Population normative data for three cognitive screening tools for older adults in sub-Saharan Africa
Bibliographic record
Abstract
ABSTRACT In sub-Saharan Africa (SSA),cognitive screening is complicated by both cultural and educational factors, and the existing normative values may not be applicable. The Identification of Dementia in Elderly Africans (IDEA) cognitive screen is a low-literacy measure with good diagnostic accuracy for dementia. Objective: The aim of this study is to report normative values for IDEA and other simple measures [i.e., categorical verbal fluency, the Consortium to Establish a Registry for Alzheimer’s Disease (CERAD) 10-word list] in representative community-dwelling older adults in SSA. Methods: Individuals aged ≥60 years resident in 12 representative villages in Kilimanjaro, Tanzania and individuals aged ≥65 years resident within three communities in Akinyele Local Government Area, Oyo State, Nigeria underwent cognitive screening. The normative data were generated by the categories of age, sex, and education. Results: A total of 3,011 people in Tanzania (i.e., 57.3% females and 26.4% uneducated) and 1,117 in Nigeria (i.e., 60.3% females and 64.5% uneducated) were screened. Individuals with higher age, lower education, and female gender obtained lower scores. The 50th decile values for IDEA were 13 (60–64 years) vs. 8/9 (above 85 years), 10–11 uneducated vs. 13 primary educated, and 11/12 in females vs. 13 in males. The normative values for 10-word list delayed recall and categorical verbal fluency varied with education [i.e., delayed recall mean 2.8 [standard deviation (SD) 1.7] uneducated vs. 4.2 (SD 1.2) secondary educated; verbal fluency mean 9.2 (SD 4.8) uneducated vs. 12.2 (SD 4.3) secondary educated], substantially lower than published high-income country values. Conclusions: The cut-off values for commonly used cognitive screening items should be adjusted to suit local normative values, particularly where there are lower levels of education.
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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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".