Feasibility of WHO mhGAP-intervention guide in reducing experienced discrimination in people with mental disorders: a pilot study in a rural Kenyan setting
Bibliographic record
Abstract
AimsStigma can have a negative impact on help-seeking behaviour, treatment adherence and recovery of people with mental disorders. This study aimed to determine the feasibility of the WHO Mental Health Treatment Gap Interventions Guidelines (mhGAP-IG) to reduce stigma in face-to-face contacts during interventions for specific DSM-IV/ICD 10 diagnoses over a 6-month period. METHODS: This study was conducted in 20 health facilities across Makueni County in southeast Kenya which has one of the poorest economies in the country and has no psychiatrist or clinical psychologist. We recruited 2305 participants from the health facilities catchment areas that had already been exposed to community mental health services. We measured stigma using DISC-12 at baseline, followed by training to the health professionals on intervention using the WHO mhGAP-IG and then conducted a follow-up DISC-12 assessment after 6 months. Proper management of the patients by the trained professionals would contribute to the reduction of stigma in the patients. RESULTS: There was 59.5% follow-up at 6 months. Overall, there was a significant decline in 'reported/experienced discrimination' following the interventions. A multivariate linear mixed model regression indicated that better outcomes of 'unfair treatment' scores were associated with: being married, low education, being young, being self-employed, higher wealth index and being diagnosed with depression. For 'stopping self' domain, better outcomes were associated with being female, married, employed, young, lower wealth index and a depression diagnosis. In regards to 'overcoming stigma' domain; being male, being educated, employed, higher wealth index and being diagnosed with depression was associated with better outcomes. CONCLUSIONS: The statistically significant (p < 0.05) reduction of discrimination following the interventions by trained health professionals suggest that the mhGAP-IG may be a useful tool for reduction of discrimination in rural settings in low-income countries.
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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 | 0.005 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".