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Record W2885336597

COMMUNITY PERCEPTIONS AND KNOWLEDGE OF MENTAL ILLNESS IN THE RURAL KISUMU REGION OF KENYA

2018· article· en· W2885336597 on OpenAlexaffvenue
Naima Kotadia

Bibliographic record

VenueUBC Faculty of Medicine medical journal · 2018
Typearticle
Languageen
FieldPsychology
TopicMigration, Health and Trauma
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsFocus groupMental healthMental illnessMedicineRural communityStigma (botany)Community health workersQualitative researchRural areaFamily medicinePsychiatryNursingEnvironmental healthPopulationSocioeconomicsHealth services
DOInot available

Abstract

fetched live from OpenAlex

Objective: The Global Health Initiative (GHI) at the University of British Columbia collaborated with the NGO, Kenya Partners in Community Transformation (PCT), to explore community knowledge, beliefs and practices surrounding mental health and illness in the rural Kisumu region. Methods: Five focus group discussions (FGDs) were held in three rural communities within the Kisumu region. Demographic groups surveyed included: women (n=54), men (n=14), and Community Health Workers (CHWs; n=36). Focus groups probed community mental health knowledge and included case–based vignettes describing presentations of mental illnesses as outlined in the Diagnostic and Statistical Manual of Mental Disorders, 5th Edition. Results: Participant responses on mental health and mental illness definitions were generally well understood; however, stigmatizing perceptions were present among community members an CHWs. Medical–based etiologies and treatment were rarely suggested for psychiatric illness, and CHWs did not identify themselves as a resource for mental illness cases. Significant barriers to accessing mental healthcare exist in the area, including stigma, financial strain, and long distances to care centers. Conclusion: Overall, FGDs with community members and CHWs indicated education on mental health was limited. Qualitative data gathered will be used to tailor WHO mental health modules to meet the unique needs of CHWs living in the rural Kisumu region of Kenya.

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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.693
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.058
GPT teacher head0.406
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

Classification

machine, unvalidated

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

Study designQualitative
Domainnot available
GenreEmpirical

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

Citations1
Published2018
Admission routes2
Has abstractyes

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