Comparison of the Telephone‐Montreal Cognitive Assessment (T‐MoCA) and Telephone Interview for Cognitive Status (TICS) as Remote Screening Tests for Early Alzheimer’s Disease.
Bibliographic record
Abstract
Abstract Background The number of Americans with Alzheimer’s disease (AD) is expected to rise to nearly 14 million by 2060. This alarming number shows a critical need for brief mental status tests that can be administered remotely (e.g., by telephone or videoconferencing) to large numbers of individuals while maintaining the ability to reliably detect cognitive impairment related to AD. Therefore, we sought to validate a recently developed, remotely administered cognitive screening measure, the T‐MoCA, against an established remote measure, the TICS, and prior in‐person clinical and cognitive assessment that provided clinical diagnosis. Relationships with CSF biomarkers of AD were also examined. Methods The TICS and T‐MoCA were completed approximately one‐week apart by 215 participants at the UCSD ADRC. Test order was partially counterbalanced. Extensive in‐person clinical and neuropsychological assessment had been completed on average 1.5 years prior and participants classified as cognitively normal (CN; n = 167), mild cognitive impairment (MCI; n = 25) or dementia (n = 23). CSF had been obtained from 79 participants within 48 months of remote testing and levels of Aβ 1–40 and 1–42, phosphorylated tau (p‐tau), and total tau were measured. Results TICS and T‐MoCA scores were highly correlated overall (r = .787;p<.001), and moderately within specific MCI (r = .657;p<.001) and dementia (r = .673,p = .001) groups (r = .309, p<.001 for CN only). Groups differed significantly on TICS (F(2,212) = 156.66;p<.001) and T‐MoCA (F(2,210) = 143.72;p<.001), with dementia Conclusion The T‐MoCA and TICS are valid brief cognitive screening tests with remote administration that can distinguish individuals with cognitive impairment from those who are cognitively normal. The two tests have similar discriminative ability and degree of association with levels of AD biomarkers in CSF. Thus, the T‐MoCA and TICS are promising measures to meet the growing need for remote cognitive screening for AD.
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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 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".