In-Home Assistive Technology May Help Protect Dementia Caregivers from Declining Sleep Efficiency: A Randomized Control Trial
Bibliographic record
Abstract
OBJECTIVES: Caregivers for people with dementia (PWDs) often experience sleep problems due to stressors associated with their role (e.g. concern about PWDs' nighttime wandering). We investigated whether a technology system, People Power Caregiver (PPCg), that helps monitor the caregiver's home would benefit caregivers' sleep. METHODS: = 62.73, SD = 11.10, range = 32-89) were assigned to a fully activated PPCg condition or control condition (Study 1: partially active PPCg; Study 2: waitlist control). Caregivers completed the Pittsburgh Sleep Quality Index at baseline, three-months, and six-months. RESULTS: Caregivers in the control conditions reported significantly worsening sleep efficiency whereas in comparison, those in the active conditions reported improving sleep efficiency. CONCLUSIONS: Given how critical sleep is both for caregivers' health and the care they provide, these findings underscore potential benefits of in-home technologies for protecting caregivers' sleep. CLINICAL IMPLICATIONS: Technology-based interventions that help monitor the home may support caregivers' sleep. Protecting caregivers' sleep may also preserve their ability to provide high-quality care as their loved one's disease and associated functional decline progresses.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.001 |
| 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 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".