Type 1 DiabetesNCT04016987
Automated Structured Education Based on an App and AI in Chinese Patients With Type 1 Diabetes
A study testing Automated structured education intervention based on an app and artificial intelligence in people with Type 1 Diabetes, run by Second Xiangya Hospital of Central South University at 1 site in China.
Trial summary
In recent years, more and more attention has been paid to diabetes self-management. Glycemic control and self-management skills of patients with type 1 diabetes (T1DM) in China are poor. Read more about this study
- Who is it for?
- Ages 18 to 50 years
- Conditions the study is for
- Type 1 Diabetes
- What is being tested?
- Automated structured education intervention based on an app and artificial intelligence
- Type of treatment
- Lifestyle or therapy programme
- Could I receive a placebo?
- No, everyone receives an active treatment
- How many people
- 138 participants
- Where
- 1 siteChina
- Study dates
- 8 Sep 2020to Dec 2023
- 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 50 years
- All sexes
- No healthy volunteers
- Adult
Who may be able to join
- Individuals diagnosed with Type 1 Diabetes according to the 1999 World Health Organization report
- Insulin dependence from disease onset
- Aged 18-50 years
- With a disease duration over 6 months
- With a HbA1c level over 7%
- Treated T1DM with multiple daily injections or insulin pump
- Individuals who own smartphone and are capable of using wechat or apps
Who cannot join
- Age below 18 years or above 50 years
- Being pregnant
- With mental disorders
- Have any other condition or disease that may hamper from compliance with the protocol or complication of the trial
- Already using a smartphone app for managing diabetes
- Having chronic complications including diabetic retinopathy, diabetic nephropathy or diabetic foot, diabetic neuropathy
Trial locations and contacts
1 site in 1 country.
China1 site, 1 recruiting
- Recruiting
Institute of Metabolism and Endocrinology, Second Xiangya Hospital, Central South University
Changsha, 410011
Xia Li, MD/PHD, +86 17373199692
About this study
Official title: Automated Structured Education Intervention Based on an App and Artificial Intelligence in Chinese Patients With Type 1 Diabetes
In recent years, more and more attention has been paid to diabetes self-management. Glycemic control and self-management skills of patients with type 1 diabetes (T1DM) in China are poor. Artificial intelligence (AI) and the Internet offer a new way to improve the self-management skills of patients with chronic diseases. Few studies have combined AI technology with structured education intervention of type 1 diabetes. This study is innovative in that it compares the effectiveness of smartphone app between usual care, as well as automatic and individualized app education and standardized app education to explore whether the individualized treatment advocated by the latest guideline will bring any additional benefit to T1DM patients. The ultimate goal is to provide an effective and convenient approach for glycemic control of type 1 diabetes and reduce related disease burden in China.
Read the detailed description
This is a single-blinded, 1:1 paralleled group cluster randomized controlled trial (RCT). The intervention will last for 24 weeks. The laboratory staff who test the HbA1c level, the outcome assessor who collects the blood glucose data, and the statisticians will be blinded to the treatment allocation.
Sample size estimation: We propose to enroll 138 patients with type 1 diabetes (T1DM) by considering withdrawals, 69 in the smartphone app groups and 69 in the routine care group. Sample size estimation is based on hypothesized changes in the primary outcome HbA1c.
In order to ensure high quality data, two staff are responsible for the input of original data into the database to check and confirm the accuracy. When the data entered by two staff independently, the auxiliary staff decides which data to use.
Data analysis will be conducted under the intention-to-treat principle by including all the randomized patients in the data analysis. Missing data will be filled in with multiple imputation method. Any substantial difference in baseline characteristics will be adjusted with mixed-model regression analysis. Sensitivity analysis will be conducted by using per-protocol data by excluding those patients who drop out of the RCT.
- Conditions
- Type 1 Diabetes
- Being tested
- Automated structured education intervention based on an app and artificial intelligence
- Medical subject headings
- Diabetes Mellitus, Type 1
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Automated structured education intervention based on an app and artificial intelligenceBehavioural
In the 24-week intervention period, the experimental group receives automated push notifications supported by artificial intelligent algorithm.
| Study group | Role | What they receive |
|---|---|---|
| Automated, Individualized Education | Experimental | Subjects will be given instructions to install the patient-end App, which includes the following functions: diabetes education, patient-doctor communication, diabetes diary, peer support, reminder for blood sugar test and related abnormal results. They receive push notifications that provides recommended education materials which meet the needs of the patient by considering his/her baseline diabetes-related knowledge. Receives: Behavioral: Automated structured education intervention based on an app and artificial intelligence |
| Routine care | No intervention | Subjects only receive the education provided by health-care professionals in the outpatient department |
What is being measured
The primary outcome is the main question the study is designed to answer.
changes in serum hemoglobin A1c level
A1c reflects the average blood glucose level in the past 2-3 months.
