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Record W4409942782 · doi:10.17975/sfj-2025-004

Social, communicational, and emotional effects of social skills interventions on autistic minors

2025· article· en· W4409942782 on OpenAlexvenueno aff
Morgan Synn

Bibliographic record

VenueSTEM Fellowship Journal · 2025
Typearticle
Languageen
FieldPsychology
TopicFamily and Disability Support Research
Canadian institutionsnot available
Fundersnot available
KeywordsSocial emotional learningPsychologyAutismPsychological interventionSocial skillsDevelopmental psychologySocial psychologyCognitive psychologyPsychiatry

Abstract

fetched live from OpenAlex

This study examines how social skills interventions affect the quality of conversation skills and emotional competence of autistic children and adolescents. These abilities can both improve quality of life and social wellbeing in autistic individuals who often experience social difficulties, thus making this a crucial field of investigation. The studies analyzed were identified on databases such as JSTOR and the NIH; we also utilized published works from the Journal of Autism and Developmental Disorders, Journal of Communication Disorders, and the Journal of Intellectual & Developmental Disability, among others. In this systematic review, 23 studies satisfied the inclusion criteria. Studies found improvements in conversation skills such as verbalizations, initiations, responses, greetings, and usage of facial expressions/gestures. Some improvements for emotional competence consist of emotion recognition, emotional expression, and internal emotion regulation. In addition, many studies found generalization—application of learned skills in similar real-life situations—of social and emotional skills over time when following up a few months post-intervention. The majority of studies had large effect sizes (paired Cohen’s d). These findings suggest that social interventions, especially those that are group- or school-based, have positive effects on social and emotional abilities in autistic minors, as well as the generalization of these skills in real life following the programs.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.801
Threshold uncertainty score0.796

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.059
GPT teacher head0.427
Teacher spread0.368 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

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