Evidence map›Paper›PMID 40024967›Full record

ArticleJournal of autism and developmental disorders2025

Using Language Environment Analysis System (LENA) in Natural Settings to Characterize Outcomes of Pivotal Response Treatment.

Emily F Ferguson, Morgan Steele, Rachel K Schuck, Maria Estefania Millan, Robin A Libove, Jennifer M Phillips, Grace W Gengoux, Antonio Y Hardan

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Article in Journal of autism and developmental disorders, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

8 authors.

Emily F FergusonDivision of Child and Adolescent Psychiatry, Department of Psychiatry and Behavioral Sciences, School of Medicine, Stanford University, Stanford, CA, USA. eferguso@stanford.edu.ORCID http://orcid.org/0000-0002-2771-6346
Morgan SteeleRoss University School of Medicine, Miramar, FL, USA.
Rachel K SchuckDivision of Child and Adolescent Psychiatry, Department of Psychiatry and Behavioral Sciences, School of Medicine, Stanford University, Stanford, CA, USA.
Maria Estefania MillanDivision of Child and Adolescent Psychiatry, Department of Psychiatry and Behavioral Sciences, School of Medicine, Stanford University, Stanford, CA, USA.
Robin A LiboveDivision of Child and Adolescent Psychiatry, Department of Psychiatry and Behavioral Sciences, School of Medicine, Stanford University, Stanford, CA, USA.
Jennifer M PhillipsDivision of Child and Adolescent Psychiatry, Department of Psychiatry and Behavioral Sciences, School of Medicine, Stanford University, Stanford, CA, USA.
Grace W GengouxDivision of Child and Adolescent Psychiatry, Department of Psychiatry and Behavioral Sciences, School of Medicine, Stanford University, Stanford, CA, USA.
Antonio Y HardanDivision of Child and Adolescent Psychiatry, Department of Psychiatry and Behavioral Sciences, School of Medicine, Stanford University, Stanford, CA, USA.

Funding

NIDCD NIH HHS DC01368902
6 · The paper itself

Abstract

purposeDespite the importance of monitoring changes in expressive language in early intervention, existing approaches to language assessment are often costly, time-intensive, and capture limited variability in autistic children. The Language ENvironmental Analysis (LENA) system has thus received considerable attention as an automated approach that may hold promise for capturing fine-grained changes in language development in a more efficient and cost-effective manner. However, evaluations of the utility of the LENA system for tracking response to early intervention in unstructured contexts are currently limited.

methodsThis study aimed to build on prior research through evaluating the use of LENA in the context of a well-defined clinical sample from a randomized controlled trial (RCT) of Pivotal Response Treatment (PRT) that demonstrated expressive language gains across standardized and manually-coded measures.

resultsExploration of automatically-derived LENA metrics (i.e., child vocalizations, conversational turns) revealed no significant association with standardized language assessments (i.e., Mullen expressive language subscale, MacArthur Bates Communicative Development Inventory, Vineland-II expressive language subscale). Furthermore, relative to the delayed treatment group, children participating in PRT did not show significantly greater improvement in the number of vocalizations or conversational turns during naturalistic, daylong LENA recordings collected in home settings from baseline to post-intervention.

conclusionImplications and future directions for natural language sampling and the measurement of expressive language in early intervention are discussed.

Indexed as

Autism spectrum disorderEarly interventionLENANatural language samplingOutcome measurementPivotal response treatment

Identifiers

PMID40024967

What OpenQuestion holds

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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.