Technology-assisted weight management interventions: systematic review of clinical trials

An updated study protocol for a real-life digital 12-month weight management program, the Healthy Weight Coaching

Obesity is an important health concern that poses many public health challenges. Evidence-based treatment modalities, capable of cost-effectively reaching large patient groups are needed. In this paper, we present the design and methods of the updated national, 12-month, digital weight management program, the Healthy Weight Coaching (HWC). The major updates, as compared to the previous version, are related to the theoretical background of the obesity management and updated BMI cut-offs. The HWC is available, based on physicians' referrals, to adult Finnish citizens with BMI ≥30 kg/m2 or ≥27 kg/m2 with a comorbidity, who have a health-based need to lose weight. Rooted in the principles of behavioural therapy, the HWC focuses on teaching coping skills, guides to healthy self-reflection, and supports concrete lifestyle changes as part of healthy weight loss. The automated weekly training sessions, supplemented by 3-8 exercises, form the basis of the program. These sessions address topics such as diet, physical activity, stress management, and rest and recovery. Additionally, a personal coach is allocated to each patient to provide tailored support. At baseline, patients record their weight, height, and waist circumference, online, and complete questionnaires on lifestyle, diet, physical activity, sleep, psychological factors, and health. Thereafter weight recording is conducted at least every 4 weeks, while the questionnaires and measuring the weight circumference are repeated at 3, 6, 9, and 12 months. In addition, patients can make use of diaries and peer group chats for additional support. Data collected from the consenting patients will be used for research purposes with the weight change from baseline to 12 months as the main outcome in the real-life observational study. The study will provide invaluable insights into the application of digital modalities in the treatment of obesity.

Which components of behavioral weight management programs are essential for weight loss in people living with obesity? A rapid review of systematic reviews

The optimal treatment and organization of care for people with obesity is one of the greatest challenges facing today's health services. While surgery and pharmacotherapy offer effective treatment options for some people with obesity, behavioral interventions are important to support long-term behavioral change. However, little is known about the most effective components of behavioral interventions, and this is especially the case for people with complex or severe obesity (i.e. body mass index [BMI] > 35 kg/m2). Accordingly, the current rapid review aimed to identify which behavior change techniques (BCTs) are effective for weight loss in adults with (severe) obesity. A secondary aim was to review the effects of BCTs on dietary behaviors and physical activity, and psychological outcomes, recognizing that behavioral interventions commonly target these. A search of Scopus, Ovid Medline, and Web of Science resulted in 1227 results, with 22 reviews eligible for inclusion. The most commonly reported BCTs were self-monitoring and goal setting, but these had variable effects on weight in adults with obesity. Combining these BCTs with other self-regulatory techniques led to increased weight loss. Further, for adults with severe obesity, so-called 'nudge' techniques and self-regulatory techniques were associated with greater weight loss. Three reviews also found that while self-monitoring increased physical activity, behavioral commitments increased changes to dietary behaviors. BCTs were not associated with psychological well-being. The review confirms that behavioral interventions have an impact in weight management, including for individuals with more complex or severe obesity, but highlights the need for further investigation of their use within clinical settings.

A Systematic Review of eHealth Interventions to Promote Physical Activity in Adults with Obesity or Overweight

Use of information and communication technology to improve health, known as eHealth, is an emerging concept in healthcare that may present opportunities to promote physical activity in adults with obesity. The purpose of this research was to systematically review eHealth intervention studies to promote physical activity in adults with obesity. Five electronic databases were used. Two authors screened articles, assessed risk of bias, and extracted data independently. A qualitative data synthesis for summarizing the findings was performed using harvest plots. In the search, 2276 articles were identified, and 18 studies met all inclusion criteria. Study quality ranged from poor to good. The included studies varied in intervention technology (e.g., web-based), physical activity assessment (e.g., device-based), and control group (e.g., wait-list). Behavioral change techniques used in the included studies were consistent with some techniques (e.g., self-monitoring) known as effective in face-to-face interventions, but more efficiently employed in eHealth using information and communication technology. Overall, this systematic review showed that a web-based or physical activity monitor-based eHealth intervention had the potential to effectively promote physical activity in adults with obesity. Some recommendations for future eHealth interventions to promote physical activity in adults with obesity were provided (e.g., use of theory, accelerometers).

Essential elements of weight loss apps for a multi-ethnic population with high BMI: a qualitative study with practical recommendations

Smartphone weight loss apps are constantly being developed but the essential elements needed by a multi-ethnic population with overweight and obesity remains unclear. Purpose: To explore the perceptions of an Asian multi-ethnic population with overweight and obesity on the essential elements of weight loss apps. Twenty two participants were purposively sampled from a specialist weight management clinic in Singapore from 13 April to 30 April 2021. Recorded interviews were conducted using face-to-face and videoconferencing modalities. Data saturation was reached at the 18th participant. Data analysis was performed using inductive content analysis with constant comparison between and within transcripts. Findings: Three themes and eight subthemes on the essential app components emerged-(a) comprehensive and flexible calorie counters; (b) holistic, gradual and individualized behavior change recommendations tailored for people with overweight and obesity, and (c) just-in-time reminders of future consequences. There was a need to incorporate flexible options for food logging; break down general recommendations into small steps towards sustainable changes; tailor app contents for people with overweight and obesity; and evoke one's considerations of future consequences. Future weight loss apps should be designed to meet the needs of those with overweight and obesity, the very population that needs assistance with weight loss. Future apps could consider leveraging the capacity of artificial intelligence to provide personalized weight management in terms of sustaining self-regulation behaviors, optimizing goal-setting and providing personalized and timely recommendations for weight loss.

