Evidence map›Paper›PMID 40560962›Full record

ArticlePloS one2025

A crowding free digital interface to help French-speaking children learn to read.

Viet Chau Linh Nguyen, Guillaume Lio, Thomas Perret, Alice Gomez, Angela Sirigu

Abstract read
In one paragraph

Article in PloS one, 2025. 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

5 authors.

Viet Chau Linh NguyenInstitute of Cognitive Science Marc Jeannerod, Centre National de la Recherche Scientifique, Bron, France.ORCID 0009-0007-6034-2079
Guillaume LioInstitute of Cognitive Science Marc Jeannerod, Centre National de la Recherche Scientifique, Bron, France.
Thomas PerretInstitute of Cognitive Science Marc Jeannerod, Centre National de la Recherche Scientifique, Bron, France.
Alice GomezInstitute of Cognitive Science Marc Jeannerod, Centre National de la Recherche Scientifique, Bron, France.
Angela SiriguInstitute of Cognitive Science Marc Jeannerod, Centre National de la Recherche Scientifique, Bron, France.ORCID 0000-0002-1299-5442

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Learning to read is a challenging task for first-graders. Letter crowding in the peripheral visual field has been identified as a key interference process during reading acquisition. To reduce crowding and enhance selective attention, we designed a new way to read (Digit-tracking) in which words and sentences appear blurred. By sliding the index finger along the blurred text, the letters just above the finger position appear unblurred and are seen in foveal vision. We hypothesized that this approach might facilitate orthographic decoding and promote reading skills. Using a tablet device, two groups of first-grade children (N = 54) were trained on digit-tracking exercises and paper exercises using a crossover design. Results showed that performance in letter, syllable and meaningless text-reading was significantly higher after digit-tracking training compared to paper-based training. Using the recorded finger trajectories as a proxy for eye movements, we found that text scanning patterns (saccade length, landing position, regressive saccades) predicted children's decoding and fluency. We conclude that training with the digit-tracking procedure accelerates decoding and reading fluency in school beginners and may provide a sensitive metric of reading competence.

Indexed as

LanguageLearningReadingChildEye MovementsFemaleHumansMale

Identifiers

PMID40560962
PMCPMC12193705

What OpenQuestion holds

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LicenceCC BY
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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.