Web/Smartphone-based Lifestyle Coaching Program in Pregnant Women With Gestational Diabetes
SMART-GDM
Effects of a Web/Smartphone-based Lifestyle Coaching Program on Gestational Weight Gain in Pregnant Women With Gestational Diabetes
1 other identifier
interventional
340
1 country
1
Brief Summary
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.
Trial Health
Trial Health Score
Automated assessment based on enrollment pace, timeline, and geographic reach
participants targeted
Target at P75+ for not_applicable
Started Sep 2017
1 active site
Health score is calculated from publicly available data and should be used for screening purposes only.
Trial Relationships
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Study Timeline
Key milestones and dates
First Submitted
Initial submission to the registry
August 1, 2017
CompletedFirst Posted
Study publicly available on registry
August 15, 2017
CompletedStudy Start
First participant enrolled
September 5, 2017
CompletedPrimary Completion
Last participant's last visit for primary outcome
April 26, 2019
CompletedStudy Completion
Last participant's last visit for all outcomes
May 1, 2019
CompletedMay 29, 2019
November 1, 2018
1.6 years
August 1, 2017
May 27, 2019
Conditions
Keywords
Outcome Measures
Primary Outcomes (1)
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 Outcomes (19)
Absolute GWG stratified by whether or not the subject has EGWG for the gestational weeks at recruitment
during the pregnancy until delivery
Absolute gestational weight gain
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
during the pregnancy until delivery
Adherence to SMBG
From recruitment until delivery
Average readings of self-monitored blood glucose
From recruitment until delivery
- +14 more secondary outcomes
Study Arms (2)
Intervention
EXPERIMENTALPatients 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.
Control
NO INTERVENTIONPatients 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.
Interventions
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.
Eligibility Criteria
You may qualify if:
- 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.
You may not qualify if:
- 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).
Contact the study team to confirm eligibility.
Sponsors & Collaborators
- National University Hospital, Singaporelead
- Jana Carecollaborator
Study Sites (1)
National University Hospital
Singapore, 119228, Singapore
Related Publications (30)
American Diabetes Association. Diagnosis and classification of diabetes mellitus. Diabetes Care. 2014 Jan;37 Suppl 1:S81-90. doi: 10.2337/dc14-S081. No abstract available.
PMID: 24357215BACKGROUNDChong YS, Cai S, Lin H, Soh SE, Lee YS, Leow MK, Chan YH, Chen L, Holbrook JD, Tan KH, Rajadurai VS, Yeo GS, Kramer MS, Saw SM, Gluckman PD, Godfrey KM, Kwek K; GUSTO study group. Ethnic differences translate to inadequacy of high-risk screening for gestational diabetes mellitus in an Asian population: a cohort study. BMC Pregnancy Childbirth. 2014 Oct 2;14:345. doi: 10.1186/1471-2393-14-345.
PMID: 25273851BACKGROUNDYew TW, Khoo CM, Thai AC, Kale AS, Yong EL, Tai ES. The Prevalence of Gestational Diabetes Mellitus Among Asian Females is Lower Using the New 2013 World Health Organization Diagnostic Criteria. Endocr Pract. 2014 Oct;20(10):1064-9. doi: 10.4158/EP14028.OR.
PMID: 24936548BACKGROUNDBellamy L, Casas JP, Hingorani AD, Williams D. Type 2 diabetes mellitus after gestational diabetes: a systematic review and meta-analysis. Lancet. 2009 May 23;373(9677):1773-9. doi: 10.1016/S0140-6736(09)60731-5.
PMID: 19465232BACKGROUNDKim C, Newton KM, Knopp RH. Gestational diabetes and the incidence of type 2 diabetes: a systematic review. Diabetes Care. 2002 Oct;25(10):1862-8. doi: 10.2337/diacare.25.10.1862.
