Objectives <p>Mental health concerns are rising, particularly among post-secondary students, who may lack access to traditional therapeutic resources due to barriers like long wait times and high costs. To help address these challenges, we explored the potential of large language model-based chatbots for supporting mental health and well-being in student populations.</p> Method <p>We conducted two studies, lasting 1 week and 4 weeks, to examine the effectiveness of chatbot support over different durations. Both studies compared two chatbot training groups — one mindfulness-focused and one value-focused — against an active check-in-only control condition. The primary outcome measure was the improvement in well-being through the Mindfulness-to-Meaning (MM) pathway, a process in which enhanced decentering, the ability to see one’s experience from a wider perspective, leads to improved positive reappraisal, the ability to find constructive and empowered interpretations of experience.</p> Results <p>All conditions showed evidence of stress reduction. However, compared to the active control group, both training styles at both durations resulted in improved well-being via the MM pathway. This effect was primarily driven by significant improvements in decentering. For the longer duration only, we also observed enhanced reappraisal.</p> Conclusions <p>These findings highlight the potential of chatbot-based training to enhance student well-being by promoting key regulatory skills within the broader MM pathway. While not a replacement for traditional resources, chatbot-based support may function as a scalable, accessible complement— particularly for individuals facing barriers to in-person care. Integrating such tools into student support may help sustain well-being through personalized, skill-based training while recognizing the specific affordances and limitations of technology-mediated formats.&#xa0;</p> Preregistration <p>All measures and analysis methods were preregistered prior to data collection (<a href="https://osf.io/hxdvf">https://osf.io/hxdvf</a>).</p>