Multicenter Validation of the English Version of the Dépistage Cognitif de Québec: a Cognitive Screening Tool for Atypical Dementias
Bibliographic record
Abstract
BACKGROUND: Early detection of atypical dementia remains difficult partly because of the absence of specific cognitive screening tools. This creates undue delays in diagnosis and management. The Dépistage Cognitif de Québec (DCQ; dcqtest.org) was developed in French and later validated in participants with atypical syndromes. We report the validation of the English version. METHODS: This multicentre prospective validation study was conducted in 10 centers across Canada and the United States on 260 English-speaking participants aged over 50. We translated and modified the original French DCQ to add targeted stimuli to the Visusopatial Index and social cognition vignettes to the Behavioral Index. A backward translation was performed and equivalence between languages was assessed by administering both tests to 30 bilingual participants. RESULTS: Mean DCQ total score (out of 100) was 95.0 (SD = 3.6). Spearman's correlation coefficient showed a strong and significant correlation (r = 0.49, p < .001) with the Montreal Cognitive Assessment. Test-retest reliability was good (Spearman's coefficient = 0.72, p < .001) and interrater reliability, excellent (intraclass correlation = 0.97, p < .001). Normative data shown in percentiles were stratified by age and education for a population-based sample of 260 English-speaking controls aged between 50 and 87 years old. CONCLUSIONS: Similar to the French version, the English DCQ proved to be a valid cognitive screening test. The original version was very sensitive to detect atypical dementias such as primary progressive aphasias, Alzheimer's disease' variants and syndromes along the frontotemporolobar degeneration spectrum. This 20-min test can be administered à la carte and offers an alternative to detailed comprehensive neuropsychological evaluations.
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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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".