Evidence map›Paper›PMID 37185876›Full record

ArticleJournal of child psychology and psychiatry, and allied disciplines2023

The importance and challenges of improving early identification of language abilities: a commentary on Gasparini et al. (2023).

Nicola Botting, Helen Spicer-Cain

Abstract readComment
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In one paragraph

Article in Journal of child psychology and psychiatry, and allied disciplines, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

2 authors.

Nicola BottingLanguage and Communication Science, City University of London, London, UK.
Helen Spicer-CainLanguage and Communication Science, City University of London, London, UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Finding early predictors of later language skills and difficulties is fraught with challenges because of the wide developmental variation in language. Gasparini et al. (Journal of Child Psychology and Psychiatry, 2023) aimed to address this issue by applying machine learning methods to parent reports taken from a large longitudinal database (Early Language in Victoria Study). Using this approach, they identify two short, straightforward item sets, taken at 24 and 36 months, that can adequately predict language difficulties when children are 11 years of age. Their work represents an exciting step towards earlier recognition and support for children with Developmental Language Disorder. This commentary highlights the advantages and challenges of identifying early predictors of language in this way, and discusses future directions that can build on this important contribution.

Indexed as

CognitionLanguage Development DisordersChildHumansRecognition, Psychology

Identifiers

PMID37185876

What OpenQuestion holds

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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.