Cognitive reserve and mild cognitive impairment in older adults of low socioeconomic status: evidence from an observational study in Colombia
Bibliographic record
Abstract
OBJECTIVES: The construct of cognitive reserve (CR) suggests that environmental factors influence cognition over time, resulting in a more resilient response to pathology or adverse conditions in some individuals. The goal of this study was to identify and analyze differences in CR among older adults of low socioeconomic status (SES). METHODS: A sample of 102 older adults, both with (n = 52) and without (n = 50) amnestic mild cognitive impairment (aMCI), underwent a cognitive assessment protocol including the Cognitive Reserve Index Questionnaire (CRIq). Participants' SES levels were classified using the European Society for Opinion and Marketing Research Standard Demographic Classification. Mean and distributional comparisons, logistic regression, and receiver operating characteristic (ROC) analysis were conducted. RESULTS: Mean comparisons and distribution analysis showed that participants with aMCI had lower CR than those without aMCI. Logistic regression models revealed that CRIq score predicted aMCI in this population (OR = 0.955, p < .001), particularly through education (OR = 0.546, p < .001) and work (OR = 0.970, p < .001) dimensions. ROC curve results indicate the model has adequate discriminatory power, with an area under the curve (AUC) of 0.738. DISCUSSION: Low CR is a sign of pathological cognition in low SES older adults. A higher level of CR in subjects with low SES, even if not meeting the criteria for High CR, has a role in mitigating aMCI. Future studies expand on these findings by examining the relationship between CR and SES in the brain-behavior association, including biomarkers such as the A/T/N framework.
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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 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 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) | 0.001 | 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".