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Record W3109380201 · doi:10.1017/s2045796020001031

The use of mechanical restraint in Pacific Rim countries: an international epidemiological study

2020· article· en· W3109380201 on OpenAlexaff
Giles Newton‐Howes, M. K. Savage, Richard Arnold, T. Hasegawa, Vincent S. Staggs, Steve Kisely

Bibliographic record

VenueEpidemiology and Psychiatric Sciences · 2020
Typearticle
Languageen
FieldPsychology
TopicHealthcare Decision-Making and Restraints
Canadian institutionsDalhousie University
Fundersnot available
KeywordsEpidemiologyPacific RimMedicinePsychologyOceanographyGeologyPathology

Abstract

fetched live from OpenAlex

AIMS: The use of mechanical restraint is a challenging area for psychiatry. Although mechanical restraint remains accepted as standard practice in some regions, there are ethical, legal and medical reasons to minimise or abolish its use. These concerns have intensified following the Convention on the Rights of Persons with Disabilities. Despite national policies to reduce use, the reporting of mechanical restraint has been poor, hampering a reasonable understanding of the epidemiology of restraint. This paper aims to develop a consistent measure of mechanical restraint and compare the measure within and across countries in the Pacific Rim. METHODS: We used the publicly available data from four Pacific Rim countries (Australia, New Zealand, Japan and the United States) to compare and contrast the reported rates of mechanical restraint. Summary measures were computed so as to enable international comparisons. Variation within each jurisdiction was also analysed. RESULTS: International rates of mechanical restraint in 2017 varied from 0.03 (New Zealand) to 98.9 (Japan) restraint events per million population per day, a variation greater than 3000-fold. Restraint in Australia (0.17 events per million) and the United States (0.37 events per million) fell between these two extremes. Variation as measured by restraint events per 1000 bed-days was less extreme but still substantial. Within all four countries there was also significant variation in restraint across districts. Variation across time did not show a steady reduction in restraint in any country during the period for which data were available (starting from 2003 at the earliest). CONCLUSIONS: Policies to reduce or abolish mechanical restraint do not appear to be effecting change. It is improbable that the variation in restraint within the four examined Pacific Rim countries is accountable for by psychopathology. Greater efforts at reporting, monitoring and carrying out interventions to achieve the stated aim of reducing restraint are urgently needed.

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)0.012
metaresearch head score (Gemma)0.011
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.055
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0120.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
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 head0.331
GPT teacher head0.478
Teacher spread0.147 · 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.

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

Citations37
Published2020
Admission routes1
Has abstractyes

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