Policy, Ethics and drama-based Research in Psychiatric Hospitals in Kano
Bibliographic record
Abstract
This paper examines how the Nigeria mental health policy and ethics affect the conduct of drama-based research in psychiatric hospitals in Kano. This research becomes apposite with the endemic nature of mental health cases like substance abuse and substance use disorder in the country. The 2019 United Nations Office on Drugs and Crime (UNODC) survey reports that 14.3 million Nigerians suffer from substance use and abuse, and this figure constitutes a significant proportion of the World Health Organisation report that one in every four Nigerians (an average of 50 million) are challenged with a mental health condition. Using participant observation, questionnaire and key informant interview, the paper explores the knowledge of mental health practitioners about policies on mental health in Nigeria with a view to understanding how it affects their ethical practices and attitudes towards multidisciplinary research like dramatherapy with patients of substance use disorder. Findings from this research is significant for the realisation of best practices in engaging creative and artistic practices in providing care for people with mental health crisis like substance use disorder.
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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 | 0.035 | 0.040 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.020 | 0.031 |
| Scholarly communication | 0.015 | 0.005 |
| Open science | 0.001 | 0.010 |
| Research integrity | 0.005 | 0.007 |
| 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".