Accuracy of the Montreal Cognitive Assessment in Detecting Mild Cognitive Impairment and Dementia in the Rural African Population
Bibliographic record
Abstract
OBJECTIVE: The incidence of dementia in the sub-Saharan Africa is rising. However, screening tools for cognitive decline that fits their linguistic and cultural context are lacking. The aim of this study was to determine the accuracy of the Kiswahili version of Montreal Cognitive Assessment (K-MoCA) to detect mild cognitive impairment or dementia among older adults in the rural Tanzania. METHODS: We recruited 259 community-dwelling older adults in Chamwino district, Tanzania. The concurrent validity and discriminatory power of K-MoCA were examined by comparing its score with IDEA cognitive screening and psychiatrist's diagnosis using DSM-V, respectively. All the questionnaires were administered in face-to-face interview. RESULTS: K-MoCA demonstrated acceptable reliability (Cronbach's alpha = 0.780). Concurrent validity was evident by its significant correlation with the IDEA screening test (Pearson's r = 0.651, p < 0.001). Using the psychiatrist's rating as the reference, the optimal cut-off score for MCI and dementia was 19 and 15, respectively, which yielded the sensitivity of 70% and specificity of 60% for MCI, and sensitivity of 72% and specificity of 60% for dementia. Further analysis indicated that education and age influence performance on K-MoCA. CONCLUSION: Overall, the K-MoCA is a reliable and valid tool for measuring cognitive decline. However, its limited discriminatory power for MCI and dementia may be compromised by the cultural irrelevance of some items.
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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 | 0.001 | 0.001 |
| 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".