Evidence map›Paper›PMID 39699005›Full record

ArticleDevelopmental medicine and child neurology2025

Psychometric evaluation of the Autism Symptom Dimensions Questionnaire.

Thomas W Frazier, Anastasia Dimitropoulos, Leonard Abbeduto, Melissa Armstrong-Brine, Shanna Kralovic, Andy Shih, Antonio Y Hardan, Eric A Youngstrom, Mirko Uljarević, Verbal Beginnings Team

Abstract read
In one paragraph

Article in Developmental medicine and child neurology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
–field-weighted citation impact
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

6 citing papers in PubMed.

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  5. Psychometric evaluation of the Autism Symptom Dimensions Questionnaire.Developmental medicine and child neurology · 2025
    Article
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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

10 authors.

Thomas W FrazierDepartment of Psychology, John Carroll University, University Heights, OH, USA.ORCID 0000-0002-6951-2667
Anastasia DimitropoulosDepartment of Psychological Sciences, Case Western Reserve University, Cleveland, OH, USA.
Leonard AbbedutoDepartment of Psychiatry and Behavioral Sciences and MIND Institute, University of California, Davis, CA, USA.
Melissa Armstrong-BrineMetroHealth Autism Assessment Clinic, MetroHealth Medical Center, Cleveland, OH, USA.
Shanna KralovicDivision of Developmental Behavioral Pediatrics and Psychology, University Hospitals Case Medical Center, Cleveland, OH, USA.
Andy ShihAutism Speaks, Princeton, NJ, USA.
Antonio Y HardanDepartment of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA, USA.
Eric A YoungstromDepartment of Psychology and Neuroscience, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
Mirko UljarevićDepartment of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA, USA.ORCID 0000-0002-8414-4209
Verbal Beginnings Team

Funding

A Big Data Approach Toward the Development of New Quantitative Autism Severity Scores from Existing InstrumentsR15MH129815 · NIMH · JOHN CARROLL UNIVERSITY · PI FRAZIER, THOMAS WILLIAM · 2022 to 2022
$385k
Autism Speaks 12776NIMH NIH HHS R15 MH129815NIMH NIH HHS R15 MH129815-01
6 · The paper itself

Abstract

aimTo replicate and extend previous psychometric findings for the Autism Symptom Dimensions Questionnaire (ASDQ).

methodUsing a cross-sectional design in two samples, including a total of 3366 children and adolescents (aged 2-17 years; 1399 with autism spectrum disorder) and a small case series, factor structure, measurement invariance, reliability, construct validity, screening and diagnostic efficiency, and detection of reliable change were examined for the ASDQ.

resultsStrong psychometric properties were observed, including replicable factor structure, strong measurement invariance, adequate-to-excellent scale and conditional reliability, strong convergent and discriminant validity, and good screening efficiency. Importantly, two crucial measurement aspects required for a good treatment outcome measure were found, that is, good test-retest stability and the potential to detect reliable change. As expected for an informant-reported questionnaire, diagnostic efficiency was weak.

interpretationThe ASDQ showed evidence of favorable and well-replicated psychometric properties in two samples. Good screening but weak diagnostic efficiency, coupled with good test-retest stability, suggest that optimal clinical use is in screening and in detailed clinical characterization beyond what is offered by current informant-reported measures, with the potential for monitoring response to intervention. Despite relative brevity, the ASDQ provides good coverage of broad and specific aspects of the autism behavioral phenotype, which is consistent with the criteria of the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition.

Indexed as

Autism Spectrum DisorderAutistic DisorderPsychometricsAdolescentChildChild, PreschoolCross-Sectional StudiesFactor Analysis, StatisticalFemaleHumansMaleReproducibility of ResultsSurveys and Questionnaires

Identifiers

PMID39699005
PMCPMC12066973

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Registered trials

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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.