AI-Integrated Mobile Education and Self-Management in Hemodialysis

NCT07300761 | Not Yet Recruiting

• 1 other identifier: B.30.2.ATA.0.01.00/726
• Study Type: interventional
• Target: 76
• Locations: 0 countries
• Sites: N/A

Brief Summary

This randomized controlled trial aims to evaluate the effectiveness of an Artificial Intelligence-supported mobile education application designed to enhance self-care behaviors, arteriovenous fistula (AVF) care practices, and key biochemical parameters among adult hemodialysis (HD) patients. Chronic Kidney Disease (CKD) and its most common renal replacement therapy, hemodialysis, impose a substantial physical, psychological, and socioeconomic burden on patients. HD patients frequently experience fatigue, pain, cramping, sleep disturbances, thirst and fluid restriction challenges, dietary limitations, AVF-related complications, and emotional distress. These difficulties highlight the importance of strengthening patients' self-care abilities and promoting active involvement in disease management. Despite the prevalence of mobile health (mHealth) technologies in chronic disease management, existing applications for HD patients remain limited, and none have integrated personalized artificial intelligence-based educational support. The absence of AI-driven patient education represents a significant gap in nursing science and digital health innovation. This project addresses that gap by developing and testing a structured, evidence-based mobile education program supported by artificial intelligence, designed specifically for HD patients. The study will enroll 76 eligible hemodialysis patients from Bitlis State Hospital and Bitlis Tatvan State Hospital. Participants will be randomly assigned to either the intervention group or the control group using simple randomization. The intervention group will receive access to the AI-supported mobile application for six weeks, which includes modules on kidney function, CKD and treatment options, symptom management, dietary adherence, fluid management, treatment adherence, and AVF care. Each module incorporates written content, videos, visuals, voice-supported reading features, and an integrated "Ask a Question" function allowing patients to communicate directly with the research team. The control group will receive routine clinical care without additional intervention. The artificial intelligence component will assist with content personalization, monitoring of patient engagement, data storage, automated reminders for non-active users, and supportive feedback based on learning progress and biochemical trends. The development of the mobile application will be guided by expert opinions from nephrology specialists, dialysis nurses, academicians, and dietitians. Readability of educational materials will be assessed using the Ateşman Readability Formula. A pilot study will be conducted prior to the trial to evaluate usability using the Web Analysis and Measurement Inventory (WAMMI). Data collection will include a Patient Identification Form, the Hemodialysis Arteriovenous Fistula Self-Care Behavior Scale, the Hemodialysis Self-Management Scale, and a Biochemical Parameters Tracking Form. Pre-test data will be collected before the intervention; post-test data will be collected at the end of the six-week intervention period. Biochemical parameters will include BUN, creatinine, albumin, potassium, phosphorus, hemoglobin, uric acid levels, Kt/V, and dry weight, obtained from routine clinical records without additional blood sampling. The primary outcomes will assess changes in self-care and self-management behaviors based on validated scales. Secondary outcomes will examine changes in biochemical parameters between the intervention and control groups. Data analysis will be performed using SPSS, employing descriptive statistics, normality testing, and appropriate statistical comparison tests, with significance set at p \< 0.05. Ethical approval will be obtained from the appropriate institutional ethics committee, and written informed consent will be secured from all participants. Data confidentiality will be ensured using encrypted login systems and secure storage processes. This trial is expected to contribute significantly to the scientific literature by being the first AI-supported mobile education intervention tailored for hemodialysis patients. Anticipated benefits include improved self-care behaviors, increased patient autonomy, reduced AVF complications, better adherence to dietary and fluid restrictions, and improved biochemical outcomes. Broader impacts of the project include the potential reduction of hospitalization rates, decreased healthcare costs, increased quality of life for HD patients, and the establishment of a digital model that can be adapted for other chronic disease populations. Ultimately, this study aims to demonstrate that integrating artificial intelligence with mobile health education can create a transformative approach to patient empowerment, clinical care, and chronic disease management within the field of nephrology and nursing.

Conditions

Hemodialysis Patient; Patient Education; Self Care

Keywords

Artificial Intelligence; Patient Education; Mobile Application; Self-Care, Hemodialysis; Nursing Care

Outcome Measures

Primary Outcomes (1)

• Scale for Assessing Self-Care Behaviors Related to Arteriovenous Fistula in Hemodialysis Patients

  Scale for Assessing Self-Care Behaviors Related to Arteriovenous Fistula in Hemodialysis Patients This scale was developed by Sousa et al. to assess patients' self-care behaviors related to arteriovenous fistula and to monitor educational processes. The scale was originally developed in Portuguese, and its validity and reliability for the Turkish population were established by İkiz and Yıldırım Usta. The scale consists of 16 items rated on a 5-point Likert-type scale and includes two subscales: Symptom Management (items 1, 3, 6, 11, 13, and 16) Complication Prevention (items 2, 4, 5, 7, 8, 9, 10, 12, 14, and 15) The total score ranges from 16 to 80, with higher scores indicating a higher level of self-care. The Cronbach's alpha reliability coefficient of the scale is 0.91. The average administration time is approximately 2-3 minutes.

