NCT07390461

Brief Summary

The goal of this clinical trial is to learn if a Artificial Intelligence integrated Mixed Reality-based High-Alert Medications Management Simulation Program (AIMR-HAM) helps hospital nurses manage high-alert medicines (HAMs) more safely. MR mixes real and virtual elements to let nurses practice in realistic scenarios. The main questions are: Does the AIMR-HAM improve nurses' medication safety skills? Does the AIMR-HAM lower medication errors and improve clinical performance? Researchers will compare two groups to answer these questions: Intervention group: AIMR-HAM Control group: standard education only Who can take part: Nurses who work at large hospitals and have 1 to 6 years of clinical experience. About 60 nurses will join the study. What participants will do: Attend the assigned training (AIMR-HAM or standard education only). Complete short tests and surveys before and after training to measure skills, communication, and clinical reasoning. Report any medication errors that occur during the study. Why this matters: The study will show whether AIMR-HAM training can improve how nurses handle HAMs and make patient care safer.

Trial Health

35
At Risk

Trial Health Score

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

Trial has exceeded expected completion date
Enrollment
60

participants targeted

Target at P25-P50 for not_applicable

Timeline
Completed

Started Mar 2026

Status
not yet recruiting

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

Trial Relationships

Click on a node to explore related trials.

Study Timeline

Key milestones and dates

First Submitted

Initial submission to the registry

January 28, 2026

Completed
8 days until next milestone

First Posted

Study publicly available on registry

February 5, 2026

Completed
27 days until next milestone

Study Start

First participant enrolled

March 4, 2026

Completed
Same day until next milestone

Primary Completion

Last participant's last visit for primary outcome

March 4, 2026

Completed
2 days until next milestone

Study Completion

Last participant's last visit for all outcomes

March 6, 2026

Completed
Last Updated

February 5, 2026

Status Verified

January 1, 2026

Enrollment Period

Same day

First QC Date

January 28, 2026

Last Update Submit

January 28, 2026

Conditions

Healhty

Keywords

High-alert medicationsnursemixed realityartificial intelligencemedication safety

Outcome Measures

Primary Outcomes (1)

  • High-Alert Medication clinical performance

    The high-alert medication clinical performance competency assessment will utilize a questionnaire developed by our research team. The tool consists of 23 questions, of which 4 will vary depending on the simulation progress, resulting in a final assessment measuring 19 questions. Each item will be graded by the instructor on a scale of 0 for failure or incorrect execution, 1 for insufficient or inadequate execution, and 2 for accurate execution. The developed items will undergo a validity assessment by six experts before being revised and supplemented for use. Higher scores indicate greater clinical performance in high-alert medication.

    Baseline, immediately post-intervention

Secondary Outcomes (3)

  • Global Interpersonal Communication Competence

    Baseline, immediately post-intervention

  • Clinical Reasoning Competency

    Baseline, immediately post-intervention

  • Medication Safety Competence

    Baseline, immediately post-intervention

Study Arms (2)

Arm 1

EXPERIMENTAL

Participants receive a Artificial Intelligence integrated Mixed Reality-based High-Alert Medications Management Simulation Program

Other: Artificial Intelligence integrated Mixed Reality-based Simulation Program

Arm 2

ACTIVE COMPARATOR

Participants receive the hospital's standard medication-management education

Other: Standard medication-management education

Interventions

Standard medication-management educationOTHER

Participants receive the hospital's standard medication-management education (didactic lectures, case discussions, and workshops)

Arm 2
Artificial Intelligence integrated Mixed Reality-based Simulation ProgramOTHER

Participants in the intervention arm receive Artificial Intelligence integrated Mixed Reality-based High-Alert Medications Management Simulation Program

Arm 1

Eligibility Criteria

Sexall
Healthy VolunteersYes
Age GroupsChild (0-17), Adult (18-64), Older Adult (65+)

You may qualify if:

  • Nurses with at least one to six years of clinical experience.
  • Those who understand the purpose and procedures of this study and have given written consent to participate.
  • Those who have no physical or cognitive limitations in using mixed reality devices.
  • ④ Those who are able to communicate in Korean and understand and respond to questions.

