Evaluation of a Brief Survey Instrument for Assessing Subtle Differences in Cognitive Function Among Older Adults
Bibliographic record
Abstract
Most measures of cognitive function used in large-scale surveys of older adults have limited ability to detect subtle differences across cognitive domains, and standard clinical instruments are impractical to administer in general surveys. The Montreal Cognitive Assessment (MoCA) can address this need, but has limitations in a survey context. Therefore, we developed a survey adaptation of the MoCA, called the MoCA-SA, and describe its psychometric properties in a large national survey. Using a pretest sample of older adults (n=120), we reduced MoCA administration time by 26%, developed a model to accurately estimate full MoCA scores from the MoCA-SA, and tested the model in an independent clinical sample (n=93). The validated 18-item MoCA-SA was then administered to community-dwelling adults aged 62 to 91 as part of the National Social life Health and Aging Project Wave 2 sample (n=3196). In National Social life Health and Aging Project Wave 2, the MoCA-SA had good internal reliability (Cronbach α=0.76). Using item-response models, survey-adapted items captured a broad range of cognitive abilities and functioned similarly across sex, education, and ethnic groups. Results demonstrate that the MoCA-SA can be administered reliably in a survey setting while preserving sensitivity to a broad range of cognitive abilities and similar performance across demographic subgroups.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".