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Record W2119063497 · doi:10.1186/2046-4053-3-26

Discharge instructions for caregivers in the context of pediatric emergency care: a narrative synthesis protocol

2014· article· en· W2119063497 on OpenAlexafffund
Janet Curran, Andrea Murphy, Mandi Newton, Roger Zemek, Lisa Hartling, Amy C. Plint, Jill Chorney, Shannon MacPhee, Samuel Campbell, Mona Jabbour, Darlene Boliver, David Petrie, Randy Colwell, Kate MacWilliams, Alicia Nolan

Bibliographic record

VenueSystematic Reviews · 2014
Typearticle
Languageen
FieldMedicine
TopicEmergency and Acute Care Studies
Canadian institutionsChildren's Hospital of Eastern OntarioUniversity of AlbertaDartmouth General HospitalIzaak Walton Killam Health CentreDalhousie University
FundersCanadian Institutes of Health Research
KeywordsMedicineProtocol (science)NarrativeContext (archaeology)Emergency departmentMedical emergencyNursingMedical educationAlternative medicine

Abstract

fetched live from OpenAlex

BACKGROUND: The period following discharge from a pediatric emergency department (ED) can be a time of significant vulnerability for caregivers who provide ongoing care to their child when they return home. Discharge communication practice varies widely at the individual practitioner and departmental level. At present, there are no nationally accepted guidelines for discharge communication for children and/or their caregivers in the ED.The primary objective of this knowledge synthesis is to understand how and why discharge instructions work and under what conditions. We will also examine the contextual factors and barriers and facilitators associated with discharge communication across varied ED settings. METHODS/DESIGN: Using an integrated narrative approach, we will synthesize different types of evidence and explore relationships within and between included studies to develop a theory-based and knowledge user-informed discharge communication practice guideline. We will follow key principles for knowledge synthesis including: (1) involvement of a multidisciplinary team (for example, information specialists, statisticians, and content experts); (2) developing focused and answerable questions in collaboration with the knowledge users; (3) using a systematic method including specific tools and techniques appropriate for answering questions concerned with effectiveness and the implementation of interventions; and, (4) involving knowledge users throughout the process in an integrated knowledge translation approach. DISCUSSION: This collaborative and narrative approach will be a determining factor in increasing the reliability, validity and relevance of the study findings for healthcare practice and policy decision-makers. TRIAL REGISTRATION: PROSPERO registration number: CRD42014007106.

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)0.001
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.749
Threshold uncertainty score0.437

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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)0.0000.000

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 head0.041
GPT teacher head0.347
Teacher spread0.305 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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

Citations13
Published2014
Admission routes2
Has abstractyes

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