ORIGINAL RESEARCH article
Front. Psychol.
Sec. Media Psychology
Construction and validation of the Emotional Trust in Artificial Intelligence Scale (CEIA)
Berle Estalin Briones-Llamoctanta
Ronald Garnique Hinostroza
Roberto Estrada Medina
Josué Edison Turpo-Chaparro
Peruvian Union University, Lima, Peru
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Abstract
Background: Emotional trust in Artificial Intelligence (AI) has become a crucial component of human-AI interaction, especially in academia, where generative systems are used for academic, communicational, and socio-emotional purposes. While research has advanced in cognitive trust, there is a lack of validated instruments that rigorously assess the affective dimension of trust, which involves processes of perceived authenticity, emotional validation, affective recognition, and the establishment of symbolic bonds with artificial agents. Objective: To develop and psychometrically validate the Emotional Confidence in Artificial Intelligence Scale (CEIA) in university students, examining its factor structure, reliability, convergent and discriminant validity, as well as its measurement invariance by sex. Methods: 605 Peruvian university students, aged 16 to 88 years (M = 22.93, SD = 7.35), participated in the study. Item distributions, item-total correlations, and descriptive statistics were analyzed. Internal structure was assessed using Exploratory Factor Analysis (EFA) with polychoric correlations and Confirmatory Factor Analysis (CFA). Reliability was estimated using Cronbach's alpha and McDonald's omega. Convergent and discriminant validity were examined using AVE, CR, and HTMT. Sex invariance was assessed using multigroup CFA with the WLSMV estimator. Results: The EFA supported a multidimensional structure consistent with the theoretical model. The CFA confirmed a four-factor solution—Perceived Authenticity, Emotional Validation, Affective Recognition, and Symbolic Bonding—with adequate fit indices (CFI = .944; TLI = .937; RMSEA = .073; SRMR = .033). The dimensions showed high internal consistency (α = .91–.94; ω = .91–.94) and satisfactory evidence of convergent and discriminant validity. Invariance analysis demonstrated metric invariance and partial scalar invariance between men and women. Conclusion: The CEIA is a valid, reliable, and partially sex-invariant instrument for assessing emotional trust in AI among university students. It constitutes a robust tool for research, technological design, and the ethical development of AI systems with affective capabilities.
Summary
Keywords
artificial intelligence, Emotional trust, factor analysis, Human-AI interaction, Measurement invariance, Psychometric validation
Received
26 November 2025
Accepted
19 February 2026
Copyright
© 2026 Briones-Llamoctanta, Garnique Hinostroza, Estrada Medina and Turpo-Chaparro. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
*Correspondence: Berle Estalin Briones-Llamoctanta
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