Sex and race influence objective and self-report sleep and circadian measures in emerging adults independently of risk for bipolar spectrum disorder
Bibliographic record
Abstract
Abstract There is a need to better understand key factors that impact sleep and circadian function for young adults of differing races and sexes. Sex and race are common factors contributing to disparities in health outcomes; however, the influence of these variables on sleep and circadian patterns for young adults are not well known. Multiple objective and self-report facets of sleep and circadian function were assessed (melatonin onset, actigraphy, and sleep diaries) in an ecological momentary assessment study of 150 emerging adults (Mage = 21.8 years; 58.7% female; 56% White, 22.7% Black, 21.3% Other ethnicity) at high or low risk for bipolar spectrum disorder (BSD). Controlling for BSD risk status, sex and race were significant predictors of objective and self-reported sleep and circadian rhythm measures. Males self-reported better sleep efficiency and exhibited later dim light melatonin onset phase than females, whereas females exhibited more actigraphy-measured sleep periods. White participants exhibited more actigraphy-measured total sleep time (TST), better sleep efficiency, and fewer sleep periods, and more self-reported TST and better sleep efficiency than Black participants. Our findings enhance the literature by utilizing robust measurement of sleep and circadian parameters to extend previous findings to a young adult sample at high or low risk for BSD.
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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 | 0.000 | 0.002 |
| 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) | 0.002 | 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".