Cross-sectional associations between medical affirmation, social connectedness, and psychological well-being in transgender and gender-diverse adults.
Bibliographic record
Abstract
Many transgender and gender-diverse adults (i.e., those whose gender identities or expressions differ from their sex presumed at birth) affirm their identities medically and, in addition, rely on their social networks for identity-related support. While both medical affirmation and social connectedness are linked to well-being, their combined effects and differences across gender identities remain underexplored. The present article aimed to examine how medical affirmation and social connectedness are associated with psychological well-being among transgender men, transgender women, and nonbinary adults. Findings from a study involving 342 participants from Australia, Canada, the United Kingdom, and the United States, conducted in July 2020, revealed that medical affirmation was associated with better well-being. General social support, however, was a stronger predictor of well-being than medical affirmation. Community connectedness with trans people did not uniquely predict well-being. These findings hint at the importance of a holistic approach to gender-affirming care-one that integrates both medical affirmation and social connectedness to effectively foster trans adults' well-being.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".