EPA-1005 - Sleep markers and depression in outpatient adolescents youth
Bibliographic record
Abstract
Major Depressive Disorder (MDD) is a common health problem characterized by low mood, sadness and irritability. Sleep disturbances are a central feature of depression and adolescence is a period of rapid change in sleep physiology. To evaluate the categorization of sleep change in three of sleep elements : REM changes; Slow weave sleep changes and fragmentation of sleep. We evaluated this as a tool to detect depression To assess features of sleep macro architecture as markers for evaluating and detecting adolescent depression Adolescents completed a two-week protocol that included a formal psychiatric interview, standardized scales, polysomnographic (PSG) assessment, actigraphy, salivary melatonin sampling, and holter monitoring. Depressed adolescents (n = 22) differed from controls (n = 20) on features of sleep macroarchitecture measured by PSG. 59% of the depressed subjects had more than one PSG marker from each category as compared to control (N = 20). This indicates that subjects who were depressed on clinical assessments using the standardized scales and evaluations had changes in sleep suggestive of depression The categorization of sleep change in three categories of sleep components (see above) can be a useful tool to detect depression. The results suggests that the individual markers of depression in children and adolescents may not be as effective as the categorization of sleep changes into three categories and using this general approach
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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 | 0.000 |
| 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 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".