Self Attachment

Self-attachment techniques (SAT) aim to improve mental well-being by leveraging principles of attachment theory through digital interventions. Current research focuses on developing conversational agents, often chatbots, employing rule-based systems, deep learning classifiers for emotion recognition, and large language models (LLMs) to generate empathetic and engaging responses, across multiple languages. These AI-driven approaches are evaluated through human trials, demonstrating potential for accessible and scalable mental health support, particularly in addressing issues like social isolation and anxiety. The effectiveness of these digital tools in delivering SAT is being rigorously assessed, with a focus on improving user engagement and therapeutic outcomes.