Minority Stress, Resilience, and Trouble Falling Asleep Among Gender and Sexual Minority Adolescents
Bibliographic record
Abstract
INTRODUCTION: Gender and sexual minority adolescents experience greater stress and report worse sleep outcomes compared to their cisgender and/or heterosexual peers. Understanding how minority stress and resilience factors are linked to sleep health provides levers for improving sleep within these populations. METHODS: = 15.6 years; 65% white), we compared gender/sex and sexuality subgroups' trouble falling asleep and conducted linear regressions relating trouble falling asleep to minority stress (i.e., violent victimization, bias-based victimization, and family rejection) and resilience (i.e., familial warmth, family acceptance, gender-affirming environments, teacher support, trusted adult at school, and presence of a gender-sexuality alliance [GSA]) factors for both gender and sexual minority adolescents. RESULTS: We found small but significant differences in sleep across gender/sex categories, with gender minorities and youth assigned female at birth having worse sleep than cisgender sexual minorities and youth assigned male at birth, respectively. Further, violent LGBTQ+ victimization and gender expression-based victimization were associated with more trouble falling asleep, and familial warmth was associated with less trouble falling asleep for both groups. For cisgender sexual minorities, family rejection and gender-based victimization were also linked with worse sleep while presence of a GSA and a trusted adult at school were linked with better sleep. For gender minorities, gender-segregated restroom use was also linked with better sleep. CONCLUSIONS: Victimization prevention, increased access to school supports, and improved family connectedness may help enhance LGBTQ+ youth sleep quality and overall health.
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How this classification was reachedexpand
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 | 0.001 | 0.000 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".