Psychometrics and diagnostic properties of the Montreal Cognitive Assessment 5‐min protocol in screening for Mild Cognitive Impairment and dementia among older adults in Tanzania: A validation study
Bibliographic record
Abstract
BACKGROUND: The prevalence of dementia in Tanzania, as in other developing countries, is progressively increasing. Yet international screening instruments for mild cognitive impairment are lacking. OBJECTIVES: The aim of this study was to determine the psychometrics and the diagnostic ability of the Montreal Cognitive Assessment 5 minutes protocol (MoCA-5-min) among older adults in the rural Tanzania. METHODS: The MoCA-5-min and the Identification and Intervention for Dementia in Elderly Africans (IDEA) cognitive screening were concurrently administered through face to face to 202 community-dwelling older adults in Chamwino district. Exploratory factor analysis (EFA) using principal component method and oblique rotation was performed to determine the underlying factor structure of the scale. The concurrent and construct as well as predictive validities of the MoCA-5-min were examined by comparing its score with IDEA cognitive screening and psychiatrist's diagnosis using DSM-V criteria, respectively. RESULTS: The EFA found that all the MoCA-5-min items highly loaded into one component, with factor loading ranging from 0.550 to 0.879. The intraclass correlation coefficient for 6 weeks test-retest reliability was 0.85. Its strong significant correlation with the IDEA screening (Pearson's r = 0.614, p < 0.001) demonstrated a good concurrent validity. Using the psychiatrist's rating as the gold standard, MoCA-5-min demonstrated the optimal cut-off score for MCI at 22, which yielded the sensitivity of 80% and specificity of 74%; and dementia at score of 16 giving a sensitivity of 90% and specificity of 80%. Upon stratifying the sample into different age groups, the optimal cut-off scores tended to decrease with the increase in age. CONCLUSION: The MoCA-5-min is reliable and provides a valid and accurate measure of cognitive decline among older population in the rural settings of Tanzania. The use of varying cut-off scores across age groups may ensure more precise discriminatory power of the MoCA-5-min. IMPLICATIONS FOR PRACTICE: Availability of the MoCA-5-min in Tanzania will facilitate clinicians to timely detect dementia at both pre-clinical and clinical stages. Its availability will also encourage further research and international collaborations in dementia prevention programs.
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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 | 0.013 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".