Hemodialysis PatientAI-MOBI-HEMODINCT07300761
AI-Integrated Mobile Education and Self-Management in Hemodialysis
A study testing AI-Supported Mobile Education in people with Hemodialysis Patient and Patient Education, run by Ataturk University.
Trial 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. Read more about this study
- Who is it for?
- Ages 18 to 65 years
- Conditions the study is for
- Hemodialysis Patient, Patient Education, Self Care
- What is being tested?
- AI-Supported Mobile Education
- Type of treatment
- Lifestyle or therapy programme
- Could I receive a placebo?
- No, everyone receives an active treatment
- How many people
- 76 participants
- Where
- No sites listed yet
- Study dates
- 2 Jan 2026to 2 Aug 2026
- Phase
- Interventional
- Are there results?
- Not yet: the study is under way
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 18 to 65 years
- All sexes
- No healthy volunteers
- Adult, Older adult
Who may be able to join
- 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.
Who cannot join
- 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
Trial locations and contacts
No sites are listed yet. Contact the study team or a site near you to ask about taking part.
About this study
Official title: A Randomized Controlled Trial to Evaluate the Effect of an Artificial Intelligence-Supported Mobile Education Application on Self-Care Behaviors, Arteriovenous Fistula Care, and Biochemical Parameters in Hemodialysis Patients
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.
Read more
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.
Read the detailed description
This project is a Randomized Controlled Interventional Thesis study designed to bridge a critical gap in chronic disease management literature: the lack of personalized, technology-supported education for Hemodialysis (HD) patients.Study Rationale and ObjectivesWhile HD treatment is life-saving, patients face multiple, complex issues, including AVF complications, fluid restriction difficulties, and emotional distress, all requiring high levels of patient self-care and self-management. Existing mobile health (mHealth) applications for HD patients are limited and typically lack personalized features.The core objective is to test the central hypothesis (H1) that an AI-supported mobile education program will have a statistically significant positive effect on patients' self-management scores, AVF self-care behavior scores, and objectively measured biochemical parameters (including creatinine, albumin, and KT/V) compared to routine care.Methodology and Unique Intervention FeaturesThe study follows a strict four-stage methodological plan:Content Design and Validation: The mobile application content is developed based on current literature and then rigorously validated by expert consensus (involving at least ten specialists, including nephrologists, dialysis nurses, and dietitians). Content readability is verified using the Ateşman formula to ensure patient comprehension. Pilot Study and Usability: A preliminary pilot study is conducted with a small group (excluded from the main study) to assess the application's usability and acceptability using the WAMMI (Website Analysis and Measurement Inventory) scale before the main intervention begins.Randomized Intervention: Seventy-six eligible patients are randomly assigned to either the Intervention Group (receiving the mobile education for 6 weeks) or the Control Group (receiving only routine care).Outcome Measurement and AnalysisPrimary outcomes focus on patient behavior and knowledge, measured by pre- and post-tests (after 6 weeks) using validated instruments: the Hemodialysis Self-Management Scale and the AVF Self-Care Behavior Assessment Scale. Secondary outcomes are clinical, measured by tracking biochemical parameters (BUN, creatinine, albumin, etc.) obtained directly from the patient's hospital records, thus avoiding additional invasive procedures. Data analysis will be conducted using SPSS, with a significance level set at p < 0.05.Expected Impact and Value AddedSuccessful completion is expected to demonstrate significant clinical and economic value by:Improving patient quality of life and autonomy.Reducing the incidence of complications (e.g., AVF failure) and subsequently lowering hospital readmission rates.Providing a cost-effective, sustainable model for chronic disease education that can reduce the financial burden on health institutions and social security.Contributing a novel, evidence-based technological solution to the field of nursing and mHealth literature.
- Conditions
- Hemodialysis Patient, Patient Education, Self Care
- Being tested
- AI-Supported Mobile Education
- Keywords
- Artificial Intelligence, Patient Education, Mobile Application, Self-Care, Hemodialysis, Nursing Care
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
AI-Supported Mobile EducationBehavioural
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.
| Study group | Role | What they receive |
|---|---|---|
| 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. Receives: Behavioral: AI-Supported Mobile Education |
| Control Group | No intervention | Patients receiving routine care and education. |
What is being measured
The primary outcome is the main question the study is designed to answer.
