Mental health services: the African gap
Bibliographic record
Abstract
Purpose – Neuropsychiatric disorders account for a substantial proportion of disease burden and disability in Africa. Despite this, mental health systems are under-resourced in Africa, as in most parts of the world, creating a “treatment gap” and denying the African population the right to mental health achieved through access to mental health services. The paper aims to discuss these issues. Design/methodology/approach – The mental health systems of African countries were compared with figures for all low- and middle-income countries (LAMICS) using data from the World Health Organization Assessment Instrument for Mental Health Systems. Comparable global figures were also available for some indicators from the WHO's World Mental Health Atlas 2011. Findings – Selected indicators of mental health systems are presented for 14 African countries and shows that they are lower as compared to figures for all other LAMICS and also global figures. The treatment gap for mental disorders is much higher in Africa than comparable global figures. For example, the treatment gap for mood disorders has been estimated from 95 to 100 per cent for some African countries. Originality/value – There is an imbalance between need and service provision in the area of mental health across the world but particularly in Africa. Despite this, there are a greater number of outpatient than inpatient services in Africa which provides an opportunity for development of community-based services. There are also many encouraging examples of effective approaches to reducing the burden of neuropsychiatic disease in Africa.
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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 | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| 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 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".