Nutrition counseling and monitoring via tele-nutrition for healthy diet for people with spinal cord injury: A case series analyses

OBJECTIVE

To evaluate the effect of a tele-nutrition counseling program on diet quality, weight, waist circumference, and quality of life in people with spinal cord injury (SCI).

DESIGN

Prospective observational study.

PARTICIPANTS

Fifteen participants with SCI were enrolled from an acute inpatient rehabilitation unit and outpatient SCI clinic; ten participants completed the intervention.

INTERVENTIONS

Six tele-nutrition counseling sessions over 3 months, utilizing videoconferencing and a photographic food diary.

OUTCOME MEASURES

Weight, waist circumference, Life Satisfaction Index A (LSIA), Knowledge and Nutrition Evaluation with Supplement on Eating Behavior, and Program Satisfaction Survey (PSS).

RESULTS

Ten participants completed both baseline and 3-month follow-up evaluations and were used in this analysis. There were no statistically significant changes from baseline to 3-month follow up in weight, waist circumference, Knowledge and Nutrition Evaluation, and LSIA (P > .48). Using the Supplement on Eating Behavior total score to measure overall changes in healthy food choices, 9 out of 10 participants rated their healthy food choices as improving (P = .008). A post-hoc exploratory itemized analysis on the Supplement on Eating Behavior revealed significant improvements from baseline to 3-month follow-up in participant's self-reported choice of balanced meals (P = .008), reading food labels (P = .031), logging meals (P = .007), and monitoring portions of eating favorite foods (P = .031). Participants endorsed a 97-100% satisfaction rating in relation to perceived health benefits, equipment, and program satisfaction.

CONCLUSION

This study provides preliminary data suggesting that tele-nutrition is an efficacious intervention that may improve diet quality for individuals with SCI.

Informing the Physical Activity Evaluation Framework: A Scoping Review of Reviews

OBJECTIVE

Robust program evaluations can identify effective promotion strategies. This scoping review aimed to analyze review articles (including systematic reviews, meta-analysis, meta-synthesis, scoping review, narrative review, rapid review, critical review, and integrative reviews) to systematically map and describe physical activity program evaluations published between January 2014 and July 2020 to summarize key characteristics of the published literature and suggest opportunities to strengthen current evaluations.

DATA SOURCE

We conducted a systematic search of the following databases: Medline, Scopus, Sportdiscus, Eric, PsycInfo, and CINAHL.

INCLUSION/EXCLUSION CRITERIA

Abstracts were screened for inclusion based on the following criteria: review article, English language, human subjects, primary prevention focus, physical activity evaluation, and evaluations conducted in North America.

EXTRACTION

Our initial search yielded 3193 articles; 211 review articles met the inclusion criteria.

SYNTHESIS

We describe review characteristics, evaluation measures, and "good practice characteristics" to inform evaluation strategies.

RESULTS

Many reviews (72%) did not assess or describe the use of an evaluation framework or theory in the primary articles that they reviewed. Among those that did, there was significant variability in terminology making comparisons difficult. Process indicators were more common than outcome indicators (63.5% vs 46.0%). There is a lack of attention to participant characteristics with 29.4% capturing participant characteristics such as race, income, and neighborhood. Negative consequences from program participation and program efficiency were infrequently considered (9.3% and 13.7%).

CONCLUSION

Contextual factors, negative outcomes, the use of evaluation frameworks, and measures of program sustainability would strengthen evaluations and provide an evidence-base for physical activity programming, policy, and funding.

Optimization of an mHealth lifestyle intervention for families with hereditary cancer syndromes: Study protocol for a multiphase optimization strategy feasibility study

BACKGROUND

Individuals at increased hereditary risk of cancer are an important target for health promotion and cancer prevention interventions. Health-4-Families uses the Multiphase Optimization STrategy (MOST) framework and is designed to pilot digital delivery strategies for a distance-based, 16-week intervention to promote weight management, healthy diet, and increased physical activity among individuals with BRCA1/BRCA2 or DNA mismatch repair (MMR) pathogenic germline variants. This communication describes participant recruitment and the design of the Health-4-Families pilot study.

METHODS

Health-4-Families is a full-factorial (16 condition) randomized pilot study of four lifestyle intervention components: social networking, telephone or email coaching, text messaging, and self-monitoring. The primary outcome was feasibility and satisfaction with these study components. Participants with pathogenic germline variants were identified via clinic surveillance lists and advocacy organizations and were invited to participate with family members. All participants had to report meeting at least one of the following criteria: (1) having a BMI ≥ 25 kg/m2, (2) consuming <5 servings of fruit and vegetables per day, or (3) getting <150 min of moderate-to-vigorous intensity activity per week.

RESULTS

The majority of screened potential participants with pathogenic variants (83%) were eligible; 86% of those eligible provided informed consent and 79% (n = 104) completed baseline. A total of 206 family members were nominated by study participants and 49% (n = 102) completed baseline.

DISCUSSION

Recruitment data suggest that individuals with pathogenic germline variants, who are at increased risk for hereditary cancers, are motivated to participate in digital lifestyle interventions. This recruitment success highlights the importance of identifying and prioritizing effective and efficient intervention components for hereditary cancer families. We intend to use the outcomes of our pilot study to inform a fully-powered factorial study for this community.

