Research on the application and effect of artificial intelligence technology in mental health assessment

Abstract

This study investigates the application and effectiveness of artificial intelligence (AI) technologies in mental health assessment, synthesizing findings from recent research and implementation studies. Through a comprehensive analysis of both quantitative and qualitative data, we examine the performance metrics of AI-based assessment tools compared to traditional methods, demonstrating significant improvements in accuracy (91% vs 82%), efficiency (37.8% reduction in assessment time), and user satisfaction (4.3/5 overall rating). The research framework encompasses literature review, methodology design, data collection, and evaluation of implementation outcomes across multiple healthcare facilities. Our findings indicate that AI-based mental health assessment tools not only enhance clinical efficiency but also improve diagnostic accuracy and patient engagement. However, challenges regarding cultural diversity in training data, privacy concerns, and regulatory compliance need to be addressed. The study provides practical recommendations for implementing AI-based mental health assessment systems and outlines future research directions to overcome current limitations. These insights contribute to the evolving landscape of digital mental healthcare and offer valuable guidance for healthcare providers considering AI integration in their clinical practice.