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Record W2012005329 · doi:10.3109/10903127.2013.856505

Creation and Delphi-method Refinement of Pediatric Disaster Triage Simulations

2014· article· en· W2012005329 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenuePrehospital Emergency Care · 2014
Typearticle
Languageen
FieldHealth Professions
TopicDisaster Response and Management
Canadian institutionsResearch CanadaUniversity of British Columbia
FundersU.S. Public Health Service
KeywordsTriageMedicineChecklistLikert scaleDelphi methodPsychological interventionMedical emergencyDebriefingFidelityCLARITYMedical educationPatient safetyNursingMedical physicsHealth careComputer sciencePsychologyArtificial intelligence

Abstract

fetched live from OpenAlex

OBJECTIVE: There is a need for rigorously designed pediatric disaster triage (PDT) training simulations for paramedics. First, we sought to design three multiple patient incidents for EMS provider training simulations. Our second objective was to determine the appropriate interventions and triage level for each victim in each of the simulations and develop evaluation instruments for each simulation. The final objective was to ensure that each simulation and evaluation tool was free of bias toward any specific PDT strategy. METHODS: We created mixed-methods disaster simulation scenarios with pediatric victims: a school shooting, a school bus crash, and a multiple-victim house fire. Standardized patients, high-fidelity manikins, and low-fidelity manikins were used to portray the victims. Each simulation had similar acuity of injuries and 10 victims. Examples include children with special health-care needs, gunshot wounds, and smoke inhalation. Checklist-based evaluation tools and behaviorally anchored global assessments of function were created for each simulation. Eight physicians and paramedics from areas with differing PDT strategies were recruited as Subject Matter Experts (SMEs) for a modified Delphi iterative critique of the simulations and evaluation tools. The modified Delphi was managed with an online survey tool. The SMEs provided an expected triage category for each patient. The target for modified Delphi consensus was ≥85%. Using Likert scales and free text, the SMEs assessed the validity of the simulations, including instances of bias toward a specific PDT strategy, clarity of learning objectives, and the correlation of the evaluation tools to the learning objectives and scenarios. RESULTS: After two rounds of the modified Delphi, consensus for expected triage level was >85% for 28 of 30 victims, with the remaining two achieving >85% consensus after three Delphi iterations. To achieve consensus, we amended 11 instances of bias toward a specific PDT strategy and corrected 10 instances of noncorrelation between evaluations and simulation. CONCLUSIONS: The modified Delphi process, used to derive novel PDT simulation and evaluation tools, yielded a high degree of consensus among the SMEs, and eliminated biases toward specific PDT strategies in the evaluations. The simulations and evaluation tools may now be tested for reliability and validity as part of a prehospital PDT curriculum.

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.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.144
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.030
GPT teacher head0.418
Teacher spread0.388 · 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