PMID: 12351492BACKGROUNDSchwartz N, Nachum Z, Green MS. The prevalence of gestational diabetes mellitus recurrence--effect of ethnicity and parity: a metaanalysis. Am J Obstet Gynecol. 2015 Sep;213(3):310-7. doi: 10.1016/j.ajog.2015.03.011. Epub 2015 Mar 7.
PMID: 25757637BACKGROUNDCatalano PM, Kirwan JP, Haugel-de Mouzon S, King J. Gestational diabetes and insulin resistance: role in short- and long-term implications for mother and fetus. J Nutr. 2003 May;133(5 Suppl 2):1674S-1683S. doi: 10.1093/jn/133.5.1674S.
PMID: 12730484BACKGROUNDChen PY, Finkelstein EA, Ng MJ, Yap F, Yeo GS, Rajadurai VS, Chong YS, Gluckman PD, Saw SM, Kwek KY, Tan KH. Incremental Cost-Effectiveness Analysis of Gestational Diabetes Mellitus Screening Strategies in Singapore. Asia Pac J Public Health. 2016 Jan;28(1):15-25. doi: 10.1177/1010539515612908. Epub 2015 Oct 28.
PMID: 26512030BACKGROUNDMarseille E, Lohse N, Jiwani A, Hod M, Seshiah V, Yajnik CS, Arora GP, Balaji V, Henriksen O, Lieberman N, Chen R, Damm P, Metzger BE, Kahn JG. The cost-effectiveness of gestational diabetes screening including prevention of type 2 diabetes: application of a new model in India and Israel. J Matern Fetal Neonatal Med. 2013 May;26(8):802-10. doi: 10.3109/14767058.2013.765845. Epub 2013 Feb 14.
PMID: 23311860BACKGROUNDLohse N, Marseille E, Kahn JG. Development of a model to assess the cost-effectiveness of gestational diabetes mellitus screening and lifestyle change for the prevention of type 2 diabetes mellitus. Int J Gynaecol Obstet. 2011 Nov;115 Suppl 1:S20-5. doi: 10.1016/S0020-7292(11)60007-6.
PMID: 22099435BACKGROUNDWeile LK, Kahn JG, Marseille E, Jensen DM, Damm P, Lohse N. Global cost-effectiveness of GDM screening and management: current knowledge and future needs. Best Pract Res Clin Obstet Gynaecol. 2015 Feb;29(2):206-24. doi: 10.1016/j.bpobgyn.2014.06.009. Epub 2014 Aug 21.
PMID: 25225056BACKGROUNDGoh SY, Ang SB, Bee YM, Chen YT, Gardner DS, Ho ET, Adaikan K, Lee YC, Lee CH, Lim FS, Lim HB, Lim SC, Seow J, Soh AW, Sum CF, Tai ES, Thai AC, Wong TY, Yap F. Ministry of Health Clinical Practice Guidelines: Diabetes Mellitus. Singapore Med J. 2014 Jun;55(6):334-47. doi: 10.11622/smedj.2014079.
PMID: 25017409BACKGROUNDCarreno CA, Clifton RG, Hauth JC, Myatt L, Roberts JM, Spong CY, Varner MW, Thorp JM Jr, Mercer BM, Peaceman AM, Ramin SM, Carpenter MW, Sciscione A, Tolosa JE, Saade GR, Sorokin Y; Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD) Maternal-Fetal Medicine Units (MFMU) Network. Excessive early gestational weight gain and risk of gestational diabetes mellitus in nulliparous women. Obstet Gynecol. 2012 Jun;119(6):1227-33. doi: 10.1097/AOG.0b013e318256cf1a. Erratum In: Obstet Gynecol. 2012 Sep;120(3):710. Saade, George R [added].
PMID: 22617588BACKGROUNDKim SY, Sharma AJ, Sappenfield W, Wilson HG, Salihu HM. Association of maternal body mass index, excessive weight gain, and gestational diabetes mellitus with large-for-gestational-age births. Obstet Gynecol. 2014 Apr;123(4):737-44. doi: 10.1097/AOG.0000000000000177.
