<![CDATA[Depression in college students is a mental health issue that often goes undetected due to limited access to services, low awareness, and strong social stigma against seeking help. This situation calls for early detection methods that are more accessible, anonymous, and acceptable to students. This study aims to examine college students’ readiness to use an AI-based depression symptom screening website by identifying key influencing factors through the perspectives of the Technology Readiness Index (TRI) and the Technology Acceptance Model (TAM). A qualitative case study approach was employed involving ten undergraduate students enrolled in the Elementary School Teacher Education program. Data were collected through in-depth online interviews and analyzed using thematic analysis. The findings reveal that students exhibit high levels of optimism and innovativeness toward the use of AI in mental health screening. However, concerns were also raised regarding data privacy, the accuracy of screening results, and the perceived lack of emotional sensitivity in AI-mediated interactions. The study concludes that students’ readiness to adopt AI-based mental health screening technologies is influenced not only by digital competence but also by trust, emotional comfort, and cultural acceptance. These findings imply the importance of collaboration between technology developers, higher education institutions, and mental health professionals in developing AI-based screening systems that are ethical, empathetic, safe, and culturally responsive.]]>
