Web/Smartphone-based Lifestyle Coaching Program in Pregnant Women With Gestational Diabetes

Study Overview
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Brief Summary
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Gestational diabetes mellitus (GDM) affects one fifth of Singaporean pregnancies and can result in short and long term complications for mother and child. Mobile applications are effective in improving diabetes care and weight related behaviors through improved self-management. A multidisciplinary healthcare team from National University Hospital, Singapore has worked with Jana Care to develop the Habits-GDM smartphone app, a lifestyle coaching program specific for gestational diabetes. It consists of interactive lessons to provide patient education, diet, activity and weight tracking tools, messaging platform for coaching and motivating patients towards healthy behavior beneficial for gestational diabetes. It interfaces with the Aina device, a novel hardware sensor that plugs into any smartphone and can be used for glucose monitoring. This study aims to test the effectiveness of this app in preventing excessive weight gain in pregnancy among patients with gestational diabetes.

Detailed Description
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Gestational diabetes mellitus (GDM) is defined as glucose intolerance of any degree with onset or first recognition during pregnancy. In Singapore, 20-30% of pregnant women are affected by GDM. If poorly controlled, GDM is associated with various maternal and perinatal morbidities such as increased cesarean deliveries, preeclampsia, preterm labour, macrosomia, neonatal hypoglycemia etc. It is well recognized now that GDM is also associated with long-term metabolic complications in mothers and offspring. Women with a history of GDM have increased risk of GDM in subsequent pregnancies, and at high risk of developing Type 2 diabetes after pregnancy. Infants born to mothers with GDM are also at increased risk of developing obesity and diabetes in later life. An increasing number of studies, including studies in Singapore, suggest that screening and management of GDM can be cost-effective, although these results are highly dependent on intervention efficacy. In Singapore, individuals with GDM are first advised to adopt diet modification, and if glycemic control is not on target despite diet control, insulin therapy is the next line of treatment. In all cases, patients need to perform self-monitoring of blood glucose (SMBG) to guide treatment decisions. These strategies aim to reduce the risks maternal and perinatal complications. In addition to that, preventing excessive gestational weight gain (GWG) is another important goal in women with GDM. This is because excessive GWG is not only associated with higher risks of delivering a large for gestational age infant, but is also the strongest risk factor for postpartum weight retention, and an important predictor for future development of Type 2 diabetes. Lifestyle intervention programs have been shown to be effective in reducing GWG in pregnant women. One thing in common among diet modification, SMBG and achieving optimum GWG is that they involve self-management, and hence require a certain degree of self-efficacy in women with GDM. To achieve this in the National University Hospital (NUH), patients are referred to a gestational diabetes clinic for education. At this time, if the patient's plasma glucose at 0 minute and/or 120 minutes of a 75g oral glucose tolerance test (OGTT) is <7.0 mmol/L and <11.1 mmol/L respectively, this is conducted in a group teaching session lasting 1 - 1.5 hours, with 4 - 6 patients per group, led by a diabetes nurse educator and a dietitian. If the patient's plasma glucose at 0 minutes and/or 120 minutes of a 75g OGTT is ≥7.0 and ≥11.1 mmol/L respectively, this is conducted in an individual session lasting 1 hour with a diabetes nurse educator and a dietitian. Patients are initiated on capillary glucose monitoring, typically 7 times a day, 2-3 days in a week. Subsequently, their care is provided by their obstetrician until such time as the obstetrician feels that insulin is required, in which case they are often referred back to the endocrinology service for the initiation and management of insulin therapy. Capillary glucose monitoring is carried out using a glucometer that is purchased by the patient, and the patient duly records blood glucose on a paper record which will be shown to her obstetrician at the clinic appointments every 2 - 4 weeks. In addition, weight is generally monitored at the clinic visit. Advice on diet and lifestyle modification is provided by the obstetrician based on the results of capillary glucose monitoring at the clinic visit. In between appointments, there is limited interaction between healthcare providers unless the patient identifies a problem and contacts the provider. This arrangement has some limitations. Firstly, it has been demonstrated that spacing learning activities over a period of time improves encoding and long term retention of information. As such, the current method of providing all the education that a patient needs in a single session is less likely to be optimal for retention of information. Secondly, the collection of information (through capillary glucose monitoring) is often separated from any feedback from health care providers by days or weeks. In general, the lifestyle activities (whether diet or physical activities) which generate any abnormal blood glucose results occur in close proximity to the glucose readings (often hours before rather than weeks). By the time feedback is received, the patient often does not recall the events that generated the abnormal readings. More importantly, it does not provide any meaningful feedback to the patient that allows modification of the risk of an episode of hyperglycemia. In fact, this generates a significant amount of distress for the patient. It has been shown that the distress perceived in response to a stressor is much greater when the person experiencing the stressor does not have a way to control the occurrence of the stressor. In this context, the lack of timely feedback that is actionable related to blood glucose or weight, results in significant distress on the part of patients and results in a failure to adhere to efforts to monitor or control blood glucose. In a recent mixed-methods feasibility study to assess acceptability of mobile-application based support tool for women with GDM in NUH, most reported significant stress from the burden of management and desire