Artificial Intelligence-Supported Mobile Application For Diabetes Self-Management

NCT ID: NCT06650098

Last Updated: 2025-03-25

Study Results

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

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Recruitment Status

NOT_YET_RECRUITING

Clinical Phase

NA

Total Enrollment

156 participants

Study Classification

INTERVENTIONAL

Study Start Date

2025-04-01

Study Completion Date

2026-06-01

Brief Summary

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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.

Detailed Description

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pre-test post-test control group design

Conditions

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Diabetes Mellitus Artificial Intelligence (AI) Self-management

Study Design

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Allocation Method

RANDOMIZED

Intervention Model

PARALLEL

Primary Study Purpose

SUPPORTIVE_CARE

Blinding Strategy

SINGLE

Participants

Study Groups

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WEB based application

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.

Group Type EXPERIMENTAL

WEB based application

Intervention Type OTHER

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.

artificial intelligence-supported mobile application

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.

Group Type EXPERIMENTAL

artificial intelligence-supported mobile application

Intervention Type OTHER

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.

control group

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

Group Type NO_INTERVENTION

No interventions assigned to this group

Interventions

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artificial intelligence-supported mobile application

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.

Intervention Type OTHER

WEB based application

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.

Intervention Type OTHER

Eligibility Criteria

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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
Eligible Sex

ALL

Accepts Healthy Volunteers

No

Sponsors

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Uludag University

OTHER

Sponsor Role lead

Responsible Party

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Nilhan Toyer Sahin

Phd Student

Responsibility Role PRINCIPAL_INVESTIGATOR

Locations

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Istanbul Basaksehir Cam and Sakura City Hospital

Istanbul, Başakşehir, Turkey (Türkiye)

Site Status

Countries

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Turkey (Türkiye)

Central Contacts

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Nilhan NŞ Töyer Şahin, PhD Student

Role: CONTACT

+905333752295

Seda SP PEHLİVAN, Associate Professor

Role: CONTACT

Facility Contacts

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Muhittin BALTA General Hospital Deputy Chief Physician, Doctor

Role: primary

+90 212 909 60 00

Other Identifiers

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2024-12/16

Identifier Type: -

Identifier Source: org_study_id

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