Evidence map›Paper›PMID 32960647›Full record

ArticleAmerican journal of speech-language pathology2020

Data-Informed Guideposts for Decision Making in Enhanced Conversational Recast Treatment.

Jessica Hall, Elena Plante

Abstract read
In one paragraph

Article in American journal of speech-language pathology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Article
  2. Less Versus More: The Effect of Recast Length in Treatment of Grammatical Errors.Language, speech, and hearing services in schools · 2024
    Article
  3. Article
  4. Translating Enhanced Conversational Recast to a Telepractice Setting.Language, speech, and hearing services in schools · 2022
    Article
  5. 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 HallDepartment of Speech, Language, and Hearing Sciences, The University of Arizona, Tucson.
Elena PlanteDepartment of Speech, Language, and Hearing Sciences, The University of Arizona, Tucson.

Funding

Identification of treatment parameters that maximize language treatment efficacy for children. TALK Initiative supplement.R01DC015642 · NIDCD · UNIVERSITY OF ARIZONA · PI MARY ALT, Elena M Plante · 2016 to 2026
$6.8M
Treatment delivery methods for children with SLIR21DC014203 · NIDCD · UNIVERSITY OF ARIZONA · PI PLANTE, ELENA M · 2014 to 2015
$377k
Probabilistic learning in developmental language disorderF32DC017373 · NIDCD · UNIVERSITY OF ARIZONA · PI HALL, JESSICA ERIN · 2018 to 2019
$80k
NIDCD NIH HHS F32 DC017373NIDCD NIH HHS R01 DC015642NIDCD NIH HHS R21 DC014203
6 · The paper itself

Abstract

Background To maximize treatment efficiency, it would be useful to determine how long to continue a treatment approach before concluding that it is not effective for a particular client, whether and when generalization of treatment is likely to occur, and at what point to end treatment once a child is approaching mastery. Method We analyzed aggregate data from 117 preschoolers with developmental language disorder from a decade of treatment studies on Enhanced Conversational Recast therapy to determine whether the timing of treatment response impacts its overall effectiveness and whether certain levels of accuracy during treatment enable 100% accurate generalization after treatment ends. Results We found that children who take longer than 10 days to answer one item correctly during treatment are unlikely to ever respond to the treatment approach. Generalization accuracy closely followed treatment accuracy, suggesting the two are tightly linked for this treatment method. We did not find evidence that attaining a certain level of accuracy below 100% during treatment enabled children to generalize with 100% accuracy after treatment ended. Conclusions Clinicians using Enhanced Conversational Recast treatment can use these markers to help make evidence-based decisions in their practice regarding how long to continue treatment. Importantly, these data suggest that stopping treatment before a child has attained 100% accuracy (for at least three sessions) does not ensure that a child will ever reach 100% accuracy on their own.

Indexed as

CommunicationLanguage TherapyChildDecision MakingHumans

Identifiers

PMID32960647
PMCPMC8740566

What OpenQuestion holds

Textmetadata
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.