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Record W4210325090 · doi:10.4236/psych.2022.131011

Mothers’ Socialization of Emotions and Theory of Mind and Emotion Regulation in Children with Autism Spectrum Disorders

2022· article· en· W4210325090 on OpenAlexaffabout
Nathalie Nader‐Grosbois, Émilie Jacobs, Stéphanie Mazzone, Nathalie Poirier

Bibliographic record

VenuePsychology · 2022
Typearticle
Languageen
FieldNeuroscience
TopicAutism Spectrum Disorder Research
Canadian institutionsUniversité du Québec à Montréal
Fundersnot available
KeywordsPsychologySocializationOpenness to experienceDevelopmental psychologyAutismEmotional expressionTheory of mindAutism spectrum disorderSocial psychologyCognition

Abstract

fetched live from OpenAlex

This study compared Belgian and Quebec mothers’ emotional profiles and socialization of the emotions of their children with autism spectrum disorders (ASD). It explored whether emotion-related reactions and conversations vary depending on children’s or mothers’ factors and culture. It examined the extent to which these maternal practices are linked with and predicted by children’s Theory of Mind (ToM) or emotion regulation. The participants were 52 children from Quebec and 49 from Belgium, matched for age and severity of autism, and their mothers. In questionnaires, mothers reported on their own educational level, emotional openness, reactions to and conversations about emotions, and on their child’s ASD symptoms, personality, ToM and emotion regulation. Independent t-tests showed that Belgian children had weaker emotion regulation than Quebec children, but similar levels in ToM; Belgian mothers were less emotionally open, they displayed less socialization of child’s positive emotions, less problem-focused and encouragement of expression to child’s negative emotions, and conversed less frequently about emotions with their child, than Quebec mothers. Other maternal reactions and the variety of emotional terms used were similar. In the whole sample, positive correlations were obtained between emotional verbs or terms used in conversations and children’s ToM and emotion regulation. Hierarchical regressions showed that reactions to negative emotions, involving minimizing, comforting, focusing on the problem and encouraging expression, partly vary according to maternal emotional openness, educational level and culture; socialization of positive emotions partly varies according to culture and educational level. Three reactions to negative emotions were partially predicted by culture and child’s age, the severity of ASD and ToM. Socialization of positive emotions was partially predicted by child’s age, severity of ASD and emotion regulation. Conversations about emotions varied depending on culture, child’s age and severity of ASD. These conversations were linked positively with supportive reactions to negative and positive emotions.

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)0.001
metaresearch head score (Gemma)0.002
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 score0.488
Threshold uncertainty score0.970

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.001
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 head0.019
GPT teacher head0.300
Teacher spread0.281 · 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

Citations3
Published2022
Admission routes2
Has abstractyes

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