Evidence map›Paper›PMID 37286643›Full record

ArticleScientific reports2023

Expressive language sampling and outcome measures for treatment trials in fragile X and down syndromes: composite scores and psychometric properties.

Leonard Abbeduto, Laura Del Hoyo Soriano, Elizabeth Berry-Kravis, Audra Sterling, Jamie O Edgin, Nadia Abdelnur, Andrea Drayton, Anne Hoffmann, Debra Hamilton, Danielle J Harvey and 1 more

Abstract read
In one paragraph

Article in Scientific reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Expressive Language Sample Concordance With ADOS-2 Scores: Autism, Down Syndrome, Fragile X Syndrome.American journal on intellectual and developmental disabilities · 2026
    Article
  3. Article
  4. A Review of Clinical Trials in Down Syndrome.International review of research in developmental disabilities · 2025
    Article
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

11 authors.

Leonard AbbedutoMIND Institute and Department of Psychiatry and Behavioral Sciences, University of California Davis Health, 2828 50Th St., Sacramento, CA, 95817, USA. LJabbeduto@ucdavis.edu.
Laura Del Hoyo SorianoMIND Institute and Department of Psychiatry and Behavioral Sciences, University of California Davis Health, 2828 50Th St., Sacramento, CA, 95817, USA.
Elizabeth Berry-KravisDepartment of Neurology, Rush University Medical Center, Chicago, IL, USA.
Audra SterlingWaisman Center and Department of Communication Sciences and Disorders, University of Wisconsin-Madison, Madison, WI, USA.
Jamie O EdginDepartment of Psychology, Sonoran UCEDD, UA Family and Community Medicine, University of Arizona, Phoenix, AZ, USA.
Nadia AbdelnurMIND Institute and Department of Psychiatry and Behavioral Sciences, University of California Davis Health, 2828 50Th St., Sacramento, CA, 95817, USA.
Andrea DraytonMIND Institute and Department of Psychiatry and Behavioral Sciences, University of California Davis Health, 2828 50Th St., Sacramento, CA, 95817, USA.
Anne HoffmannDepartment of Communication Disorders and Sciences, Rush University, Chicago, IL, USA.
Debra HamiltonDepartment of Human Genetics, Emory University School of Medicine, Atlanta, GA, USA.
Danielle J HarveyDepartment of Public Health Sciences, University of California, Davis, USA.
Angela John ThurmanMIND Institute and Department of Psychiatry and Behavioral Sciences, University of California Davis Health, 2828 50Th St., Sacramento, CA, 95817, USA.

Funding

UC Davis Clinical and Translational Science CenterUL1TR001860 · NCATS · UNIVERSITY OF CALIFORNIA AT DAVIS · PI KENYON, NICHOLAS J., LYLES, COURTNEY REES · 2016 to 2025
$47.3M
Research Project: Pathologic Significance of Maternal AutoantibodiesP50HD103526 · NICHD · UNIVERSITY OF CALIFORNIA AT DAVIS · PI LEONARD J. ABBEDUTO, Melissa Dawn Bauman · 2020 to 2026
$9.7M
Expressive Language Sampling as an Outcome MeasureR01HD074346 · NICHD · UNIVERSITY OF CALIFORNIA AT DAVIS · PI ABBEDUTO, LEONARD J. · 2013 to 2017
$3.9M
NCATS NIH HHS UL1 TR001860NICHD NIH HHS P50 HD103526NICHD NIH HHS R01 HD074346
6 · The paper itself

Abstract

The lack of psychometrically sound outcome measures has been a barrier to evaluating the efficacy of treatments proposed for core symptoms of intellectual disability (ID). Research on Expressive Language Sampling (ELS) procedures suggest it is a promising approach to measuring treatment efficacy. ELS entails collecting samples of a participant's talk in interactions with an examiner that are naturalistic but sufficiently structured to ensure consistency and limit examiner effects on the language produced. In this study, we extended previous research on ELS by analyzing an existing dataset to determine whether psychometrically adequate composite scores reflecting multiple dimensions of language can be derived from ELS procedures administered to 6- to 23-year-olds with fragile X syndrome (n = 80) or Down syndrome (n = 78). Data came from ELS conversation and narration procedures administered twice in a 4-week test-retest interval. We found that several composites emerged from variables indexing syntax, vocabulary, planning processes, speech articulation, and talkativeness, although there were some differences in the composites for the two syndromes. Evidence of strong test-retest reliability and construct validity of two of three composites were obtained for each syndrome. Situations in which the composite scores would be useful in evaluating treatment efficacy are outlined.

Indexed as

LanguageVocabularyHumansOutcome Assessment, Health CarePsychometricsReproducibility of Results

Identifiers

PMID37286643
PMCPMC10247708

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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.