ArticleScientific reports2024
How sociodemographic factors relate to trust in artificial intelligence among students in Poland and the United Kingdom.
Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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5 citing papers in PubMed.
- Health equity and public acceptance of large language models in healthcare in China: A national population-based survey.PLOS digital health · 2026Article
- Exploring the psychological factors influencing intention to use AI virtual companions: an SEM-ANN study.Frontiers in psychology · 2026Article
- Governing digital misinformation: A computational analysis of platform intervention using a three-party evolutionary game model.PloS one · 2026Article
- Integrating Large Language Models Into UAE Community Pharmacies: Pharmacists' Perspectives on Benefits, Concerns, and Implementation Barriers.International journal of telemedicine and applications · 2026Article
- Emotional Intelligence and Adolescents' Use of Artificial Intelligence: A Parent-Adolescent Study.Behavioral sciences (Basel, Switzerland) · 2025Article
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2 authors.
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Abstract
The article aims to determine the sociodemographic factors associated with the level of trust in artificial intelligence (AI) based on cross-sectional research conducted in late 2023 and early 2024 on a sample of 2098 students in Poland (1088) and the United Kingdom (1010). In the times of AI progressively penetrating people's everyday life, it is important to identify the sociodemographic predictors of trust in this increasingly dynamically developing technology. The theoretical framework for the article is the extended Unified Theory of Acceptance and Use of Technology (UTAUT), which highlights the significance of sociodemographic variables as predictors of trust in AI. We performed a multivariate ANOVA and regression analysis, comparing trust in AI between students from Poland and the UK to identify the significant predictors of trust in this technology. The significant predictors of trust were nationality, gender, length of study, place of study, religious practices, and religious development. There is a need for research into the sociodemographic factors of trust in AI and for expanding the UTAUT to include new variables.
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