Canadian Indigenous Cognitive Assessment (CICA): Inter‐rater reliability and criterion validity in Anishinaabe communities on Manitoulin Island, Canada
Bibliographic record
Abstract
INTRODUCTION: Despite increasing dementia rates, few culturally informed cognitive assessment tools exist for Indigenous populations. The Canadian Indigenous Cognitive Assessment (CICA) was adapted with First Nations on Manitoulin Island, Canada, and provides a brief, multi-domain cognitive assessment in English and Anishinaabemowin. METHODS: Using community-based participatory research (CBPR) methods, we assessed the CICA for inter-rater and test-retest reliability in 15 individuals. We subsequently evaluated validity and established meaningful CICA cut-off scores in 55 individuals assessed by a geriatrician. RESULTS: The CICA demonstrated strong reliability (intra-class coefficient = 0.95 [0.85,0.98]). The area under the curve (AUC) was 0.98 (0.94, 1.00), and the ideal cut-point to identify likely cases of dementia was a score of less than or equal to 34 with sensitivity of 100% and specificity of 85%. DISCUSSION: When used with older First Nations men and women living in First Nations communities, the CICA offers a culturally safe, reliable, and valid assessment to support dementia case-finding.
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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 | 0.006 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".