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Record W4390932817 · doi:10.3389/fpubh.2023.1309154

The Family-Check-Up® Autism Implementation Research (FAIR) Study: protocol for a study evaluating the effectiveness and implementation of a family-centered intervention within a Canadian autism service setting

2024· article· en· W4390932817 on OpenAlexafffundabout
Teresa Bennett, Irene Drmic, Julie Gross, Marc Jambon, Melissa Kimber, Anat Zaidman‐Zait, Kathryn Andrews, Eric Duku, Stelios Georgiades, Andrea González, Magdalena Janus, E. Lipman, Paulo Pires, Heather Prime, Caroline Roncadin, Mackenzie Salt, R. Shine

Bibliographic record

VenueFrontiers in Public Health · 2024
Typearticle
Languageen
FieldPsychology
TopicFamily and Disability Support Research
Canadian institutionsWilfrid Laurier UniversityHamilton Health SciencesYork UniversityMcMaster UniversityMcMaster Children's Hospital
FundersMcMaster University
KeywordsAutismMental healthIntervention (counseling)Socioeconomic statusMedicinePsychologyPublic healthPsychiatryClinical psychologyDevelopmental psychologyPopulationNursingEnvironmental health

Abstract

fetched live from OpenAlex

Introduction Prevalence rates of emotional and behavior problems (EBP) in autistic children and youth are high (40–70%), and often cause severe and chronic impairment. Furthermore, autistic children are also more likely to experience family “social-ecological” adversity compared to neurotypically developing peers, including social isolation, child maltreatment, caregiver mental illness, and socioeconomic risk. These family stressors increase the risk of co-occurring EBP among autistic children and can often impede access to evidence-based care, thus amplifying long-term health inequities for autistic children and their caregivers. In the current autism services landscape, there are few scalable, evidence-based programs that adequately address these needs. TheFamily Check-Up (FCU®)is a brief, strength-based, and tailored family-centered intervention that supports positive parenting and explicitly assesses the social determinants of child and family mental health within an ecological framework. Studies have demonstrated long-term positive child and caregiver outcomes in other populations, but the FCU® has not been evaluated in families of autistic children and youth. Therefore, we aimed to evaluate FCU® implementation within an established, publicly funded Autism Program in Ontario, Canada, with delivery by autism therapists, to demonstrate sustainable effectiveness within real-world settings. Methods In this study, we outline the protocol for a hybrid implementation-effectiveness approach with two key components: (1) A parallel-arm randomized controlled trial ofN= 80 autistic children/youth (ages 6–17 years) and high levels of EBP and their caregivers. Primary and secondary outcomes include child EBP, and caregiver well-being and parenting. (2) A mixed methods implementation study, to describe facilitators and barriers to implementation of the FCU® within an autism service setting. Discussion Scalable, ecologically focused family-centered interventions offer promise as key components of a public health framework aimed at reducing mental health inequities among autistic children, youth, and their caregivers. Results of this study will inform further program refinement and scale-up.

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)0.067
metaresearch head score (Gemma)0.045
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.865
Threshold uncertainty score0.355

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0670.045
Meta-epidemiology (narrow)0.0070.006
Meta-epidemiology (broad)0.0080.006
Bibliometrics0.0040.004
Science and technology studies0.0110.004
Scholarly communication0.0050.005
Open science0.0070.004
Research integrity0.0070.008
Insufficient payload (model declined to judge)0.0760.012

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 head0.253
GPT teacher head0.578
Teacher spread0.325 · 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 designNot applicable
Domainnot available
GenreProtocol

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

Citations5
Published2024
Admission routes3
Has abstractyes

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