Primary health care providers knowledge of dementia and cognitive assessment tools for elderly populations in Southeast Nigeria: A pilot survey
Bibliographic record
Abstract
Objectives: Primary health care remains the widely available first point of medical care in Nigeria and in other low- and middle-income countries. Recognizing the rising prevalence of dementia in these settings, primary healthcare providers should be trained on cognitive assessment. However, little is known about the current Nigerian primary healthcare providers' knowledge of dementia, cognitive assessment tools, and use in elderly populations. The aim of this study was to evaluate primary healthcare providers' knowledge of dementia and cognitive assessment tools in Southeast Nigeria in preparation for the introduction of digital tablet-based assessment tool. Methods: This is a cross-sectional mixed method descriptive pilot survey carried out in a comprehensive healthcare center affiliated with Nnamdi Azikiwe University Teaching Hospital. Fifty healthcare workers participated. Convenience sampling was employed involving all consenting primary healthcare providers in comprehensive healthcare center-Nnamdi Azikiwe University Teaching Hospital. A structured questionnaire was distributed for generation of both qualitative and quantitative data. Result: The mean age of the 50 primary healthcare providers was 36.6 years, with females constituting 80%. Mean practice duration was 10.8 years. Their response on the mean age at which patients may need a cognitive assessment was reported as 52.8 years. Primary healthcare providers reported that dementia is associated with memory loss and can be genetically inherited. None of the respondents were familiar with Montreal cognitive assessment, or any form of tablet-based cognitive assessment tool. Most (86%) knew about the mini mental state examination. Conclusion: Primary healthcare providers are deficient in knowledge of dementia Alzheimer's or cognitive assessment tools, and so they do not routinely carryout cognitive screening in elderly patients during clinic visits. It is important to train all cadres of primary healthcare staff on the use and benefit of cognitive assessment using culturally validated user-friendly tool to improve quality of care for the elderly population.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".