Sleep quality in caregivers of patients with Alzheimer's disease and Parkinson's disease and its relationship to quality of life
Bibliographic record
Abstract
BACKGROUND: Knowledge about sleep complaints of caregivers of patients with Alzheimer's disease (AD) and Parkinson's disease (PD) is limited, and we lack information about the relationship between caregivers' sleep problems and their quality of life (QoL). METHODS: We evaluated subjective sleep quality and its relationship to QoL in a group of 80 caregivers of patients with AD (ADCG, n = 40) and PD (PDCG, n = 40), and in 150 controls. Information about night-time complaints was collected using the Pittsburgh Sleep Quality Index (PSQI). QoL was measured using the McGill QoL Questionnaire. RESULTS: Eighteen ADCG (45%), 22 PDCG (55%), and 45 (30%) controls reported poor sleep quality. Mean global PSQI score of PDCG (6.25 ± 3.9) was not significantly different from that of ADCG (5.8 ± 3.5; p = 0.67). However, both PDCG and ADCG scored significantly higher than control group (4.3 ± 3.1; p < 0.01). ADCG frequently reported difficulties falling asleep (72.5%) and disturbed sleep (100%). PDCG reported reduced subjective sleep quality (80%) and increased sleep disturbances (100%). Poor sleep quality was associated with depressive symptoms and correlated with QoL in caregivers of both groups, particularly the psychological symptoms domain. CONCLUSIONS: Among caregivers of patients with AD and PD, poor sleep quality is frequent and significantly linked to QoL and depressive symptoms. Identifying the nature of sleep disturbances not only in patients but also in their caregivers is important as appropriate treatment may lead to a better management of the needs of families coping with these patients.
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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 | 0.004 |
| 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".