AI-Assistive Technology Adoption and Mental Health Disorders in Visually Impaired University Students

The rapid integration of Artificial Intelligence Assistive Technology (AIAT) into higher education has generated new avenues for visually impaired university students, primarily in enhancing accessibility, self-autonomy, and academic performance. This study examined associations between AIAT-related perceptions and mental-health indicators (depression, anxiety, and stress) among visually impaired higher education students in the Kingdom of Saudi Arabia (KSA). A quantitative research approach was employed, using a self-administrated questionnaire targeting 390 visually impaired students in KSA universities. Partial least squares structural equation modelling (PLS-SEM) was employed as the main data analysis technique. The findings emphasised two important issues. First, performance expectancy (PE) of AIAT adoption, Effort expectancy (EE), and social influence (SI) are forceful psychological facilitators that can buffer against the feeling of depression and anxiety in visually impaired university students. Second, minimising the feeling of stress requires more than the existence of good infrastructure or social support; it necessitates systemic and ongoing interventions, comprising proactive university support, an accessible learning context, and personalised training programmes. These insights highlight the need for implementing inclusive support systems that combine technological, psychological, and university dimensions to promote the advantages of AIAT adoption for visually impaired students.