Clinical nurses are frequently exposed to high emotional demands due to heavy workloads, time pressure, patient suffering, and the interpersonal complexity of clinical care. These stressors may contribute to compassion fatigue, burnout, reduced resilience, and decreased occupational well-being. However, timely and accessible psychological support is often limited in busy clinical environments, and many nurses may hesitate to seek help due to stigma, time constraints, or limited resources. This study is a prospective, randomized, controlled, parallel-group interventional trial designed to evaluate the feasibility and effectiveness of an on-demand, human-centered emotional support intervention delivered through a LINE-based GPT assistant. The AI assistant provides real-time supportive conversations, reflective prompts, stress-coping guidance, and resilience-enhancing strategies tailored specifically for clinical nurses, offering a private and easily accessible support resource. Eligible clinical nurses (target sample size: 100-120) are randomly assigned to either an Intervention Group, which interacts with the AI assistant, or a Control Group, which receives non-interactive static messages, over a four-week intervention period. Primary outcomes include changes in compassion fatigue, burnout, and compassion satisfaction, as measured by the Professional Quality of Life Scale (ProQOL). Secondary outcomes include changes in resilience (Brief Resilience Scale), general self-efficacy (General Self-Efficacy Scale), and perceived stress (Perceived Stress Scale-10). The results of this study are expected to provide evidence on the feasibility and potential effectiveness of AI-based emotional support as a scalable and accessible tool to promote psychological well-being among clinical nurses, thereby informing future digital mental health interventions in healthcare settings.
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Change in Compassion Fatigue, Burnout, and Compassion Satisfaction (ProQOL)
Timeframe: Baseline and Week 4