Ageing and mental health resources for older persons in the African region of the World Health Organization
Bibliographic record
Abstract
Africa is a region where a demographic transition from high child mortality and low life expectancy, to low child mortality and high life expectancy is only just beginning. Nevertheless, some countries already have a growing number of persons over the age of 60 – a number that is likely to increase rapidly. As a consequence, the number of older persons with mental disorders is likely to increase. To better understand the organisation of care for older persons, data are being collected to reduce the imbalance between ‘disease information’ and ‘resource information’ – information that addresses older persons’ needs in terms of mental health care. This review presents some results from the continent. Mental health problems among older adults are still not a public health priority in Africa, but careful examination of each country nevertheless reveals certain specificities, such as divergent life expectancy and different values regarding ageing. The authors present some recommendations for the development of care for old persons with mental disorders, based on the general recommendations made by the World Health Organization (WHO) in the World Health Report 2001 (WHR 2001), and by the WHO and the World Psychiatric Association (WPA) in some consensus statements on psychiatry of the elderly.
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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 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.113 | 0.013 |
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".