Development and usability evaluation of AI-based acute coronary syndrome nursing education program for nursing students

Status

Active, not recruiting

Phases

Unknown

Study type

Interventional

Source

CRIS

Registry ID

KCT0012387

Enrollment

Registered

2026-08-03

Start date

2026-08-10

Completion date

Unknown

Last updated

2026-08-10

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

None listed

Interventions

Behavioral : Participants will receive a 15-minute orientation and use the web-based artificial intelligence-based acute coronary syndrome nursing education program for approximately 60 minutes. The p

a chest pain assessment and patient education scenario using an artificial intelligence patient chatbot

patient status reporting to an artificial intelligence physician using the Situation-Background-Assessment-Recommendation structure

individualized performance feedback

and a gamified performance dashboard. Each participant will complete at least one conversation with the artificial intelligence patient chatbot and one conversation with the artificial intelligence ph

Eligibility

Sex/Gender

All

Inclusion criteria

Inclusion criteria: Third- or fourth-year undergraduate nursing students enrolled at the College of Nursing, Chonnam National University Students who have completed cardiovascular nursing coursework within adult health nursing

Exclusion criteria

Exclusion criteria: Students who have completed separate education or training related to acute coronary syndrome or electrocardiography within one month before the start of the study Students who report technical barriers to using generative artificial intelligence

Design outcomes

Primary

Measure	Time frame
Total and subscale scores of the Generative Artificial Intelligence Chatbot Perception Scale, including usefulness, ease of use, intention for continued use, immersion, and anthropomorphism.	—

Secondary

Measure	Time frame
Mental demand, physical demand, temporal demand, performance, effort, and frustration scores measured using the National Aeronautics and Space Administration Task Load Index;Task completion time, task completion rate, number of errors, and number of requests for assistance;Completeness of patient information collection and adherence to the Situation-Background-Assessment-Recommendation elements assessed from learner-artificial intelligence dialogue logs;Categories derived from individual interviews regarding communication with the artificial intelligence patient and physician, effectiveness of feedback, learning experience, efficiency, and areas for improvement	—

Measure

Time frame

Mental demand, physical demand, temporal demand, performance, effort, and frustration scores measured using the National Aeronautics and Space Administration Task Load Index;Task completion time, task completion rate, number of errors, and number of requests for assistance;Completeness of patient information collection and adherence to the Situation-Background-Assessment-Recommendation elements assessed from learner-artificial intelligence dialogue logs;Categories derived from individual interviews regarding communication with the artificial intelligence patient and physician, effectiveness of feedback, learning experience, efficiency, and areas for improvement

—

Countries

Korea, Republic of

Contacts

Public ContactSun-Hee Moon

Chonnam National University

sunnymon@jnu.ac.kr+82-62-530-4952

Outcome results