NCT07141433

Brief Summary

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:

  1. 1.Does LLM-assisted training improve nurses' comprehensive emergency response capabilities in PHEs?
  2. 2.Does it specifically enhance rescue skills and occupational protection abilities? Researchers will compare the experimental group (receiving routine PHE training + LLM-assisted learning) to the control group (receiving routine PHE training only) to see if LLM supplementation leads to significantly greater improvements in targeted emergency competencies.

Trial Health

87
On Track

Trial Health Score

Automated assessment based on enrollment pace, timeline, and geographic reach

Enrollment
204

participants targeted

Target at P75+ for not_applicable

Timeline
Completed

Started Oct 2024

Shorter than P25 for not_applicable

Geographic Reach
1 country

1 active site

Status
completed

Health score is calculated from publicly available data and should be used for screening purposes only.

Trial Relationships

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Study Timeline

Key milestones and dates

Study Start

First participant enrolled

October 1, 2024

Completed
3 months until next milestone

Primary Completion

Last participant's last visit for primary outcome

December 31, 2024

Completed
Same day until next milestone

Study Completion

Last participant's last visit for all outcomes

December 31, 2024

Completed
8 months until next milestone

First Submitted

Initial submission to the registry

August 19, 2025

Completed
7 days until next milestone

First Posted

Study publicly available on registry

August 26, 2025

Completed
Last Updated

August 26, 2025

Status Verified

August 1, 2025

Enrollment Period

3 months

First QC Date

August 19, 2025

Last Update Submit

August 19, 2025

Conditions

Outcome Measures

Primary Outcomes (1)

  • 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)

Study Arms (2)

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: * Reviewing knowledge covered in training sessions * Answering questions and clarifying uncertainties * Exploring unfamiliar concepts related to PHE response (Intervention: Standard PHE curriculum + LLM-enabled interactive learning support)

Other: LLM-Assisted Public Health Emergency Training ProgramOther: Standard Public Health Emergency Training Program

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)

Other: Standard Public Health Emergency Training Program

Interventions

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: * Standardized PHE training (online lectures + offline simulations) covering professional knowledge, skills, and emergency drills (e.g., infectious disease response, trauma management). * LLM-enabled interactive support: Structured guidance to use LLMs for: 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.

LLM-Assisted PHE Training Group

The hospital's existing public health emergency (PHE) training program without AI augmentation. Participants receive: * Identical core content as the experimental group: Professional knowledge, skills training, and emergency drills for PHE response (e.g., disaster protocols, infection control). * Explicit restriction: Prohibited from using LLMs or any AI tools for learning support. * Delivery: Hybrid format (online + offline), 1-month duration, 20-minute sessions. Distinguishing feature: Represents traditional training methods reliant on instructor-led content without personalized, on-demand AI-driven reinforcement.

LLM-Assisted PHE Training GroupStandard PHE Training Group

Eligibility Criteria

Age18 Months - 35 Months
Sexall
Healthy VolunteersYes
Age GroupsChild (0-17)

You may qualify if:

  • Holds a valid nursing professional qualification certificate;
  • ≤5 years of nursing work experience;
  • Voluntarily agrees to participate in the training program。

You may not qualify if:

  • Inability to complete the 1-month training program (e.g., planned leave, transfer, or resignation during the study period)
  • Prior experience using Large Language Models (LLMs) for professional training (to avoid confounding effects)
  • Refusal to comply with group assignment protocols (e.g., control group participants attempting to use LLMs)

Contact the study team to confirm eligibility.

Sponsors & Collaborators

Study Sites (1)

The Affiliated Hospital of Guizhou Medical University

Guiyang, Guizhou, 550004, China

Location

Study Design

Study Type
interventional
Phase
not applicable
Allocation
RANDOMIZED
Masking
DOUBLE
Who Masked
PARTICIPANT, INVESTIGATOR
Purpose
SUPPORTIVE CARE
Intervention Model
PARALLEL
Sponsor Type
OTHER
Responsible Party
SPONSOR

Study Record Dates

First Submitted

August 19, 2025

First Posted

August 26, 2025

Study Start

October 1, 2024

Primary Completion

December 31, 2024

Study Completion

December 31, 2024

Last Updated

August 26, 2025

Record last verified: 2025-08

Data Sharing

IPD Sharing
Will not share

Locations