Clinical trial NCT06650098: Artificial Intelligence-Supported Mobile Application For Diabetes Self-Management
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
Study type: INTERVENTIONAL
Overall status: NOT_YET_RECRUITING
Phase: NA
Conditions: Diabetes Mellitus
Artificial Intelligence (AI)
Self-management
Keywords: diabetes mellitus
artificial intelligence
self-management
level of knowledge
compliance with Treatment
Lead sponsor: Uludag University
Sponsor class: OTHER
First posted: 2024-10-21
Enrollment: 156
Sex: ALL
Standard ages: CHILD
ADULT
OLDER_ADULT
Accepts healthy volunteers: no
Allocation: RANDOMIZED
Intervention model: PARALLEL
Primary purpose: SUPPORTIVE_CARE

Brief summary: 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\&amp;#39;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\&amp;#39;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

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

Primary outcomes:
measure: Diabetes Self-Management Scale (DSMS)
timeFrame: 6 months
Secondary outcomes:
measure: Adult diabetes knowledge scale (ADSL)
timeFrame: 6 months
measure: Morisky Medication Adherence Scale (MMAS-8)
timeFrame: 6 months
Other outcomes:
Locations:
city: İstanbul
country: Turkey
facility: Istanbul Basaksehir Cam and Sakura City Hospital
state: Başakşehir
Study officials:
References: