Aging research in the time of COVID‐19: A telephone screen for subjective cognitive concerns in community‐dwelling ethnically diverse older adults
Bibliographic record
Abstract
Abstract Background There is an urgent need for validation of remotely‐administered cognitive screens to identify older adults at risk for dementia, to monitor disease progression, and to facilitate follow‐up when in‐person visits are not feasible. Restrictions on in‐person cognitive assessments due to COVID‐19 have spurred a growing literature on telephone‐based cognitive screening. However, few studies have evaluated the value of telephone‐administered screens of subjective cognitive concerns (SCC), an important early marker of dementia‐risk. Method Einstein Aging Study participants (subsample, n=455; Mage=77.0; Myears education=15.0; 64.1% women; 46.4% White) completed the Telephone Screen for Subjective Cognitive Concerns (T‐SSCC), a 16‐item measure of self‐reported memory, language, executive functioning, visuospatial/navigation, concentration, calculation, and mental clarity concerns, as well as the Telephone Montreal Cognitive Assessment (T‐MoCA). In‐person assessments included the paper‐and‐pencil Cognitive Change Index (CCI) and comprehensive neuropsychological evaluation. Classification as cognitively normal (CN; n=288) or mild cognitive impairment (MCI; n=153) was based on Jak/Bondi criteria. Primary analyses included correlations between the objective and subjective screening instruments, and logistic regression to evaluate the association between the T‐SSCC and MCI status. Result Total endorsement of concerns on the T‐SSCC (OR 1.095, CI 1.018‐1.178, p=0.015) was significantly associated with MCI status. In particular, endorsement of “Do any of these problems interfere with your daily life?” was strongly related to MCI (OR 2.296, CI 1.284‐4.108, p=0.005). The T‐SSCC was moderately correlated with the in‐person CCI (r[114]=0.577, p<0.001). A small but significant relationship was observed between the T‐SSCC and T‐MoCA (r[258]=‐0.206, p<0.001). Conclusion To our knowledge, this is the first study to validate a telephone SCC screen in response to the crucial need for such remotely administered measures. The T‐SSCC was significantly associated MCI status; furthermore, specific items related to the impact of cognitive problems in daily life were particularly sensitive to MCI. Such SCC measures are brief, accessible, and well‐tolerated and may provide additionally valuable information that enhances remotely‐administered cognitive screens.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".