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Record W7042624856

The place of ethics in mental health nurses’ clinical judgment in the use of seclusion

2013· dissertation· en· W7042624856 on OpenAlexaff

Bibliographic record

VenueMspace (University of Manitoba) · 2013
Typedissertation
Languageen
FieldPsychology
TopicHealthcare Decision-Making and Restraints
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsNucleofectionGestational periodHyporeflexiaTSG101PretextArticular cartilage damageDemotion
DOInot available

Abstract

fetched live from OpenAlex

Seclusion is an intervention used in mental health settings, with nurses playing a key role in decisions related to secluding a patient. The purpose of this interpretive description study was to explore the place of ethics in mental health nurses’ clinical judgements on seclusion use. Data collection involved interviews of nine registered psychiatric nurses and eight registered nurses. Nurses described their experiences with seclusion and identified factors that impacted their decision to seclude. Ethical tensions related to seclusion use were outlined. Two themes were identified. The complexity of promoting safety and preventing harm illustrates nurses’ sometimes competing responsibilities to keep people safe, understanding of power differentials and patient vulnerability, and recognition of the various types of harms that can arise with seclusion. The importance of knowing for ethical action with seclusion use highlights the role of knowing oneself, the patient, other team members, and the unit in judgments to seclude.

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)0.057
metaresearch head score (Gemma)0.098
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.057
Threshold uncertainty score0.300

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0570.098
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0160.067
Scholarly communication0.0140.008
Open science0.0020.009
Research integrity0.0020.008
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 head0.130
GPT teacher head0.404
Teacher spread0.274 · 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 designQualitative
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
Published2013
Admission routes1
Has abstractyes

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