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Record W2757726848 · doi:10.1111/inm.12379

Multidimensional approach to restraint minimization: The journey of a specialized mental health organization

2017· article· en· W2757726848 on OpenAlexaff
Alexandra Hernandez, Sanaz Riahi, Melanie I. Stuckey, Barbara Mildon, Philip E. Klassen

Bibliographic record

VenueInternational Journal of Mental Health Nursing · 2017
Typearticle
Languageen
FieldPsychology
TopicHealthcare Decision-Making and Restraints
Canadian institutionsUniversity of TorontoOntario Shores Centre for Mental Health Sciences
Fundersnot available
KeywordsSeclusionMedicineMental healthIncident reportPatient isolationPsychiatryEmergency medicineUniversity hospital

Abstract

fetched live from OpenAlex

The executive-level witnessing and review of restraint events has been identified as a key strategy for restraint minimization. In the present study, we examined the changes in restraint practices at a tertiary-level mental health-care facility with implementation of an initiative, in which representatives from senior management, professional practice, peer support, and clinical ethics witnessed seclusion and restraint events, and rounded with clinical teams to discuss timely release and brainstorm prevention strategies. Interrupted time series analysis compared the change from pre-implementation (14 months prior) to postimplementation (35 months' following) in the number of incidents/month, total hours/month, and average hours/incident/month for each of seclusion and mechanical restraint. With implementation, there was a step decrease in average hours/seclusion (-28.3 hours/seclusion, P < 0.001) and total seclusion hours (-1264.5 hours, P = 0.002). The postimplementation rate of decrease of -0.9 hours/incident/month was different than the pre-implementation rate of increase of 0.7 hours/incident/month for mechanical restraint (P = 0.03). Pre-implementation, there was a rate of decrease of 6.1 incidents/month (P < 0.001) and 4.5 incidents/month (P = 0.001) for seclusion and mechanical restraint, respectively. Postimplementation, there was a rate of increase of 0.3 incidents/month and a rate of decrease of 0.05 incidents/month for seclusion and mechanical restraint, respectively, both of which were different than pre-implementation (seclusion: P < 0.001, mechanical restraint: P = 0.002). In conclusion, the total hours of seclusion and average hours per seclusion and per restraint incident were reduced, demonstrating the value of leadership witnessing and daily rounds in promoting restraint minimization in tertiary-level mental health care.

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 score0.712
Threshold uncertainty score0.700

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
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 head0.071
GPT teacher head0.454
Teacher spread0.382 · 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

Citations19
Published2017
Admission routes1
Has abstractyes

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