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Record W1990608617 · doi:10.3109/01612840.2010.520102

Nursing Practices Recorded in Reports of Episodes of Seclusion

2010· article· en· W1990608617 on OpenAlexaffabout
Caroline Larue, Alexandre Dumais, Aline Drapeau, Geneviève Ménard, Marie‐Hélène Goulet

Bibliographic record

VenueIssues in Mental Health Nursing · 2010
Typearticle
Languageen
FieldPsychology
TopicHealthcare Decision-Making and Restraints
Canadian institutionsHôpital Louis-H LafontaineUniversité de Montréal
Fundersnot available
KeywordsSeclusionPsychiatryMedicineEveningNursing staffPsychiatric hospitalNursingPsychology

Abstract

fetched live from OpenAlex

The purpose of this study is to describe the nursing practices recorded in reports of patient episodes of seclusion, with or without restraints, in a specialized psychiatric facility in Quebec. The reports for all adult patients secluded (n = 4863) in a psychiatric unit between April 1, 2007 and March 31, 2009, were examined. Descriptive analyses were performed. The main reasons for seclusion were agitation, disorganization, and aggressive behaviour. The alternative methods that were attempted included stimulus reduction, extra medication, and working with the patient to find a solution. Few families were notified about their relation's seclusion. More hours of seclusion were reported in the evening and at night. Our results are comparable to those obtained by other investigators. Some of the variables have not been the subject of much research: for example, health conditions during seclusion with or without restraint and partnerships with family members. Our findings also suggest that, in their analyses, studies should differentiate between cognitive-impairment and adult-psychiatry units as well as long-term seclusion and short-term seclusion. The information reported by the nurse makes no distinction between short-stay and long-stay adult psychiatric units. Only one psychiatric facility was investigated in this study, precluding generalization.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.879
Threshold uncertainty score0.878

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.048
GPT teacher head0.516
Teacher spread0.468 · 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.

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

Citations16
Published2010
Admission routes2
Has abstractyes

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