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Record W4220716951 · doi:10.1080/09540261.2022.2027348

Human rights in mental healthcare; A review of current global situation

2022· review· en· W4220716951 on OpenAlexaff
Artin Mahdanian, Marc Laporta, Nathalie Drew Bold, Michelle Funk, Dainus Puras

Bibliographic record

VenueInternational Review of Psychiatry · 2022
Typereview
Languageen
FieldPsychology
TopicHealthcare Decision-Making and Restraints
Canadian institutionsMcGill UniversityDouglas Mental Health University Institute
FundersWorld Health Organization
KeywordsHuman rightsMental healthConvention on the Rights of Persons with DisabilitiesPsychosocialGlobal mental healthConventionPolitical scienceHealth carePsychologyPublic relationsMedicinePsychiatryLaw

Abstract

fetched live from OpenAlex

The relationship between mental health and human rights is complex and bidirectional. Global mental health movements have been emphasizing the promotion of human rights in mental health care in accordance with the UN Convention on the Rights of Persons with Disabilities and the WHO QualityRights Initiative. The main objective of this review is to have an overview of the current global situation of human rights in mental health services by performing a review of scientific literature. The literature search and elimination process yielded a total of 26 articles focussing on human rights-related reports and tools. Further assessment of these articles clearly shows that despite significant improvements in mental health service delivery in the past decade, there is still substantial reporting of the continuing prominence of stigmatizing attitudes, and human rights violations and abuses in mental health settings. The human rights perspective requires society, particularly policymakers, to actively promote necessary conditions for all individuals to fully realize their rights. We suggest developing a more comprehensive model in mental health that integrates human rights into existing services and approaches. A model that recognizes that all people with mental health conditions and psychosocial disabilities are rights holders.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.647
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0060.000

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.

Opus teacher head0.106
GPT teacher head0.532
Teacher spread0.426 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designSystematic review
Domainnot available
GenreReview

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".

Quick stats

Citations51
Published2022
Admission routes1
Has abstractyes

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