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Record W2292781554 · doi:10.1542/peds.2015-2851s

Toward Practice Advancement in Emergency Care for Children With Autism Spectrum Disorder

2016· article· en· W2292781554 on OpenAlexafffund
David Nicholas, Lonnie Zwaigenbaum, Barbara Muskat, William Craig, Amanda S. Newton, Justine Cohen-Silver, Raphael Sharon, Andrea Greenblatt, Christopher Kilmer

Bibliographic record

VenuePEDIATRICS · 2016
Typearticle
Languageen
FieldHealth Professions
TopicAdolescent and Pediatric Healthcare
Canadian institutionsUniversity of TorontoHospital for Sick ChildrenUniversity of AlbertaUniversity of Calgary
FundersCanadian Institutes of Health Research
KeywordsMedicineAutism spectrum disorderEmergency departmentPreparednessQualitative researchHealth careFocus groupAutismSituational ethicsNursingPsychiatryPsychology

Abstract

fetched live from OpenAlex

BACKGROUND AND OBJECTIVE: There is increasing recognition that children with autism spectrum disorder (ASD) experience challenges in busy clinical environments such as the emergency department (ED). ASD may heighten adverse responses to sensory input or transitions, which can impose greater difficulty for a child to cope with situational demands. These problems can be amplified in the ED because of its busy and unpredictable nature, wait times, and bodily care. There is little literature documenting ED-based needs of children with ASD to inform clinical guidelines. The objective was to identify stakeholder perspectives in determining clinical priorities and recommendations to guide ED service delivery for children with ASD. METHODS: After qualitative interviews with children, parents, and health care providers conducted in a previous phase of this study, focus groups were convened with parents of children with ASD, ED clinicians, and ED administrators (total n = 60). Qualitative data were analyzed based on an interpretive description approach. RESULTS: Participants identified the ED and its delivery of care as insufficient to meet the unique needs of children with ASD. The following clinical priorities were identified: ASD-focused preparedness for ED procedures and processes, wait time management, proactive strategies for sedation and restraint, child-focused support, health care provider capacity building, post-ED follow-up resources, and transition planning to adult care. Heightened child- and family-centered care were strongly recommended.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.348
Threshold uncertainty score0.599

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)0.0000.000

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 head0.038
GPT teacher head0.397
Teacher spread0.359 · 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 designObservational
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

Citations56
Published2016
Admission routes2
Has abstractyes

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