The increasing prevalence of mental health challenges among young adults has driven growing interest in affective computing technologies that foster emotional support and psychological well-being. This study aims to design and evaluate an emotionally adaptive chatbot that promotes positive mental well-being through empathetic and user-centered interactions. Grounded in affective and positive computing frameworks, this research examines the influence of Emotion-Adaptive Capability, Perceived Empathy of the Chatbot, and Usability & Interaction Quality on Positive Mental Well-Being. A quantitative approach was employed by distributing an online questionnaire to young adult respondents who had interacted with emotion-aware chatbot systems. The collected data were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM) via SmartPLS to test the hypothesized relationships. The results are expected to demonstrate that chatbots with higher emotional adaptability, greater perceived empathy, and better usability significantly enhance users’ psychological well-being. This study contributes to the development of human-centered affective computing by providing empirical evidence on how emotionally intelligent chatbot design can positively influence mental health outcomes. The findings offer practical implications for designers and developers aiming to create AI systems that are not only functional but also emotionally supportive and aligned with humanistic technology values.
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