Measured: from baseline to week 12, 24
Secondary outcomes (18)
changes in Time in range (TIR)
TIR measures the time where the blood glucose remains within the proposed target range.
Measured: from baseline to week 12, 24
Chinese version of Diabetes Quality of Life scale
Diabetes Quality of Life scale (DQOL) is a wildly used 46-item tool for assessing the quality of life related to diabetes in three aspects: diabetes satisfaction (15 items), impact (20 items), and worry (11 items). Each item is responded to on a 5-point Likert scale, with score of 1 represents "always affected", "always worried", or "never satisfied" and a score of 5 indicates "no impact", "no worries", or "always satisfied". Higher total score reflects better quality of life. A Chinese version of DQOL has been translated and validated in the diabetic population from Mainland China and will be adopted in this trial.
Measured: from baseline to week 12, 24
Diabetes Self-Management Scale
Diabetes Self-Management Scale is used to assess diabetes self-management behaviors. This scale contains six aspects with a total of 14 items: dietary management, physical activity, self-monitoring of blood sugar, medical treatment, foot care and smoking. Except for smoking, the other five aspects with 11 items ask the number of days during the last week (ie. how many days did you test your blood sugar during the last 7 days?...). One of the dietary questions (ie. days of high-fat diet consumption) is reversely scored (the more days the fewer score), and the rest are positively scored in 0-7 points. The overall score uses the above five aspects of 11 questions, with a minimum score of 0 and maximum score of 77. Higher score reflects better the self-management behaviors.
Measured: from baseline to week 12, 24
Chinese version of Diabetes Self-Care Activities
Diabetes Self-Care Activities (SDSCA) is used to assess diabetes self-care behavior. This scale contains six behavior related scales: general dietary, specific dietary, glucose monitoring, physical activity, foot care, and smoking. Absolute weekly frequency or consistency of diabetes self-care activities are scored with a 0-7 ranged scale, with higher scores reflecting better performance in self-care behaviors. The internal consistency reliability and construct validity of SDSCA was supported by its psychometric test based on an adult diabetes population. A validated Chinese version of the SDSCA (C-SDSCA) is available for this trial.
Measured: from baseline to week 12, 24
Diabetes Empowerment Scale-Short Form
Patients' diabetes-related psychosocial self-efficacy will be evaluated with the Diabetes Empowerment Scale-Short Form, which was a short form of Diabetes Empowerment Scale developed from the America population with type 1 or type 2 diabetes. A revised Chinese version is available for the Mainland China population. The Chinese version DES-SF includes 8 domains with 1 item for each (i.e., assessing the need for change, developing a plan, overcoming barriers, asking for support, supporting oneself, coping with emotion, motivating oneself, and making diabetes care choices appropriate for one's priorities and circumstances). Each item is responded on a 5-point Likert scale, with 1 indicating strongly disagree and 5 indicating strongly agree. Total score ranges from 8 to 40, with higher scores reflect a better psychosocial self-efficacy.
Measured: from baseline to week 12, 24
State-Trait Anxiety Inventory (STAI)
State-Trait Anxiety Inventory (STAI) is used for assessing patients psychological status. The Chinese version STAI consists of two sub-scales to measure both state and trait anxiety states. Each of the two anxiety states will be measured with a 20-item sub-scale, and each item will be scored from 1 to 4. The total score for both state and trait anxiety range from 20 to 80, with high scores indicating more serious anxiety.
Measured: from baseline to week 12, 24
Beck's Depression Inventory (BDI)
Beck's Depression Inventory (BDI) is used for assessing patients psychological status. The Chinese version BDI (CBDI) consists of 21 self-rated items. Each item will be scored from 0 to 3, with the total score ranges from 0 to 63, and a higher score indicates more serious depression.
Measured: from baseline to week 12, 24
Fasting blood glucose
the blood sugar level after fasting for eight hours
Measured: from baseline to week 12, 24
Systolic blood pressure
Systolic blood pressure
Measured: from baseline to week 12, 24
Diastolic blood pressure
Diastolic blood pressure
Measured: from baseline to week 12, 24
Total cholesterol
serum total cholesterol level
Measured: from baseline to week 12, 24
High-density lipoprotein (HDL) cholesterol
serum HDL level
Measured: from baseline to week 12, 24
Low-density lipoprotein (LDL) cholesterol
serum LDL level
Measured: from baseline to week 12, 24
Triglycerides
serum triglycerides level
Measured: from baseline to week 12, 24
Height in meters
Height in meters will be measured.
