Factors Associated With Sleep Disturbance Amongst Youth With Bipolar Disorder.
Bibliographic record
Abstract
Background: While sleep disturbances and their impact on functioning are well-established in adults with bipolar disorder (BD), little is known about this topic in youth. Objective: This study investigates the prevalence and correlates of sleep disturbance among youth with BD. Methods: The study included 103 youth (72 BD, 31 healthy controls [HC]), ages 14-20 years. Study measures included a semi-structured diagnostic interview and the Pittsburgh Sleep Quality Index (PSQI). PSQI yields a global score and 7 subscale scores. Analyses examined between group differences in PSQI scores, and correlates of PSQI within BD. Results: BD youth had significantly higher (worse) global sleep scores, and higher scores on 5/7 subscales (quality, latency, disturbance, sleep medication use, daytime dysfunction). In univariate analyses, poorer sleep quality was associated with higher lifetime and current depression severity, mixed mood state, self-reported affective lability, and borderline personality traits. Lifetime lithium treatment and euthymic mood state were associated with better sleep scores. In multivariate analyses, greater current depression severity and self-reported affective lability were most robustly associated with poor sleep quality. Conclusions: Converging with data from adults, present findings indicate greater sleep disturbance among youth with BD versus HC. Also convergent with adults with BD, mood disturbance, whether depression severity or emotional lability, comprised the predominant correlates of sleep disturbance among youth with BD. Future research is warranted to better understand the temporal association between sleep disturbance and its correlates in youth with BD. Relatedly, interventions that address both mood and sleep disturbances may help improve overall functioning.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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 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".