Screening for Instrumental Activities of Daily Living in Sub-Saharan Africa: A Balance Between Task Shifting, Simplicity, Brevity, and Training
Bibliographic record
Abstract
BACKGROUND: Task shifting has been suggested as one way to help manage the increasing burden of dementia in sub-Saharan Africa (SSA). However, brief, easy-to-use and valid screening tools are needed to support this approach. Our team has developed an 11-item questionnaire to assess instrumental activities of daily living (IADLs) in SSA, the Identification and Intervention for Dementia in Elderly Africans (IDEA)-IADL questionnaire. We aimed to externally validate the questionnaire and develop a shorter, more efficient version. METHODS: A community-based sample of 329 older adults in 4 rural villages was screened for dementia using the validated IDEA cognitive screen and the 11-item IDEA-IADL questionnaire. A stratified sample was assessed for Diagnostic and Statistical Manual of Mental Disorders (Fourth Edition) dementia by a United Kingdom-based doctor, who was blinded to the results of screening. Area under the receiver operating characteristic (AUROC) curve analysis was used to assess validity, and factor analysis and regression modeling were used to develop a shorter version of the questionnaire. RESULTS: A 3-item IDEA-IADL questionnaire was developed and externally validated in the study sample. The questionnaire was deemed to be valid and enhanced screening performance in 2 villages (AUROC: 0.857 and 0.895) but detracted from the accuracy of the IDEA cognitive screen in the other 2 villages (AUROC: 0.591 and 0.639). These differences appeared to be due to differences in interpretation of responses to questions by the assessors. CONCLUSIONS: A brief IDEA-IADLs scale was developed and worked well in some villages. However, our study highlights a training need if brief screening tools to assess IADLs are to be effectively used by nonspecialists in low-resource settings.
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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 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".