Measured: from baseline to week 12, 24
Weight in kilograms
Weight in kilograms will be measured.
Measured: from baseline to week 12, 24
Patients engagement with the app
Patients' engagement with the app will be measured in terms of communications with the clinician and the utilization of the smartphone app. Specifically, the number of messages sent to patients, the number of message responses, the number of video calls/phone calls with patients, the number of logs entered by patients, and time spent in the health education module will be collected.
Measured: automatically collected by the app from baseline to week 24
Adverse events
Safety-related outcomes including hypoglycemic events, hospitalization, and emergency room visits will be collected at each follow-up time point including the monthly telephone interview.
Measured: every 4 weeks from baseline to week 24
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted12 Jul 2019
- Study start8 Sep 2020
- Primary completionDec 2021 (estimated)
- Study completionDec 2023 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Publications (1)Papers the sponsor has linked to this study.
- Other trials for Type 1 DiabetesStudies 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
- Treatment
- Allocation
- Randomised
- Intervention model
- Parallel groups
- Masking
- Single blind
- Who is masked
- Outcomes assessor
- Enrolment
- 138 participants (estimated)
Sponsor and investigators
- Lead sponsor
- Second Xiangya Hospital of Central South University
- Sponsor type
- University, hospital or other
- Responsible party
- Principal investigator, Xia Li, Second Xiangya Hospital of Central South University
- Investigators
- Xia Li, MD/PHD, Principal investigator, Central South University
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT04016987
- Sponsor's protocol ID
- AI App-EC T1D 2019
- Status last verified
- Sep 2020
- First submitted
- 5 Jul 2019
- Last updated
- 16 Sep 2020
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No
Publications
Huang F, Wu X, Xie Y, Liu F, Li J, Li X, Zhou Z. An automated structured education intervention based on a smartphone app in Chinese patients with type 1 diabetes: a protocol for a single-blinded randomized controlled trial. Trials. 2020 Nov 23;21(1):944. doi: 10.1186/s13063-020-04835-9.
PubMed 33225982
Study at a glance
From the registry record, last updated by the sponsor on 16 Sep 2020. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Automated Structured Education Intervention Based on an App and Artificial Intelligence in Chinese Patients With Type 1 Diabetes
- ClinicalTrials.gov ID
- NCT04016987
- Acronym / sponsor ID
- AI App-EC T1D 2019
- Conditions
- Type 1 Diabetes
- Study type
- Interventional
- Recruitment status
- Unknown status
- Enrolment
- 138 participants (estimated)
- Lead sponsor
- Second Xiangya Hospital of Central South UniversityUniversity, hospital or other
- Study start
- 8 Sep 2020 (actual)
- Primary completion
- Dec 2021 (estimated)
- Study completion
- Dec 2023 (estimated)
- First posted
- 12 Jul 2019 (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.
In recent years, more and more attention has been paid to diabetes self-management. Glycemic control and self-management skills of patients with type 1 diabetes (T1DM) in China are poor. Artificial intelligence (AI) and the Internet offer a new way to improve the self-management skills of patients with chronic diseases. Few studies have combined AI technology with structured education intervention of type 1 diabetes. This study is innovative in that it compares the effectiveness of smartphone app between usual care, as well as automatic and individualized app education and standardized app education to explore whether the individualized treatment advocated by the latest guideline will bring any additional benefit to T1DM patients. The ultimate goal is to provide an effective and convenient approach for glycemic control of type 1 diabetes and reduce related disease burden in China.
Detailed description
This is a single-blinded, 1:1 paralleled group cluster randomized controlled trial (RCT). The intervention will last for 24 weeks. The laboratory staff who test the HbA1c level, the outcome assessor who collects the blood glucose data, and the statisticians will be blinded to the treatment allocation.
Sample size estimation: We propose to enroll 138 patients with type 1 diabetes (T1DM) by considering withdrawals, 69 in the smartphone app groups and 69 in the routine care group. Sample size estimation is based on hypothesized changes in the primary outcome HbA1c.
In order to ensure high quality data, two staff are responsible for the input of original data into the database to check and confirm the accuracy. When the data entered by two staff independently, the auxiliary staff decides which data to use.
Data analysis will be conducted under the intention-to-treat principle by including all the randomized patients in the data analysis. Missing data will be filled in with multiple imputation method. Any substantial difference in baseline characteristics will be adjusted with mixed-model regression analysis. Sensitivity analysis will be conducted by using per-protocol data by excluding those patients who drop out of the RCT.
