Exploration of Mental Health and Stress Among Nursing Interns Through a Chatbot: A Single-Group Pilot Study.
Journal:
Nurse educator
Published Date:
Jan 15, 2026
Abstract
BACKGROUND: Nursing interns face early clinical distress; chatbot-based mental health tools show promise, although evidence of their feasibility and educational value remains insufficient. PURPOSE: To evaluate the application feasibility and effectiveness of the Xiao Ling Assistant Chatbot (X-LAC) for addressing mental health challenges, monitoring stress, and detecting early warning signals of psychological distress among nursing students participating in a clinical internship. METHODS: A 4-week single-group study with 61 nursing interns tested X-LAC's daily chatbot-based support and keyword-triggered alerts; pre/post mental health and stress were assessed. RESULTS: Well-being improved (12-20); suicidal ideation declined (10-4). The chatbot flagged 16 high-risk expressions per 100 messages, notably so tired and under pressure; 60.6% reported internship distress. CONCLUSION: Chatbot support shows promise for clinical training, reducing stress and enabling early detection. Integrating artificial intelligence for risk prediction is warranted while retaining human oversight for critical cases.
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