Evidence map›Paper›PMID 42389691›Full record

ArticleFrontiers in veterinary science2026

Artificial intelligence in veterinary education: self-perceived knowledge, use, and attitudes among veterinary students in Spain and Portugal.

Ana Lourdes Oropesa, Santiago Mendo-Lázaro, Antonio Gonzalez, Benito León-Del-Barco, José Antonio Tapia

Abstract read
In one paragraph

Article in Frontiers in veterinary science, 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

5 authors.

Ana Lourdes OropesaToxicology Area, Department of Animal Health, Faculty of Veterinary Sciences, University of Extremadura, Cáceres, Spain.
Santiago Mendo-LázaroDepartment of Psychology and Anthropology, Faculty of Teacher Training, University of Extremadura, Cáceres, Spain.
Antonio GonzalezDepartment of Physiology, Faculty of Veterinary Sciences, University of Extremadura, Cáceres, Spain.
Benito León-Del-BarcoDepartment of Psychology and Anthropology, Faculty of Teacher Training, University of Extremadura, Cáceres, Spain.
José Antonio TapiaDepartment of Physiology, Faculty of Veterinary Sciences, University of Extremadura, Cáceres, Spain.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Artificial intelligence (AI), especially generative AI and large language models, is increasingly influencing higher education and health professions training. However, there is still limited empirical evidence about what veterinary students know about AI, how they use it, and how they perceive it. The aim of this study was to evaluate self-perceived AI-related knowledge, use, and attitudes among veterinary students in Spain and Portugal, and to analyze the influence of institutional context, prior AI training, and digital engagement. A cross-sectional survey was conducted during the 2023-2024 academic year with 340 undergraduate and postgraduate veterinary students from public and private institutions in Spain and Portugal. The questionnaire included sociodemographic questions and nine Likert-scale items assessing self-perceived AI knowledge, use, and attitudes. Composite scores were calculated and transformed using the Percentage of Maximum Possible (POMP) method (0-100 scale). Internal consistency of the instrument was high (

Indexed as

AI literacyartificial intelligencecurriculum integrationdigital engagementhealth professions educationveterinary education

Identifiers

PMID42389691
PMCPMC13318702

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.