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Record W3028640378 · doi:10.1177/1362361320922058

Prediction of social behavior in autism spectrum disorders: Explicit versus implicit social cognition

2020· article· en· W3028640378 on OpenAlexaff
Cara M. Keifer, Amori Yee Mikami, J. P. Morris, Erin J. Libsack, Matthew D. Lerner

Bibliographic record

VenueAutism · 2020
Typearticle
Languageen
FieldNeuroscience
TopicAutism Spectrum Disorder Research
Canadian institutionsUniversity of British Columbia
FundersNational Institute of Mental HealthJefferson Scholars FoundationInternational Max Planck Research School for Environmental, Cellular and Molecular MicrobiologyAssociation for Psychological ScienceAmerican Psychological AssociationAmerican Psychological Foundation
KeywordsPsychologySocial cognitionAutismAutism spectrum disorderCognitionConceptualizationCognitive psychologyDevelopmental psychologyMotor cognitionSocial cognitive theorySocial relationSocial psychologyNeuroscience

Abstract

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Deficient social communication and interaction behaviors are a hallmark feature of individuals with autism spectrum disorder. These social communication and interaction deficits potentially stem from problems with explicit social cognition (i.e. processes that are controlled and largely conscious) as well as with implicit social cognition (i.e. processes that are fast, spontaneous, and primarily unconscious). This study aimed to investigate the relative contributions of implicit and explicit social cognition factors as predictors of multi-informant measures of social communication and interaction behaviors in a sample of 34 youth with clinical diagnoses of autism spectrum disorder. Behavioral, cognitive, and electrophysiological indices of implicit and explicit social cognition were entered into partial least squares regression models designed to identify latent factors that optimally predict parent-report, observer-coded, and clinician-rated social communication, and interaction outcomes. Results indicated that while both implicit and explicit social cognition factors optimally predicted outcomes, implicit social cognition factors were relatively more predictive. Findings have important implications for the conceptualization and measurement of social functioning as well as the development of targeted social interventions in autism spectrum disorder populations. Lay abstract Difficulties with social communication and interaction are a hallmark feature of autism spectrum disorder. These difficulties may be the result of problems with explicit social cognition (effortful and largely conscious processes) such as learning and recalling social norms or rules. Alternatively, social deficits may stem from problems with implicit social cognition (rapid and largely unconscious processes) such as the efficient integration of social information. The goal of this study was to determine how problems in explicit and implicit social cognition relate to social behavior in 34 youth with autism spectrum disorder. We measured aspects of implicit and explicit social cognition abilities in the laboratory using behavioral, cognitive, and brain (electrophysiological) measures. We then used those measures to predict “real-world” social behavior as reported by parents, clinicians, and independent observers. Results showed that overall better aspects of implicit and explicit social cognition predicted more competent social behavior. In addition, the ability to fluidly integrate social information (implicit social cognition) was more frequently related to competent social behavior that merely knowing what to do in social situations (explicit social cognition). These findings may help with the development of interventions focusing on improving social deficits.

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)0.002
metaresearch head score (Gemma)0.017
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 score0.004
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.017
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
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 head0.072
GPT teacher head0.317
Teacher spread0.245 · 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

Citations43
Published2020
Admission routes1
Has abstractyes

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