Diabetic Patients,Self-Care,Artificial Intelligence-Based,Self-EfficacyNCT06985680
Diabetic Patients,Self-Efficacy,Self-Care Behaviors,Artificial Intelligence-Based
A study testing LINE@ Diabetes Health Education Chatbot in people with Diabetic Patients,Self-Care,Artificial Intelligence-Based,Self-Efficacy and Type 2 Diabetes Mellitus (T2DM), run by Chia-Tzu Line at 1 site in China.
Trial summary
This study employed an experimental research design using a randomized controlled trial methodology. Group allocation was performed randomly by generating serial numbers through a computer. Read more about this study
- Who is it for?
- Ages 18 to 80 yearsHealthy volunteers can take part
- Conditions the study is for
- Diabetic Patients,Self-Care,Artificial Intelligence-Based,Self-Efficacy, Type 2 Diabetes Mellitus (T2DM)
- What is being tested?
- LINE@ Diabetes Health Education Chatbot
- Type of treatment
- Lifestyle or therapy programme
- Could I receive a placebo?
- No, everyone receives an active treatment
- How many people
- 104 participants
- Where
- 1 siteChina
- Study dates
- 1 Feb 2024to 18 Feb 2025
- Phase
- Interventional
- Are there results?
- None posted in the registry
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 80 years
- All sexes
- Healthy volunteers accepted
- Adult, Older adult
Who may be able to join
- Diagnosed with type 2 diabetes by a physician and enrolled as a patient in the Diabetes Collaborative Care Network.
- Aged 18 years or older.
- Owns a smartphone and agrees to join the "Diabetes Smart Helper" LINE@ Diabetes Health Education Chatbot application.
- HbA1c level greater than 7.0% (as referenced in Changsieng et al., 2023; Selçuk-Tosun \& Zincir, 2019).
Who cannot join
- Patients undergoing hemodialysis or peritoneal dialysis.
- Patients diagnosed with mental illness.
- Illiterate patients.
Trial locations and contacts
1 site in 1 country.
About this study
Official title: Exploring the Impact of Artificial Intelligence-Based Health Education on Self-Efficacy, Self-Care Behaviors, and Glycemic Control in Diabetic Patients
This study employed an experimental research design using a randomized controlled trial methodology. Group allocation was performed randomly by generating serial numbers through a computer. Participants were then randomly assigned to either the experimental or control group by placing the serial numbers into opaque envelopes and selecting envelopes in random order as patients arrived for appointments.
The experimental group received conventional face-to-face education in addition to participating in the "Diabetes Smart Assistant" Line@ diabetes education robot program. Education was delivered individually in a one-on-one manner. Researchers spent 15 minutes instructing participants on the operation and usage of the Line@ diabetes education robot program, followed by educational content delivery. Educational sessions lasted for 30 minutes on the day of enrollment, and 15 minutes each at the 3rd and 6th months of enrollment, totaling three one-on-one educational sessions. Additionally, participants received telephone consultations for follow-up during the enrollment period. Telephone education sessions were conducted in the first week of enrollment, the second month, and the fourth month, each lasting 10 minutes, totaling three sessions.
The control group received routine education and had follow-up visits every three months for one-on-one education. Data collection for both groups occurred at the time of enrollment, and at the 3rd and 6th months of enrollment.
- Conditions
- Diabetic Patients,Self-Care,Artificial Intelligence-Based,Self-Efficacy, Type 2 Diabetes Mellitus (T2DM)
- Being tested
- LINE@ Diabetes Health Education Chatbot
- Medical subject headings
- Diabetes Mellitus, Type 2
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
LINE@ Diabetes Health Education ChatbotBehavioural
Upon opening the LINE application, the research subjects need to enter "Diabetes Smart Helper" in the LINE@ Diabetes Health Education Chatbot. Once added to the program, the LINE interface will directly display six small windows for diabetes symptoms/complications, diet, medication, exercise, mental health, and others, facilitating self-selection by users.
| Study group | Role | What they receive |
|---|---|---|
| LINE@ Diabetes Health Education Chatbot | Other | The research involves the application of the "Diabetes Smart Helper" LINE@ Diabetes Health Education Chatbot for intervention measures. This application includes AI automatic message responses and provides push notifications of diabetes-related medical and healthcare knowledge to ensure that the public receives accurate medical information (Chinese Diabetes Health Education Association, 2021). Receives: Behavioral: LINE@ Diabetes Health Education Chatbot |
What is being measured
The primary outcome is the main question the study is designed to answer.
