Electronic Monitoring Of Mom's Schedule (eMOMS™): Protocol for a feasibility randomized controlled trial to improve postpartum weight, blood sugars, and breastfeeding among high BMI women

Digital Health and Machine Learning Technologies for Blood Glucose Monitoring and Management of Gestational Diabetes

Innovations in digital health and machine learning are changing the path of clinical health and care. People from different geographical locations and cultural backgrounds can benefit from the mobility of wearable devices and smartphones to monitor their health ubiquitously. This paper focuses on reviewing the digital health and machine learning technologies used in gestational diabetes - a subtype of diabetes that occurs during pregnancy. This paper reviews sensor technologies used in blood glucose monitoring devices, digital health innovations and machine learning models for gestational diabetes monitoring and management, in clinical and commercial settings, and discusses future directions. Despite one in six mothers having gestational diabetes, digital health applications were underdeveloped, especially the techniques that can be deployed in clinical practice. There is an urgent need to (1) develop clinically interpretable machine learning methods for patients with gestational diabetes, assisting health professionals with treatment, monitoring, and risk stratification before, during and after their pregnancies; (2) adapt and develop clinically-proven devices for patient self-management of health and well-being at home settings ("virtual ward" and virtual consultation), thereby improving clinical outcomes by facilitating timely intervention; and (3) ensure innovations are affordable and sustainable for all women with different socioeconomic backgrounds and clinical resources.

Effects of online support and social media communities on gestational diabetes: A systematic review

BACKGROUND

Gestational diabetes mellitus (GDM) is a common complication in pregnancy that can lead to negative maternal and fetal outcomes. Online support interventions have been suggested as a potential tool to improve the management of GDM.

OBJECTIVE

This systematic review aimed to summarize the effectiveness of social media and online support interventions for the management of GDM.

METHODS

We conducted a thorough systematic search across Web of Science, Scopus, and PubMed, following PRISMA guidelines, and supplemented it with a manual search. Our results included both qualitative and quantitative research. We rigorously assessed quantitative studies for bias using ROBINS-I and RoB 2 tools, ensuring the reliability of our findings.

RESULTS

We incorporated a total of 22 studies, which were comprised of ten qualitative and twelve quantitative studies. Online support interventions were found to have a positive impact on promoting self-care and improving healthcare outcomes for women with GDM. Individualized diet and exercise interventions resulted in lower odds of weight gain and GDM diagnosis, while online prenatal education increased breastfeeding rates. In addition, telemedicine options reduced the need for in-person clinical visits and improved patient satisfaction.

CONCLUSIONS

Online support interventions show potential to improve outcomes in patients with GDM in this small literature review. Future research is also necessary to determine the effectiveness of different types of online interventions and identify strategies to improve engagement and the quality of the information provided through online resources.

Electronic Monitoring of Mom's Schedule (eMOMSTM): A Qualitative Study of Experiences in a Lifestyle Change Program with Lactation Support

PURPOSE

To elicit feedback from participants who completed the eMOMSTM study, a feasibility randomized controlled trial (NCT04021602), on their perceptions of program strengths and weaknesses.

STUDY DESIGN

Qualitative - Semi-structured, telephone interview guide using open-ended questions.

SETTING

Rural Great Plains state, United States.

PARTICIPANTS

Of 26 individuals who completed the eMOMSTM study, 24 consented to an interview.

METHOD

Interviews were completed between October 2020 and May 2021. Audio-recordings were transcribed verbatim and organized in Microsoft 365. Data were analyzed using an exploratory, inductive thematic analysis.

RESULTS

Participants' mean age was 27.5 (± 5.4) years and mean pre-pregnancy BMI was 29.5 kg/m2 (± 2.7). The majority (71%) were non-Hispanic White and 54% had a high school education/some college. Based on specific areas of inquiry, the following themes emerged: convenience of online program access using Facebook, importance of health coach's support and online interaction, positivity toward improving one's health, increased consciousness of health behaviors, diverse lactation educational needs, importance of educational materials on depression, and grief over the loss of birth expectations during COVID-19.

CONCLUSION

Findings suggest participants' perceived value of a lifestyle change program coupled with lactation education and support delivered using social media. Findings inform future studies to further adapt lifestyle change programs.

