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The goal of this pragmatic randomized controlled trial is to evaluate the effectiveness of an AI-enabled mobile health management application ("Better Pregnancy" app), grounded in the Theory of Planned Behavior, in preventing gestational diabetes mellitus (GDM) among pregnant women at high risk of GDM, and to assess its impact on maternal and infant health outcomes.
Study Population: Eligible participants are pregnant women aged 18-49 years, with a singleton pregnancy, gestational age <12 weeks at enrollment, and at least one GDM risk factor (age ≥35 years, pre-pregnancy BMI ≥24 kg/m², family history of diabetes, previous history of GDM, prior delivery of a macrosomic infant [birth weight ≥4000 g], or polycystic ovary syndrome). Participants must have no heart, liver, or kidney diseases, use an Android smartphone, and provide written informed consent.
The main questions it aims to answer are:
Can the AI-driven mobile lifestyle intervention reduce the incidence of GDM in high-risk pregnant women?
Does the intervention improve lifestyle behaviors (diet, physical activity, sleep) and glycemic control (measured by continuous glucose monitoring) in participants?
What is the adherence, acceptability, and cost-effectiveness of this intervention in real-world clinical settings?
Comparison: Researchers will compare two groups of pregnant women: the intervention group (receiving the AI-enabled "Better Pregnancy" app plus routine antenatal care) and the control group (receiving routine antenatal care alone).
Participants will:
Enroll in the first trimester (<12 weeks of gestation) and complete a baseline lifestyle and health status questionnaire
In the intervention group: watch 7 cognitive-attitudinal videos within the first week, then complete 12 weeks of AI-driven personalized intervention (daily check-ins, receiving tailored recommendations on diet, physical activity, sleep, etc.)
During the intervention period, participants in the intervention group will wear a continuous glucose monitoring device for 7 days to assess the impact of the intervention on glycemic fluctuations
Complete the first follow-up lifestyle and health status assessment after the intervention (approximately in the second trimester)
Undergo an oral glucose tolerance test during the second trimester (24-28 weeks)
Complete the second follow-up lifestyle and health status assessment in the third trimester (≥28 weeks)
Complete the third follow-up lifestyle and health status assessment at 42 days postpartum, along with collection of delivery outcomes and infant health information
A subset of participants may voluntarily provide blood and stool samples for mechanistic studies
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| Intervention Group: AI-Enabled Mobile Health Management App Plus Routine Antenatal Care | Experimental | Participants receive a 12-week AI-powered intervention via the "PregSelfCare" app plus routine antenatal care. The intervention includes: (1) watching 7 theory-based videos and completing an attitude questionnaire in week 1; (2) daily check-in (mood, water, fruit, bowel movements, sunlight, weight) and receiving AI-driven personalized recommendations (diet photo feedback, step goals, sleep advice, emotion-relief videos, supplement reminders) during weeks 1-12, with content dynamically adjusted based on baseline lifestyle assessment and adherence; (3) wearing a continuous glucose monitor for 7 days; (4) completing a satisfaction questionnaire after the intervention (week 12), with a subset invited for semi-structured interviews. |
|
| Control Group: Routine Antenatal Care Alone | No Intervention | Participants in the control group receive routine antenatal care and standardized pregnancy health education (including verbal guidance and conventional brochures) provided by their hospitals. They do not have access to the "Better Pregnancy" app and receive no additional mobile health intervention. Data collection, including questionnaires and oral glucose tolerance tests, is completed at the same time points as the intervention group. After study completion, control participants will be offered access to the app. |
| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| Multi-component lifestyle intervention | Behavioral | Participants receive a 12-week AI-powered intervention via the "PregSelfCare" app plus routine antenatal care. The intervention includes: (1) watching 7 theory-based videos and completing an attitude questionnaire in week 1; (2) daily check-ins (mood, water, fruit, bowel movements, sunlight, weight) and receiving AI-driven personalized recommendations (diet photo feedback, step goals, sleep advice, emotion-relief videos, supplement reminders) during weeks 1-12, with content dynamically adjusted based on baseline lifestyle assessment and adherence; (3) wearing a continuous glucose monitor for 7 days; (4) completing a satisfaction questionnaire after the intervention (week 12), with a subset invited for semi-structured interviews. |
| Measure | Description | Time Frame |
|---|---|---|
| The prevalence of gestational diabetes mellitus | The diagnostic criteria for Potential simultaneous submissions were found in: International Journal of Nursing Sciences will follow the International Association of Diabetes and Pregnancy Study Groups (IADPSG) guidelines. Glucose tolerance tests will be conducted at 24 weeks of gestation (calculated from the last menstrual period). According to the diagnostic criteria, reference values for fasting, one-hour, and two-hour blood glucose levels are 5.1 mmol/L, 10.0 mmol/L, and 8.5 mmol/L, respectively. A diagnosis of gestational diabetes mellitus is confirmed if any of these values meet or exceed the specified thresholds | 24 Weeks |
| Measure | Description | Time Frame |
|---|---|---|
| Adverse pregnancy and adverse birth outcomes | Maternal pregnancy outcomes and general neonatal outcomes were collected via self administered scales | 42 days postpartum |
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Inclusion Criteria:
Pregnant women aged ≥18 years
Singleton pregnancy
Gestational age <13+6 weeks at enrollment
At least one of the following GDM risk factors:
Polycystic ovary syndrome
Use of an Android smartphone
No severe heart, liver, or kidney diseases
Voluntary participation and signed informed consent
Exclusion Criteria:
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| Name | Role | Phone | Extension | |
|---|---|---|---|---|
| Fangbiao Tao, PhD | Contact | 13856986775 | taofangbiao@126.com | |
| Tiemei Li, PhD | Contact | 13541602092 | tiemei.li@foxmail.com |
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| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Anhui Medical University | Hefei | Anhui | 231200 | China |
| PubMed Identifier | Type | Citation | Retractions |
|---|---|---|---|
| 41135300 | Background | Duan B, Liu L, Ma C, Liu Z, Gou B, Liu W. Effects of mobile health management model on the prevention of gestational diabetes mellitus in pregnant women at risk of gestational diabetes: A randomized controlled trial. Int J Nurs Stud. 2026 Jan;173:105252. doi: 10.1016/j.ijnurstu.2025.105252. Epub 2025 Oct 16. |
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|
| ID | Term |
|---|---|
| D016640 | Diabetes, Gestational |
| ID | Term |
|---|---|
| D011248 | Pregnancy Complications |
| D005261 | Female Urogenital Diseases and Pregnancy Complications |
| D000091642 | Urogenital Diseases |
| D003920 | Diabetes Mellitus |
| D044882 | Glucose Metabolism Disorders |
| D008659 | Metabolic Diseases |
| D009750 | Nutritional and Metabolic Diseases |
| D004700 | Endocrine System Diseases |
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