Measuring Cognition: The Chicago Cognitive Function Measure in the National Social Life, Health and Aging Project, Wave 2
Bibliographic record
Abstract
OBJECTIVES: To describe the development of a multidimensional test of cognition for the National Social life, Health and Aging Project (NSHAP), the Chicago Cognitive Function Measure (CCFM). METHOD: CCFM development included 3 steps: (a) A pilot test of the Montreal Cognitive Assessment (MoCA) to create a standard protocol, choose specific items, reorder items, and improve clarity; (b) integration into a CAPI-based format; and (c) evaluation of the performance of the CCFM in the field. The CCFM was subsequently incorporated into NSHAP, Wave 2 (n = 3,377). RESULTS: The pre-test (n = 120) mean age was 71.35 (SD 8.40); 53% were female, 69% white, and 70% with college or greater education. The MoCA took an average of 15.6min; the time for the CCFM was 12.0 min. CCFM scores (0-20) can be used as a continuous outcome or to adjust for cognition in a multivariable analysis. CCFM scores were highly correlated with MoCA scores (r = .973). Modeling projects MoCA scores from CCFM scores using the equation: MoCA = (1.14 × CCFM) + 6.83. In Wave 2, the overall weighted mean CCFM score was 13.9 (SE 0.13). DISCUSSION: A survey-based adaptation of the MoCA was successfully integrated into a nationally representative sample of older adults, NSHAP Wave 2.
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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 | 0.005 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".