Electronic Monitoring Of Mom's Schedule (eMOMSTM): Recruitment of pregnant populations with elevated BMI in a feasibility randomized controlled trial

Underrepresentation of pregnant populations in randomized controlled trials of lifestyle change interventions is concerning due to high attrition and providers' limited clinical time. The purpose of this evaluative study was to assess intervention uptake of pregnant individuals enrolled in a three-arm feasibility randomized controlled trial, electronic Monitoring Of Mom's Schedule (eMOMS^TM), examining lifestyle changes and lactation support alone, and in combination. Measures included: (1) participation and completion rates, and characteristics of intervention completers versus other eligible participants; and (2) provider experiences with screening and enrolling pregnant participants. Pregnant people with a pre-pregnancy body mass index ≥ 25 and < 35 kg/m² were enrolled into the eMOMS^TM trial between September 2019 - December 2020. Of the 44 consented participants, 35 were randomized, at a participation rate of 35%, and 26 completed the intervention, resulting in a completion rate of 74%. Intervention completers were slightly older and entered the study earlier in pregnancy compared to non-completers. Completers were more likely to be first-time mothers, resided in urban areas, had higher educational attainment, and were slightly more racially and ethnically diverse. A majority of providers reported willingness to participate, believed the study aligned with their organization's mission, and were satisfied with using iPads for screening. Lessons learned to guide recruitment success include use of: (1) designated research staff in combination with physician support; and (2) user-friendly technology to help mitigate time burden on physicians and their staff. Future work should focus on successful strategies to recruit/retain pregnant populations in clinical trials.

Simulation of 3D Body Shapes for Pregnant and Postpartum Women

Several studies have reported that pre-pregnant women’s body mass index (BMI) affects women’s weight gain with complications during pregnancy and the postpartum weight retention. It is important to control the BMI before, during and after pregnancy. Our objectives are to develop a technique that can compute and visualize 3D body shapes of women during pregnancy and postpartum in various gestational ages, BMI, and postpartum durations. Body changes data from 98 pregnant and 83 postpartum women were collected, tracked for six months, and analyzed to create 3D model shapes. This study allows users to simulate their 3D body shapes in real-time and online, based on weight, height, and gestational age, using multiple linear regression and morphing techniques. To evaluate the results, precision tests were performed on simulated 3D pregnant and postpartum women’s shapes. Additionally, a satisfaction test on the application was conducted on new 149 mothers. The accuracy of the simulation was tested on 75 pregnant and 74 postpartum volunteers in terms of relationships between statistical calculation, simulated 3D models and actual tape measurement of chest, waist, hip, and inseam. Our results can predict accurately the body proportions of pregnant and postpartum women.

Interventions to support women with overweight or obesity or gestational diabetes mellitus to initiate and continue breastfeeding: Systematic review and meta-analysis

Exclusive breastfeeding is recommended for the first 6 months of life and benefits both mother and child. Women with overweight/obesity or gestational diabetes are at risk for poor breastfeeding outcomes. This review evaluates the efficacy of breastfeeding interventions in these at-risk populations. The review followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses statement. Five databases were searched for interventions from inception to May 2020. Nineteen trials including 2,740 participants, 226 of which were dyads, were included. Intervention increased any breastfeeding at ≥6 months (OR 1.43, 95% CI [1.05-1.95]), and women in the intervention group were 90% more likely to exclusively breastfeed at 1-2 weeks (OR 1.9, 95% CI [1.17-3.09]) and more than twice as likely to exclusively breastfeed at 4-6 weeks (OR 2.23, 95% CI [1.27-3.90]) within the sensitivity analysis. These findings support breastfeeding interventions improving exclusive early postpartum breastfeeding and any breastfeeding from 6 months in women with gestational diabetes or obesity/overweight. Further randomized controlled trials with harmonized breastfeeding outcome reporting are needed to confirm efficacy.

Behavioural interventions delivered through interactive social media for health behaviour change, health outcomes, and health equity in the adult population

BACKGROUND

Social networking platforms offer a wide reach for public health interventions allowing communication with broad audiences using tools that are generally free and straightforward to use and may be combined with other components, such as public health policies. We define interactive social media as activities, practices, or behaviours among communities of people who have gathered online to interactively share information, knowledge, and opinions.

OBJECTIVES

We aimed to assess the effectiveness of interactive social media interventions, in which adults are able to communicate directly with each other, on changing health behaviours, body functions, psychological health, well-being, and adverse effects. Our secondary objective was to assess the effects of these interventions on the health of populations who experience health inequity as defined by PROGRESS-Plus. We assessed whether there is evidence about PROGRESS-Plus populations being included in studies and whether results are analysed across any of these characteristics.

SEARCH METHODS

We searched CENTRAL, CINAHL, Embase, MEDLINE (including trial registries) and PsycINFO. We used Google, Web of Science, and relevant web sites to identify additional studies and searched reference lists of included studies. We searched for published and unpublished studies from 2001 until June 1, 2020. We did not limit results by language.

SELECTION CRITERIA

We included randomised controlled trials (RCTs), controlled before-and-after (CBAs) and interrupted time series studies (ITSs). We included studies in which the intervention website, app, or social media platform described a goal of changing a health behaviour, or included a behaviour change technique. The social media intervention had to be delivered to adults via a commonly-used social media platform or one that mimicked a commonly-used platform. We included studies comparing an interactive social media intervention alone or as a component of a multi-component intervention with either a non-interactive social media control or an active but less-interactive social media comparator (e.g. a moderated versus an unmoderated discussion group). Our main outcomes were health behaviours (e.g. physical activity), body function outcomes (e.g. blood glucose), psychological health outcomes (e.g. depression), well-being, and adverse events. Our secondary outcomes were process outcomes important for behaviour change and included knowledge, attitudes, intention and motivation, perceived susceptibility, self-efficacy, and social support.