Study design
- Primary purpose
- Treatment
- Allocation
- Randomised
- Intervention model
- Parallel groups
- Masking
- Single blind (outcomes assessor)
- Number of arms
- 2
| Arm | Type | Receives |
|---|---|---|
| Automated, Individualized Education | Experimental | Behavioral: Automated structured education intervention based on an app and artificial intelligenceSubjects will be given instructions to install the patient-end App, which includes the following functions: diabetes education, patient-doctor communication, diabetes diary, peer support, reminder for blood sugar test and related abnormal results. They receive push notifications that provides recommended education materials which meet the needs of the patient by considering his/her baseline diabetes-related knowledge. |
| Routine care | No intervention | –Subjects only receive the education provided by health-care professionals in the outpatient department |
Who may qualify
- Ages
- 18 to 50 years
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult
Key inclusion criteria (7 listed)
- Individuals diagnosed with Type 1 Diabetes according to the 1999 World Health Organization report
- Insulin dependence from disease onset
- Aged 18-50 years
- With a disease duration over 6 months
- With a HbA1c level over 7%
Key exclusion criteria (6 listed)
- Age below 18 years or above 50 years
- Being pregnant
- With mental disorders
- Have any other condition or disease that may hamper from compliance with the protocol or complication of the trial
- Already using a smartphone app for managing diabetes
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 |
|---|---|---|
| Automated structured education intervention based on an app and artificial intelligenceIn the 24-week intervention period, the experimental group receives automated push notifications supported by artificial intelligent algorithm. | Behavioural | Automated, Individualized Education |
Primary outcome
changes in serum hemoglobin A1c level
Time frame: from baseline to week 12, 24
A1c reflects the average blood glucose level in the past 2-3 months.
18 secondary outcomes
changes in Time in range (TIR)
Time frame: from baseline to week 12, 24
Chinese version of Diabetes Quality of Life scale
Time frame: from baseline to week 12, 24
Diabetes Self-Management Scale
Time frame: from baseline to week 12, 24
Chinese version of Diabetes Self-Care Activities
Time frame: from baseline to week 12, 24
Diabetes Empowerment Scale-Short Form
Time frame: from baseline to week 12, 24
State-Trait Anxiety Inventory (STAI)
Time frame: from baseline to week 12, 24
Beck's Depression Inventory (BDI)
Time frame: from baseline to week 12, 24
Fasting blood glucose
Time frame: from baseline to week 12, 24
Systolic blood pressure
Time frame: from baseline to week 12, 24
Diastolic blood pressure
Time frame: from baseline to week 12, 24
Total cholesterol
Time frame: from baseline to week 12, 24
High-density lipoprotein (HDL) cholesterol
Time frame: from baseline to week 12, 24
Low-density lipoprotein (LDL) cholesterol
Time frame: from baseline to week 12, 24
Triglycerides
Time frame: from baseline to week 12, 24
Height in meters
Time frame: from baseline to week 12, 24
Weight in kilograms
Time frame: from baseline to week 12, 24
Patients engagement with the app
Time frame: automatically collected by the app from baseline to week 24
Adverse events
Time frame: every 4 weeks from baseline to week 24
Results and safety
Results are not available in the source record.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 16 Sep 2020.
- Derived from this study: PubMed 33225982Huang F, Wu X, Xie Y, Liu F, Li J, Li X, Zhou Z. An automated structured education intervention based on a smartphone app in Chinese patients with type 1 diabetes: a protocol for a single-blinded randomized controlled trial. Trials. 2020 Nov 23;21(1):944. doi: 10.1186/s13063-020-04835-9.
- Individual participant dataSharing planned: No
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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. This study is not recruiting at the moment.
Xia Li, MD/PHD principal investigator
Central South University
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
A study testing Automated structured education intervention based on an app and artificial intelligence in people with Type 1 Diabetes, run by Second Xiangya Hospital of Central South University 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 7 inclusion and 6 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: status not confirmed, as of the sponsor's last update on 16 Sep 2020. 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?
Results are not available in the source record.
How can a doctor refer a patient or contact the research team?
Contact Xia Li, MD/PHD (+86 17373199692, lixia2014@vip.163.com), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
changes in serum hemoglobin A1c level (time frame: from baseline to week 12, 24). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
On the ClinicalTrials.gov record for NCT04016987, which also lists 1 linked publication.
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 16 Sep 2020; AzTrials last refreshed its copy on 31 Oct 2026.