Social environment profiles and cognitive outcomes: a cross-sectional latent class analysis using the Canadian Longitudinal Study on Aging
Bibliographic record
Abstract
Objectives The present study evaluated associations between social environment profiles and cognitive outcomes among generally healthy adults using cross-sectional data from the Canadian Longitudinal Study on Aging (CLSA) Comprehensive Cohort (n = 19,793).Method Latent class analysis classified participants into social environment profiles based on social network size, social support, social cohesion, and social isolation. Three profiles emerged, which were labeled as representing weaker, intermediate, and stronger social environments (16.6%, 40.4%, and 42.9% of the sample, respectively). Scores on eight cognitive tests were combined into three domains: executive function, episodic memory, and prospective memory. Analyses of covariance assessed associations between the social environment profiles and executive function and episodic memory, while prospective memory was assessed with logistic regression.Results Significant associations between the social environment profiles and the three cognitive domains were observed among all statistical models (all p ≤ 0.001). Executive function and episodic memory scores significantly differed between all three profiles, while prospective memory differed between the weaker and stronger profile. The effect sizes of associations were weak, potentially reflecting the generally cognitively healthy sample.Conclusion The social environment is linked with cognitive functioning, but further research is needed to assess the clinical relevance and utility as a target for health promotion.
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".