Artificial Intelligence-Supported Mobile Application For Diabetes Self-Management
For patients and families
In plain language
An automatic summary of structured registry data. It is an orientation aid, not a substitute for the official protocol or a physician assessment.
- What is being studied
- The protocol lists: artificial intelligence-supported mobile application, WEB based application.
- Who it may be relevant to
- Registry conditions: Diabetes Mellitus, Artificial Intelligence (AI), Self-management. Basic parameters: No limits · All.
- What needs checking
- Age, condition and sex are only basic indicators. Prior treatment, laboratory values and other mandatory requirements appear in the eligibility criteria below.
- Where it takes place
- Turkey (Türkiye)
- Next step
- Save the trial, show it to the treating physician, and confirm current recruitment with the study center. Costs, documents and travel →
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Official title
The Effect of Web-Based and Artificial Intelligence-Assisted Personalized Applications on Knowledge Levels Compliance With Treatment and Self-Management Among Diabetic Individuals
Overview
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
pre-test post-test control group design
Interventions
- Other 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 - 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 visitin
Primary outcome measures
- Diabetes Self-Management Scale (DSMS) [Time frame: 6 months]
Secondary outcome measures (2)
- Adult diabetes knowledge scale (ADSL) [Time frame: 6 months]
- Morisky Medication Adherence Scale (MMAS-8) [Time frame: 6 months]
Eligibility criteria
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
Criteria are shown verbatim from the registry (in English). Final eligibility is always assessed by the study center.
Healthy volunteers: No
Study design
- Allocation
- Randomized
- Model
- Parallel assignment
- Masking
- Single blind
- Primary purpose
- Supportive care
Study locations
Turkey (Türkiye) · 1 center
- Istanbul Basaksehir Cam and Sakura City Hospital — Istanbul
Identifiers
NCT: NCT06650098 · 2024-12/16