Effect of a Multimodal Lifestyle Intervention on Sleep and Cognitive Function in Older Adults with Probable Mild Cognitive Impairment and Poor Sleep: A Randomized Clinical Trial
Bibliographic record
Abstract
BACKGROUND: Poor sleep is common among older adults with mild cognitive impairment (MCI) and may contribute to further cognitive decline. Whether multimodal lifestyle intervention that combines bright light therapy (BLT), physical activity (PA), and good sleep hygiene can improve sleep in older adults with MCI and poor sleep is unknown. OBJECTIVE: To assess the effect of a multimodal lifestyle intervention on sleep in older adults with probable MCI and poor sleep. METHODS: This was a 24-week proof-of-concept randomized trial of 96 community-dwelling older adults aged 65-85 years with probable MCI (<26/30 on the Montreal Cognitive Assessment) and poor sleep (>5 on the Pittsburgh Sleep Quality Index [PSQI]). Participants were allocated to either a multimodal lifestyle intervention (INT); or 2) education + attentional control (CON). INT participants received four once-weekly general sleep hygiene education classes, followed by 20-weeks of: 1) individually-timed BLT; and 2) individually-tailored PA promotion. Our primary outcome was sleep efficiency measured using the MotionWatch8© (MW8). Secondary outcomes were MW8-measured sleep duration, fragmentation index, wake-after-sleep-onset, latency, and PSQI-measured subjective sleep quality. RESULTS: There were no significant between-group differences in MW8 measured sleep efficiency at 24-weeks (estimated mean difference [INT -CON]: 1.18%; 95% CI [-0.99, 3.34]), or any other objective-estimate of sleep. However, INT participants reported significantly better subjective sleep quality at 24-weeks (estimated mean difference: -1.39; 95% CI [-2.72, -0.06]) compared to CON. CONCLUSION: Among individuals with probable MCI and poor sleep, a multimodal lifestyle intervention improves subjective sleep quality, but not objectively estimated sleep.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| 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".