SLEEP AND DEPRESSIVE SYMPTOMS IN COMMUNITY-DWELLING OLDER ADULTS: FINDINGS FROM AMBULATORY SLEEP EEG
Bibliographic record
Abstract
Abstract There is limited and inconsistent evidence on the association between electroencephalography (EEG) measured sleep and depressive symptoms among community-dwelling older adults. This study investigated the cross-sectional association between EEG-measured sleep and depressive symptoms in 72 community-dwelling older adults without dementia [Age> 65 years; Montreal Cognitive Assessment (MoCA)>17], using baseline data from a randomized clinical trial (NCT03959202). Sleep and depressive symptoms were measured using two-night in-home sleep EEG (Sleep Profiler™) and the Geriatric Depression Scale (GDS-15). Multiple linear regression analyses were conducted with each sleep parameter as the primary predictor and GDS score as the outcome; models were adjusted for age, sex, race, education, marital status, chronic conditions, and MoCA score. Several sleep variables were associated with depressive symptoms (GDS score), including a higher percentage of sleep stage N1 (b = 0.11, 95% confidence interval [CI]: 0.02 – 0.20) and N2 (b = 0.04, 95% CI: 0.00 – 0.08), a lower percentage of N3 sleep (b = -0.04, 95%CI: -0.08 – -0.01), greater wake after sleep onset [b = 0.01, 95%CI: 0.00 – 0.02], and more awakenings ≥ 90s/hour (b = 0.87, 95%CI: 0.21–1.53). Neither total sleep time nor sleep efficiency were associated with GDS score. In conclusion, we found that more lighter (stage N1, N2) sleep, less deep (N3) sleep, and more fragmented sleep, measured by EEG, were associated with more depressive symptoms among community-dwelling older adults without dementia. Sleep architecture and fragmentation may play more important roles than sleep duration in relation to depression.
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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 | 0.001 | 0.003 |
| 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".