What Are We Measuring When We Evaluate Digital Interventions for Improving Lifestyle? A Scoping Meta-Review

Background: Lifestyle Medicine (LM) aims to address six main behavioral domains: diet/nutrition, substance use (SU), physical activity (PA), social relationships, stress management, and sleep. Digital Health Interventions (DHIs) have been used to improve these domains. However, there is no consensus on how to measure lifestyle and its intermediate outcomes aside from measuring each behavior separately. We aimed to describe (1) the most frequent lifestyle domains addressed by DHIs, (2) the most frequent outcomes used to measure lifestyle changes, and (3) the most frequent DHI delivery methods. Methods: We followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA-ScR) Extension for Scoping Reviews. A literature search was conducted using MEDLINE, Cochrane Library, EMBASE, and Web of Science for publications since 2010. We included systematic reviews and meta-analyses of clinical trials using DHI to promote health, behavioral, or lifestyle change. Results: Overall, 954 records were identified, and 72 systematic reviews were included. Of those, 35 conducted meta-analyses, 58 addressed diet/nutrition, and 60 focused on PA. Only one systematic review evaluated all six lifestyle domains simultaneously; 1 systematic review evaluated five lifestyle domains; 5 systematic reviews evaluated 4 lifestyle domains; 14 systematic reviews evaluated 3 lifestyle domains; and the remaining 52 systematic reviews evaluated only one or two domains. The most frequently evaluated domains were diet/nutrition and PA. The most frequent DHI delivery methods were smartphone apps and websites. Discussion: The concept of lifestyle is still unclear and fragmented, making it hard to evaluate the complex interconnections of unhealthy behaviors, and their impact on health. Clarifying this concept, refining its operationalization, and defining the reporting guidelines should be considered as the current research priorities. DHIs have the potential to improve lifestyle at primary, secondary, and tertiary levels of prevention-but most of them are targeting clinical populations. Although important advances have been made to evaluate DHIs, some of their characteristics, such as the rate at which they become obsolete, will require innovative research designs to evaluate long-term outcomes in health.

eHealth interventions targeting nutrition, physical activity, sedentary behavior, or obesity in adults: A scoping review of systematic reviews

A vast body of evidence regarding eHealth interventions for nutrition, physical activity, sedentary behavior, and obesity exists. This scoping review of systematic reviews aimed to evaluate the current level of evidence in this growing field. Seven electronic databases were searched for systematic reviews published until October 27, 2019. The systematic reviews must have included adult participants only and have evaluated eHealth behavioral interventions with the primary aim of changing nutrition, physical activity, and sedentary behavior or treating or preventing overweight and obesity. One hundred and six systematic reviews, published from 2006 to 2019, were included. Almost all (n = 98) reviews evaluated the efficacy of interventions. Over half (n = 61) included interventions focused on physical activity, followed by treatment of obesity (n = 28), nutrition (n = 22), prevention of obesity (n = 18), and sedentary behavior (n = 6). Many reviews (n = 46) evaluated one type of eHealth intervention only, while 60 included two or more types. Most reviews (n = 67) were rated as being of critically low methodological quality. This scoping review identified an increasing volume of systematic reviews evaluating eHealth interventions. It highlights several evidence gaps (e.g., evaluation of other outcomes, such as reach, engagement, or cost effectiveness), guiding future research efforts in this area.

A randomized controlled trial of an innovative, user-friendly, interactive smartphone app-based lifestyle intervention for weight loss

OBJECTIVES

Most electronically delivered lifestyle interventions are labor intensive, requiring logging onto websites and manually recording activity and diet. Cumbersome technology and lack of a human coach may have contributed to the limitations of prior interventions. In response, the current program of research created a comprehensive electronically delivered lifestyle intervention using a user-friendly, interactive, smartphone app-based model, and evaluated it in a randomized controlled trial.

METHODS

Twenty-eight adults, body mass index 25-42 kg/m2, with smartphones and sedentary jobs, were randomized to the intervention, along with conventional outpatient weight-management visits every 3 months, or to a wait-listed control group that received only weight-management visits. The intervention included wearable activity trackers, smartscales, food photography logs, physician-driven app-based behavioral coaching, and peer support via the app. The prespecified primary outcome was a comparison of change in weight in kilograms, in the intervention versus control group at 6 months.

RESULTS

At 6 months, the intervention group experienced a statistically significant weight change of -7.16 ± 1.78 kg (mean ± SE, 95% CI -11.05 to -3.26, p < 0.01), which differed from the weight change in controls by -4.16 ± 2.01 kg (95% CI -8.29 to -0.02, p < 0.05, prespecified primary outcome). Weight change in the control group was -3.00 ± 1.05 kg (95% CI -5.27 to -0.73, p < 0.05). Waist circumference and hemoglobin A1c significantly improved (intervention vs. control: p < 0.01, p < 0.05, respectively, prespecified secondary outcomes). Weight change in the intervention group correlated with numbers of food photographs participants shared (rho = -0.86, p < 0.01), numbers of their text messages (rho = -0.80, p < 0.01), number of times and days each participant stepped on the smartscale (rho = -0.73, p < 0.01; rho = -0.608, p < 0.05, respectively), and mean daily step counts (rho = -0.55, p < 0.05).

CONCLUSION

This app-based electronically delivered lifestyle intervention produced statistically significant, clinically meaningful weight loss and improved metabolic health. Engagement with the intervention correlated strongly with weight loss. Given the limited sample size, larger and longer studies of this intervention are needed.

