Feasibility of at-home online cognitive screening prior to primary care wellness visits for older adults
Bibliographic record
Abstract
BACKGROUND: Timely identification of mild cognitive impairment (MCI) is critical for maximizing early intervention opportunities in older adults at risk for dementia. This study evaluated the feasibility, acceptability, and validity of novel digital cognitive tests in primary care. METHODS: In a two-phase pilot study across three clinics, 51 older adults completed digital cognitive assessments remotely on personal devices followed by supervised tablet-based cognitive screening in-clinic and the Montreal Cognitive Assessment (MoCA). Surveys and interviews assessed patient and provider acceptability. Digital test completion rates were examined to assess feasibility. RESULTS: Completion rates ranged from 61.5% - 76% for the at-home assessments and 81.8% for in-clinic testing. Participants generally preferred at-home testing. Providers found in-clinic testing acceptable but identified barriers related to device access and EMR integration. All but one digital test showed moderate correlations with the MoCA. CONCLUSION: Digital cognitive screening-whether remote or in-clinic-shows promise for primary care implementation.
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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 | 0.011 | 0.030 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.003 | 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".