposure, but are underrepresented in research. OBJECTIVE: Elicit experiences of gender-diverse youth who live with chronic pain. METHODS: Semistructured interviews were conducted with youth virtually using Zoom. Youth were recruited from a Canadian tertiary care pediatric hospital, community-based clinics, and the general population. Interviews were recorded, transcribed, and analyzed with a patient partner using reflexive thematic analysis, integrating relevant existing theoretical and empirical models for understanding gender and pain, identity development, minority stress, and intersectionality. RESULTS: The final sample included 19 youth who represented a variety of gender identities and pain conditions and reported accessing a range of types and levels of care. Three themes were identified through qualitative analysis: (1) the fight to legitimize both their pain and gender, (2) the tension between affirming gender and managing pain and the role of gender euphoria as a buffer against pain, and (3) the role of intersecting (eg, neurodiversity and race) identities in understanding gender-diverse youths' pain experiences. CONCLUSIONS: In a diverse sample of gender-diverse youth who live with chronic pain, experiences of invalidation and difficulty managing pain were experienced in the context of unique stressors and sources of joy in living as a gender-diverse individual. These results point to the need for more intersectional and affirming pain research and integration of findings into clinical practice.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".