Feasibility and Validity of the Self-administered Computerized Assessment of Mild Cognitive Impairment With Older Primary Care Patients
Bibliographic record
Abstract
We investigated whether a validated computerized cognitive test, the Computerized Assessment of Mild Cognitive Impairment (CAMCI), could be independently completed by older primary care patients. We also determined the optimal cut-off for the CAMCI global risk score for mild cognitive impairment against an independent neuropsychological reference standard. All eligible patients aged 65 years and older, seen consecutively over 2 months by 1 family practice of 13 primary care physicians, were invited to participate. Patients with a diagnosis or previous work-up for dementia were excluded. Primary care physicians indicated whether they, the patient, or family had concerns about each patient's cognition. A total of 130 patients with cognitive concerns and a matched sample of 133 without cognitive concerns were enrolled. The CAMCI was individually administered after instructions to work independently. Comments were recorded verbatim. A total of 259 (98.5%) completed the entire CAMCI. Two hundred and forty-one (91.6%) completed it without any questions or after simple acknowledgment of their question. Lack of computer experience was the only patient characteristic that decreased the odds of independent CAMCI completion. These results support the feasibility of using self-administered computerized cognitive tests with older primary care patients, given the increasing reliance on computers by people of all ages. The optimal cut-off score had a sensitivity of 80% and specificity of 74%.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".