Evidence map›Paper›PMID 33027686›Full record

ArticleJournal of the American Academy of Child and Adolescent Psychiatry2021

Extracting Latent Subdimensions of Social Communication: A Cross-Measure Factor Analysis.

Shuting Zheng, Aaron Kaat, Cristan Farmer, Stephen Kanne, Stelios Georgiades, Catherine Lord, Amy Esler, Somer L Bishop

Open access · greenAbstract read
In one paragraph

Article in Journal of the American Academy of Child and Adolescent Psychiatry, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
1.9field-weighted citation impact, top 14% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

13 citing papers in PubMed, 25 citations in OpenAlex.

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  12. The Diagnosis of Autism: From Kanner to DSM-III to DSM-5 and Beyond.Journal of autism and developmental disorders · 2021
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors at 7 institutions in 2 countries.

Shuting ZhengUCSF Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA. Electronic address: shuting.zheng@ucsf.edu.
Aaron KaatFeinberg School of Medicine, Northwestern University, Chicago, Illinois.
Cristan FarmerPediatrics & Developmental Neuroscience Branch, National Institute of Mental Health, Bethesda, Maryland.
Stephen KanneCenter for Autism and the Developing Brain, Weill Cornell Medicine College, White Plains, New York.
Stelios GeorgiadesMcMaster University and Offord Centre for Child Studies, Ontario, Canada.
Catherine LordUCLA Semel Institute for Neuroscience & Human Behavior, Center for Autism Research and Treatment, David Geffen School of Medicine, University of California, Los Angeles.
Amy EslerCenter for Neurobehavioral Development, Division of Clinical Behavioral Neuroscience, University of Minnesota, Minneapolis.
Somer L BishopUCSF Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA.
University of California, San Francisco · USCornell University · USMcMaster University · CANational Institute of Mental Health · USNorthwestern University · USUniversity of California, Los Angeles · USUniversity of Minnesota · US

Funding

Development of a standardized measure of social-communication abilities for children with neurodevelopmental disordersR01HD093012 · NICHD · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI BISHOP, SOMER L. · 2017 to 2022
$3.2M
CIHRNICHD NIH HHS R01 HD093012
6 · The paper itself

Abstract

objectiveSocial communication deficits associated with autism spectrum disorder (ASD) are commonly represented as a single behavioral domain. However, increased precision of measurement of social communication is needed to promote more nuanced phenotyping, both within the autism spectrum and across diagnostic boundaries.

methodA large sample (N = 1,470) of 4- to 10-year-old children was aggregated from across 4 data sources, and then randomly split into testing and validation samples. A total of 57 selected social communication items from 3 widely used autism symptom measures (the Autism Diagnostic Observation Scale [ADOS], Autism Diagnostic Interview-Revised [ADI-R], and Social Responsiveness Scale [SRS]) were analyzed in the multi-trait/multi-method factor analysis framework. The selected model was then confirmed with the validation sample.

resultsThe 4-substantive factor model, with 3 orthogonal method factors, was selected using the testing sample based on fit indices and then confirmed with the validation sample. Two of the factors, "Basic Social Communication Skills" and "Interaction Quality," were similar to those identified in a previous analysis of the ADOS, Module 3. Two additional factors, "Peer Interaction and Modification of Behavior" and "Social Initiation and Affiliation," also emerged. Factor scores showed nominal correlations with age and verbal IQ.

conclusionIdentification of subdimensions could inform the creation of better conceptual models of social communication impairments, including mapping of how the cascading effects of social communication deficits unfold in ASD versus other disorders. Especially if extended to include both older and younger age cohorts and individuals with more varying developmental levels, these efforts could inform phenotype-based exploration for biological and genetic mechanisms by pinpointing specific mechanisms that contribute to various types of social communication deficits.

Indexed as

Autism Spectrum DisorderAutistic DisorderChildChild, PreschoolCommunicationFactor Analysis, StatisticalHumansSocial BehaviorSocial SkillsAutism Diagnostic Interview−Revised (ADI-R)Autism Diagnostic Observation Scale (ADOS)measurementphenotypingSocial Responsiveness Scale (SRS)

Identifiers

PMID33027686
PMCPMC8019433
OpenAlexW3091119768

What OpenQuestion holds

Textmetadata
LicenceTDM
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.