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Record W3011936817 · doi:10.1186/s13643-020-01310-z

Implementation strategies in emergency management of children: a scoping review protocol

2020· review· en· W3011936817 on OpenAlexaff
Alex Aregbesola, Ahmed M Abou-Setta, Maya M. Jeyaraman, George N. Okoli, Olt Lam, Kathryn M. Sibley, Terry P. Klassen

Bibliographic record

VenueSystematic Reviews · 2020
Typereview
Languageen
FieldHealth Professions
TopicHealth Policy Implementation Science
Canadian institutionsGeorge & Fay Yee Centre for Healthcare InnovationUniversity of ManitobaChildren's Hospital Research Institute of Manitoba
Fundersnot available
KeywordsCINAHLMedicineProtocol (science)MEDLINEInclusion (mineral)Emergency managementMedical emergencyVariety (cybernetics)Medical educationNursingPsychological interventionAlternative medicineComputer sciencePsychology

Abstract

fetched live from OpenAlex

BACKGROUND: Behavior change is not simple, and the introduction of guidelines or protocols does not mean that they will be followed. As such, implementation strategies are vital for the uptake and sustainability of changes in medical protocols. Medical or mental emergencies may be life-threatening, especially in children due to their unique physiological needs. In emergency departments (EDs), where timely decisions are often made, practice change requires thoughtful considerations regarding the best approaches to implementation. As there are many studies reporting on a wide variety of implementation strategies in the emergency management of children in EDs, we aim to identify and map the characteristics of these studies. METHODS: We will conduct a scoping review to identify various implementation strategies in the emergency management of children using the Arksey and O'Malley framework. We will search MEDLINE (Ovid), Embase (Ovid), Cochrane Central (Wiley), and CINAHL (Ebsco), from inception to May 29, 2019, for implementation studies among the pediatric population (≤ 21 years) in a pediatric emergency setting. Two pairs of reviewers will independently select studies for inclusion and extract the data. We will perform a descriptive, narrative analysis of the characteristics of the identified implementation strategies. DISCUSSION: We will present specific characteristics and outcome measures of all included studies in a tabular form. The results of this review are expected to help identify and characterize successful implementation strategies in the emergency management of children in EDs. SYSTEMATIC REVIEW REGISTRATION: Open Science Framework https://osf.io/h6jv2.

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)0.104
metaresearch head score (Gemma)0.120
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.104
Threshold uncertainty score0.550

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1040.120
Meta-epidemiology (narrow)0.0050.005
Meta-epidemiology (broad)0.0150.013
Bibliometrics0.0260.023
Science and technology studies0.0050.006
Scholarly communication0.0100.011
Open science0.0070.008
Research integrity0.0090.006
Insufficient payload (model declined to judge)0.0630.010

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 head0.665
GPT teacher head0.736
Teacher spread0.071 · 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 designNot applicable
Domainnot available
GenreProtocol

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

Citations2
Published2020
Admission routes1
Has abstractyes

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