摘要
Digital therapeutics have emerged as a transformative approach in addressing mental health challenges, offering evidence-based, technology-driven interventions. As mental health disorders become increasingly prevalent globally, traditional methods of treatment often fail to meet the growing demand due to limited accessibility, stigmatization, and resource constraints. Digital therapeutics leverage advanced technologies, including artificial intelligence (AI), to bridge these gaps, providing scalable and personalized mental health solutions. AI has revolutionized this domain by enabling adaptive, data-driven interventions that cater to individual needs, ranging from mood disorders to complex conditions like post-traumatic stress disorder (PTSD) and depression. At a broader level, digital therapeutics represent a paradigm shift in healthcare, transitioning from generalized care models to highly personalized and proactive frameworks. AI-driven innovations, such as natural language processing (NLP), predictive analytics, and machine learning algorithms, have enhanced the efficacy of digital mental health tools by facilitating real-time monitoring, symptom analysis, and tailored therapeutic recommendations. These innovations integrate seamlessly with wearables, mobile applications, and virtual reality, providing patients with accessible and engaging platforms for mental health management. However, while AI-based digital therapeutics show immense promise, challenges remain. Ethical concerns about data privacy, bias in AI algorithms, and equitable access need to be addressed to maximize their potential. Additionally, integrating these tools into existing healthcare systems requires alignment with regulatory frameworks and clinician support. By narrowing the focus to personalized treatment approaches, this paper explores how AI-driven digital therapeutics can advance mental health care, providing actionable insights into creating more inclusive, effective, and accessible interventions.