A Scoping Review of AI-Driven Digital Interventions in Mental Health Care: Mapping Applications Across Screening, Support, Monitoring, Prevention, and Clinical Education

This collection of recent arXiv papers surveys a range of AI topics with clear security and safety implications: AI-driven mental-health interventions (LLMs, chatbots, voice agents) that raise privacy, bias, and human-AI collaboration risks; generative Legal AI (GLAI) that is prone to hallucination and automation bias, threatening explainability and legal rights; per-user embedding probes (POLAR) and large-scale resume analyses that enable author-level profiling, deanonymization, and sensitive population inferences; multi-agent/agent‑ecosystem work that surfaces emergent trust, lifecycle, and操