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.
Measured: 6 weeks
Secondary outcomes (1)
Hemodialysis Self-Management Scale
This scale assesses self-management behaviors in patients undergoing hemodialysis. The scale consists of 11 items rated on a 4-point Likert-type scale (Never = 1, Sometimes = 2, Often = 3, Always = 4). Total scores range from 11 to 44, with higher scores indicating better self-management.
The scale includes four subscales: partnership (items 5 and 7), self-care (items 1, 4, and 8), problem solving (items 2, 3, and 6), and emotional management (items 9, 10, and 11).
Measured: 6 weeks.
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted24 Dec 2025
- Study start2 Jan 2026 (estimated)
- Primary completion2 Feb 2026 (estimated)
- Study completion2 Aug 2026 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Hemodialysis PatientStudies of the same condition, open and under way.
- More trials run by Ataturk UniversityThe sponsor's other registered studies.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Interventional
- Phase
- Phase N/A
- Primary purpose
- Supportive care
- Allocation
- Randomised
- Intervention model
- Parallel groups
- Model description
- 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
- Masking
- None (open label)
- Enrolment
- 76 participants (estimated)
Sponsor and investigators
- Lead sponsor
- Ataturk University
- Sponsor type
- University, hospital or other
- Responsible party
- Principal investigator, yakup dilbilir, Ataturk University
- Investigators
- Mehtap KAVURMACI, Prof. Dr., Study director, Ataturk University
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT07300761
- Sponsor's protocol ID
- B.30.2.ATA.0.01.00/726
- Acronym
- AI-MOBI-HEMODI
- Status last verified
- Dec 2025
- First submitted
- 25 Nov 2025
- Last updated
- 24 Dec 2025
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No: Individual Participant Data (IPD) will not be shared with other researchers outside of the primary study team. This decision is based on the data being collected specifically for the completion of a doctoral thesis and for publication of the study results. The ethical approval and informed consent procedures primarily cover the use of the data for this singular project. To ensure the strictest adherence to patient privacy and confidentiality agreements, the raw data will remain securely restricted to the principal investigators.
Study at a glance
From the registry record, last updated by the sponsor on 24 Dec 2025. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- A Randomized Controlled Trial to Evaluate the Effect of an Artificial Intelligence-Supported Mobile Education Application on Self-Care Behaviors, Arteriovenous Fistula Care, and Biochemical Parameters in Hemodialysis Patients
- ClinicalTrials.gov ID
- NCT07300761
- Acronym / sponsor ID
- AI-MOBI-HEMODI / B.30.2.ATA.0.01.00/726
- Conditions
- Hemodialysis Patient, Patient Education, Self Care
- Keywords
- Artificial Intelligence, Patient Education, Mobile Application, Self-Care, Hemodialysis, Nursing Care
- Study type
- Interventional
- Recruitment status
- Not yet recruiting
- Enrolment
- 76 participants (estimated)
- Lead sponsor
- Ataturk UniversityUniversity, hospital or other
- Study start
- 2 Jan 2026 (estimated)
- Primary completion
- 2 Feb 2026 (estimated)
- Study completion
- 2 Aug 2026 (estimated)
- First posted
- 24 Dec 2025 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
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.
