Diagnostic accuracy of the Montreal Cognitive Assessment (MoCA) for cognitive screening in old age psychiatry: Determining cutoff scores in clinical practice. Avoiding spectrum bias caused by healthy controls
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Bibliographic record
Abstract
OBJECTIVE/METHODS: The Montreal Cognitive Assessment (MoCA) is an increasingly used screening tool for cognitive impairment. While it has been validated in multiple settings and languages, most studies have used a biased case-control design including healthy controls as comparisons not representing a clinical setting. The purpose of the present cross-sectional study is to test the criterion validity of the MoCA for mild cognitive impairment (MCI) and mild dementia (MD) in an old age psychiatry cohort (n = 710). The reference standard consists of a multidisciplinary, consensus-based diagnosis in accordance with international criteria. As a secondary outcome, the use of healthy community older adults as additional comparisons allowed us to underscore the effects of case-control spectrum-bias. RESULTS: The criterion validity of the MoCA for cognitive impairment (MCI + MD) in a case-control design, using healthy controls, was satisfactory (area under the curve [AUC] 0.93; specificity of 73% less than 26), but declined in the cross-sectional design using referred but not cognitive impaired as comparisons (AUC 0.77; specificity of 37% less than 26). In an old age psychiatry setting, the MoCA is valuable for confirming normal cognition (greater than or equal to 26, 95% sensitivity), excluding MD (greater than or equal to 21; negative predictive value [NPV] 98%) and excluding MCI (greater than or equal to 26;NPV 94%); but not for diagnosing MD (less than 21; positive predictive value [PPV] 31%) or MCI (less than 26; PPV 33%). CONCLUSIONS: This study shows that validating the MoCA using healthy controls overestimates specificity. Taking clinical and demographic characteristics into account, the MoCA is a suitable screening tool-in an old age psychiatry setting-for distinguishing between those in need of further diagnostic investigations and those who are not but not for diagnosing cognitive impairment.
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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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 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 it