Evidence map›Paper›PMID 32952259›Full record

ArticleAphasiology2020

Main concepts for two picture description tasks: An addition to.

Jessica D Richardson, Sarah Grace Hudspeth Dalton

Abstract read
In one paragraph

Article in Aphasiology, 2020. 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
–field-weighted citation impact
1 · What the graph read from it

What it found

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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.

  1. Acute-Phase Machine Learning Prediction of 12-Month Aphasia and Discourse Recovery.medRxiv : the preprint server for health sciences · 2026
    Article
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  6. Clinical Guidelines for Eliciting Discourse Using the RHDBank Protocol.American journal of speech-language pathology · 2022
    Article
  7. Article
  8. Article
  9. Article
  10. Using AphasiaBank for Discourse Assessment.Seminars in speech and language · 2020
    Article
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  12. Article
  13. 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

2 authors.

Jessica D RichardsonUniversity of New Mexico, MSC 01 1195, Albuquerque, NM 87131, (505) 277-1765.
Sarah Grace Hudspeth DaltonUniversity of New Mexico, MSC 01 1195, Albuquerque, NM 87131, (470) 281-0470.

Funding

University of New Mexico (UNM) Center for Brain Recovery and RepairP20GM109089 · NIGMS · UNIVERSITY OF NEW MEXICO HEALTH SCIS CTR · PI SHUTTLEWORTH, CLAUDE W · 2015 to 2024
$22.7M
NIGMS NIH HHS P20 GM109089
6 · The paper itself

Abstract

backgroundProposition analysis of the discourse of persons with aphasia has a long history, yielding important advancements in our understanding of communication impairments in this population. Recently, discourse measures have been considered primary outcome measures, and multiple calls have been made for improved psychometric properties of discourse measures.

aimsTo advance the use of discourse analysis in persons with aphasia by providing Main Concept Analysis checklists and descriptive statistics for healthy control performance on the analysis for the Cat in the Tree and Refused Umbrella narrative tasks utilized in the AphasiaBank database protocol. METHODS & PROCEDURES: Ninety-two control transcripts, stratified into four age groups (20-39 years; 40-59; 60-79; 80+), were downloaded from the AphasiaBank database. Relevant concepts were identified, and those spoken by at least one-third of the control sample were considered to be a main concept. A multi-level coding system was used to determine the accuracy and completeness of the main concepts produced by control speakers. OUTCOMES &

resultsMain concept checklists for two discourse tasks are provided. Descriptive statistics are reported and examined to assist readers with evaluation of the normative data.

conclusionsThese checklists provide clinicians and researchers with a tool to reliably assess the discourse of persons with aphasia. They also help address the gap in available psychometric data with which to compare persons with aphasia to healthy controls.

Indexed as

aphasiaAphasiaBankdiscourse analysismain conceptnormative referencepicture descriptionpicture stimuli

Identifiers

PMID32952259
PMCPMC7500506

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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.