Training of front-line health workers in Somalia on mental health: A mixed-methods effectiveness study on the implementation of mental health gap action programme (mhGAP)
Bibliographic record
Abstract
Background: In 2020, The Federal Ministry of Health, the World Health Organization and the Somali National University rolled out a capacity-building programme called mental health gap action programme (mhGAP). An eight-day training was delivered to 24 front-line health workers serving local communities and internally displaced persons in five regions across south-central Somalia. This study assessed the effectiveness of mhGAP-training in improving participants’ knowledge, understanding and management of priority mental health conditions. Methods: A mixed-methods sequential design was applied to collect and analyze quantitative and qualitative data. Participants responded to pre- and post-tests with 16 multiple-choice questions, tailored to the content of the training. Quantitative data was analyzed using median scores. Four interviews were conducted five months after the mhGAP-training to collect data on value and effectiveness. Qualitative data were thematically analyzed. Results: Median scores were higher in the post-test compared with the pre-test, with 11 (IQR: 9.5-13) in the post-test and 7 (IQR: 4-9.5) in the pre-test. A Wilcoxon signed-ranked test revealed that the post-test score was significantly higher (MD =11, n =24) compared to the pre-test score (Md =7, n =24), z=-3.82, p =0.001, with a large effect size, r =0.5. The participants believed that their new knowledge and clinical skills-set gained had improved readiness for managing mental, neurological and substance use conditions. Conclusion: The findings indicate effectiveness of mhGAP-training for integrating mental health in primary health care. Given the limited human resources capacity and conditions in Somalia, the study has identified a way to expand mental health care to hard-to-reach communities. Training community health workers using a tailor-made training package of mhGAP can establish a continuum of care for marginalized people living with mental health conditions. This may contribute to reducing the substantial treatment gap for mental health care in Somalia.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.017 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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 source (direct Gemma or distilled Codex), 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".