for supporting tools that would aid control of blood glucose as an adjunct to self-monitoring. It is the investigators' hypothesis that by providing education that is spaced out over 1-2 weeks and providing feedback that is timely and actionable to the patient, it will improve adherence to lifestyle modification, reduce patient distress and improve clinical outcomes for women with GDM. Singapore has among the highest smartphone use in the world, with a smartphone adoption rate of 88%. Such widespread adoption of mobile phones and smartphone provides a promising opportunity to improve diabetes care and self-management, and to intervene on weight-related behaviors in new and exciting ways. There is emerging evidence that mobile technologies improve outcomes in patients with diabetes in the short term. For these reasons, the investigators have developed a mobile application to aid in the management of GDM. This is carried out with a company called Jana Care. Jana Care has developed the Habits Program (http://www.habitsprogram.com), a lifestyle coaching program which is available on Apple App Store and Google Play, two of the most commonly used smartphone app platforms. This was developed based on the Diabetes Prevention Program and Look-AHEAD Trial. It targets behavioral change by providing a personalized diabetes management program which consists of 12 interactive video lessons, diet, physical activity and weight tracking tools, interactive messaging platform with the lifestyle coaches, and daily short messaging tips. It interfaces with the Aina device, a novel hardware sensor that plugs into any smartphone and can be used to measure blood glucose. The glucose readings measured are automatically transferred to the Habits Program application. It is able to generate weekly reports for patients to assess their progress. In 2013, a pilot study was conducted by Madras Diabetes Research Foundation & Dr. Mohan's Diabetes Specialties Center, World Health Organization Collaborating Center for Non-communicable Diseases, International Diabetes Federation Center for Education, Chennai, in collaboration with Jana Care, to look at the effect of the Habits Program on changes in weight, caloric intake and physical activity in 64 overweight adults at high-risk of developing diabetes, over a period of 16 weeks. The participants achieved moderate weight loss of 4.2%, up to a maximum of 11kg. Average daily calorie and fat intake decreased by 28% and 44% respectively, while daily physical activity increased from 3438 steps (week 1) to 8459 steps (week 16) (p<0.05). Statistics collected by Jana Care from commercial deployment with approximately 13,000 individuals also showed self-reported weight loss of 4.3% and physical activity improvement of 26% at 12 weeks. Another randomized-control trial to assess the effectiveness of the program is currently underway in India, funded by the Department of Biotechnology, Government of India, in collaboration with Madras Diabetes Research Foundation, Chennai and All India Institute of Medical Sciences (AIIMS), Delhi. The Habits Program, however, is not specifically designed for the management of GDM. Working with the Department of Obstetrics and Gynecology we have developed a workflow to manage patients with GDM by optimizing blood glucose control through lifestyle modification and achieving optimal GWG. We have worked with Jana Care to develop 'Habits-GDM' - an app modified from the Habits Program which is designed specifically to support this workflow, which takes into account the nutritional requirements and limitations on exercise during pregnancy, and the need to prevent excessive weight gain (as opposed to weight loss in the original Habits Program). The program has been customized for use in Singapore including translation (with modification of messaging) and a Singapore food database. The investigators hypothesize that the use of a web/smartphone-based coaching program specific for the management of GDM can improve clinical outcomes among women with GDM. The investigators propose to conduct a randomised clinical trial to study the efficacy of the Habits-GDM program in clinical practice in Singapore. The primary outcome would be the percentage of patients who have excessive gestational weight gain (EGWG) according to the 2009 US Institute of Medicine (IOM) guidelines. GDM provides an ideal clinical scenario for the use of smartphone technologies to improve self-efficacy and clinical outcomes. In Singapore, women of child bearing age well versed with using smartphone apps, these individuals are generally highly motivated, engaged to improve their own health and well-being of the fetus. In a preliminary studies, this seems to be an acceptable and preferred mode of providing information and care. The most popular option for obtaining support for management would be a web-based or smartphone app-based resource, with 58.8% of the participants rated it as their most preferred choice. More traditional source of information such as individual counselling, group teaching or printed education materials were less preferred. Furthermore, this phase of life and intervention period is short-lived and lasts a further 5-6 months from the time of diagnosis of GDM and therefore avoids the potential problem of technology fatigue of a largely lifestyle modification intervention. Despite pregnancy being a precious window of opportunity to bring about lasting beneficial for patients and their offspring, and smartphone-based resources being the preferred source of information by women with GDM, there are very few smartphone apps that are designed specifically to support self-management of GDM. Moreover, there is a need for such apps to be customized to the local context in terms of language, nutritional habits and food sources; and integrated to a reliable degree with existing healthcare services, clinical workflow and setup. To the investigators' knowledge, there are no such apps that fulfil these characteristics and features that are currently available in Singapore and in this region, and globally there are only two other similar trials among the GDM population which is being carried out - one in Norway and another in Ireland. This study will result in a unique clinical application for GDM that integrates lifestyle coaching with glucose monitoring and can be used to treat GDM with minimal manpower commitment. The improved clinical outcomes are not only relevant to the current pregnancy but also have significant impact on the future metabolic health of both mothers and offspring throughout later life.

