How emotional regulation mediates the link between AI attachment and perceived loneliness: a study of Saudi university students

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Introduction This study aimed to explore how people manage their emotions, specifically through cognitive reappraisal and emotional suppression, and whether these strategies mediate the relationship between artificial intelligence attachment (AIA) and perceived loneliness (PL), using a structural equation modeling (SEM) approach. Method The current study adopted a structural equation modeling (SEM) approach to examine the direct and indirect relationships among engagement with AIA, ERS, and PL. The study population consisted of undergraduate students in Saudi Arabia. Participants who reported using AI technologies, such as chatbots, in their academic or personal lives were included in the study, as determined by an initial screening question in the questionnaire. Given the large size of the study population and the difficulty of accurately defining it, a representative sample consisted of (743) was selected. Results The results indicated moderate levels of AIA, cognitive reappraisal (CR), expressive suppression (ES), and PL. Furthermore, the results revealed statistically significant direct effects of CR and ES on PL. On the other hand, no statistically significant direct effects of any of the AIA subscales were observed on PL. Interestingly, statistically significant indirect effects of the AIA on PL were found through the emotional response system: CR and ES. Discussion These findings highlight the fundamental role of emotion regulation in shaping individuals' experiences of PL during interactions with AI. Also, these findings suggested that it is not simply the interaction with AI itself that matters, but instead how individuals manage their emotions in response to it. Therefore, it is advisable to design mentoring programs that support student development and strengthen their emotion regulation system, thereby reducing their dependence on digital technologies.

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