PMID: 24785599BACKGROUNDMargerison Zilko CE, Rehkopf D, Abrams B. Association of maternal gestational weight gain with short- and long-term maternal and child health outcomes. Am J Obstet Gynecol. 2010 Jun;202(6):574.e1-8. doi: 10.1016/j.ajog.2009.12.007. Epub 2010 Feb 4.
PMID: 20132923BACKGROUNDMcClure CK, Catov JM, Ness R, Bodnar LM. Associations between gestational weight gain and BMI, abdominal adiposity, and traditional measures of cardiometabolic risk in mothers 8 y postpartum. Am J Clin Nutr. 2013 Nov;98(5):1218-25. doi: 10.3945/ajcn.112.055772. Epub 2013 Sep 18.
PMID: 24047920BACKGROUNDEades CE, Styles M, Leese GP, Cheyne H, Evans JM. Progression from gestational diabetes to type 2 diabetes in one region of Scotland: an observational follow-up study. BMC Pregnancy Childbirth. 2015 Feb 3;15:11. doi: 10.1186/s12884-015-0457-8.
PMID: 25643857BACKGROUNDBogaerts AF, Devlieger R, Nuyts E, Witters I, Gyselaers W, Van den Bergh BR. Effects of lifestyle intervention in obese pregnant women on gestational weight gain and mental health: a randomized controlled trial. Int J Obes (Lond). 2013 Jun;37(6):814-21. doi: 10.1038/ijo.2012.162. Epub 2012 Oct 2.
PMID: 23032404BACKGROUNDHui AL, Back L, Ludwig S, Gardiner P, Sevenhuysen G, Dean HJ, Sellers E, McGavock J, Morris M, Jiang D, Shen GX. Effects of lifestyle intervention on dietary intake, physical activity level, and gestational weight gain in pregnant women with different pre-pregnancy Body Mass Index in a randomized control trial. BMC Pregnancy Childbirth. 2014 Sep 24;14:331. doi: 10.1186/1471-2393-14-331.
PMID: 25248797BACKGROUNDRonnberg AK, Ostlund I, Fadl H, Gottvall T, Nilsson K. Intervention during pregnancy to reduce excessive gestational weight gain-a randomised controlled trial. BJOG. 2015 Mar;122(4):537-44. doi: 10.1111/1471-0528.13131. Epub 2014 Nov 4.
PMID: 25367823BACKGROUNDGarabedian LF, Ross-Degnan D, Wharam JF. Mobile Phone and Smartphone Technologies for Diabetes Care and Self-Management. Curr Diab Rep. 2015 Dec;15(12):109. doi: 10.1007/s11892-015-0680-8.
PMID: 26458380BACKGROUNDTufano JT, Karras BT. Mobile eHealth interventions for obesity: a timely opportunity to leverage convergence trends. J Med Internet Res. 2005 Dec 20;7(5):e58. doi: 10.2196/jmir.7.5.e58.
PMID: 16403722BACKGROUNDKnowler WC, Barrett-Connor E, Fowler SE, Hamman RF, Lachin JM, Walker EA, Nathan DM; Diabetes Prevention Program Research Group. Reduction in the incidence of type 2 diabetes with lifestyle intervention or metformin. N Engl J Med. 2002 Feb 7;346(6):393-403. doi: 10.1056/NEJMoa012512.
PMID: 11832527BACKGROUNDLook AHEAD Research Group; Wing RR, Bolin P, Brancati FL, Bray GA, Clark JM, Coday M, Crow RS, Curtis JM, Egan CM, Espeland MA, Evans M, Foreyt JP, Ghazarian S, Gregg EW, Harrison B, Hazuda HP, Hill JO, Horton ES, Hubbard VS, Jakicic JM, Jeffery RW, Johnson KC, Kahn SE, Kitabchi AE, Knowler WC, Lewis CE, Maschak-Carey BJ, Montez MG, Murillo A, Nathan DM, Patricio J, Peters A, Pi-Sunyer X, Pownall H, Reboussin D, Regensteiner JG, Rickman AD, Ryan DH, Safford M, Wadden TA, Wagenknecht LE, West DS, Williamson DF, Yanovski SZ. Cardiovascular effects of intensive lifestyle intervention in type 2 diabetes. N Engl J Med. 2013 Jul 11;369(2):145-54. doi: 10.1056/NEJMoa1212914. Epub 2013 Jun 24.
