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Record W2332090554 · doi:10.1097/pec.0000000000000651

Barriers and Facilitators to Implementing the HEADS-ED

2016· article· en· W2332090554 on OpenAlexaffabout
Kate MacWilliams, Janet Curran, J Racek, Paula Cloutier, Mario Cappelli

Bibliographic record

VenuePediatric Emergency Care · 2016
Typearticle
Languageen
FieldMedicine
TopicEmergency and Acute Care Studies
Canadian institutionsChildren's Hospital of Eastern Ontario
Fundersnot available
KeywordsFocus groupMedicineEmergency departmentContext (archaeology)Mental healthQualitative researchConceptual frameworkMedical educationOptimismNursingPsychologyPsychiatrySocial psychology

Abstract

fetched live from OpenAlex

OBJECTIVES: This study sought to identify barriers and facilitators to the implementation of the HEADS-ED, a screening tool appropriate for use in the emergency department (ED) that facilitates standardized assessments, discharge planning, charting, and linking pediatric mental health patients to appropriate community resources. METHODS: A qualitative theory-based design was used to identify barriers and facilitators to implementing the HEADS-ED tool. Focus groups were conducted with participants recruited from 6 different ED settings across 2 provinces (Ontario and Nova Scotia). The Theoretical Domains Framework was used as a conceptual framework to guide data collection and to identify themes from focus group discussions. RESULTS: The following themes spanning 12 domains were identified as reflective of participants' beliefs about the barriers and facilitators to implementing the HEADS-ED tool: knowledge, skills, beliefs about capabilities, social professional role and identity, optimism, beliefs about consequences, reinforcement, environmental context and resources, social influences, emotion, behavioral regulation and memory, and attention and decision process. CONCLUSIONS: The HEADS-ED has the potential to address the need for better discharge planning, complete charting, and standardized assessments for the increasing population of pediatric mental health patients who present to EDs. This study has identified potential barriers and facilitators, which should be considered when developing an implementation plan for adopting the HEADS-ED tool into practice within EDs.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.489
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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 head0.009
GPT teacher head0.287
Teacher spread0.278 · 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 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

Citations15
Published2016
Admission routes2
Has abstractyes

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