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.

1. Study Design and Randomization MechanismThis study utilizes a Pre-Post Parallel Intervention Design. To enhance internal validity, minimize selection bias, and account for unit-level characteristics, a Stratified Cluster Randomization approach is employed. Clinical units are stratified into three tiers based on assessed work intensity: High Intensity (e.g., ICUs and ED), Medium Intensity (e.g., medical and surgical wards), and Low Intensity (e.g., psychiatric and rehabilitation wards). Within each stratum, the nursing unit or ward serves as the cluster. Clusters are then randomly assigned (1:1 ratio) to either the Intervention Group or the Control Group, ensuring that all nurses within a single unit belong to the same study arm. The planned total sample size is N=120, distributed across approximately 18 clusters.2. Intervention Protocol (4-Week Period)The intervention period spans four weeks (28 days). The core tool is a customized GPT dialogue model integrated with the LINE Official Account (LINE OA) platform, widely used by the target population.Intervention Group (Interactive AI Support)Participants receive a two-part daily intervention: a daily push message and access to a two-way AI interaction. They are encouraged to actively engage in free-form psychological support dialogue with the LINE GPT assistant. The AI's response logic is rigorously defined via Prompt Engineering to focus on clinical work stress, emotional coping, and resilience-promoting strategies. Crucially, the AI is programmed with ethical guardrails to gently redirect users back to the clinical stress axis if they deviate to non-work related or sensitive topics, and strictly prohibit the provision of any medical, diagnostic, or therapeutic advice.Control Group (Static Message Control)Participants in the control group receive daily static text messages. The content themes are identical to the push messages received by the intervention group, but the channel lacks any interactive AI response capability.3. Study Procedures and Data Collection TimelineThe entire study spans a minimum of six weeks, structured into three distinct phases.The process begins in Weeks 1-2 with recruitment and baseline assessment. Following informed consent, participants are oriented to the study platform (LINE OA) and complete the Pre-Test Questionnaire. This baseline assessment, which takes approximately 25-30 minutes, captures all demographic/occupational variables and the initial scores for all primary and secondary outcome scales (ProQOL, GSE, PSS-10, BRS).Immediately following baseline assessment, the 4-week intervention period commences, spanning from approximately Week 3 through Week 6. Throughout this period, both the intervention and control groups receive their respective daily messages. To track subjective engagement and experience, all participants are required to complete a brief "AI Use Feedback Simple Form" weekly, which takes approximately 5 minutes.Upon completion of the four weeks, the study enters the Post-Test phase at the end of Week 6. All participants complete the same battery of outcome scales (re-measurement of ProQOL, GSE, PSS-10, BRS) and the AI Use Satisfaction Questionnaire. The Intervention Group is additionally requested to complete an Open-ended Feedback Questionnaire to provide rich qualitative data on their experience with the GPT assistant.4. Statistical Analysis PlanData will be anonymized using unique study IDs prior to analysis. Due to the stratified cluster randomization, the analysis will employ methods suitable for clustered data structures to account for Intracluster Correlation (ICC). The Primary Analysis will utilize Generalized Estimating Equations (GEE) to model the change in outcomes over time, specifically testing the "Time $\times$ Group" interaction to assess the intervention effect. The nursing unit/ward will be specified as the cluster variable in the GEE model. Linear Mixed-Effects Models (LMM) may be used for supplementary or sensitivity analysis. Covariates such as nursing tenure and baseline stress levels will be included in the models for adjustment and exploratory analysis. Qualitative data from the open-ended feedback will be analyzed using Content Analysis to categorize emerging themes.

Inclusion Criteria:

1. Adults aged 20 to 65 years.
2. Currently employed as clinical nursing staff in the participating institution, including inpatient wards or intensive care units.
3. Able to read Traditional Chinese and receive daily messages via LINE or Email.
4. Willing to participate and able to provide written informed consent.
5. Expected to remain employed in the clinical unit for the full 4-week study period (not planning resignation or extended leave).

Exclusion Criteria:

1. Refusal or inability to provide informed consent.
2. Unable to receive daily messages through LINE or Email (e.g., no smartphone or internet access).
3. Currently undergoing psychiatric treatment or in the acute phase of major physical/mental illness, where participation may interfere with clinical care.
4. Cognitive or communication impairments that prevent understanding of study material or completion of questionnaires.

Individual participant data (IPD) will not be shared because the study involves sensitive information from clinical nursing staff, including psychological measures and message-based interactions, which cannot be fully de-identified without risk of re-identification. The approved IRB protocol does not include provisions for external data sharing.

No masking was implemented. This is a cluster-randomized, parallel-group behavioral intervention in which both participants and investigators are aware of whether they receive interactive AI emotional support messages or static non-interactive messages. Outcomes are assessed using self-administered questionnaires.