Evidence map›Paper›PMID 41339656›Full record

ArticleScientific data2025

A dataset of word recognition accuracy, times, and prevalence for 4,562 verbs and 4,562 pseudoverbs of Spanish.

Miguel Ángel Pérez-Sánchez, Javier Marín, Romina San Miguel-Abella, Elena Herrera, María González-Nosti

Abstract readDataset
In one paragraph

Article in Scientific data, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0cells of the map it votes in
0citing papers in PubMed
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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.

Miguel Ángel Pérez-SánchezGrupo de Investigación Ciencia Cognitiva, Departamento de Psicología Básica y Metodología, Facultad de Psicología, CEIR Campus Mare Nostrum (CMN), Universidad de Murcia, Campus de Espinardo, 30100, Murcia, Spain. maperez@um.es.ORCID http://orcid.org/0000-0001-8638-0283
Javier MarínGrupo de Investigación Ciencia Cognitiva, Departamento de Psicología Básica y Metodología, Facultad de Psicología, CEIR Campus Mare Nostrum (CMN), Universidad de Murcia, Campus de Espinardo, 30100, Murcia, Spain.
Romina San Miguel-AbellaDepartamento de Psicología, Universidad de Oviedo, Oviedo, Asturias, Spain.
Elena HerreraDepartamento de Psicología, Universidad de Oviedo, Oviedo, Asturias, Spain.
María González-NostiDepartamento de Psicología, Universidad de Oviedo, Oviedo, Asturias, Spain.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The current database comprises behavioral data from 267 healthy Spanish adults aged 18 to 51, who participated in a visual lexical decision task conducted in a laboratory setting. Raw data on response accuracy and latencies are available for 4,565 verbs and 4,565 pseudoverbs, along with word prevalence-calculated from accuracy in that task. Additionally, a filtered dataset containing response times (RTs) for only correct responses, applying commonly used thresholds for outliers, is provided. Reliability analyses (via ICC) demonstrated good to excellent scores for the entire dataset. Criterion and construct validity, including a comparative analysis with other databases, were also examined, yielding satisfactory results. The new data can facilitate researchers in conducting virtual or pilot experiments, exploring novel research questions, or constructing models of word recognition. Furthermore, they may be of interest at the clinical level, such as in the selection of materials for cognitive rehabilitation, as the behavioral data and prevalence can be utilized to organize words based on their difficulty for training purposes.

Indexed as

LanguageAdolescentAdultFemaleHumansMaleMiddle AgedReaction TimeSpainYoung Adult

Identifiers

PMID41339656
PMCPMC12800016

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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.