DATA COLLECTION AND ANALYSIS

We used a pre-tested data extraction form and collected data independently, in duplicate. Because we aimed to assess broad outcomes, we extracted only one outcome per main and secondary outcome categories prioritised by those that were the primary outcome as reported by the study authors, used in a sample size calculation, and patient-important.

MAIN RESULTS

We included 88 studies (871,378 participants), of which 84 were RCTs, three were CBAs and one was an ITS. The majority of the studies were conducted in the USA (54%). In total, 86% were conducted in high-income countries and the remaining 14% in upper middle-income countries. The most commonly used social media platform was Facebook (39%) with few studies utilising other platforms such as WeChat, Twitter, WhatsApp, and Google Hangouts. Many studies (48%) used web-based communities or apps that mimic functions of these well-known social media platforms. We compared studies assessing interactive social media interventions with non-interactive social media interventions, which included paper-based or in-person interventions or no intervention. We only reported the RCT results in our 'Summary of findings' table. We found a range of effects on health behaviours, such as breastfeeding, condom use, diet quality, medication adherence, medical screening and testing, physical activity, tobacco use, and vaccination. For example, these interventions may increase physical activity and medical screening tests but there was little to no effect for other health behaviours, such as improved diet or reduced tobacco use (20,139 participants in 54 RCTs). For body function outcomes, interactive social media interventions may result in small but important positive effects, such as a small but important positive effect on weight loss and a small but important reduction in resting heart rate (4521 participants in 30 RCTs). Interactive social media may improve overall well-being (standardised mean difference (SMD) 0.46, 95% confidence interval (CI) 0.14 to 0.79, moderate effect, low-certainty evidence) demonstrated by an increase of 3.77 points on a general well-being scale (from 1.15 to 6.48 points higher) where scores range from 14 to 70 (3792 participants in 16 studies). We found no difference in effect on psychological outcomes (depression and distress) representing a difference of 0.1 points on a standard scale in which scores range from 0 to 63 points (SMD -0.01, 95% CI -0.14 to 0.12, low-certainty evidence, 2070 participants in 12 RCTs). We also compared studies assessing interactive social media interventions with those with an active but less interactive social media control (11 studies). Four RCTs (1523 participants) that reported on physical activity found an improvement demonstrated by an increase of 28 minutes of moderate-to-vigorous physical activity per week (from 10 to 47 minutes more, SMD 0.35, 95% CI 0.12 to 0.59, small effect, very low-certainty evidence). Two studies found little to no difference in well-being for those in the intervention and control groups (SMD 0.02, 95% CI -0.08 to 0.13, small effect, low-certainty evidence), demonstrated by a mean change of 0.4 points on a scale with a range of 0 to 100. Adverse events related to the social media component of the interventions, such as privacy issues, were not reported in any of our included studies. We were unable to conduct planned subgroup analyses related to health equity as only four studies reported relevant data.

AUTHORS' CONCLUSIONS

This review combined data for a variety of outcomes and found that social media interventions that aim to increase physical activity may be effective and social media interventions may improve well-being. While we assessed many other outcomes, there were too few studies to compare or, where there were studies, the evidence was uncertain. None of our included studies reported adverse effects related to the social media component of the intervention. Future studies should assess adverse events related to the interactive social media component and should report on population characteristics to increase our understanding of the potential effect of these interventions on reducing health inequities.

Feasibility of a Digital Intervention to Promote Healthy Weight Management among Postpartum African American/Black Women

The study aim was to implement and evaluate the feasibility of a culturally informed (“BeFAB”) app for African American/Black women to address postpartum weight. Women (n = 136; mean age = 27.8 ± 5.4; mean BMI = 32.5 ± 4.3) were recruited from postpartum units, and randomly assigned to receive BeFAB (n = 65) or usual care (n = 71) for 12 weeks. App content included didactic lessons delivered via a virtual coach, app-based messages, goal setting and tracking, and edutainment videos. Feasibility outcomes included recruitment, retention and engagement, and self-reported acceptability. Behavioral (i.e., diet, physical activity), psychosocial (i.e., stress, coping, support, self-efficacy) and weight outcomes were also examined. Recruitment goals were met, but attrition was high, with 56% retention at 12 weeks. Approximately half of participants accessed the app and set a goal ≥one time, but <10% reported achieving a nutrition or activity goal. Among study completers, ≥60% found the app content at least somewhat helpful. Within-group changes for BeFAB among completers were found for increased moderate-to-vigorous physical activity and decreased fruit/vegetable intake and weight. Findings indicate initial feasibility of recruiting postpartum women to participate in a digital healthy body weight program but limited use, reflecting low acceptability and challenges in engagement and retention. Future research is needed on strategies to engage and retain participants in postpartum interventions.