Detailed description
This project is a Randomized Controlled Interventional Thesis study designed to bridge a critical gap in chronic disease management literature: the lack of personalized, technology-supported education for Hemodialysis (HD) patients.Study Rationale and ObjectivesWhile HD treatment is life-saving, patients face multiple, complex issues, including AVF complications, fluid restriction difficulties, and emotional distress, all requiring high levels of patient self-care and self-management. Existing mobile health (mHealth) applications for HD patients are limited and typically lack personalized features.The core objective is to test the central hypothesis (H1) that an AI-supported mobile education program will have a statistically significant positive effect on patients' self-management scores, AVF self-care behavior scores, and objectively measured biochemical parameters (including creatinine, albumin, and KT/V) compared to routine care.Methodology and Unique Intervention FeaturesThe study follows a strict four-stage methodological plan:Content Design and Validation: The mobile application content is developed based on current literature and then rigorously validated by expert consensus (involving at least ten specialists, including nephrologists, dialysis nurses, and dietitians). Content readability is verified using the Ateşman formula to ensure patient comprehension. Pilot Study and Usability: A preliminary pilot study is conducted with a small group (excluded from the main study) to assess the application's usability and acceptability using the WAMMI (Website Analysis and Measurement Inventory) scale before the main intervention begins.Randomized Intervention: Seventy-six eligible patients are randomly assigned to either the Intervention Group (receiving the mobile education for 6 weeks) or the Control Group (receiving only routine care).Outcome Measurement and AnalysisPrimary outcomes focus on patient behavior and knowledge, measured by pre- and post-tests (after 6 weeks) using validated instruments: the Hemodialysis Self-Management Scale and the AVF Self-Care Behavior Assessment Scale. Secondary outcomes are clinical, measured by tracking biochemical parameters (BUN, creatinine, albumin, etc.) obtained directly from the patient's hospital records, thus avoiding additional invasive procedures. Data analysis will be conducted using SPSS, with a significance level set at p < 0.05.Expected Impact and Value AddedSuccessful completion is expected to demonstrate significant clinical and economic value by:Improving patient quality of life and autonomy.Reducing the incidence of complications (e.g., AVF failure) and subsequently lowering hospital readmission rates.Providing a cost-effective, sustainable model for chronic disease education that can reduce the financial burden on health institutions and social security.Contributing a novel, evidence-based technological solution to the field of nursing and mHealth literature.
Study design
- Primary purpose
- Supportive care
- Allocation
- Randomised
- Intervention model
- Parallel groups
- Masking
- None (open label)
- Number of arms
- 2
- Model description
- 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
| Arm | Type | Receives |
|---|---|---|
| AI-Supported Mobile Education Group | Experimental | Behavioral: AI-Supported Mobile EducationThis 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. |
| Control Group | No intervention | –Patients receiving routine care and education. |
Who may qualify
- Ages
- 18 to 65 years
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
Key inclusion criteria (6 listed)
- 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.
Key exclusion criteria (3 listed)
- 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
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| AI-Supported Mobile EducationThis 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. | Behavioural | AI-Supported Mobile Education Group |
Primary outcome
Scale for Assessing Self-Care Behaviors Related to Arteriovenous Fistula in Hemodialysis Patients
Time frame: 6 weeks
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.
1 secondary outcome
Hemodialysis Self-Management Scale
Time frame: 6 weeks.
Results and safety
This study is still under way. Results are not available in the source record yet.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 24 Dec 2025.
- Individual participant dataSharing planned: No. Individual Participant Data (IPD) will not be shared with other researchers outside of the primary study team. This decision is based on the data being collected specifically for the completion of a doctoral thesis and for publication of the study results. The ethical approval and informed consent procedures primarily cover the use of the data for this singular project. To ensure the strictest adherence to patient privacy and confidentiality agreements, the raw data will remain securely restricted to the principal investigators.
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part.
Mehtap KAVURMACI, Prof. Dr. study director
Ataturk University
Questions about this trial
What is this clinical trial studying?
A study testing AI-Supported Mobile Education in people with Hemodialysis Patient and Patient Education, run by Ataturk University.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 6 inclusion and 3 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: opening soon, as of the sponsor's last update on 24 Dec 2025. Status can change between updates, so confirm with the study contact before making plans.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
This study is still under way. Results are not available in the source record yet.
How can a doctor refer a patient or contact the research team?
Contact Mehtap Kavurmacı, prof. dr. (+905309327579, mehtap.kavurmaci@atauni.edu.tr), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Scale for Assessing Self-Care Behaviors Related to Arteriovenous Fistula in Hemodialysis Patients (time frame: 6 weeks). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 24 Dec 2025.