Sleep disturbances in spousal caregivers of individuals with Alzheimer's disease
Bibliographic record
Abstract
BACKGROUND: Although sleep problems are commonly reported among dementia caregivers, the nature and frequency of caregiver sleep disruptions, and their relationship to health status, has received little empirical attention to date. METHODS: The current study investigated the sleep situations of a sample of 60 spousal caregivers currently residing with a Alzheimer disease care recipient, including the frequency of nocturnal disruptions by the care recipient, and the reasons for these disruptions. In addition, exploratory correlations were computed between caregiver sleep variables and health outcomes. RESULTS: Some 63% of spousal caregivers reported sleep disruptions due to the nocturnal behavior of the recipients of their care. Poorer caregiver sleep quality was associated with higher frequency of nocturnal disruptions by the care recipient, the care recipient needing to use the bathroom, and wandering, higher caregiver depressive symptoms, and higher levels of caregiver role burden. The frequency of nocturnal disruptions was associated with poorer mental health status and a greater number of depressive symptoms. CONCLUSIONS: Results suggest that nocturnal disruptions by the care recipient may have adverse health consequences for spousal caregivers, and that further study of the determinants of caregiver sleep quality and health outcomes are warranted.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 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".