Evidence map›Paper›PMID 39715991›Full record

ArticlePsychonomic bulletin & review2025

Lexical integration of novel words learned through natural reading.

Anezka Smejkalova, Fabienne Chetail

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Article in Psychonomic bulletin & review, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

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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

1 citing paper in PubMed.

  1. 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.

Anezka SmejkalovaLaboratoire Cognition Langage & Développement (LCLD), Centre de Recherche Cognition et Neurosciences (CRCN), Université Libre de Bruxelles (ULB), Av. F. Roosevelt, 50 /CP 191, 1050, Brussels, Belgium. anezka.smejkalova@ulb.be.ORCID http://orcid.org/0000-0002-0299-4796
Fabienne ChetailLaboratoire Cognition Langage & Développement (LCLD), Centre de Recherche Cognition et Neurosciences (CRCN), Université Libre de Bruxelles (ULB), Av. F. Roosevelt, 50 /CP 191, 1050, Brussels, Belgium.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Lexical competition between newly acquired and already established representations of written words is considered a marker of word integration into the mental lexicon. To date, studies about the emergence of lexical competition involved mostly artificial training procedures based on overexposure and explicit instructions for memorization. Yet, in real life, novel word encounters occur mostly without explicit learning intent, through reading texts with words appearing rarely. This study examined the lexical integration of words learned through text reading. In Experiment 1, two groups of participants read a short book with embedded novel words. Only one group was asked to memorize the unfamiliar words. In the semantic categorization task, we found evidence for lexical competition with slower responses to existing orthographic neighbors (e.g., hublot) of the newly learned words (e.g., hubbot) than to a set of matched items. This effect was found independently of the group 24 h after initial exposure. In addition, a facilitation pattern was observed immediately after the reading session. However, post hoc analyses suggested that the competition effect was mainly driven by the data from the group receiving explicit learning instructions. Experiment 2 aimed to replicate the findings obtained in the group without explicit learning instructions. The results revealed the same pattern, characterized by a facilitatory effect immediately after the reading session and an inhibitory effect 24 h after the exposure. Overall, these results showed that lexical competition emerged from a naturalistic reading after a delay, regardless of whether participants were asked to learn novel words or not.

Indexed as

LearningPattern Recognition, VisualReadingAdultFemaleHumansMalePsycholinguisticsSemanticsYoung AdultLexical competitionNovel word learningVisual word recognition

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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.