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Record W4386410713 · doi:10.1136/bmjgh-2023-013232

Reimagining global mental health in Africa

2023· review· en· W4386410713 on OpenAlexaff
Dawit Wondimagegn, Clare Pain, Nardos Seifu, Carrie Cartmill, Azeb Asaminew Alemu, Cynthia Whitehead

Bibliographic record

VenueBMJ Global Health · 2023
Typereview
Languageen
FieldPsychology
TopicMental Health Treatment and Access
Canadian institutionsThe Wilson CentreUniversity Health NetworkWomen's College HospitalUniversity of Toronto
Fundersnot available
KeywordsMental healthHealth carePublic healthDistressPublic relationsCurriculumEconomic growthPolitical scienceMedicinePsychologySociologyNursingPsychiatryEconomicsPsychotherapist

Abstract

fetched live from OpenAlex

In 2001, the WHO launched The World Health Report most specifically addressing low-income and middle-income countries (LAMICs). It highlighted the importance of mental health (MH), identifying the severe public health impacts of mental ill health and made 10 recommendations. In 2022, the WHO launched another world MH report and reaffirmed the 10 recommendations, while concluding that 'business as usual for MH will simply not do' without higher infusions of money. This paper suggests the reason for so little change over the last 20 years is due to the importation and imposition of Western MH models and frameworks of training, service development and research on the assumption they are relevant and acceptable to Africans in LAMICs. This ignores the fact that most mental and physical primary care occurs within local non-Western traditions of healthcare that are dismissed and assumed irrelevant by Western frameworks. These trusted local institutions of healthcare that operate in homes and spiritual spaces are in tune with the lives and culture of local people. We propose that Western foundations of MH knowledge are not universal nor are their assumptions of society globally applicable. Real change in the MH of LAMICs requires reimagining. Local idioms of distress and healing, and explanatory models of suffering within particular populations, are needed to guide the development of training curricula, research and services. An integration of Western frameworks into these more successful approaches are more likely to contribute to the betterment of MH for peoples in LAMICs.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.810
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0040.000
Bibliometrics0.0000.003
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.005

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.

Opus teacher head0.222
GPT teacher head0.579
Teacher spread0.357 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreReview

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".

Quick stats

Citations17
Published2023
Admission routes1
Has abstractyes

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