Subjective sleep characteristics associated with anxiety and depression in older adults: a population‐based study
Bibliographic record
Abstract
OBJECTIVE: Sleep complaints are often associated with anxiety and depression, but the specific complaints related to each syndrome are poorly characterized, especially in older adults. The objective was to identify subjective sleep characteristics specific to anxiety and depression in this population. METHODS: A random sample of 2393 individuals aged 65 years or older was used. Anxiety and depression were categorized using DSM-V criteria for phobias, panic disorder, generalized anxiety disorder, unspecified anxiety disorder, major depressive episode, and depressive episode with insufficient symptoms. Subjective sleep characteristics were measured using the Pittsburgh Sleep Quality Index. Logistic regression models predicting anxiety or depression were used to determine the independent sleep characteristics associated with each syndrome adjusting for age, sex, education level, cognitive functioning, anxiolytic/sedative/hypnotic use, antidepressants use, subjective health, chronic diseases, cardiovascular conditions, and anxiety or depression (as appropriate). RESULTS: Nearly all Pittsburgh Sleep Quality Index subscales were significantly associated with anxiety, but these subscales shared variance and only sleep duration in hours, sleep disturbance score, and daytime functioning score were independently related to anxiety. Within these significant subscales, the main specific sleep complaints associated with anxiety were daytime sleepiness and sleep disturbances related to coughing/snoring, feeling cold, and bad dreams. The use of sleeping medication was the only specific sleep characteristic associated with depression. CONCLUSIONS: These results suggest that in older adults, symptoms of short sleep duration, daytime sleepiness and sleep disturbances are independently related to anxiety while the use of sleep medication is independently associated to depression.
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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 | 0.000 | 0.000 |
| 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) | 0.000 | 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".