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Record W4200233565 · doi:10.3389/fresc.2021.748346

Investigating the Associations Between Child Autistic Symptoms, Socioeconomic Context, and Family Life: A Pilot Study

2021· article· en· W4200233565 on OpenAlexafffund
Frank Koziarz, Caroline Roncadin, Anna Kata, Eric Duku, Amber Cauwenbergs, William J. Mahoney, Briano Di Rezze, Colleen Anderson, Irene Drmic, Judy Eerkes, Kathleen Dekker, Katholiki Georgiades, Lorraine Hoult, Olaf Kraus de Camargo, Olivia Ng, Peter Rosenbaum, Ronit Mesterman, Stephen J. Gentles, Sue Robertson, Teresa Bennett, Stelios Georgiades

Bibliographic record

VenueFrontiers in Rehabilitation Sciences · 2021
Typearticle
Languageen
FieldPsychology
TopicFamily and Disability Support Research
Canadian institutionsHamilton Health SciencesMcMaster Children's HospitalMcMaster UniversityWilfrid Laurier UniversityImpact
FundersMcMaster University
KeywordsSocioeconomic statusContext (archaeology)PsychologyDevelopmental psychologyAutismClinical psychologyMedicineEnvironmental healthGeography

Abstract

fetched live from OpenAlex

Objective: The day-to-day experience of families with an Autistic child may be shaped by both, child characteristics and available resources, which often are influenced by the socioeconomic context of the family. Using a socioecological approach, this study explored the quantitative associations between child autistic symptoms, family socioeconomic status, and family life. Methods: Data came from the Pediatric Autism Research Cohort—PARC Study (pilot). Parents of children with a recent diagnosis of autism completed a set of assessments, including the Autism Family Experience Questionnaire, Autism Impact Measure, and a Sociodemographic Questionnaire. A series of multiple, iterative linear regression models were constructed to ascertain quantitative associations between child autistic symptoms, socioeconomic context, and family life. Results: A total of 50 children (mean age: 76 months; SD: 9.5 months; and 84% male) with data on the variables of interest were included in the analysis. The frequency of child autistic symptoms was associated with family life outcomes (p = 0.02 and R2 = 24%). Once autistic symptom frequency, symptom impact, and sociodemographic variables were considered, parents of higher educational attainment reported worse family life outcomes compared to their lesser-educated counterparts. This cumulative regression model had considerable explanatory capability (p = 0.01, R2 = 40%). Conclusion: This study demonstrates the utility of using a socioecological approach to examine the dynamic interplay between child characteristics and family circumstances. Our findings suggest that family life for parents (of an autistic child) who have obtained higher education is reported (by the parents themselves) as less satisfactory compared to that of parents without higher education, once adjusted for the autistic symptom frequency of child, symptom impact, and income. These findings can inform the design and delivery of more family-centered care pathways during the years following a diagnosis of autism.

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)0.002
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.012
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.001
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 head0.064
GPT teacher head0.367
Teacher spread0.303 · 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 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

Citations5
Published2021
Admission routes2
Has abstractyes

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