Exploring the Influence of Loneliness on Cognitive Decline: Differential Effects in White and Black Older Adults
Bibliographic record
Abstract
Abstract Background Approximately 25% of adults 65+ are socially isolated. Social isolation (i.e., loneliness), or the perceived absence of an available and acceptable social network, may be associated with increased cognitive decline. However, there is a limited understanding of how social isolation influences cognitive decline and if this relationship differs as a function of race. Methods A total of 3,082 participants (n = 1943 Whites, n = 1139 Blacks) with 20,882 follow‐ups over 10 years were included from the RUSH database. Participants completed the De Jong Gierveld Loneliness Scale and were identified as having either high or low loneliness using a median split of perceived social isolation. Participants were then divided into one of four groups based on race (White vs Black) and loneliness (High vs Low): 1) White‐High (n = 1030), 2) White‐Low (n = 913), 3) Black‐High (n = 493), 4) Black‐Low (n = 646). Linear mixed‐effects models examined group differences in cognitive change over time (global cognition, episodic memory, semantic memory, visuospatial ability, and working memory). Results White adults with high loneliness exhibited increased rates of cognitive change compared to low and high loneliness Black adults in all domains (p<.01). Compared to White adults with low loneliness, Whites with high loneliness exhibited increased decline in all domains except processing speed and visuospatial ability (p<.001). Black adults with high loneliness exhibited increased decline compared to Black adults with low loneliness in all domains (p<.01). Conclusion Our study reveals a robust association between loneliness and cognitive decline in older adults, with White individuals experiencing a more pronounced impact than their Black counterparts. These findings underscore the need for targeted interventions to address loneliness, particularly among White older adults, to mitigate cognitive decline and promote healthy aging.
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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 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".