Effectiveness of Digital Interventions for Reducing Behavioral Risks of Cardiovascular Disease in Nonclinical Adult Populations: Systematic Review of Reviews

BACKGROUND

Digital health interventions are increasingly being used as a supplement or replacement for face-to-face services as a part of predictive prevention. They may be offered to those who are at high risk of cardiovascular disease and need to improve their diet, increase physical activity, stop smoking, or reduce alcohol consumption. Despite the popularity of these interventions, there is no overall summary and comparison of the effectiveness of different modes of delivery of a digital intervention to inform policy.

OBJECTIVE

This review aims to summarize the effectiveness of digital interventions in improving behavioral and health outcomes related to physical activity, smoking, alcohol consumption, or diet in nonclinical adult populations and to identify the effectiveness of different modes of delivery of digital interventions.

METHODS

We reviewed articles published in the English language between January 1, 2009, and February 25, 2019, that presented a systematic review with a narrative synthesis or meta-analysis of any study design examining digital intervention effectiveness; data related to adults (≥18 years) in high-income countries; and data on behavioral or health outcomes related to diet, physical activity, smoking, or alcohol, alone or in any combination. Any time frame or comparator was considered eligible. We searched MEDLINE, Embase, PsycINFO, Cochrane Reviews, and gray literature. The AMSTAR-2 tool was used to assess review confidence ratings.

RESULTS

We found 92 reviews from the academic literature (47 with meta-analyses) and 2 gray literature items (1 with a meta-analysis). Digital interventions were typically more effective than no intervention, but the effect sizes were small. Evidence on the effectiveness of digital interventions compared with face-to-face interventions was mixed. Most trials reported that intent-to-treat analysis and attrition rates were often high. Studies with long follow-up periods were scarce. However, we found that digital interventions may be effective for up to 6 months after the end of the intervention but that the effects dissipated by 12 months. There were small positive effects of digital interventions on smoking cessation and alcohol reduction; possible effectiveness in combined diet and physical activity interventions; no effectiveness for interventions targeting physical activity alone, except for when interventions were delivered by mobile phone, which had medium-sized effects; and no effectiveness observed for interventions targeting diet alone. Mobile interventions were particularly effective. Internet-based interventions were generally effective.

CONCLUSIONS

Digital interventions have small positive effects on smoking, alcohol consumption, and in interventions that target a combination of diet and physical activity. Small effects may have been due to the low efficacy of treatment or due to nonadherence. In addition, our ability to make inferences from the literature we reviewed was limited as those interventions were heterogeneous, many reviews had critically low AMSTAR-2 ratings, analysis was typically intent-to-treat, and follow-up times were relatively short.

TRIAL REGISTRATION

PROSPERO International Prospective Register of Systematic Reviews CRD42019126074; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=126074.

Use of Technology-Based Interventions in the Treatment of Patients with Overweight and Obesity: A Systematic Review

Introduction: Obesity is one of the most important health problems worldwide. The prevalence of obesity has increased dramatically in the last decades and is now recognized as a global epidemic. Given the dramatic consequences of obesity, new intervention approaches based on the potential of technologies have been developed. Methods: We conducted a systematic review of studies using PubMed, ScienceDirect, Cochrane Library, and MedLine databases to assess how different types of technologies may play an important role on weight loss in obese patients. Results: Forty-seven studies using different types of technologies including smartphones, app, websites, virtual reality and personal digital assistant were included in the review. About half of interventions (47%) found a significant effect of the technology-based interventions for weight lost in obese patients. The provision of feedback could also be effective as a complement to interventions carried out using technology to promote weight loss. Conclusions: The use of technologies can be effective to increase weight loss in patients with obesity improving treatment adherence through self-monitoring.

Long-Term Weight Management Using Wearable Technology in Overweight and Obese Adults: Systematic Review

Background

Although there are many wearable devices available to help people lose weight and decrease the rising prevalence of obesity, the effectiveness of these devices in long-term weight management has not been established.

Objective

This study aimed to systematically review the literature on using wearable technology for long-term weight loss in overweight and obese adults.

Methods

We searched the following databases: Medical Literature Analysis and Retrieval System Online, EMBASE, Compendex, ScienceDirect, Cochrane Central, and Scopus. The inclusion criteria were studies that took measurements for a period of ≥1 year (long-term) and had adult participants with a BMI >24. A total of 2 reviewers screened titles and abstracts and assessed the selected full-text papers for eligibility. The risk of bias assessment was performed using the following tools appropriate for different study types: the Cochrane risk of bias tool, Risk Of Bias In Nonrandomized Studies-of Interventions, A MeaSurement Tool to Assess systematic Reviews, and 6 questions to trigger critical thinking. The results of the studies have been provided in a narrative summary.

Results

We included five intervention studies: four randomized controlled trials and one nonrandomized study. In addition, we used insights from six systematic reviews, four commentary papers, and a dissertation. The interventions delivered by wearable devices did not show a benefit over comparator interventions, but overweight and obese participants still lost weight over time. The included intervention studies were likely to suffer from bias. Significant variances in objectives, methods, and results of included studies prevented meta-analysis.

Conclusions

This review showed some evidence that wearable devices can improve long-term physical activity and weight loss outcomes, but there was not enough evidence to show a benefit over the comparator methods. A major issue is the challenge of separating the effect of decreasing use of wearable devices over time from the effect of the wearable devices on the outcomes. Consistency in study methods is needed in future long-term studies on the use of wearable devices for weight loss.

