Exploration of Mental Health and Stress Among Nursing Interns Through a Chatbot: A Single-Group Pilot Study
Ya-Wen Kuo1,2, Wen-Li Hou3, Susan Fetzer4
1Professor (Kuo), Department of Nursing, Chang Gung University of Science and Technology, Chiayi Campus, Puzi, Chiayi County, Taiwan.
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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