Assessing Cognition Remotely: Expanding the Reach of Cognitive Testing for Older Adults at Risk for Dementia in a Randomized Controlled Trial
Bibliographic record
Abstract
Little is known about whether cognitive assessments can be completed remotely by older adults at risk for dementia, and there is no consensus on which tool is best. The SYNchronising Exercises, Remedies in GaIt and Cognition at Home (SYNERGIC@Home) study evaluated the feasibility of a home-based, double-blind, randomized-controlled trial to improve gait and cognition in individuals at risk for dementia. This paper reports a secondary analytic outcome of the cognitive tests used. The three aims were: 1) to examine whether the Montreal Cognitive Assessment (MoCA 8.1 Audiovisual), Cognitive- Functional Composite2 (CFC2), and Telephone Cognitive Screen (T-CogS) could be administered remotely; 2) to compare each tool; 3) to evaluate changes in cognition following the intervention. Sixty participants were randomized to one of four physical/cognitive exercise intervention arms, with 52 participants completing the intervention. Cognitive tests were done in the homes of participants via Zoom for Healthcare™. All 52 participants completed the assessments. The interquartile range (IQR) for the MoCA was 4, the CFC2 was 8, and the T-CogS was 1. At baseline, 11.5% scored perfectly on the MoCA, 0% scored perfectly on the CFC2, and 62% scored perfectly on the T-CogS. Scores on the MoCA (p=.076), CFC2 (p=.053), and T-CogS (p=.281) were not statistically significantly different from baseline to post-intervention. This study demonstrates that these cognitive tests can be administered remotely, with the MoCA and the CFC2 being the most sensitive to variability in scores.
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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 | 0.007 | 0.009 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.004 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".