Advancing Evidence-Based Mental Health Research for College Students Through Biotechnology Innovations

Zhang Xingxing
Jiangsu Vocational College of Business, Nantong, Jiangsu, 226000, China

DOI:https://doi.org/10.5912/jcb2525

Abstract:

This study pioneers the integration of biotechnology with evidence-based research to enhance the precision of mental health assessment among college students. By leveraging bioinformatics and neuroimaging techniques, the research develops an intelligent mental health education system that aligns with biotech-driven insights into brain function and emotional regulation. The framework integrates data from wearable biosensors with machine learning algorithms to dynamically monitor stress biomarkers and sleep patterns—key biological indicators of mental well-being. An evidence-based treatment module, incorporating biobehavioral interventions validated through randomized controlled trials, is established to offer personalized mental health strategies. The system architecture incorporates biofeedback mechanisms to customize cognitive-behavioral therapy (CBT) protocols, addressing individual neurobiological variations. Functional modules include real-time mood analysis using facial expression recognition and biometric stress detection, enabling proactive and adaptive mental health support. Experimental validation using electroencephalography (EEG) and salivary cortisol assays demonstrates the system’s effectiveness, reducing anxiety symptoms by 22% compared to traditional methods. This research contributes to the field of biotechnology by establishing a scalable, data-driven platform for translating biological markers into actionable mental health interventions, supporting the development of innovative and evidence-based wellness programs in academic settings.