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Record W3019932286 · doi:10.5334/ijic.4696

“Improving Access to Early Childhood Developmental Surveillance for Children from Culturally and Linguistically Diverse (CALD) Background”

2020· article· en· W3019932286 on OpenAlexaff
Karen Edwards, Tania Rimes, Rebecca Smith, Ritin Fernandez, Lisa Stephenson, Jane Son, Vanessa Sarkozy, Deborah Perkins, Valsamma Eapen, Susan Woolfenden

Bibliographic record

VenueInternational Journal of Integrated Care · 2020
Typearticle
Languageen
FieldMedicine
TopicInfant Development and Preterm Care
Canadian institutionsChildren’s Health Research Institute
Fundersnot available
KeywordsMedicineOutreachAttendanceEarly childhoodHealth careChild developmentNursingFamily medicinePsychologyDevelopmental psychologyPsychiatry

Abstract

fetched live from OpenAlex

INTRODUCTION: Developmental vulnerabilities in pre-school aged children from culturally and linguistically diverse (CALD) backgrounds with low English proficiency are less likely to be identified through universal developmental surveillance. Barriers include low parental health literacy and low rates of attendance to mainstream child and family health services. Late detection of developmental vulnerabilities can have lifelong impacts on life trajectory. METHOD: Integrated outreach early childhood developmental surveillance was trialled in South East Sydney by local health services with non-government organisations (NGO) delivering early childhood education and support. NGO staff were trained in Parents Evaluation of Developmental Status (PEDS), a validated developmental screening tool to explore parental/carer and provider concerns [1]. Families with children identified with developmental concerns by NGO staff were referred to co-located or visiting Child and Family Health Nurses (CFHN), community child health, speech pathology or developmental services for developmental screening, assessment and/or care planning. RESULTS: Integrated health and NGO services improved access to developmental surveillance for CALD families in a non-threatening environment enabled by co-locating CFHN, or through visits by paediatric medical/speech pathology staff to participating playgroups. CONCLUSIONS AND DISCUSSION: Integration supported vulnerable families from CALD backgrounds to access developmental surveillance through child and family health services but required flexibility and adjustments by all involved.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.089
Threshold uncertainty score0.565

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)0.0000.000

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 head0.018
GPT teacher head0.278
Teacher spread0.261 · 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

Citations22
Published2020
Admission routes1
Has abstractyes

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