The brief cognitive assessment tool (BCAT): cross-validation in a community dwelling older adult sample
Bibliographic record
Abstract
Background:Cognitive impairment is underrecognized and misdiagnosed among community-dwelling older adults. At present, there is no consensus about which cognitive screening tool represents the “gold standard.” However, one tool that shows promise is the Brief Cognitive Assessment Tool (BCAT), which was originally validated in an assisted living sample and contains a multi-level memory component (e.g. word lists and story recall items) and complex executive functions features (e.g. judgment, set-shifting, and problem-solving).Methods:The present study cross-validated the BCAT in a sample of 75 community-dwelling older adults. Participants completed a short battery of several individually administered cognitive tests, including the BCAT and the Montreal Cognitive Assessment (MoCA). Using a very conservative MoCA cut score of <26, the base rate of cognitive impairment in this sample was 35%.Results:Adequate internal consistency and strong evidence of construct validity were found. A receiver operating characteristic (ROC) curve was calculated from sensitivity and 1-specificity values for the classification of cognitively impaired versus cognitively unimpaired. The area under the ROC curve (AUC) for the BCAT was .90, p < 0.001, 95% CI [0.83, 0.97]. A BCAT cut-score of 45 (scores below 45 suggesting cognitive impairment) resulted in the best balance between sensitivity (0.81) and specificity (0.80).Conclusions:A BCAT cut-score can be used for identifying persons to be referred to appropriate healthcare professionals for more comprehensive cognitive assessment. In addition, guidelines are provided for clinicians to interpret separate BCAT memory and executive dysfunction component scores.
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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 | 0.002 | 0.002 |
| 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 | 0.001 |
| 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".