Situational analysis to inform development of primary care and community-based mental health services for severe mental disorders in Nepal
Bibliographic record
Abstract
BACKGROUND: Nepal is representative of Low and Middle Income Countries (LMIC) with limited availability of mental health services in rural areas, in which the majority of the population resides. METHODS: This formative qualitative study explores resources, challenges, and potential barriers to the development and implementation of evidence-based Comprehensive Community-based Mental Health Services (CCMHS) in accordance with the mental health Gap Action Programme (mhGAP) for persons with severe mental health disorders and epilepsy. Focus Group Discussions (FGDs, n = 9) and Key-Informant Interviews (KIIs, n = 26) were conducted in a rural district in western Nepal. Qualitative data were coded using the Framework Analysis Method employing QSR NVIVO software. RESULTS: Health workers, general community members, and persons living with mental illness typically attributed mental illness to witchcraft, curses, and punishment for sinful acts. Persons with mental illness are often physically bound or locked in structures near their homes. Mental health services in medical settings are not available. Traditional healers are often the first treatment of choice. Primary care workers are limited both by lack of knowledge about mental illness and the inability to prescribe psychotropic medication. Health workers supported upgrading their existing knowledge and skills through mhGAP resources. Health workers lacked familiarity with basic computing and mobile technology, but they supported the introduction of mobile technology for delivering effective mental health services. Persons with mental illness and their family members supported the development of patient support groups for collective organization and advocacy. Stakeholders also supported development of focal community resource persons to aid in mental health service delivery and education. CONCLUSION: Health workers, persons living with mental illness and their families, and other stakeholders identified current gaps and barriers related to mental health services. However, respondents were generally supportive in developing community-based care in rural Nepal.
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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 | 0.011 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.001 | 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".