The Chinese Version Diabetes Management Self-Efficacy Scale
This study employs the Chinese Version Diabetes Management Self-Efficacy Scale (C-DMSES) developed by S. F. Wu et al. (2008) for assessment. The scale covers nutrition (9 items), exercise and weight control (4 items), medication management (3 items), and blood glucose and foot care (4 items). Scoring is based on an 11-point Likert scale, where 10 points indicate "very confident" and 0 points indicate "not confident at all." The total score ranges from 0 to 200, with higher scores indicating stronger self-efficacy, meaning that patients have greater confidence in performing diabetes self-care behaviors such as blood glucose monitoring, dietary management, control, and medication adherence. This scale is used for patients with type 2 diabetes in Taiwan, and the internal consistency reliability of the four subscales is as follows: dietary self-efficacy (α = .93), adherence to medical advice self-efficacy (α = .79), exercise and weight control self-efficacy (α = .81), and blood glucose mo
Measured: 6 months.
The Summary of Diabetes Self-Care Activities
The Summary of Diabetes Self-Care Activities (SDSCA) published by Toobert et al. (2000) was used, which includes 25 questions covering six aspects, including diet, exercise, self-monitoring of blood glucose, smoking, self-care behavior counseling, and medication. The questionnaire was modified by Qiu (2002) to measure the self-care behavior of diabetes in Chinese. There are 10 structured questions, including foot care (3 questions), diet (2 questions), exercise (2 questions), medication (2 questions) and blood sugar monitoring (1 question). This scale monitors the daily self-care of diabetes in the past 7 days. The second question is a reverse question, and the other questions are scored in a positive way. The 7-day frequency method is used for calculation. The questionnaire scale is calculated from 0 to 7 points. Each question has a maximum score of 7 points and a minimum score of 0. For example, if the questions in the questionnaire are completed for 1 day, it represents 1 point, an
Measured: 6 months.
blood glucose control
This study is based on the 2022 Clinical Care Guidelines for Type 2 Diabetes. Blood sugar control indicators include blood sugar level before meals, blood sugar level 2 hours after meals, and HbA1c value. It is recommended that good blood sugar control indicators for patients with type 2 diabetes are blood sugar level before meals maintained at 80-130 mg/dl, blood sugar level 2 hours after meals maintained at 80-160 mg/dl, and HbA1c value < 7.0% (Diabetes Society of the Republic of China, 2022). The above test values are from the medical records of the subjects.
The testing equipment used by the hospital in this case has passed ISO 1589:2012, with the certification number 1575, and meets the relevant standards. According to the requirements of the National Health Insurance Diabetes Medical Benefit Improvement Program, diabetic patients must undergo a blood test every 3 months. Patients must complete the blood test 3 to 7 days before outpatient consultation. The blood draw time of th
Measured: 6 months.
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted22 May 2025
- Study start1 Feb 2024
- Primary completion1 Nov 2024
- Study completion18 Feb 2025
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Diabetic Patients,Self-Care,Artificial Intelligence-Based,Self-EfficacyStudies of the same condition, open and under way.
