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Record W1481036344 · doi:10.1111/cch.12193

The impact of restraint reduction meetings on the use of restrictive physical interventions in <scp>E</scp>nglish residential services for children and young people

2014· article· en· W1481036344 on OpenAlexfundno aff
Roy Deveau, Sarah Leitch

Bibliographic record

VenueChild Care Health and Development · 2014
Typearticle
Languageen
FieldPsychology
TopicHealthcare Decision-Making and Restraints
Canadian institutionsnot available
FundersMcGill University
KeywordsRestrictivenessPsychological interventionReduction (mathematics)PsychologyEnvironmental healthBusinessMedicinePsychiatryMathematics

Abstract

fetched live from OpenAlex

AIM: The aim was to examine the impact of post restraint reduction meetings upon the frequency and restrictiveness of restraint use in English children's residential services. BACKGROUND: Attention has been drawn to the misuse, overuse and safety of some techniques used to physically restrain children in residential services. Successful interventions to reduce restraints have been reported, mostly from the USA. RESULTS: Demonstrate a significant overall reduction in both, frequency and restrictiveness of restraints; the greatest percentage decrease in the most restrictive floor restraints. Whilst five services reduced both frequency and restrictiveness, five services showed some increases in frequency and/or restrictiveness of restraints employed. CONCLUSIONS: Restraint reduction is most effectively reduced through employing multiple strategies and that post restraint reduction meetings maybe one useful component. Organisations seeking to promote restraint reduction meetings need to allocate sufficient priority and resources to support these.

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)0.002
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.021
Threshold uncertainty score0.042

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.036
GPT teacher head0.360
Teacher spread0.324 · 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 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

Citations15
Published2014
Admission routes1
Has abstractyes

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