mental health

Predicting and Understanding College Student Mental Health with Interpretable Machine Learning

Mental health issues among college students have reached critical levels, significantly impacting academic performance and overall wellbeing. Predicting and understanding mental health status among college students is challenging due to three main …

AffectEval: A Modular and Customizable Affective Computing Framework

The field of affective computing focuses on recognizing, interpreting, and responding to human emotions, and has broad applications across education, child development, and human health and wellness. However, developing affective computing pipelines …

Unlocking Mental Health: Exploring College Students' Well-being through Smartphone Behaviors

The global mental health crisis is a pressing concern, with college students particularly vulnerable to rising mental health disorders. The widespread use of smartphones among young adults, while offering numerous benefits, has also been linked to …

Digital Wellbeing Redefined: Toward User-Centric Approach for Positive Social Media Engagement

The prevalence of social media and its escalating impact on mental health has highlighted the need for effective digital wellbeing strategies. Current digital wellbeing interventions have primarily focused on reducing screen time and social media …

CAREForMe: Contextual Multi-Armed Bandit Recommendation Framework for Mental Health

The COVID-19 pandemic has intensified the urgency for effective and accessible mental health interventions in people's daily lives. Mobile Health (mHealth) solutions, such as AI Chatbots and Mindfulness Apps, have gained traction as they expand …