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Record W3184710475 · doi:10.5430/jnep.v11n11p48

Simulation-based education for staff managing aggression and high-risk behaviors in children with autism spectrum disorder in the hospital setting: A pilot and feasibility cluster randomized controlled trial

2021· article· en· W3184710475 on OpenAlexvenueno aff
Marijke Mitchell, Fiona Newall, Melissa Heywood, Jenni Sokol, Katrina Williams

Bibliographic record

VenueJournal of Nursing Education and Practice · 2021
Typearticle
Languageen
FieldHealth Professions
TopicHealth Policy Implementation Science
Canadian institutionsnot available
FundersUniversity of MelbourneAustralian Government
KeywordsAutismRandomized controlled trialAutism spectrum disorderIntellectual disabilityAggressionCluster randomised controlled trialMedicinePsychologyClinical psychologyPsychiatry

Abstract

fetched live from OpenAlex

Background and objective: Aggression and high-risk behaviors, which can result in behavioral emergencies, are common in children with autism and can be magnified in the hospital environment. Children with autism, with or without intellectual disability, have complex communication needs which require a sophisticated level of knowledge, understanding and skill from health care professionals. Pediatric acute care nursing staff are often not trained and lack confidence in managing children with autism. The purpose of this study was to conduct a pilot and feasibility cluster randomized controlled trial (RCT) of simulation-based education for staff in managing behavioral emergencies with autism spectrum disorder (ASD) in the hospital setting.Methods: This study used a mixed method, to explore the acceptability and feasibility of delivering a large-scale cluster RCT and assess trial processes including recruitment, completion rates, contamination, and outcome measures. The simulation-based training format comprised two scenarios involving an adolescent with autism, intellectual disability and aggressive behaviors. Two pediatric wards of similar size and patient complexity were selected to participate in the study and randomized to receive either simulation-based education plus web-based education materials or web-based education materials only. Results: The RCT design is feasible with recruitment, acceptability and completion rates reaching target. Self-perceived baseline levels of confidence in managing aggression in children were mid-range and lower for children with autism and intellectual disability. Forty to fifty percent of intervention participants rated the training highly in terms of developing skills and knowledge respectively. The mean group score for observer ratings of de-escalation across four simulations was 20 out of a possible 35. Data for ward aggression were not collected.Conclusions: Simulation-based education is an acceptable training format for acute care pediatric nurses. This study is feasible to conduct as a cluster RCT with some modifications to this protocol including assessment of baseline differences in confidence. Observer ratings of de-escalation skills indicated that more than one episode of training may be required for acute care pediatric staff to successfully de-escalate aggressive incidents. As such, we will use repeated simulation scenario exercises for each intervention group in the next trial.

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)0.009
metaresearch head score (Gemma)0.012
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.045

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.012
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0030.003
Bibliometrics0.0010.001
Science and technology studies0.0010.002
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0080.001

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 head0.144
GPT teacher head0.577
Teacher spread0.432 · 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 designRandomized trial
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

Citations4
Published2021
Admission routes1
Has abstractyes

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