- 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
- Not applicable
- Intervention model
- Single group
- Masking
- None (open label)
- Enrolment
- 104 participants (actual)
Sponsor and investigators
- Lead sponsor
- Chia-Tzu Line
- Sponsor type
- University, hospital or other
- Responsible party
- Sponsor-investigator, Chia-Tzu Line, WeiGong Memorial Hospital
- Investigators
- chia-tzu lin, Principal investigator, not related
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT06985680
- Sponsor's protocol ID
- WeiGongMemorial
- Status last verified
- Jul 2024
- First submitted
- 10 Mar 2024
- Last updated
- 22 May 2025
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No
Study at a glance
From the registry record, last updated by the sponsor on 22 May 2025. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Exploring the Impact of Artificial Intelligence-Based Health Education on Self-Efficacy, Self-Care Behaviors, and Glycemic Control in Diabetic Patients
- ClinicalTrials.gov ID
- NCT06985680
- Acronym / sponsor ID
- WeiGongMemorial
- Conditions
- Diabetic Patients,Self-Care,Artificial Intelligence-Based,Self-Efficacy, Type 2 Diabetes Mellitus (T2DM)
- Study type
- Interventional
- Recruitment status
- Completed
- Enrolment
- 104 participants (actual)
- Lead sponsor
- Chia-Tzu LineUniversity, hospital or other
- Study start
- 1 Feb 2024 (actual)
- Primary completion
- 1 Nov 2024 (actual)
- Study completion
- 18 Feb 2025 (actual)
- First posted
- 22 May 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 study employed an experimental research design using a randomized controlled trial methodology. Group allocation was performed randomly by generating serial numbers through a computer. Participants were then randomly assigned to either the experimental or control group by placing the serial numbers into opaque envelopes and selecting envelopes in random order as patients arrived for appointments.
The experimental group received conventional face-to-face education in addition to participating in the "Diabetes Smart Assistant" Line@ diabetes education robot program. Education was delivered individually in a one-on-one manner. Researchers spent 15 minutes instructing participants on the operation and usage of the Line@ diabetes education robot program, followed by educational content delivery. Educational sessions lasted for 30 minutes on the day of enrollment, and 15 minutes each at the 3rd and 6th months of enrollment, totaling three one-on-one educational sessions. Additionally, participants received telephone consultations for follow-up during the enrollment period. Telephone education sessions were conducted in the first week of enrollment, the second month, and the fourth month, each lasting 10 minutes, totaling three sessions.
The control group received routine education and had follow-up visits every three months for one-on-one education. Data collection for both groups occurred at the time of enrollment, and at the 3rd and 6th months of enrollment.
Study design
- Primary purpose
- Supportive care
- Allocation
- Not applicable
- Intervention model
- Single group
- Masking
- None (open label)
- Number of arms
- 1
| Arm | Type | Receives |
|---|---|---|
| LINE@ Diabetes Health Education Chatbot | Other | Behavioral: LINE@ Diabetes Health Education ChatbotThe research involves the application of the "Diabetes Smart Helper" LINE@ Diabetes Health Education Chatbot for intervention measures. This application includes AI automatic message responses and provides push notifications of diabetes-related medical and healthcare knowledge to ensure that the public receives accurate medical information (Chinese Diabetes Health Education Association, 2021). |
Who may qualify
- Ages
- 18 to 80 years
- Sex
- All
- Healthy volunteers
- Accepted
- Age groups
- Adult, Older adult
Key inclusion criteria (4 listed)
- Diagnosed with type 2 diabetes by a physician and enrolled as a patient in the Diabetes Collaborative Care Network.
- Aged 18 years or older.
- Owns a smartphone and agrees to join the "Diabetes Smart Helper" LINE@ Diabetes Health Education Chatbot application.
- HbA1c level greater than 7.0% (as referenced in Changsieng et al., 2023; Selçuk-Tosun \& Zincir, 2019).
Key exclusion criteria (3 listed)
- Patients undergoing hemodialysis or peritoneal dialysis.
- Patients diagnosed with mental illness.
- Illiterate patients.