You may not qualify if:

  • Those who do not wish to participate in the study. ② Those who have participated in education related to high-alert medications within the past six months.
  • Those who are unable or have difficulty participating in the mixed reality education program due to visual, hearing, or neurological impairments, or adverse effects such as dizziness or motion sickness.
  • Those who voluntarily withdraw from the study midway through.

Contact the study team to confirm eligibility.

Sponsors & Collaborators

Related Publications (1)

  • Bae, J., Lee, J., Choi, M., Jang, Y., Park, C. G., & Lee, Y. J. (2023). Development of the clinical reasoning competency scale for nurses. BMC nursing, 22(1), 138. Elendu, C., Amaechi, D. C., Okatta, A. U., Amaechi, E. C., Elendu, T. C., Ezeh, C. P., & Elendu, I. D. (2024). The impact of simulation-based training in medical education: A review. Medicine, 103(27), e38813. Fernández-Alcántara, M., Escribano, S., Juliá-Sanchis, R., Castillo-López, A., Pérez-Manzano, A., Macur, M., Kalender-Smajlović, S., García-Sanjuán, S., & Cabañero-Martínez, M. J. (2025). Virtual Simulation Tools for Communication Skills Training in Health Care Professionals: Literature Review. JMIR Medical Education, 11(1), e63082. Frost, J., Delaney, L., & Fitzgerald, R. (2020). Exploring the application of mixed reality in nurse education. BMJ Simulation & Technology Enhanced Learning, 6(4), 214. Fu, Y., Hu, Y., & Sundstedt, V. (2022). A systematic literature review of virtual, augmented, and mixed reality game applications in healthcare. ACM Transactions on Computing for Healthcare (HEALTH), 3(2), 1-27. Gaffney, T. A., Hatcher, B. J., & Milligan, R. (2016). Nurses' role in medical error recovery: an integrative review. Journal of clinical nursing, 25(7-8), 906-917. Han, Y., Chen, J., Xu, Y., Huang, P., & Hou, L. (2024). Nurse-led medication management as a critical component of transitional care for preventing drug-related problems. Aging Clinical and Experimental Research, 36(1), 151. Hodkinson, A., Tyler, N., Ashcroft, D. M., Keers, R. N., Khan, K., Phipps, D., Abuzour, A., Bower, P., Avery, A., & Campbell, S. (2020). Preventable medication harm across health care settings: a systematic review and meta-analysis. BMC medicine, 18(1), 313. Jeon, H. G., & Jeong, H. W. (2025). Effectiveness of a Mixed Reality Simulation Program for Dyspnoea Care on New Nurses' Clinical Competency: A Mixed-Methods Study. Nurse Education in Practice, 104397. Mardani, A., Griffiths, P., & Vaismoradi, M. (202

    RESULT

Central Study Contacts

Hwigon Jeon, Ph.D. student

CONTACT

+82-10-5121-0700tjdans779@gmail.com

Study Design

Study Type
interventional
Phase
not applicable
Allocation
RANDOMIZED
Masking
TRIPLE
Who Masked
PARTICIPANT, INVESTIGATOR, OUTCOMES ASSESSOR
Purpose
HEALTH SERVICES RESEARCH
Intervention Model
PARALLEL
Sponsor Type
OTHER
Responsible Party
PRINCIPAL INVESTIGATOR
PI Title
professor

Study Record Dates

First Submitted

January 28, 2026

First Posted

February 5, 2026

Study Start

March 4, 2026

Primary Completion

March 4, 2026

Study Completion

March 6, 2026

Last Updated

February 5, 2026

Record last verified: 2026-01