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Record W3168791991 · doi:10.1002/aur.2551

Keep it simple: Identification of basic versus complex emotions in spoken language in individuals with autism spectrum disorder without intellectual disability: A meta‐analysis study

2021· review· en· W3168791991 on OpenAlexaff
Michal Icht, Gil Zukerman, Esther Ben‐Itzchak, Boaz M. Ben‐David

Bibliographic record

VenueAutism Research · 2021
Typereview
Languageen
FieldNeuroscience
TopicAutism Spectrum Disorder Research
Canadian institutionsToronto Rehabilitation InstituteUniversity of TorontoUniversity Health Network
Fundersnot available
KeywordsSadnessPsychologyAutism spectrum disorderHappinessAutismIdentification (biology)Intellectual disabilityBoredomDevelopmental psychologyCognitive psychologyClinical psychologyAngerSocial psychologyPsychiatry

Abstract

fetched live from OpenAlex

Daily functioning involves identifying emotions in spoken language, a fundamental aspect of social interactions. To date, there is inconsistent evidence in the literature on whether individuals with autism spectrum disorder without intellectual disability (ASD-without-ID) experience difficulties in identification of spoken emotions. We conducted a meta-analysis (literature search following the PRISMA guidelines), with 26 data sets (taken from 23 peer-reviewed journal articles) comparing individuals with ASD-without-ID (N = 614) and typically-developed (TD) controls (N = 640), from nine countries and in seven languages (published until February 2020). In our analyses there was no sufficient evidence to suggest that individuals with HF-ASD differ from matched controls in the identification of simple prosodic emotions (e.g., sadness, happiness). However, individuals with ASD-without-ID were found to perform significantly worse than controls in identification of complex prosodic emotions (e.g., envy and boredom). The level of the semantic content of the stimuli presented (e.g., sentences vs. strings of digits) was not found to have an impact on the results. In conclusion, the difference in findings between simple and complex emotions calls for a new-look on emotion processing in ASD-without-ID. Intervention programs may rely on the intact abilities of individuals with ASD-without-ID to process simple emotions and target improved performance with complex emotions. LAY SUMMARY: Individuals with autism spectrum disorder without intellectual disability (ASD-without-ID) do not differ from matched controls in the identification of simple prosodic emotions (e.g., sadness, happiness). However, they were found to perform significantly worse than controls in the identification of complex prosodic emotions (e.g., envy, boredom). This was found in a meta-analysis of 26 data sets with 1254 participants from nine countries and in seven languages. Intervention programs may rely on the intact abilities of individuals with ASD-without-ID to process simple 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 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)0.007
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Bibliometrics, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.559
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0050.001
Bibliometrics0.0050.025
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0030.002
Research integrity0.0000.004
Insufficient payload (model declined to judge)0.0030.000

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 head0.264
GPT teacher head0.473
Teacher spread0.209 · 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.

Study designMeta-analysis
Domainnot available
GenreReview

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

Citations39
Published2021
Admission routes1
Has abstractyes

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