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The goal of this randomized controlled trial is to evaluate the immediate efficacy of a Large Language Model (LLM)-assisted training program in enhancing nurses' emergency response capabilities in 204 practicing nurses with ≤5 years of experience from tertiary hospitals in Guiyang, China, focusing on public health emergencies (PHEs). The main questions it aims to answer are:
Participants will:
Complete pre- and post-training assessments (Nurse Self-Assessment Scale for Emergency Response Ability, Nurse's Emergency Response Capacity Scale for PHEs).
Undergo a one-month PHE training program. (Experimental Group Only): Use LLMs for knowledge review, question answering, and exploring unfamiliar concepts during the training period.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| LLM-Assisted PHE Training Group | Other | Participants in this arm receive the routine hospital-based public health emergency (PHE) training program supplemented with Large Language Model (LLM) technology for auxiliary learning. During the 1-month training period, they are instructed and encouraged to use LLMs for:
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| Standard PHE Training Group | Other | Participants in this arm receive only the routine hospital-based public health emergency (PHE) training program. They are explicitly restricted from using LLMs or any other artificial intelligence tools for assisted learning throughout the 1-month training period. (Intervention: Standard PHE curriculum without AI augmentation) |
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| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| LLM-Assisted Public Health Emergency Training Program | Other | A hybrid training program integrating the hospital's standard public health emergency (PHE) curriculum with Large Language Model (LLM) technology as an auxiliary learning tool. Participants receive:
Reviewing session content Resolving knowledge uncertainties via Exploring unfamiliar PHE concepts • Duration: 1 month, with 20-minute sessions. Distinguishing feature: Uses LLMs to dynamically adapt to individual learning needs, enabling on-demand knowledge reinforcement and overcoming spatiotemporal limitations of traditional training. |
| Measure | Description | Time Frame |
|---|---|---|
| Comprehensive Emergency Response Capability Total Score Nurse's Self-Assessment Capability Total Score | Baseline (pre-training) and immediately post-intervention (after 1 month of training) |
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Inclusion Criteria:
Exclusion Criteria:
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| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| The Affiliated Hospital of Guizhou Medical University | Guiyang | Guizhou | 550004 | China |
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| Standard Public Health Emergency Training Program | Other | The hospital's existing public health emergency (PHE) training program without AI augmentation. Participants receive:
Distinguishing feature: Represents traditional training methods reliant on instructor-led content without personalized, on-demand AI-driven reinforcement. |
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