Official Title
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Effects of a Web/Smartphone-based Lifestyle Coaching Program on Gestational Weight Gain in Pregnant Women With Gestational Diabetes

Conditions
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Weight Gain, Gestational Diabetes, Pregnancy Complications

Intervention / Treatment
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* Behavioral: Habits-GDM mobile app


Participation Criteria
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Eligibility Criteria
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Inclusion Criteria: Ability to provide informed consent. Women aged 21 years and older. Singleton pregnancy. GDM diagnosed between 12 to 30 weeks of gestation, based on the 2013 World Health Organization (WHO) criteria, i.e. either of the following: fasting plasma glucose ≥5.1 mmol/L, 60-minute plasma glucose ≥10.0 mmol/L, 120-minute plasma glucose ≥8.5 mmol/L, during a 75g oral glucose tolerance test (OGTT). Possesses a smartphone and ability to navigate a smartphone app. Proficient in English language. Plan to deliver the baby in National University Hospital. Exclusion Criteria: Multiple pregnancy. Pre-existing diabetes (type 1 diabetes, type 2 diabetes, or other specific types of diabetes) diagnosed prior to current pregnancy. GDM diagnosed before 12 weeks of gestation. No weight available in first trimester (at or before 12 weeks gestation) of the pregnancy. Need for insulin therapy from the start of diagnosis of GDM, as determined by the primary clinician. Heart failure. Chronic kidney disease Feeding and eating disorders. History of bariatric surgery. Long-term systemic corticosteroids use. Impaired mobility. Concomitant participation in another clinical study (i.e. Phase I-III clinical studies) with investigational medicinal product(s).

Ages Eligible for Study
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Minimum Age: 21 Years

Sexes Eligible for Study
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Female

Accepts Healthy Volunteers
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No

Study Plan
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How is the study designed?
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Design Details

Primary Purpose: Supportive Care
Allocation: Randomized
Intervention Model: Parallel Assignment
Interventional Model Description: This is a prospective, randomised, controlled, parallel-group, single centre study. Study subjects will be randomised into either the intervention or the control arm in a 1:1 ratio. The randomisation will be stratified by ethnicity (Chinese or non-Chinese) and pre-pregnancy BMI (BMI of <25kg/m2 or ≥25kg/m2), and will be performed using computer-generated randomisation.
Masking: None (Open Label)


