Disordered eating behaviors among transgender youth: Probability profiles from risk and protective factors
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
PURPOSE: Research has documented high rates of disordered eating for lesbian, gay, and bisexual youth, but prevalence and patterns of disordered eating among transgender youth remain unexplored. This is despite unique challenges faced by this group, including gender-related body image and the use of hormones. We explore the relationship between disordered eating and risk and protective factors for transgender youth. METHODS: An online survey of 923 transgender youth (aged 14-25) across Canada was conducted, primarily using measures from existing youth health surveys. Analyses were stratified by gender identity and included logistic regressions with probability profiles to illustrate combinations of risk and protective factors for eating disordered behaviors. RESULTS: Enacted stigma (the higher rates of harassment and discrimination sexual minority youth experience) was linked to higher odds of reported past year binge eating and fasting or vomiting to lose weight, while protective factors, including family connectedness, school connectedness, caring friends, and social support, were linked to lower odds of past year disordered eating. Youth with the highest levels of enacted stigma and no protective factors had high probabilities of past year eating disordered behaviors. DISCUSSION: Our study found high prevalence of disorders. Risk for these behaviors was linked to stigma and violence exposure, but offset by social supports. Health professionals should assess transgender youth for disordered eating behaviors and supportive resources. © 2016 Wiley Periodicals, Inc.(Int J Eat Disord 2017; 50:515-522).
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it