Human rights and the use of psychiatric medication
Bibliographic record
Abstract
Purpose – Formal recognition of the human rights of people living with mental health problems has greatly progressed. We must ask ourselves, however, to what extent the formal recognition of these rights has transformed the culture of psychiatric care and improved their quality of life. Gaining Autonomy & Medication Management (GAM) is an approach that strives to empower service users and providers and promotes the exercise of users’ rights by transforming their relationship with the central component of psychiatric treatment in community services: psychopharmacology. The purpose of this paper is to show how GAM highlights the issues surrounding the establishment of a culture of rights. Design/methodology/approach – For this analysis qualitative data were collected in Brazil and in Quebec, Canada, through over 100 interviews done with people living with mental health issues and practitioners who participated in the different GAM implementation projects. Findings – Issues, challenges and obstacles facing the instauration of a human rights culture in mental health services are presented. The profound changes that the understanding and exercise of users’ rights bring to the lives of individuals are supported by excerpts illustrating recurring issues, situations and common experiences that appear in the various contexts of the two different countries. Research limitations/implications – This is not a parallel study taking place into two countries. The methodologies used were different, and as a consequence the comparative power can be limited. However, the results reveal striking similarities. Originality/value – There is scant research on human rights in mental health services in the community, and the issues surrounding the prescribing and follow-up of pharmacological treatment. The joint analysis of the researches in Brazil and in Canada, identified common challenges which are intertwined with the dominant approach of biomedical psychiatry.
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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 | 0.010 | 0.027 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.031 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.009 | 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".