Evidence map›Paper›PMID 42780887›Full record

SynthesisFrontiers in psychology2026

Eye-tracking studies on developmental language disorder: a systematic review.

Ziteng Liu, Qihang Jiang

Abstract readSystematic Review
In one paragraph

Synthesis in Frontiers in psychology, 2026. 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

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.

Ziteng LiuSchool of English, University of Nottingham, Nottingham, United Kingdom.
Qihang JiangSchool of Humanities & Languages, University of New South Wales, Sydney, NSW, Australia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Developmental language disorder (DLD) is a neurodevelopmental condition characterized by persistent difficulties in language acquisition and processing. While traditional behavioral and neurophysiological methods have provided valuable insights, eye-tracking has emerged as a powerful tool for capturing real-time cognitive processing during language comprehension. However, evidence from eye-tracking studies in DLD remains underrepresented and fragmented across linguistic domains and experimental paradigms. This systematic review synthesizes 33 empirical studies and examines how eye-tracking has been used to investigate real-time language processing in children with DLD. The review focuses on three key dimensions: (a) cognitive-linguistic domains addressed, (b) paradigms and eye-movement metrics employed, and (c) recurring processing differences between children with DLD and typically developing (TD) counterparts. The synthesis reveals three broadly consistent processing patterns in DLD: slower processing efficiency, reduced predictive processing, and increased reliance on semantic cues over morphosyntactic information. These patterns suggest that language difficulties in DLD are not solely attributable to representational deficits but are closely linked to inefficiencies in real-time integration and competition resolution during language processing. By consolidating findings across paradigms, this review provides a cognitively grounded account of DLD and highlights the role of eye-tracking in uncovering underlying processing mechanisms. Implications for theoretical models of language processing and future methodological directions are discussed.

Indexed as

cognitive processingdevelopmental language disorder (DLD)eye-trackinglanguage developmentlanguage processinglinguistic domainssystematic review

Identifiers

PMID42780887
PMCPMC13597889

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.