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Record W1981418532 · doi:10.1097/yco.0b013e328330cd15

Compulsory treatment in psychiatry

2009· review· en· W1981418532 on OpenAlexaff
Kathleen Sheehan

Bibliographic record

VenueCurrent Opinion in Psychiatry · 2009
Typereview
Languageen
FieldPsychology
TopicHealthcare Decision-Making and Restraints
Canadian institutionsMcMaster University
Fundersnot available
KeywordsPsychiatryMedicinePsychology

Abstract

fetched live from OpenAlex

PURPOSE OF REVIEW: Compulsory treatment is a common, yet controversial, practice in psychiatry. This paper reviews recent studies on the use of compulsory measures in hospital, the community and special populations. RECENT FINDINGS: Researchers continue to examine the rates and patterns of involuntary hospitalization. However, they have extended their investigations to care in the community, acknowledging it as the primary locus of treatment for most patients. Research shows that the implementation of community mental health legislation presents complex clinical and practical issues that require further investigation. Recognition that compulsory treatment is an objective event which is subjectively experienced by patients, families and clinicians has led to research investigating stakeholder views. The therapeutic relationship has been found to be an important modifier of the experience of compulsory treatment. Recent studies have also focused on specific coercive practices, such as forced medication and seclusion, and the use of these in patient subgroups, including those with eating disorders and adolescents. The debate about whether compulsory treatment is ethical continues in the literature. SUMMARY: Compulsory treatment in psychiatry remains an ethically and clinically contentious issue. As ethical concerns are generally countered by the argument that compulsory measures can lead to beneficial clinical outcomes, further empirical investigation in this area is required.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.005
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0020.003
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0050.001

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 head0.175
GPT teacher head0.513
Teacher spread0.338 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations43
Published2009
Admission routes1
Has abstractyes

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