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Record W3130349237 · doi:10.1002/aur.2485

Alexithymia is related to poor social competence in autistic and nonautistic children

2021· article· en· W3130349237 on OpenAlexafffund
Nichole E. Scheerer, Troy Q. Boucher, Grace Iarocci

Bibliographic record

VenueAutism Research · 2021
Typearticle
Languageen
FieldNeuroscience
TopicAutism Spectrum Disorder Research
Canadian institutionsSimon Fraser UniversityWestern University
FundersNatural Sciences and Engineering Research Council of CanadaCanada First Research Excellence Fund
KeywordsAlexithymiaAutismPsychologyDevelopmental psychologyCompetence (human resources)Clinical psychologySocial psychology

Abstract

fetched live from OpenAlex

Alexithymia is characterized by difficulties identifying and describing one's own emotions and the emotions of others. These challenges with understanding emotions in people with alexithymia may give rise to difficulties with social interactions. Given that alexithymia frequently co-occurs with autism spectrum disorder (ASD), and that both populations have difficulties with social interactions, it is of interest to determine whether alexithymia can help to parse some of the heterogeneity in social competence in autistic and nonautistic individuals. The caregivers of 241 children (6-14 years old), including 120 autistic, and 121 nonautistic, rated their child's social competence using the Multidimensional Social Competence Scale (MSCS), autism traits using the Autism Spectrum Quotient (AQ), and alexithymia traits using the Children's Alexithymia Measure (CAM). Regression analyses indicated that age, IQ, sex, AQ, and CAM scores accounted for 40.2% of the variance in autistic children's, and 68.2% of the variance in nonautistic children's, parent-reported social competence. Importantly, after controlling for age, IQ, sex, and AQ scores, CAM scores alone accounted for an additional 16.2% of the variance in autistic children's, and 17.4% of the variance in nonautistic children's social competence. These results indicate that higher alexithymia traits predict lower levels of social competence, suggesting that increased difficulty in identifying and describing one's own emotions and the emotions of others is associated with poorer social competence. Furthermore, CAM scores were found to partially mediate the relationship between autistic traits and social competence, suggesting that comorbid alexithymia traits may be partially responsible for poor social competence in individuals with high autistic traits. This research contributes to the understanding of the factors associated with the development of social competence and highlights alexithymia as a potential target for identification and intervention to improve social competence. LAY SUMMARY: Alexithymia is a condition where people find it hard to think and talk about their (and others') feelings. About 50% of autistic people have alexithymia. This might be why they have social and emotional difficulties. Parents answered questions about alexithymia and social difficulties their children have. Children with more alexithymia problems had poorer social skills. Thus, alexithymia may be related to social problems faced by autistic and nonautistic children.

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)0.000
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 score0.012
Threshold uncertainty score0.023

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.058
GPT teacher head0.377
Teacher spread0.319 · 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

Citations24
Published2021
Admission routes2
Has abstractyes

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