Trial Registration

PROSPERO CRD42018096932; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=96932

Text messaging to help women with overweight or obesity lose weight after childbirth: the intervention adaptation and SMS feasibility RCT

Background

There is a need to develop weight management interventions that fit seamlessly into the busy lives of women during the postpartum period.

Objective

The objective was to develop and pilot-test an evidence- and theory-based intervention, delivered by short message service, which supported weight loss and weight loss maintenance in the postpartum period.

Design

Stage 1 involved the development of a library of short message service messages to support weight loss and weight loss maintenance, with personal and public involvement, focusing on diet and physical activity with embedded behaviour change techniques, and the programming of a short message service platform to allow fully automated intervention delivery. Stage 2 comprised a 12-month, single-centre, two-arm, pilot, randomised controlled trial with an active control.

Setting

This study was set in Northern Ireland; women were recruited via community-based approaches.

Participants

A total of 100 women with overweight or obesity who had given birth in the previous 24 months were recruited.

Interventions

The intervention group received an automated short message service intervention about weight loss and weight loss maintenance for 12 months. The active control group received automated short message service messages about child health and development for 12 months.

Main outcome measures

The main outcomes measured were the feasibility of recruitment and retention, acceptability of the intervention and trial procedures, and evidence of positive indicative effects on weight. Weight, waist circumference and blood pressure were measured by the researchers; participants completed a questionnaire booklet and wore a sealed pedometer for 7 days at baseline, 3, 6, 9 and 12 months. Outcome assessments were collected during home visits and women received a voucher on completion of each of the assessments. Qualitative interviews were conducted with women at 3 and 12 months, to gather feedback on the intervention and active control and the study procedures. Quantitative and qualitative data were used to inform the process evaluation and to assess fidelity, acceptability, dose, reach, recruitment, retention, contamination and context.

Results

The recruitment target of 100 participants was achieved (intervention, n = 51; control, n = 49); the mean age was 32.5 years (standard deviation 4.3 years); 28 (28%) participants had a household income of < £29,999 per annum. Fifteen women became pregnant during the follow-up (intervention, n = 9; control, n = 6) and withdrew from the study for this reason. At the end of the 12-month study, the majority of women remained in the study [85.7% (36/42) in the intervention group and 90.7% (39/43) in the active control group]. The research procedures were well accepted by women. Both groups indicated a high level of satisfaction with the short message service intervention that they were receiving. There was evidence to suggest that the intervention may have a positive effect on weight loss and prevention of weight gain during the postpartum period.

Limitations

The interviews at 3 and 12 months were conducted by the same researchers who collected other outcome data.

Conclusions

An evidence- and theory-based intervention delivered by short message service was successfully developed in conjunction with postpartum women with overweight and obesity. The intervention was acceptable to women and was feasible to implement in the 12-month pilot randomised controlled trial. The progression criteria for a full randomised controlled trial to examine effectiveness and cost-effectiveness were met.

Future work

Some minor refinements need to be made to the intervention and trial procedures based on the findings of the pilot trial in preparation for conducting a full randomised controlled trial.

Trial registration

Current Controlled Trial ISRCTN90393571.

Funding

This project was funded by the National Institute for Health Research (NIHR) Public Health Research programme and will be published in full in Public Health Research; Vol. 8, No. 4. See the NIHR Journals Library website for further project information. The intervention costs were provided by the Public Health Agency, Northern Ireland.

Impact of a Mobile App-Based Health Coaching and Behavior Change Program on Participant Engagement and Weight Status of Overweight and Obese Children: Retrospective Cohort Study

BACKGROUND

Effective treatment of obesity in children and adolescents traditionally requires frequent in-person contact, and it is often limited by low participant engagement. Mobile health tools may offer alternative models that enhance participant engagement.

OBJECTIVE

The aim of this study was to assess child engagement over time, with a mobile app-based health coaching and behavior change program for weight management, and to examine the association between engagement and change in weight status.

METHODS

This was a retrospective cohort study of user data from Kurbo, a commercial program that provides weekly individual coaching via video chat and supports self-monitoring of health behaviors through a mobile app. Study participants included users of Kurbo between March 2015 and March 2017, who were 5 to 18 years old and who were overweight or obese (body mass index; BMI ≥ 85th percentile or ≥ 95th percentile) at baseline. The primary outcome, engagement, was defined as the total number of health coaching sessions received. The secondary outcome was change in weight status, defined as the change in BMI as a percentage of the 95th percentile (%BMIp95). Analyses of outcome measures were compared across three initial commitment period groups: 4 weeks, 12 to 16 weeks, or 24 weeks. Multivariable linear regression models were constructed to adjust outcomes for the independent variables of sex, age group (5-11 years, 12-14 years, and 15-18 years), and commitment period. A sensitivity analysis was conducted, excluding a subset of participants involuntarily assigned to the 12- to 16-week commitment period by an employer or health plan.

RESULTS

A total of 1120 participants were included in analyses. At baseline, participants had a mean age of 12 years (SD 2.5), mean BMI percentile of 96.6 (SD 3.1), mean %BMIp95 of 114.5 (SD 16.5), and they were predominantly female 68.04% (762/1120). Participant distribution across commitment periods was 26.07% (292/1120) for 4 weeks, 61.61% (690/1120) for 12-16 weeks, and 12.32% (138/1120) for 24 weeks. The median coaching sessions (interquartile range) received were 8 (3-16) for the 4-week group, 9 (5-12) for the 12- to 16-week group, and 19 (11-25) for the 24-week group (P<.001). Adjusted for sex and age group, participants in the 4- and 12-week groups participated in -8.03 (95% CI -10.19 to -5.87) and -9.34 (95% CI -11.31 to -7.39) fewer coaching sessions, compared with those in the 24-week group (P<.001). Adjusted for commitment period, sex, and age group, the overall mean change in %BMIp95 was -0.21 (95% CI -0.25 to -0.17) per additional coaching session (P<.001).

