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Completed

NCT Number: NCT07806396

Effect of AI-Supported Virtual Patient Chatbot Training on Nursing Students' Self-Perceived Clinical Decision-Making and Gynecological Cancer Knowledge

This randomized controlled trial evaluated the effects of structured case-based training delivered through an artificial intelligence-supported educational virtual patient chatbot platform on nursing students' gynecological cancer knowledge and self-perceived clinical decision-making. Third-year undergraduate nursing students who had completed the Obstetrics and Gynecology Nursing course were randomly assigned in a 1:1 ratio to an intervention group or an assessment-only wait-list control group. The intervention group completed five AI-supported virtual patient training scenarios during a two-week access period, followed by a common virtual patient assessment. The control group completed the same virtual patient assessment without access to the training scenarios during the study assessment period. Knowledge and self-perceived clinical decision-making were assessed at baseline and immediately after the assigned study procedures. Virtual patient performance was assessed once at the final assessment.

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Key information

Age range

18 year and older

Sex eligibility

All sexes

Study type

Interventional

Phase

Not applicable

Primary location

Sakarya University

Sakarya, Turkey, 54050, Turkey (Türkiye)

Who can participate

Healthy volunteers accepted: Yes

Only the study team can determine whether someone qualifies for participation.

Inclusion criteria

  • Enrolled as a third-year undergraduate nursing student.
  • Successfully completed the Obstetrics and Gynecology Nursing (Women's Health and Diseases Nursing) course.
  • Volunteered to participate and provided digital informed consent.

Exclusion criteria

  • No additional exclusion criteria.

Treatment and study plan

AI-Supported Educational Virtual Patient Chatbot Platform

Other

A web-based educational platform integrating structured gynecological oncology scenarios, AI-supported virtual patient interaction, predefined performance criteria, sequential progression, and immediate individualized formative feedback. Participants completed five training scenarios during a two-week access period. The platform used the Claude Sonnet 4 model, API identifier claude-sonnet-4-20250514, throughout the study.

Primary outcomes

  1. Change in Clinical Decision Making in Nursing Scale-Turkish Version (CDMNS-Tr) Score

    Time frame: Baseline, before access to any group-specific study procedure, and immediately after completion of the assigned study procedures.

    The CDMNS-Tr is a 40-item scale assessing self-reported clinical decision-making. Items are rated on a 5-point Likert scale ranging from 1 (never) to 5 (always), with eighteen negatively worded items being reverse-scored. Total scores range from 40 to 200, with higher scores indicating a higher self-perception of clinical decision-making abilities.

Secondary outcomes

  1. Change in Gynecological Oncology Knowledge Test Total Score

    Time frame: Baseline, before access to any group-specific study procedure, and immediately after completion of the assigned study procedures, within approximately two weeks after baseline.

    The researcher-developed test consists of 15 multiple-choice items assessing the pathophysiology, clinical manifestations, diagnosis, treatment, complications, and nursing care of gynecological cancers. Correct answers are scored as 1 and incorrect or unanswered items as 0. Total scores range from 0 to 15, with higher scores indicating greater knowledge. Change was evaluated by comparing baseline and immediate post-intervention total scores.

Sponsors and collaborators

Lead sponsor

Sakarya University

Other

Registry information

Official study title

Effect of AI-Supported Virtual Patient Chatbot Training on Nursing Students' Self-Perceived Clinical Decision-Making and Gynecological Cancer Knowledge: A Randomized Controlled Trial

Important dates

Study start
2026
Primary completion
2026
Study completion
2026
First posted
Sep 8, 2026
Registry last updated
Sep 23, 2026

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

View the official ClinicalTrials.gov record (opens in a new tab)

This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

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