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Record W2768871312 · doi:10.1017/ipm.2017.48

A comparison of mental health legislation in five developed countries: a narrative review

2017· review· en· W2768871312 on OpenAlexaffabout
T Cronin, Pishoy Gouda, Colm McDonald, Brian Hallahan

Bibliographic record

VenueIrish Journal of Psychological Medicine · 2017
Typereview
Languageen
FieldPsychology
TopicHealthcare Decision-Making and Restraints
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsLegislationMental Health ActMental healthPsychiatryNarrativePsychologyInvoluntary treatmentMedicinePolitical scienceLaw

Abstract

fetched live from OpenAlex

OBJECTIVES: To describe similarities and differences in mental health legislation between five jurisdictions: the Republic of Ireland, England and Wales, Scotland, Ontario (Canada), and Victoria (Australia). METHODS: An in-depth examination was undertaken focussing on the process of involuntary admission, review of Admission Orders and the legal processes in relation to treatment in the absence of patient consent in each of the five jurisdictions of interest. RESULTS: All jurisdictions permit the detention of a patient if they have a mental disorder although the definition of mental disorder varies between jurisdictions. Several additional differences exist between the five jurisdictions, including the duration of admission prior to independent review of involuntary detention and the role of supported decision making. CONCLUSIONS: Across the five jurisdictions examined, largely similar procedures for admission, detention and treatment of involuntary patients are employed, reflecting adherence with international standards and incorporation of human rights-based principles. Differences exist in relation to the criteria to define mental disorder, the occurrence of automatic review hearings in a timely fashion after a patient is involuntarily admitted and the role for supported decision making under mental health legislation.

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)0.006
metaresearch head score (Gemma)0.003
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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.840
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0060.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0010.000

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 head0.485
GPT teacher head0.646
Teacher spread0.161 · 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 designNot applicable
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

Citations19
Published2017
Admission routes2
Has abstractyes

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