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Record W4399162876 · doi:10.63050/jpps.18.03.104

Frontline Staff Perceptions of the Safewards Model on a Forensic Psychiatric Unit in Canada

2021· article· en· W4399162876 on OpenAlexaffabout
Tariq Hassan, Brittany Bishop, Imtiaz Ahmad Dogar, Niall Galbraith

Bibliographic record

VenueJournal of Pakistan Psychiatric Society · 2021
Typearticle
Languageen
FieldPsychology
TopicHealthcare Decision-Making and Restraints
Canadian institutionsTrent UniversityQueen's University
Fundersnot available
KeywordsUnit (ring theory)Forensic psychiatryMedicinePerceptionNursingPsychologyPsychiatryMedical education

Abstract

fetched live from OpenAlex

Aim and Method: The Safewards model is an evidence-based program designed to increase safety on inpatient psychiatric wards. This qualitative study sought to obtain feedback regarding the Safewards program from frontline staff on an inpatient forensic unit, three years after implementation of the program, in order to determine their opinions on if the program was effective, and how the program could be improved. Results: The majority of staff expressed that Safewards is an effective and useful program that was worth the time it took to implement, and expressed some suggestions for improvement. More experienced staff are more likely to feel that the program is unnecessary, and newer staff are more likely to feel that they lack sufficient training. Clinical Implications: This feedback, taken in consideration with studies that show that Safewards is effective at reducing rates of conflict and containment, could be useful to other inpatient psychiatric wards considering implementing the Safewards program.

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)0.001
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.494
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
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 head0.022
GPT teacher head0.350
Teacher spread0.328 · 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 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
Published2021
Admission routes2
Has abstractyes

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