  6 weeks

Secondary Outcomes (1)

• Hemodialysis Self-Management Scale

  6 weeks.

Study Arms (2)

AI-Supported Mobile Education Group

EXPERIMENTAL

This arm, the AI-Supported Mobile Education Group, receives the experimental intervention for a period of 6 weeks. The intervention consists of a web-based mobile application that delivers specialized education to Hemodialysis (HD) patients. The content, developed with expert opinions, covers six key areas, including AVF care, diet adherence, fluid management, and general treatment adherence. The application is supported by Artificial Intelligence (AI), which is used to store patient data, track the patient's usage time, and automatically send reminders and motivational messages to encourage compliance. After receiving their login credentials and an orientation from the researcher, patients are expected to access and complete the education modules independently over the 6-week period.

Behavioral: AI-Supported Mobile Education

Control Group

NO INTERVENTION

Patients receiving routine care and education.

Interventions

AI-Supported Mobile Education BEHAVIORAL

This arm, the AI-Supported Mobile Education Group, receives the experimental intervention for a period of 6 weeks. The intervention consists of a web-based mobile application that delivers specialized education to Hemodialysis (HD) patients. The content, developed with expert opinions, covers six key areas, including AVF care, diet adherence, fluid management, and general treatment adherence. The application is supported by Artificial Intelligence (AI), which is used to store patient data, track the patient's usage time, and automatically send reminders and motivational messages to encourage compliance. After receiving their login credentials and an orientation from the researcher, patients are expected to access and complete the education modules independently over the 6-week period.

AI-Supported Mobile Education Group

Eligibility Criteria

• Age: 18 Years - 65 Years
• Sex: all
• Healthy Volunteers: No
• Age Groups: Adult (18-64), Older Adult (65+)

You may qualify if:

• Must be 18 years of age or older.
• Must have an Arteriovenous Fistula (AVF).
• Must not have a communication-hindering problem.
• Must be receiving outpatient Hemodialysis (HD) treatment.
• Must have been receiving HD treatment for longer than 6 months.
• Must own a smartphone and have internet access.

You may not qualify if:

• Patients who do not agree to participate in the research.
• Patients who have been diagnosed with advanced cerebrovascular and peripheral vascular insufficiency.
• Patients who do not complete the mobile education application

Sponsors & Collaborators

• Ataturk University: lead

Study Officials

• Mehtap KAVURMACI, Prof. Dr.

  Ataturk University

  STUDY DIRECTOR

Central Study Contacts

Mehtap Kavurmacı, prof. dr.

CONTACT

+905309327579; mehtap.kavurmaci@atauni.edu.tr

Study Design

• Study Type: interventional
• Phase: not applicable
• Allocation: RANDOMIZED
• Masking: NONE
• Masking Details: The project document does not state that any parties are masked (blinded) in the clinical trial. Given the nature of the intervention, the study is inherently open-label (unmasked): Participants (Patients): Patients in the Intervention Group are fully aware that they are using a mobile education application, and those in the Control Group are aware they are only receiving routine care. Therefore, participant masking is not possible. Personnel (Researchers): Researchers are responsible for introducing the application and conducting face-to-face interviews for data collection. They are aware of which group the patient belongs to. Outcome Assessment: While objective outcomes (such as biochemical parameters) are gathered from hospital records, the document does not specify a plan for an independent, blinded assessor or data analyst. In summary, as the application form does not detail any masking procedures, it must be reported that no other parties are masked.
• Purpose: SUPPORTIVE CARE
• Intervention Model: PARALLEL
• Sponsor Type: OTHER
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: research assistant

Model Details: This is a Randomized Controlled Interventional Thesis study aiming to evaluate the effect of an AI-supported mobile education application on Hemodialysis (HD) patients' self-care, AVF behaviors, and biochemical parameters. The study targets 76 HD patients (38 per group) at two hospitals in Bitlis, assigned via simple randomization. The intervention group uses the app for 6 weeks; the control group receives routine care. Data is collected via pre- and post-tests (6 weeks) using the Hemodialysis Self-Management Scale and AVF Self-Care Scale. Biochemical parameters (e.g., BUN, creatinine, albumin) are tracked using hospital records

Study Record Dates

• First Submitted: November 25, 2025
• First Posted: December 24, 2025
• Study Start: January 2, 2026
• Primary Completion: February 2, 2026
• Study Completion (Estimated): August 2, 2026
• Last Updated: December 24, 2025

Record last verified: 2025-12

Data Sharing

• IPD Sharing: Will not share