CONCLUSIONS

Among overweight and obese children using a mobile app-based health coaching and behavior change program, increased engagement was associated with longer voluntary commitment periods, and increased number of coaching sessions was associated with decreased weight status.

Self-monitoring and reminder text messages to increase physical activity in colorectal cancer survivors (Smart Pace): a pilot randomized controlled trial

Background

Over 1.3 million people live with colorectal cancer in the United States. Physical activity is associated with lower risk of colorectal cancer recurrence and mortality. Interventions are needed to increase physical activity in colorectal cancer survivors.

Methods

We conducted a 2-arm non-blinded pilot randomized controlled trial at the University of California, San Francisco among 42 individuals who had completed curative-intent treatment for colorectal cancer to determine the feasibility and acceptability of a 12-week (84 days) physical activity intervention using a Fitbit Flex™ and daily text messages. Participants were randomized 1:1 to receive the intervention with print educational materials or print educational materials alone. We explored the impact of the intervention versus usual care on physical activity using ActiGraph GT3X+ accelerometers pre−/post-intervention.

Results

We screened 406 individuals and randomized 42 to intervention (n = 21) or control (n = 21) groups. During the 12-week study, the intervention arm wore their Fitbits a median of 74 days [88% of days in study period, interquartile range: 23–83 days] and responded to a median of 34 (out of 46) text messages that asked for a reply (interquartile range: 13–38 text messages). Among the 16 intervention participants who completed the feedback survey, the majority (88%) reported that the intervention motivated them to exercise and that they were satisfied with their experience. No statistically significant difference in change in moderate-to-vigorous physical activity was found from baseline to 12 weeks between arms.

Conclusion

A 12-week physical activity intervention with a Fitbit and text messages was feasible and acceptable among colorectal cancer patients after curative treatment. Larger studies are needed to determine whether the intervention increases physical activity.

Trial registration

Clinicaltrials.gov Identifier NCT02966054. Registered 17 November 2016, retrospectively registered.

Electronic supplementary material

The online version of this article (10.1186/s12885-019-5427-5) contains supplementary material, which is available to authorized users.

Fit & quit: An efficacy trial of two behavioral post-cessation weight gain interventions

While smoking cessation leads to significant improvements in both mortality and morbidity, post-cessation weight gain partially attenuates this benefit. Even though post-cessation weight gain is small (4.7 kg on average), it is a stated reason to delay cessation attempts and is associated with smoking relapse. Fit & Quit is a randomized, controlled efficacy trial that aims to examine the ability of a weight stability intervention and a weight loss intervention to reduce post-cessation weight gain. For this purpose, Fit & Quit will randomize participants to three conditions: (a) Small Changes, a weight gain prevention intervention; (b) Look AHEAD Intensive Lifestyle Intervention; and (c) a lower-intensity bibliotherapy intervention. All conditions will receive a highly efficacious behavioral (i.e., rate reduction skills, motivational interviewing) and pharmacological (i.e., varenicline) smoking cessation program. A total of 400 participants will be recruited and randomized to the three interventions. Participants will be recruited in waves, with 10 waves of approximately 40 participants per wave. The primary outcomes of this study include post-cessation weight gain and cessation status at 12-month follow-up. Fit & Quit will integrate and adapt the strongest evidence-based interventions available for weight management and smoking cessation. Fit & Quit is highly innovative in the areas of the target population, study design, and use of technology. For these reasons, we expect that Fit & Quit will make a significant public health contribution to curtailing the important cessation barrier of post-cessation weight gain.

A framework for examining the function of digital health technologies for weight management

Research is rapidly extending its focus to develop and evaluate weight management interventions that incorporate eHealth technologies. Comparative effectiveness of eHealth interventions is partly limited by the extensive heterogeneity in intervention design, variation in use of eHealth tools, and expanding development of novel tools to promote weight management. We closely examined, characterized, and categorized the use and function of eHealth tools across a wide range of eHealth interventions for weight management in order to first create a novel schematic framework for eHealth interventions and, second, to evaluate eHealth interventions using this framework. We examined 49 randomized controlled trials from two systematic reviews evaluating the effectiveness of eHealth interventions for weight loss. Further characterization of each intervention identified common use and function of eHealth tools represented within interventions and thus important to include in the proposed framework. This resulted in six descriptive domains. We then categorized each eHealth intervention within the context of the newly developed framework. Last, we examined efficacious interventions in the context of the framework. Twenty-five randomized controlled trials reported significantly more weight loss between the intervention group utilizing eHealth, compared to a non-eHealth control intervention and/or within an eHealth intervention group. Of these 25 interventions, 15 (60%) used automated feedback (Domain 1), 13 (52%) used non-eHealth tailored feedback by a health care provider (Domain 5), and 8 (32%) used tailored feedback from a health care professional through an electronic channel (Domain 2). The proposed schematic framework offers an alternative and novel approach for comparing across interventions and informing the development and evaluation of eHealth interventions.

