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Record W4414608490 · doi:10.15273/hpj.v5i1.12297

Identifying Factors That Influence How Pediatric Patients or Their Caregivers Decide to Present to an Emergency Department: A Scoping Review Protocol

2025· review· en· W4414608490 on OpenAlexaff
Emily Devereaux, Leah Boulos, Audrey Steenbeek, Emily Gard Marshall, Janet Curran

Bibliographic record

VenueHealthy Populations Journal · 2025
Typereview
Languageen
FieldMedicine
TopicEmergency and Acute Care Studies
Canadian institutionsDalhousie UniversityIzaak Walton Killam Health Centre
Fundersnot available
KeywordsInclusion (mineral)MEDLINEProtocol (science)Emergency departmentHealth careGrey literatureFocus groupNarrativeData collection

Abstract

fetched live from OpenAlex

Objective: To map and describe the extent and type of evidence in relation to factors that influence how pediatric patients or their caregivers decide to present to an emergency department (ED). Introduction: Studies in countries with universal health care systems have suggested that while patients may consider using services outside of the hospital for care, they often end up presenting to an ED. Understanding how pediatric patients and caregivers decide to present to an ED can inform future health care design to mediate decisions before an ED presentation. Inclusion criteria: Literature will be included if it assesses patients between zero and 17 years who present to the ED and reports findings from the patient’s or caregiver’s perspectives. Studies eligible for inclusion are those that focus on ED presentations in a country with universal health care, Organisation for Economic Co-operation and Development (OECD) membership, and classification as a high-income country. Studies that focus on patients transferred to the ED from a residential or correctional facility will be excluded. Methods: A scoping review using JBI methodology will be conducted. A preliminary search indicated no scoping reviews in this field have been carried out. CINAHL, MEDLINE ALL, PsycInfo, and Embase will be searched with no date limits. No language restrictions will be applied. Data will be extracted using a standardized form. Articles will be screened and data extracted by two independent reviews, with conflicts resolved by a third reviewer or through discussion. Data will be analyzed through tables with an accompanying narrative summary and PRISMA-ScR.

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)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.458
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.196
GPT teacher head0.496
Teacher spread0.300 · 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 designSystematic review
Domainnot available
GenreReview

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

Citations0
Published2025
Admission routes1
Has abstractyes

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