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Record W7162097525 · doi:10.82308/24517

Involuntary hospitalization and treatment in first-episode psychosis: Characteristics of patients involuntarily hospitalized and/or treated

2020· dissertation· en· W7162097525 on OpenAlexaboutno aff
Nina Fainman-Adelman

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldPsychology
TopicHealthcare Decision-Making and Restraints
Canadian institutionsnot available
Fundersnot available
KeywordsInvoluntary treatmentCatchment areaSchizophrenia (object-oriented programming)PsychosisSample (material)Mental healthMEDLINEDescriptive statistics

Abstract

fetched live from OpenAlex

Background: The use of involuntary hospitalization and treatment in psychiatry remains a controversial issue. While some have argued for their importance in prevention of harm, others have cited the inconclusive evidence for their effectiveness as highly problematic. Youth with first-episode psychosis (FEP) represent a group whose engagement in services is particularly important as it is often their first time encountering mental health care. The use of coercive measures such as involuntary hospitalization and treatment has been largely under-studied in this population. Since these measures continue to be used in this population, it is important to ensure their proper use. Objectives: The objectives of the following studies were (1) to discover what is known about characteristics of FEP patients receiving involuntary hospitalization and treatment, and (2) to examine the characteristics of FEP patients receiving community treatment orders (CTOs) in a sample from a catchment area in Montreal Quebec. Methods: A systematic review was conducted, in which all studies on the characteristics of FEP patients receiving involuntary hospitalization and treatment was critically analyzed. A quantitative descriptive study was then undertaken. Characteristics that increased the likelihood of FEP patients receiving CTOs were analyzed using a patient sample (N = 688) from a catchment area in Montreal, Quebec. Results: The systematic review identified a wide variance in frequencies of the use of involuntary hospitalization and treatment. Even more, characteristics associated with increased likelihood of receiving involuntary hospitalization and treatment varied across jurisdictions and between studies. Only one study had analyzed the characteristics of FEP patients receiving community treatment orders (CTOs). The quantitative study revealed that, in this treatment setting, FEP patients may be more likely to be given a CTO if they are more uncooperative, less anxious, have lower levels of functioning, and lower levels of judgement and insight. Discussion: Taken together, it is evident from these studies that characteristics of patients who are involuntarily hospitalized or treated is an important area for continuous exploration. It is important to continue to track and investigate whether these measures are being used as intended in order to hold clinicians accountable and reduce any potential biases towards patients. This area is, as a whole, largely under-studied and requires more research attention to ensure proper use

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)0.004
metaresearch head score (Gemma)0.023
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.113
Threshold uncertainty score0.225

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.023
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0040.008
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.000
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 head0.022
GPT teacher head0.322
Teacher spread0.300 · 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 designObservational
Domainnot available
GenreEmpirical

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

Citations0
Published2020
Admission routes1
Has abstractyes

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