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Record W1924564109 · doi:10.1176/appi.ps.201500066

Mental Health Care for Vulnerable People With Complex Needs in Low-Income Countries: Two Services in West Africa

2015· article· en· W1924564109 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenuePsychiatric Services · 2015
Typearticle
Languageen
FieldHealth Professions
TopicHomelessness and Social Issues
Canadian institutionsCanadian Association of Emergency Physicians
Fundersnot available
KeywordsMental healthFocus groupMental illnessEconomic growthScale (ratio)Low and middle income countriesNursingDeveloping countryHealth careMedicineBusinessPsychologyPsychiatryGeographyEconomicsMarketing

Abstract

fetched live from OpenAlex

People with severe and enduring mental illnesses, such as schizophrenia, are among the most disabled, socially excluded, and underserved populations, especially in low- and middle-income countries. Some programs have been created to target this group. The current global development agenda emphasizes the need to provide care to vulnerable groups. This column compares two long-standing and successful programs for homeless people with mental illness in three West African countries--Nigeria, Côte d'Ivoire, and Bénin. The authors describe essential ingredients of these programs and their integration into existing systems, including funding and other resources, leadership models, and staff. The success of these programs provides support for initiatives to scale up services for people with severely disabling and complex needs, even as the focus is increasingly on cost-effectiveness of mental health integration into decentralized health services.

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.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.667
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.002
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.025
GPT teacher head0.374
Teacher spread0.349 · 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