Evidence map›Paper›PMID 37229359›Full record

ArticlePerspectives of the ASHA special interest groups2023

Assessment and Therapy Goal Planning Using Free Computerized Language Analysis Software.

Nan Bernstein Ratner, Brian MacWhinney

Open access · greenAbstract read
In one paragraph

Article in Perspectives of the ASHA special interest groups, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
1.9field-weighted citation impact, top 16% 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

3 citing papers in PubMed, 6 citations in OpenAlex.

  1. 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

2 authors at 1 institution in 1 country.

Nan Bernstein RatnerUniversity of Maryland, College Park.ORCID 0000-0002-9947-0656
Brian MacWhinneyCarnegie-Mellon University, Pittsburgh, PA.ORCID 0000-0002-4988-1342
Google (United States) · US

Funding

Improving the clinical utility of preschool language sample analysisR01DC017152 · NIDCD · UNIV OF MARYLAND, COLLEGE PARK · PI RATNER, NAN BERNSTEIN · 2018 to 2023
$2.1M
NIDCD NIH HHS R01 DC017152
6 · The paper itself

Abstract

Background: We discuss a free software system (Computerized Language Analysis [CLAN]) that can enable fast, thorough, and informative language sample analysis (LSA). Method: We describe methods for eliciting, transcribing, analyzing, and interpreting language samples. Using a hypothetical child speaker, we illustrate use KidEval to generate a diagnostic report. Results: Given LSA results suggestive of expressive language delay, we analyze further using CLAN's Developmental Sentence Score and Index of Productive Syntax routines, and outline the child's use of Brown's morphemes. Discussion: This tutorial provides an introduction to the use of free CLAN software. We discuss how LSA results can be used to structure therapy goals that address specific aspects of grammatical structure that the child may not yet demonstrate in their spoken language. Finally, we provide answers to common questions, including user support.

Identifiers

PMID37229359
PMCPMC10207730
OpenAlexW4319310817

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

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.