A tailored telephone and email based exercise intervention induced reductions in various measures of body composition in physically inactive adults: A randomized controlled trial

Obesity prevalence has increased the past decades and has become a serious public health problem. The aim of this six-month assessor-blinded, parallel-group randomized controlled trial was to assess the effect of a tailored telephone and email-based exercise intervention on various measures of body composition in a sample of apparently healthy and physically inactive adults. A total of 111 volunteering adults (40-55 yr) in Southern Norway were randomly assigned to an intervention group (IG; n = 39) or a no-information control group (CG; n = 50), by random allocation numbering. The IG received feedback on their health-related physical fitness, information on guidelines and recommendations for physical activity, a leaflet on national dietary recommendations, prompts and reminders in addition to three tailored exercise programs, one every two months, and fortnightly motivational counselling by email or telephone, alternately. The CG received no follow-up during the intervention period. The main outcome measures: weight, body mass index (BMI), waist circumference (WC) and fat percentage by skinfolds (FPskf) were assessed objectively at baseline and posttest. A one-way ANCOVA analysis, adjusted for baseline scores, gender, age, and educational level, revealed a larger reduction on all body compositional measures in the IG compared to the CG (p ≤ 0.043), except for BMI when adjusted for baseline scores. Additionally, a significantly higher percentage of the IG (64.1%) achieved a clinically significant reduction in FPskf compared to the CG (36.2%, p = 0.018). This six-month tailored telephone and email-based exercise intervention induced significant reductions on several measures of body composition in physically inactive adults.

TRIAL REGISTRATION

ClinicalTrials.gov (NCT03164239).

5. Prevention or Delay of Type 2 Diabetes: Standards of Medical Care in Diabetes-2018

The American Diabetes Association (ADA) "Standards of Medical Care in Diabetes" includes ADA's current clinical practice recommendations and is intended to provide the components of diabetes care, general treatment goals and guidelines, and tools to evaluate quality of care. Members of the ADA Professional Practice Committee, a multidisciplinary expert committee, are responsible for updating the Standards of Care annually, or more frequently as warranted. For a detailed description of ADA standards, statements, and reports, as well as the evidence-grading system for ADA's clinical practice recommendations, please refer to the Standards of Care Introduction Readers who wish to comment on the Standards of Care are invited to do so at professional.diabetes.org/SOC.

Behavioral lifestyle interventions for moderate and severe obesity: A systematic review

Moderate and severe obesity (BMI ≥35 kg/m2) affect 15% of US adults, with a projected increase over the next two decades. This study reviews evidence of behavioral lifestyle interventions for weight loss in this population. We searched PubMed, PsychInfo, CINAHL®, and Scopus through February 2016 for experimental and quasi-experimental studies that tested a dietary and/or physical activity intervention with a behavioral modification component versus a comparator; and had ≥six-month follow-up and a weight-related primary outcome. Twelve studies representing 1862 participants (mean BMI 37.5-48.3, mean age 30-54 years) were included. Nine studies compared different behavioral interventions and three tested behavioral intervention(s) versus pharmacological or surgical treatments. Among the 25 behavioral interventions in the 12 studies, 18 reported percent of participants achieving clinically significant weight loss up to 12months (32-97% achieving 5% or 3-70% achieving 10%). Three studies measured other cardiometabolic risk factors, but showed no significant risk reduction. Seven interventions with greater effectiveness (i.e., at least 31% achieving ≥10% or 62% achieving ≥5% weight loss up to one year) included multiple components (diet, physical activity, and behavioral strategies), long duration (e.g., one year), and/or intensive contacts (e.g., inpatient stays for clinic-based interventions, weekly contacts for community-based ones). Evidence for the effectiveness of behavioral interventions versus pharmacological or surgical treatment was limited. Comprehensive and intensive behavioral interventions can result in clinically significant, albeit modest, weight loss in this obese subpopulation but may not result significant improvements in other cardiometabolic risk factors. More research on scalable and sustainable interventions is needed.

Effects of an abbreviated obesity intervention supported by mobile technology: The ENGAGED randomized clinical trial

OBJECTIVE

To determine the effects on weight loss of three abbreviated behavioral weight loss interventions with and without coaching and mobile technology.

METHODS

A randomized controlled efficacy study of three 6-month weight loss treatments was conducted in 96 adults with obesity: 1) self-guided (SELF), 2) standard (STND), or 3) technology-supported (TECH). STND and TECH received eight in-person group treatment sessions. SELF and STND used paper diaries to self-monitor diet, activity, and weight; TECH used a smartphone application with social networking features and wireless accelerometer.

RESULTS

Weight loss was greater for TECH and STND than SELF at 6 months (-5.7 kg [95% confidence interval: -7.2 to -4.1] vs. -2.7 kg [95% confidence interval: -5.1 to -0.3], P < 0.05) but not 12 months. TECH and STND did not differ except that more STND (59%) than TECH (34%) achieved ≥ 5% weight loss at 6 months (P < 0.05). Self-monitoring adherence was greater in TECH than STND (P < 0.001), greater in both interventions than SELF (P < 0.001), and covaried with weight loss (r(84) = 0.36-0.51, P < 0.001).

CONCLUSIONS

Abbreviated behavioral counseling can produce clinically meaningful weight loss regardless of whether self-monitoring is performed on paper or smartphone, but long-term superiority over standard of care self-guided treatment is challenging to maintain.

