Relationship between loneliness and cognitive impairment in community-dwelling elderly in Wuhan
Bibliographic record
Abstract
Objective To examine the impact of loneliness on cognitive impairment among community-dwelling elderly people. Methods A cross-sectional survey was conducted between July and August 2015 with 895 community-dwelling elderly participants in four residential areas of Wuchang District, Wuhan.The Montreal Cognitive Assessment (MoCA) was used to measure cognitive function.Chi-square test, t-test, and multivariate linear regression were used to analyze the data. Results Multivariate linear analysis showed that loneliness was independently and negatively associated with cognitive function among the participants (β=-1.2828, 95%CI: -2.27--0.30). Participants who felt loneliness recorded lower scores on visuospatial executive, attention, and language ability than those who did not (P<0.05). Multivariate logistic analysis demonstrated that loneliness was also associated with cognitive function after adjustment for age and gender, with OR (95%CI) at 1.74(1.05-2.91) / 1.78(1.07-2.94). Loneliness remained an independent risk factor for cognitive dysfunction after adjustment for age, gender, education level, monthly income, living arrangement, physical activity, mental activity, hypertension, diabetes, frequency of social interaction, and type of social interaction, with OR (95%CI) at 1.69(1.00-2.87) / 1.72(1.02-2.90). Conclusions Loneliness is a significant and independent impact factor for cognitive dysfunction among community-dwelling elders. Key words: Loneliness; Cognition disorders
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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 | 0.001 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".