MétaCan
Menu
Back to cohort
Record W3092062483 · doi:10.1002/aur.2405

Exploring the Relationship between Prosodic Control and Social Competence in Children with and without Autism Spectrum Disorder

2020· article· en· W3092062483 on OpenAlexafffund
Nichole E. Scheerer, Jeffery A. Jones, Grace Iarocci

Bibliographic record

VenueAutism Research · 2020
Typearticle
Languageen
FieldNeuroscience
TopicAutism Spectrum Disorder Research
Canadian institutionsWilfrid Laurier UniversitySimon Fraser UniversityWestern University
FundersWestern UniversityCanadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada
KeywordsPsychologyAutismAutism spectrum disorderDevelopmental psychologySocial competenceProsodyCompetence (human resources)AudiologyCognitive psychologySocial changeSocial psychologySpeech recognitionMedicine

Abstract

fetched live from OpenAlex

Autism spectrum disorder (ASD) is a developmental disorder characterized by persistent deficits in social communication and interaction. Speech is an important form of social communication. Prosody (e.g. vocal pitch, rhythm, etc.), one aspect of the speech signal, is crucial for ensuring information about the emotionality, excitability, and intent of the speaker, is accurately expressed. The objective of this study was to gain a better understanding of how auditory information is used to regulate speech prosody in autistic and non-autistic children, while exploring the relationship between the prosodic control of speech and social competence. Eighty autistic (M = 8.48 years, SD = 2.55) and non-autistic (M = 7.36 years, SD = 2.51) participants produced vocalizations while exposed to unaltered and frequency altered auditory feedback. The parent-report Multidimensional Social Competence Scale was used to assess social competence, while the Autism-Spectrum Quotient and the Autism Spectrum Rating Scales were used to assess autism characteristics. Results indicate that vocal response magnitudes and vocal variability were similar across autistic and non-autistic children. However, autistic children produced significantly faster responses to the auditory feedback manipulation. Hierarchical multiple regressions indicated that these faster responses were significantly associated with poorer parent-rated social competence and higher autism characteristics. These findings suggest that prosodic speech production differences are present in at least a subgroup of autistic children. These results represent a key step in understanding how atypicalities in the mechanisms supporting speech production may manifest in social-communication deficits, as well as broader social competence, and vice versa. Autism Res 2020, 13: 1880-1892. © 2020 International Society for Autism Research and Wiley Periodicals LLC LAY SUMMARY: In this study, autistic and non-autistic children produced vowel sounds while listening to themselves through headphones. When the children heard their vocal pitch shifted upward or downward, they compensated by shifting their vocal pitch in the opposite direction. Interestingly, autistic children were faster to correct for the perceived vowel sound changes than their typically developing peers. Faster responses in the children with ASD were linked to poorer ratings of their social abilities by their parent. These results suggest that autistic and non-autistic children show differences in how quickly they control their speech, and these differences may be related to the social challenges experienced by autistic 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)0.004
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 score0.005
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
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 head0.196
GPT teacher head0.353
Teacher spread0.157 · 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

Citations6
Published2020
Admission routes2
Has abstractyes

Explore more

Same venueAutism ResearchSame topicAutism Spectrum Disorder ResearchFrench-language works237,207