Sleepiness, sleep time, and depression of caregivers are linked with sleep and behaviors of their paired partners with dementia
Bibliographic record
Abstract
Background: Sleep difficulties in people with Alzheimer's disease (AD) and their caregivers (CGs) have been documented. Additionally, sleep disturbances are a risk for AD indicating that poor sleep in CGs may place them at risk for AD. Little is known about the relationship between sleep in people with dementia (PWD) and their CGs. Objective: This pilot study examines sleep in PWD and CGs dyads, and the relationship between PWD sleep and CG sleep, cognition, and burden. We explore whether disordered sleep, degree of dementia and PWD behaviors are related to CG sleep difficulties and burden. Methods: We examined sleep using overnight polysomnography (PSG) and day/night activity using 14-day actigraphy in PWD/CG dyads form the Virginia Alzheimer's Disease Center Clinical Cohort. Dyad members received the Montreal Cognitive Assessment (MoCA), behavioral and mood assessments. CGs completed CG burden and preparedness assessments. Results: Mean activity from actigraphy did not differ within dyad members. PSG measurement of total sleep time (TST), sleep onset latency (SOL), sleep efficiency (SEff), and wake after sleep onset (WASO) revealed that CGs had significantly decreased TST compared to their PWD and experienced greater SOL. Lower PWD MoCA scores were unrelated to CG sleep. However, PWD neuropsychiatric symptoms and CG burden correlated with worse CG SOL. Conclusions: Our findings suggest that chronic rest and activity are linked within dyad members and that when separated, CGs experience shorter TST, lower SEff, and longer SOL than their partners. Additionally neuropsychiatric symptoms and CG burden were associated with worse CG sleep.
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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) | 0.001 | 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) | 0.000 | 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".