Evidence map›Paper›PMID 39755638›Full record

ArticleBMC psychology2025

What is the influence of psychosocial factors on artificial intelligence appropriation in college students?

Benicio Gonzalo Acosta-Enriquez, María de Los Ángeles Guzmán Valle, Marco Arbulú Ballesteros, Julie Catherine Arbulú Castillo, Carmen Graciela Arbulu Perez Vargas, Isaac Saavedra Torres, Pedro Manuel Silva León, Karina Saavedra Tirado

Abstract read
In one paragraph

Article in BMC psychology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

8 authors.

Benicio Gonzalo Acosta-EnriquezUniversidad Nacional de Trujillo, Trujillo, Perú.
María de Los Ángeles Guzmán ValleUniversidad Tecnológica del Perú, Lima, Perú. c15025@UTP.EDU.PE.
Marco Arbulú BallesterosUniversidad César Vallejo, Trujillo, Perú.
Julie Catherine Arbulú CastilloUniversidad César Vallejo, Trujillo, Perú.
Carmen Graciela Arbulu Perez VargasUniversidad César Vallejo, Trujillo, Perú.
Isaac Saavedra TorresUniversidad César Vallejo, Trujillo, Perú.
Pedro Manuel Silva LeónUniversidad César Vallejo, Trujillo, Perú.
Karina Saavedra TiradoUniversidad Nacional de Trujillo, Trujillo, Perú.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundIn recent years, the adoption of artificial intelligence (AI) has become increasingly relevant in various sectors, including higher education. This study investigates the psychosocial factors influencing AI adoption among Peruvian university students and uses an extended UTAUT2 model to examine various constructs that may impact AI acceptance and use.

methodThis study employed a quantitative approach with a survey-based design. A total of 482 students from public and private universities in Peru participated in the research. The study utilized partial least squares structural equation modeling (PLS-SEM) to analyze the data and test the hypothesized relationships between the constructs.

resultsThe findings revealed that three out of the six hypothesized factors significantly influenced AI adoption among Peruvian university students. Performance expectancy (β = 0.274), social influence (β = 0.355), and AI learning self-efficacy (β = 0.431) were found to have significant positive effects on AI adoption. In contrast to expectations, ethical awareness, perceived playfulness, AI readiness and AI anxiety did not have significant impacts on AI appropriation in this context.

conclusionThis study highlights the importance of practical benefits, the social context, and self-confidence in the adoption of AI within Peruvian higher education. These findings contribute to the understanding of AI adoption in diverse educational settings and provide a framework for developing effective AI implementation strategies in higher education institutions. The results can guide universities and policymakers in creating targeted approaches to enhance AI adoption and integration in academic environments, focusing on demonstrating the practical value of AI, leveraging social networks, and building students' confidence in their ability to learn and use AI technologies.

Indexed as

Artificial IntelligenceStudentsAdolescentAdultFemaleHumansMalePeruSelf EfficacySurveys and QuestionnairesUniversitiesYoung AdultAI appropriationArtificial intelligenceHigher educationPeruvian university studentsTechnology adoptionUTAUT2 model

Identifiers

PMID39755638
PMCPMC11700461

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.