Contributors to sleep disturbances in caregivers and care recipients with dementia
Bibliographic record
Abstract
Abstract Background Sleep disturbances in Alzheimer’s disease impact people with dementia (PWD) and caregivers (CGS) who have primary responsibility for care provision. However, it is unknown which aspects of dementia including cognitive decline and behavioral disturbance contribute most to sleep disturbances in patients and caregivers. This pilot study aims to discover what contributes most to sleep deficits, and whether these factors are consistent across both PWD and CGS. Method Patients: Six dyads with PWD and their primary CGS. Cognitive/behavioral variables: the Montreal Cognitive Assessment (MoCA) (PWD) and the Neuropsychiatric Inventory Questionnaire (NPI‐Q) completed by CGS. Polysomnography: recorded and scored for 1 night for each dyad member separately. Actigraphy: Wrist actigraphy recorded for 14 days in both members of the dyad divided into fixed rest (2200‐0600) and activity (0600‐2200) periods. Sleep variables: total sleep time (TST), sleep onset latency (SOL), nighttime activity as measured by actigraphy. Result Preliminary results indicate that severity of cognitive dysfunction measured by the MoCA correlates with sleep time (CG r = 0.6224, PWD r = 0.5421). However, presence of neuropsychiatric symptoms and caregiver distress as measured by the NPIQ correlate with sleep onset latency (CG r = 0.9432*, PWD r = 0.7819) and nighttime activity in both CGs and PWD (CG r = 0.8467, PWD r = 0.8708). * = p<0.05. Conclusion This pilot study of six PWD/CGS dyads examines the relationship between cognition, behavioral disturbance, CGS response to the behavioral disturbance, and sleep. This data indicates that sleep disturbances in PWD and their CGs cannot be explained exclusively by worsening cognitive function and likely have stronger dependence on the neuropsychiatric well‐being of the PWD and CGS emotional response. This dyadic model is unique in that it looks at the interdependence of the PWD/CGS dyad using both objective measures of sleep, cognition, and behavioral disturbance as well as subjective CGS stress. Data from additional dyads is currently being collected to increase the sample size along with the inclusion of additional variables in order to increase understanding of the relationship between PWD characteristics, caregiver burden and sleep disturbances.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".