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Record W4408667478 · doi:10.1080/02568543.2025.2475881

Developmental Screening With Indigenous Families: Perspectives of Early Years Home Visitors on the ASQ-3

2025· article· en· W4408667478 on OpenAlexafffund
Mélissa Tremblay, Anita Rachel Ewan, Zoë Kruschke, Janoah Willsie, Miya Kagan-Cassidy, Charlene Rattlesnake, Heather Downie

Bibliographic record

VenueJournal of Research in Childhood Education · 2025
Typearticle
Languageen
FieldPsychology
TopicFamily and Disability Support Research
Canadian institutionsUniversity of Alberta
FundersUniversity of AlbertaHealth Research
KeywordsPsychologyIndigenousDevelopmental psychologyEarly childhood educationEcology

Abstract

fetched live from OpenAlex

There is a need to add to the limited knowledge base regarding how developmental screening tools can be used in effective and culturally safe ways with Indigenous children and families. The purpose of the current study was to explore the developmental screening experiences of home visitors in a culturally grounded early childhood program (The Early Years Program). We sought to examine Visitors’ experiences with and perceptions of the Ages and Stages Questionnaire-Third Edition (ASQ-3). Using a qualitative descriptive method and a community-based participatory approach, we conducted focus groups with Early Years Visitors. Findings centered around two categories — (1) logistical considerations and (2) enacting a relational process – with several subcategories within each. Findings highlight the diverse functions of the ASQ-3, including as a medium for strengthening relationships and understanding developmental pathways, a catalyst for strengths-focused conversations with families, and an evaluation tool. The tool’s efficacy is deeply intertwined with the nature of its administration; participants emphasized the value of relational dynamics, preparatory measures, and adaptability of the developmental screening process. Findings add to the limited literature base regarding usage of the ASQ-3 with Indigenous families along with practical considerations for other programs seeking to use this tool.

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)0.003
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 score0.111
Threshold uncertainty score0.499

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.044
GPT teacher head0.409
Teacher spread0.365 · 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

Citations1
Published2025
Admission routes2
Has abstractyes

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