Loneliness, Sleep Quality, and Cognitive Function in Community-Dwelling Older Adults
Bibliographic record
Abstract
Abstract Loneliness is a risk factor for cognitive decline in older adults, however, the underlying mechanisms are less understood. Individuals who experience frequent loneliness tend to have poorer sleep quality. Empirical evidence supports the influence of sleep on cognitive health. This study examined the possible mediating effect of sleep characteristics on the relationship between loneliness and cognition. The study sample included 557 participants from wave 2 of the National Social Life, Health, and Aging Project who had actigraphy sleep measures (mean age = 73.17, 52.6% female). Loneliness was assessed with the 3-item UCLA Loneliness Scale. Cognitive function was measured with the Montreal Cognitive Assessment. Five sleep quality indicators were objectively recorded with wearable devices: assumed sleep time; actigraphy sleep time; time spent awake after sleep onset (WASO); sleep fragmentation; and sleep percentage (actigraphy sleep/(assumed sleep + WASO)). Path analysis model results show that WASO, fragmentation, and sleep percentage mediate the link between loneliness and cognitive function. Loneliness was positively related to WASO, and WASO was negatively associated with cognition. Loneliness correlated with increased sleep fragmentation which was associated with worse cognitive function. Individuals who had more frequent loneliness had a lower sleep percentage, and sleep percentage was positively associated with cognitive function. Nonetheless, the path from loneliness to these three sleep characteristics became insignificant after controlling for depressive symposiums. Depressive symptoms and fragmentation were found to double mediate the association between loneliness and cognitive function. Sleep and depression could be underlying pathways for the association between loneliness and cognition.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".