AI model to estimate type 2 diabetes risk in nursing students
Builds an AI model estimating type 2 diabetes risk in nursing students.
Plain-language title generated from the registry record
Registry title: AI-Based Model for Predicting Type 2 Diabetes Risk Using Lifestyle Factors Among Senior Nursing Students
Key facts
- Where
- Alexandria, EgyptSee the site
Where in Egypt
- Faculty of Nursing, Alexandria UniversityAlexandria, EgyptNo longer taking part
Questions to ask the study team
- How often do I need to come in, and for how long each time?
- Are travel costs paid?
- Can I keep my own doctor?
- What happens if I want to stop?
Trial details
- Who runs it
- Alexandria University
- Trial code
- NCT07916428
- Record updated
- 4 November 2026
- Original description
This study will develop and test an artificial intelligence (AI) model that estimates the risk of type 2 diabetes among senior (third- and fourth-year) nursing students at the Faculty of Nursing, Alexandria University, Egypt. Type 2 diabetes is common in Egypt, and many cases are not diagnosed. Daily habits such as diet, physical activity, and body weight play a major role in who develops it. Nursing students will become health care providers who teach patients about healthy living, so it is important to find those who may be at risk early.Read full original descriptionShow less
Developing an Artificial Intelligence-Based Model for Predicting Type 2 Diabetes Risk Using Lifestyle Factors Among Senior Nursing Students at Alexandria University
This study will develop and test an artificial intelligence (AI) model that estimates the risk of type 2 diabetes among senior (third- and fourth-year) nursing students at the Faculty of Nursing, Alexandria University, Egypt. Type 2 diabetes is common in Egypt, and many cases are not diagnosed. Daily habits such as diet, physical activity, and body weight play a major role in who develops it. Nursing students will become health care providers who teach patients about healthy living, so it is important to find those who may be at risk early.
About 200 students will take part. Each student will complete a questionnaire about personal information and the Health-Promoting Lifestyle Profile II, which measures health habits such as nutrition, physical activity, stress management, and health responsibility. The researcher will measure height, weight, waist size, and blood pressure. Each student's diabetes risk will be scored using the Arabic version of the Australian Type 2 Diabetes Risk Assessment Tool (AUSDRISK), which classifies risk as low, moderate, or high.
These data will be used to build a machine learning model that predicts each student's diabetes risk level from lifestyle and body measurement factors, and shows which factors influenced the prediction most. Students will then try the model and rate how useful and easy to use it is.
No treatment or intervention will be given. The study aims to support early identification of students at risk and to provide a model that nursing education programs and community health nurses could use in preventive health efforts.
Inclusion: Regularly enrolled third- or fourth-year (senior) undergraduate nursing students at the Faculty of Nursing, Alexandria University; Willing to provide written informed consent and participate voluntarily; Have access to an internet-enabled electronic device (smartphone, tablet, or computer) and basic digital literacy.
Exclusion: Previously diagnosed with type 1 or type 2 diabetes mellitus; Chronic endocrine disorders known to affect glucose metabolism; Pregnancy; Incomplete or invalid questionnaire responses.