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Record W3056214256 · doi:10.1093/pch/pxaa068.117

118 Innovating Pediatric Behavioural Assessments and Care Pathways: Community Consultation Phase

2020· article· en· W3056214256 on OpenAlexaff
Sarah Gander, Sarah Campbell, Kate Flood, Bryn Robinson

Bibliographic record

VenuePaediatrics & Child Health · 2020
Typearticle
Languageen
FieldHealth Professions
TopicChild and Adolescent Health
Canadian institutionsHorizon Health Network
Fundersnot available
KeywordsThematic analysisReferralFocus groupMental healthMultidisciplinary approachPsychologyService delivery frameworkMedicineQualitative researchService providerService (business)NursingPsychiatry

Abstract

fetched live from OpenAlex

Abstract Background It is well-documented that children facing social disparities, trauma and toxic stress will experience a disproportionate number of negative physical and mental health outcomes across their lifespan. A common manifestation of this is the increasing prevalence of behaviour-related diagnoses in school-aged children. Regardless of whether a child suffers from a true behaviour disorder, or if they are displaying symptoms that relate to complex and challenging social conditions, they require a thoughtful, collaborative and inclusive approach to their care. Community Social Pediatrics adopts such an approach. Objectives The objective of the current study is to examine and understand the experiences of children and their families during the referral and treatment process for pediatric behavioural referrals in our local region. We will also explore the perspective of service providers on the challenges and strengths of the current system. Design/Methods A focus group (n=8) using semi-structured group interviews was conducted with caregivers whose children were in various stages of care/treatment regarding behavorial issues in the region surrounding Saint John, NB. Questions focused on: experiences in the system; efficacy of services; the child’s experience; wait times; and system cohesion. Qualitative thematic analysis was used to analyze the data. Through a strategic planning exercise (n=26), we were able to engage service providers and experts in this area to delineate the challenges and strengths that they perceive in the current system, and to provide insights they have into working with families. Results The major themes identified by families were defined by positive interactions, negative interactions, barriers, their own behavioural responses to the system and the impact on the child. Families’ positive experiences were associated with respectful and effective communication, integrated wrap-around services, assistance with navigation, and a child-centred approach. Negative experiences were rooted in feeling stigmatized by service providers, lack of communication between service providers, and inadequate mental health services for children. A number of system and personal barriers were identified. The service providers echoed these issues: provide equitable and efficient access to services; understand the needs of the family; strengthen relationships with partners and clients; and create a supportive working environment. Conclusion Consultation with families and service providers identified a number of issues in how children access and engage with community services. Community Social Pediatrics seeks to impact health at the community level and addresses the needs of children in a way that reflects the social context of their lives, community and society. Assessment and care procedures that are delivered through this model aim to remove barriers, reduce fragmentation and increase collaboration and communication across the entire care team.

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)0.017
metaresearch head score (Gemma)0.025
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.037
Threshold uncertainty score0.124

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0170.025
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0080.001
Scholarly communication0.0030.002
Open science0.0040.011
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0370.004

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 head0.131
GPT teacher head0.428
Teacher spread0.297 · 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 designQualitative
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

Citations0
Published2020
Admission routes1
Has abstractyes

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