Artificial Intelligence-Supported Mobile Application for Diabetes Self-Management

Bursa Uludag University

Status: Not yet enrolling

Conditions: Diabetes Mellitus; Self-management; Artificial Intelligence (AI)

Treatments: Other: WEB based application; Other: artificial intelligence-supported mobile application

Study type: Interventional

Funder types: Other

Identifiers

NCT06650098

2024-12/16

Details and patient eligibility

About

Patients in the AI-supported mobile application group will be able to log in with a username and password that will be defined specifically for them. Patients will be informed about how the application is used during their first interview. They will enter their personal and disease characteristics (age, gender, height, weight, HbA1C, HDL, LDL) into the application at the entrance. Other sections of the application will include exercise, nutrition, medication tracking, complication tracking and diabetic foot care sections. The person will be asked to enter relevant information in these fields according to their own life and condition (for example; how many times do you use insulin per day, what are your medication times, how do you spend your day in terms of exercise, how many meals do you eat, what is your diet, do you urinate frequently, are you extremely thirsty, are you hungry often, do you have numbness in your hands and feet, etc.). After the patient enters the necessary information, they will also be asked to enter their daily blood sugar measurement values into the system. Thus, the individual's hypo/hyperglycemia risk, risk analysis, nutrition recommendations, medication reminder system, exercise reminder and incentive warnings will be communicated to the individual thanks to the AI-based mobile application. The aim of this application is to reduce the risk of complications and improve the individual's quality of life by providing personalized recommendations for all the needs of the individual, including alarms and reminders, and to support patients to continue their diabetes education and disease management more actively.

Full description

pre-test post-test control group design

Enrollment: 156 estimated patients

Sex: All

Volunteers: No Healthy Volunteers

Inclusion criteria

• Having been diagnosed with diabetes for at least 1 year
• Being between the ages of 18-65
• Being open to verbal communication
• Being able to read and write and speak Turkish
• Having a smart android phone and being able to use mobile applications
• Being willing to participate in the study

Exclusion criteria

• Having a perception disorder and psychiatric disorder that prevents the patient from communicating,
• Having a condition that prevents them from using a smart phone (advanced retinopathy and neuropathy, internet problems)
• Being on intensive insulin treatment
• Having a condition that prevents them from continuing the application phase of the study
• Wanting to leave the study

Trial design

Primary purpose: Supportive Care

Allocation: Randomized

Interventional model: Parallel Assignment

Masking: Single Blind

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156 participants in 3 patient groups

WEB based application

Experimental group

Description:

The content plan for the web-based mobile application group will be prepared with technical support as specified. Patients will be able to log in to the mobile application with a username and password that will be defined specifically for them. Patients will be informed about how the website is used during the first meeting. They will be able to access all the information they need about diabetes with the web-based mobile application. Statistical data such as the frequency of individuals visiting the site, which sections they use more often and how much time they spend will be calculated.

Treatment:

Other: WEB based application

artificial intelligence-supported mobile application

Experimental group

Description:

It is aimed that an artificial intelligence-based mobile application that includes information, nutrition, exercise programs, complications and medication tracking, personalized suggestions, alarms and reminders, which will enable diabetic individuals to follow their glucose targets, support patients in their diabetes education, awareness and disease management to continue more actively. In addition, it is aimed that patients can easily access information, prevent acute and chronic complications, present physical activity and nutrition suggestions in accordance with the person\'s lifestyle, follow up on medications with alarms and reminders, prevent the negative results of complications in advance, and improve individuals\' diabetes-specific knowledge levels, compliance with treatment, self-management and care with information and guidance about foot care to reduce the risk of diabetic feet, which is particularly risky for diabetic patients.

Treatment:

Other: artificial intelligence-supported mobile application

control group

No Intervention group

Description:

No intervention will be applied to the control group, and they will receive routine clinical and outpatient training.