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 |
|---|---|---|
| LINE@ Diabetes Health Education ChatbotUpon opening the LINE application, the research subjects need to enter "Diabetes Smart Helper" in the LINE@ Diabetes Health Education Chatbot. Once added to the program, the LINE interface will directly display six small windows for diabetes symptoms/complications, diet, medication, exercise, mental health, and others, facilitating self-selection by users. | Behavioural | LINE@ Diabetes Health Education Chatbot |
Primary outcome
The Chinese Version Diabetes Management Self-Efficacy Scale
Time frame: 6 months.
This study employs the Chinese Version Diabetes Management Self-Efficacy Scale (C-DMSES) developed by S. F. Wu et al. (2008) for assessment. The scale covers nutrition (9 items), exercise and weight control (4 items), medication management (3 items), and blood glucose and foot care (4 items). Scoring is based on an 11-point Likert scale, where 10 points indicate "very confident" and 0 points indicate "not confident at all." The total score ranges from 0 to 200, with higher scores indicating stronger self-efficacy, meaning that patients have greater confidence in performing diabetes self-care behaviors such as blood glucose monitoring, dietary management, control, and medication adherence. This scale is used for patients with type 2 diabetes in Taiwan, and the internal consistency reliability of the four subscales is as follows: dietary self-efficacy (α = .93), adherence to medical advice self-efficacy (α = .79), exercise and weight control self-efficacy (α = .81), and blood glucose mo
The Summary of Diabetes Self-Care Activities
Time frame: 6 months.
The Summary of Diabetes Self-Care Activities (SDSCA) published by Toobert et al. (2000) was used, which includes 25 questions covering six aspects, including diet, exercise, self-monitoring of blood glucose, smoking, self-care behavior counseling, and medication. The questionnaire was modified by Qiu (2002) to measure the self-care behavior of diabetes in Chinese. There are 10 structured questions, including foot care (3 questions), diet (2 questions), exercise (2 questions), medication (2 questions) and blood sugar monitoring (1 question). This scale monitors the daily self-care of diabetes in the past 7 days. The second question is a reverse question, and the other questions are scored in a positive way. The 7-day frequency method is used for calculation. The questionnaire scale is calculated from 0 to 7 points. Each question has a maximum score of 7 points and a minimum score of 0. For example, if the questions in the questionnaire are completed for 1 day, it represents 1 point, an
blood glucose control
Time frame: 6 months.
This study is based on the 2022 Clinical Care Guidelines for Type 2 Diabetes. Blood sugar control indicators include blood sugar level before meals, blood sugar level 2 hours after meals, and HbA1c value. It is recommended that good blood sugar control indicators for patients with type 2 diabetes are blood sugar level before meals maintained at 80-130 mg/dl, blood sugar level 2 hours after meals maintained at 80-160 mg/dl, and HbA1c value < 7.0% (Diabetes Society of the Republic of China, 2022). The above test values are from the medical records of the subjects. The testing equipment used by the hospital in this case has passed ISO 1589:2012, with the certification number 1575, and meets the relevant standards. According to the requirements of the National Health Insurance Diabetes Medical Benefit Improvement Program, diabetic patients must undergo a blood test every 3 months. Patients must complete the blood test 3 to 7 days before outpatient consultation. The blood draw time of th
Results and safety
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 22 May 2025.
- Individual participant dataSharing planned: No
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. This study is not recruiting at the moment.
chia-tzu lin principal investigator
not related
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
A study testing LINE@ Diabetes Health Education Chatbot in people with Diabetic Patients,Self-Care,Artificial Intelligence-Based,Self-Efficacy and Type 2 Diabetes Mellitus (T2DM), run by Chia-Tzu Line at 1 site in China.
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 4 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: finished, as of the sponsor's last update on 22 May 2025. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in China. Whether a site is taking part right now should be confirmed with that site. See every site.
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?
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
How can a doctor refer a patient or contact the research team?
The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
The Chinese Version Diabetes Management Self-Efficacy Scale (time frame: 6 months.). The study lists 3 primary outcomes in all. 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 22 May 2025; AzTrials last refreshed its copy on 31 Oct 2026.