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Use of Artificial Intelligence in Nursing Education

The Effect of Chatgpt Usage on Case Analysis and Medical Artificial Intelligence Readiness Among Nursing Students: A Randomized Controlled Trial

Status
Completed
Phases
NA
Study type
Interventional
Source
ClinicalTrials.gov
Registry ID
NCT07090408
Enrollment
59
Registered
2025-07-29
Start date
2025-02-01
Completion date
2025-06-30
Last updated
2025-07-29

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

Conditions

Artificial Intelligence

Keywords

artificial intelligence, nursing students, nursing care

Brief summary

In this study, the effect of using ChatGPT, one of the artificial intelligence tools, on nursing students' case analysis and readiness for medical artificial intelligence will be evaluated.

Detailed description

In studies on artificial intelligence in the field of nursing; it is observed that nurses reduce their workload by remotely monitoring psychiatric patients with an artificial intelligence-based sensor, there is a significant decrease in emergency room visits with an artificial intelligence-supported camera monitoring system to prevent dementia patients from falling, and the risk of pressure sores in patients in the intervention group is reduced by developing a network measurement system to predict pressure sores. Such widespread use of artificial intelligence in the nursing profession contributes to faster analysis and active management of the care process by nurses in diagnosing possible risk factors and solving any problems encountered. Thus, nurses' workload will decrease and a more efficient nursing care process will emerge. The attitude towards artificial intelligence in nursing students preparing for the profession is actually positive even in the first years of education. These results show that new generation nurses adopt artificial intelligence and its usability in the profession in the future. In fact, more academic and practical studies are needed on artificial intelligence, which has entered all professional lives in a new and rapid way. The increase in such studies, especially among students preparing for the nursing profession, will reflect both the knowledge gap in students and the necessity of proven studies in the field. The attitudes of nursing students towards new technologies and their acceptance of these innovations are especially important because they play a key role in health care. Therefore, it is necessary to learn how nursing students understand and adopt new technologies such as artificial intelligence-based technologies. When looking at the literature, it is possible to come across different studies on artificial intelligence in nursing students. However, in this study, the effect of using ChatGPT, one of the artificial intelligence tools, on case analysis and medical artificial intelligence readiness in nursing students will be evaluated.

Interventions

BEHAVIORALArtificial intelligence support

Each student in the intervention group will be asked to solve a given case example using ChatGPT support. However, students in the control group will be asked to analyze the case using their own academic knowledge without ChatGPT support.

Sponsors

Recep Tayyip Erdogan University
Lead SponsorOTHER

Study design

Allocation
RANDOMIZED
Intervention model
FACTORIAL
Primary purpose
OTHER
Masking
SINGLE (Subject)

Eligibility

Sex/Gender
ALL
Age
18 Years to No maximum
Healthy volunteers
Yes

Inclusion criteria

* Students who agree to participate in the study * 2nd year students who are actively studying in the Nursing Department of the Faculty of Health Sciences of a university * Students who use smartphones

Exclusion criteria

* Not accepting to participate in the research, * Not using a smartphone

Design outcomes

Primary

MeasureTime frameDescription
Case analysis delivery time(one lesson duration) approximately 30-40 minutesThe case analysis score was evaluated between 0 and 100 points.

Countries

Turkey (Türkiye)

Outcome results

None listed

Source: ClinicalTrials.gov · Data processed: Feb 4, 2026