Culture and mental health in Nepal: an interdisciplinary scoping review
Bibliographic record
Abstract
Efforts to address global mental health disparities have given new urgency to longstanding debates on the relevance of cultural variations in the experience and expression of distress for the design and delivery of effective services. This scoping review examines available information on culture and mental health in Nepal, a low-income country with a four-decade history of humanitarian mental health intervention. Structured searches were performed using PsycINFO, Web of Science, Medline, and Proquest Dissertation for relevant book chapters, doctoral theses, and journal articles published up to May 2017. A total of 38 publications met inclusion criteria (nine published since 2015). Publications represented a range of disciplines, including anthropology, sociology, cultural psychiatry, and psychology and explored culture in relation to mental health in four broad areas: (1) cultural determinants of mental illness; (2) beliefs and values that shape illness experience, including symptom experience and expression and help-seeking; (3) cultural knowledge of mental health and healing practices; and (4) culturally informed mental health research and service design. The review identified divergent approaches to understanding and addressing mental health problems. Results can inform the development of mental health systems and services in Nepal as well as international efforts to integrate attention to culture in global mental health.
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 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 | 0.009 | 0.040 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.014 | 0.015 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".