Leveraging Large Language Models to Enhance Emotional Intelligence Training in Anesthesiology

Abstract

Emotional intelligence is essential for high-stakes interactions in the perioperative setting. Whether addressing patient concerns, resolving conflicts, or triaging cases, anesthesiologists rely on emotional intelligence for effective communication. However, stressors such as fatigue and heavy workloads can deplete the ability to sustain emotional intelligence during critical moments. Emotional intelligence can be strengthened with structured training. Large language models (LLMs), with their ability to generate empathetic responses, offer an innovative approach to enhancing emotional intelligence training in anesthesiology. LLMs can generate a variety of on-demand scenarios that can be fine-tuned, validated, and implemented by experts. They can be used to create tailored simulation scenarios for a variety of pedagogical methods to help clinicians prepare for emotionally charged conversations and enhance their communication skills. While not a replacement for human training, LLMs can serve as easily accessible supplemental tools to bolster clinicians' emotional intelligence skills when integrated with proper oversight.

Ähnliche Arbeiten