Exploring the influence of gender dysphoria in eating disorders among gender diverse individuals
Bibliographic record
Abstract
AIM: Eating concerns, disordered eating and eating disorders have been noted to negatively impact the health and wellbeing of sexual and gender diverse individuals. The aim of this study was to explore the experiences of gender diverse Canadians accessing treatment for eating disorders or disordered eating concerns to gain a deeper understanding of how dietitians and other health providers can provide gender affirming care. METHODS: Seven self-identifying gender diverse participants were recruited and took part in semi-structured interviews. Most participants identified as white. Data was analysed using thematic analysis. RESULTS: Four themes around gender dysphoria were constructed from the data, including gender dysphoria and eating disorders, barriers to accessing eating disorder treatments, harmful eating disorder treatment strategies and suggestions for eating disorder programmers and health professionals. CONCLUSION: Gender dysphoria considerations were believed to be lacking in traditional eating disorder treatment programs. Participants saw the need for more awareness and training in this area for dietitians and other health professionals.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.005 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| 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".