PMID: 23796131BACKGROUNDInstitute of Medicine (US) and National Research Council (US) Committee to Reexamine IOM Pregnancy Weight Guidelines; Rasmussen KM, Yaktine AL, editors. Weight Gain During Pregnancy: Reexamining the Guidelines. Washington (DC): National Academies Press (US); 2009. Available from http://www.ncbi.nlm.nih.gov/books/NBK32813/
PMID: 20669500BACKGROUNDGarnweidner-Holme LM, Borgen I, Garitano I, Noll J, Lukasse M. Designing and Developing a Mobile Smartphone Application for Women with Gestational Diabetes Mellitus Followed-Up at Diabetes Outpatient Clinics in Norway. Healthcare (Basel). 2015 May 21;3(2):310-23. doi: 10.3390/healthcare3020310.
PMID: 27417764BACKGROUNDMackillop L, Loerup L, Bartlett K, Farmer A, Gibson OJ, Hirst JE, Kenworthy Y, Kevat DA, Levy JC, Tarassenko L. Development of a real-time smartphone solution for the management of women with or at high risk of gestational diabetes. J Diabetes Sci Technol. 2014 Nov;8(6):1105-14. doi: 10.1177/1932296814542271. Epub 2014 Jul 7.
PMID: 25004915BACKGROUNDBoulos MN, Brewer AC, Karimkhani C, Buller DB, Dellavalle RP. Mobile medical and health apps: state of the art, concerns, regulatory control and certification. Online J Public Health Inform. 2014 Feb 5;5(3):229. doi: 10.5210/ojphi.v5i3.4814. eCollection 2014.
PMID: 24683442BACKGROUNDKennelly MA, Ainscough K, Lindsay K, Gibney E, Mc Carthy M, McAuliffe FM. Pregnancy, exercise and nutrition research study with smart phone app support (Pears): Study protocol of a randomized controlled trial. Contemp Clin Trials. 2016 Jan;46:92-99. doi: 10.1016/j.cct.2015.11.018. Epub 2015 Nov 25.
PMID: 26625980BACKGROUNDYew TW, Chi C, Chan SY, van Dam RM, Whitton C, Lim CS, Foong PS, Fransisca W, Teoh CL, Chen J, Ho-Lim ST, Lim SL, Ong KW, Ong PH, Tai BC, Tai ES. A Randomized Controlled Trial to Evaluate the Effects of a Smartphone Application-Based Lifestyle Coaching Program on Gestational Weight Gain, Glycemic Control, and Maternal and Neonatal Outcomes in Women With Gestational Diabetes Mellitus: The SMART-GDM Study. Diabetes Care. 2021 Feb;44(2):456-463. doi: 10.2337/dc20-1216. Epub 2020 Nov 12.
PMID: 33184151DERIVED
Related Links
MeSH Terms
Conditions
Condition Hierarchy (Ancestors)
Study Design
- Study Type
- interventional
- Phase
- not applicable
- Allocation
- RANDOMIZED
- Masking
- NONE
- Purpose
- SUPPORTIVE CARE
- Intervention Model
- PARALLEL
- Sponsor Type
- OTHER
- Responsible Party
- SPONSOR
Study Record Dates
First Submitted
August 1, 2017
First Posted
August 15, 2017
Study Start
September 5, 2017
Primary Completion
April 26, 2019
Study Completion
May 1, 2019
Last Updated
May 29, 2019
Record last verified: 2018-11
Data Sharing
- IPD Sharing
- Will not share