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Record W4315477867 · doi:10.1155/2023/2925530

Resilience among Parents and Children with Autism Spectrum Disorder

2023· article· en· W4315477867 on OpenAlexafffundabout
Parisa Ghanouni, Laura Eves

Bibliographic record

VenueMental Illness · 2023
Typearticle
Languageen
FieldPsychology
TopicFamily and Disability Support Research
Canadian institutionsDalhousie University
FundersDalhousie University
KeywordsAutism spectrum disorderPsychological resiliencePsychologyResilience (materials science)Developmental psychologyAutismClinical psychologySocial psychology

Abstract

fetched live from OpenAlex

Resilience plays a pivotal role to offset stress among families of children with autism spectrum disorder (ASD). Although the majority of previous studies investigated resilience in parents, it is unclear what factors contribute to resilience in children. Thus, we aimed to explore resilience experienced by parents of children with ASD and how it affects children’s resilience. We invited 50 parents of a child with ASD, 13 years old or younger, across various Canadian provinces in an online survey. Parental resilience was positively associated with household income and negatively associated with parental stress. Resilience in children with ASD was positively associated with their social participation at home and community. Findings indicate a relationship between resilience in children with ASD and their participation, suggesting new ways to increase resilience in children with ASD by enhancing their participation.

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)0.000
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 score0.005
Threshold uncertainty score0.868

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0010.000

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 head0.015
GPT teacher head0.311
Teacher spread0.295 · 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

Citations18
Published2023
Admission routes3
Has abstractyes

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