Social engagement and cognitive decline: Exploring relationships between psychosocial functioning and cognitive performance in individuals with mild cognitive impairment
Bibliographic record
Abstract
Abstract Background Psychosocial factors have been identified as potentially modifiable risk factors for dementia (Livingston et al, 2020).Multiple social factors (e.g., participation in social activities, social support, loneliness) and indicators of mental health (e.g., depression) are associated with cognitive performance cross‐sectionally and can predict cognitive decline and risk for Alzheimer’s disease (AD) over time. However, the association between various psychosocial factors and cognitive performance across specific neuropsychological domains remain understudied in individuals at‐risk for AD. This study examined whether current psychosocial function predicted cognitive performance in individuals with mild cognitive impairment (MCI), a critical risk‐state for AD. Method We used data from the Comprehensive Assessment of Neurodegeneration and Dementia (COMPASS‐ND) study to examine psychosocial and cognitive functioning in 124 participants with MCI (MAge = 71.5 ± 6.4, MEducation = 15.5 ± 3.9). Psychosocial factors were measured using self‐reported questionnaires about mental health (e.g., depression, anxiety), perceived social function (e.g., social support, loneliness), and engagement with social networks (e.g., current participation, number of community activities). Cognitive function was assessed using a comprehensive battery of neuropsychological tests. We conducted a principal component analysis to derive composite scores for five cognitive domains (memory, executive function, verbal fluency, processing speed, and working memory). Multiple linear regression models were used to test the direct effects of various psychosocial variables on cognitive performance, controlling for age, sex, education, MoCA scores, and living circumstances. Results We found that better quality of life was associated with better scores on memory tests. We also found that current social participation was significantly associated with verbal fluency and processing speed. Specifically, those endorsing low current social participation had worse verbal fluency and processing speed scores than those endorsing normal or high current social participation. Conclusion These findings indicate that increased participation in one’s social networks, over other psychosocial factors, has a positive relationship with cognitive performance in multiple domains in individuals with MCI. Our findings provide groundwork for further psychosocial‐cognitive analyses in individuals with (or at risk for) AD to better understand the role of poor social engagement in cognitive decline. References: Livingston et al. (2020). The Lancet, 396, 413‐446.
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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 | 0.002 |
| 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 | 0.001 | 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 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".