Arms and Interventions

| Participant Group/Arm | Intervention/Treatment |
| --- | --- |
| Experimental: Intervention<br>Patients in the intervention arm will receive standard medical care and in addition to that, be given the Aina or Aina Mini device for self-monitoring of blood glucose (SMBG), the Habits-GDM mobile app, and a weighing scale. | Behavioral: Habits-GDM mobile app<br>* The intervention is a self-administered mobile app designed for GDM. It targets behavioural change by providing personalised GDM management program which consists of three main elements: lessons, tracking and coaching/feedback. Lessons contains 12 interactive modules which provide patient education on GDM. Each lesson will take approximately 10-20 minutes. Information on SMBG (linked to the Aina or Aina Mini device), weight (linked to the Bluetooth weighing scale), physical activity (physical activity tracking function in the app), and food (equipped with common local food using the Singapore food database) can be tracked and displayed visually. An interactive messaging platform is used for coaching. Generic and customised automated messages are sent from a virtual lifestyle coach to encourage and motivate patients towards healthy behaviour beneficial for GDM.<br>|
| No Intervention: Control<br>Patients in the control arm will receive standard medical care and only be given the Aina or Aina Mini device for SMBG. Standard medical care involves one session of face-to-face education by a diabetes nurse educator and a dietician. Patients are initiated on capillary glucose monitoring. Subsequently, standard clinical care is provided by their obstetrician. Participation in this study will not increase the frequency of clinic visits. The frequency of SMBG will be as clinically indicated and not increased as a result of participation in this study. Should the obstetrician feels that insulin is required, it will be initiated and if necessary the patient will be referred to the endocrinology service for management of insulin therapy. In some patients, the clinician may decide to prescribe metformin. | |

What is the study measuring?
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Primary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| Percentage of patients who have excessive gestational weight gain (EGWG) | Percentage of patients who have EGWG is the proportion of subjects whose gestational weight gain (GWG) exceed the upper range of recommended weight gain for corresponding pre-pregnancy BMI (in this study, this is calculated using the first recorded weight and height in pregnancy at or before 12 weeks gestation) according to the 2009 IOM guidelines. GWG is calculated by subtracting the first recorded weight (in kilograms) in pregnancy at or before 12 weeks gestation from the most recent weight measurement taken in the hospital (either in the clinic or in the ward) prior to delivery. Pre-pregnancy BMI is calculated using the first recorded weight (in kilograms) and height (in meters) in pregnancy at or before 12 weeks gestation. | during the pregnancy until delivery | 

Secondary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| Absolute GWG stratified by whether or not the subject has EGWG for the gestational weeks at recruitment | Absolute GWG stratified by whether or not the subject has exceeded the optimal GWG for the gestational weeks at recruitment (based on the 2009 IOM guidelines). | during the pregnancy until delivery | 
| Absolute gestational weight gain | Absolute gestational weight gain is calculated by subtracting the first recorded weight (in kilograms) in pregnancy at or before 12 weeks gestation from the most recent weight measurement taken in the hospital (either in the clinic or in the ward) prior to delivery. | during the pregnancy until delivery | 
| Percentage of patients who have EGWG according to the 2009 US IOM guidelines stratified by whether or not the subject has EGWG for the gestational weeks at recruitment | Percentage of patients who have EGWG according to the 2009 US IOM guidelines stratified by whether or not the subject has exceeded the optimal GWG for the gestational weeks at recruitment | during the pregnancy until delivery | 
| Adherence to SMBG | Numbers of SMBG performed | From recruitment until delivery | 
| Average readings of self-monitored blood glucose | Average readings of self-monitored blood glucose | From recruitment until delivery | 
| Proportion of glucose readings above glycemic targets | Glycemic targets are </=5.5 mmol/L premeals, </= 6.6 mmol/L at 2 hours post meals | From recruitment until delivery | 
| Proportion of subjects who progress to needing metformin and/or insulin therapy | Needing metformin and/or insulin therapy in addition to diet modification | From recruitment until delivery | 
| Mode of delivery | Vaginal delivery, assisted delivery, cesarean section | At delivery | 
| Hypertensive disorders in pregnancy | Pregnancy induced hypertension, preeclampsia, eclampsia | During the pregnancy until delivery | 
| Depression score | Edinburgh Postnatal Depression Scale | Between 35-37 weeks of gestation | 
| Anxiety score | State-Trait Anxiety Inventory | Between 35-37 weeks of gestation | 
| Premature delivery | Delivery before 37 weeks of gestation | At delivery | 
| Apgar score | Apgar score at 1 and 5 minutes after birth | At birth | 
| Birth weight | Weight of the baby at birth | At birth | 
| Shoulder dystocia | Shoulder dystocia at birth | At birth | 
| Birth trauma | Birth trauma at birth | At birth | 
| Neonatal hypoglycemia | Capillary blood glucose level of <2.6mmol/L | First 24 hours from birth | 
| Respiratory distress needing intubation | Respiratory distress needing intubation | At birth | 
| Neonatal intensive care unit admission | Neonatal intensive care unit admission | First 24 hours from birth | 

 Terms related to the study
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Keywords Provided by Centre Hospitalier Valida
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Gestational Diabetes, RCT, Lifestyle coaching program, Smartphone app, Gestational weight gain