Smartphone Usage, Social Media Engagement, and Willingness to Participate in mHealth Weight Management Research Among African American Women

BACKGROUND

African American women (AAW) are in a unique position to be recruited into mobile (mHealth) weight management research and programs due to their high rates of obesity and their high ownership of smartphones.

AIM

This study examined smartphone usage, social media engagement, and willingness to participate in mHealth weight management among AAW in north-central Florida, United States.

METHODS

A self-administered survey was completed by a convenience sample of 425 smartphone owners in north-central Florida.

RESULTS

Mean age was 34.84 ± 13.74, with age distribution of 18 to 29 (45%), 30 to 50 (39%), and 51+ years (17%). Mean body mass index was 29.52 ± 8.18. Most used smartphones to access the Internet daily and were engaged with eight social media sites, such as Facebook (85%), YouTube (75%), and Google+ (57%). Compared to those 51+, those 18 to 29 were more likely to use YouTube (odds ratio [OR] = 2.52, p = .017) and Instagram (OR = 10.90, p < .0001), but they were less likely to use Google+ (OR = 0.40, p = .009). Compared to those 51+, those 30 to 50 were more likely to use Instagram (β = 1.28, OR = 3.61, p = .014) and Facebook (β = 1.04, OR = 2.84, p < .006). Most were willing to participate in research that used text messages (73%), smartwatches/fitness trackers (69%), and smartphone apps (68%). Compared to those 51+, women 18 to 29 were more likely to report willingness to use a smartphone app (OR = 5.45, p < .0001) as were those 30 to 50 (OR = 3.14, p < .0001).

CONCLUSION

AAW's high ownership of smartphones, use of mHealth apps and tools, and willingness to participate in mHealth research has the potential to curb the obesity epidemic by participating in mHealth weight management programs and research.

A Systematic Review of Application and Effectiveness of mHealth Interventions for Obesity and Diabetes Treatment and Self-Management

The use of mobile and wireless technologies and wearable devices for improving health care processes and outcomes (mHealth) is promising for health promotion among patients with chronic diseases such as obesity and diabetes. This study comprehensively examined published mHealth intervention studies for obesity and diabetes treatment and management to assess their effectiveness and provide recommendations for future research. We systematically searched PubMed for mHealth-related studies on diabetes and obesity treatment and management published during 2000-2016. Relevant information was extracted and analyzed. Twenty-four studies met inclusion criteria and varied in terms of sample size, ethnicity, gender, and age of the participating patients and length of follow-up. The mHealth interventions were categorized into 3 types: mobile phone text messaging, wearable or portable monitoring devices, and applications running on smartphones. Primary outcomes included weight loss (an average loss ranging from -1.97 kg in 16 wk to -7.1 kg in 5 wk) or maintenance and blood glucose reduction (an average decrease of glycated hemoglobin ranging from -0.4% in 10 mo to -1.9% in 12 mo); main secondary outcomes included behavior changes and patient perceptions such as self-efficacy and acceptability of the intervention programs. More than 50% of studies reported positive effects of interventions based on primary outcomes. The duration or length of intervention ranged from 1 wk to 24 mo. However, most studies included small samples and short intervention periods and did not use rigorous data collection or analytic approaches. Although some studies suggest that mHealth interventions are effective and promising, most are pilot studies or have limitations in their study designs. There is an essential need for future studies that use larger study samples, longer intervention (≥ 6 mo) and follow-up periods (≥ 6 mo), and integrative and personalized innovative mobile technologies to provide comprehensive and sustainable support for patients and health service providers.

Prefrontal cortex-mediated executive function as assessed by Stroop task performance associates with weight loss among overweight and obese adolescents and young adults

People with cognitive deficits or executive dysfunction are often overweight or obese. Several human neuroimaging studies have found that executive function (EF) predicts food intake and weight gain; however, fewer studies have investigated the relationship between EF and weight loss. The Stroop task is a classic measure of EF that is used in many neuroimaging studies. In the present work, functional near infrared spectroscopy (fNIRS) data were collected during performance of the Stroop task from a sample of overweight or obese adolescents and young adults (n=31) who participated in a summer fitness and weight loss camp. We assessed the Stroop effect by interference in the reaction time (RT) to visual challenges, and by alterations in levels of oxygenated hemoglobin, as detected by fNIRS. In line with previous studies, we found that the Stroop effect was successfully induced by different visual task conditions among obese/overweight individuals. Moreover, our results reveal that better Stroop task performance is correlated with greater weight loss over a4-weekfitness intervention. Indeed, behavioral data demonstrated that reduced RT interference predicted a greater percentage of weight loss. Moreover, overweight/obese individuals with a greater hemodynamic response in the left ventrolateral and bilateral dorsolateral prefrontal cortex due to the Stroop effect lost more weight during the short-term fitness intervention than participants with lower levels of activation of these neural regions. Overall, our results support a role for prefrontal cortex-mediated EF in influencing food intake and weight loss outcomes in a population of a previously unstudied age.

Sustainable Lifestyle Change-Participatory Design of Support Together with Persons with Obesity in the Third Age

Sustainable lifestyle changes due to obesity are difficult to achieve regardless methods used. We need to know more about the lived experience of obesity and older persons' needs for support to make a sustainable change. This paper focuses on the need-finding process in designing support for a sustainable lifestyle change. Multistage focus group interviews were conducted with persons aged 61-72 living in Northern Sweden. A participatory and appreciative reflection and action (PAAR) approach was used in the group-sessions. Probes were used to increase reflections and achieve a deeper knowledge about the participants' needs of support. Data were analysed using qualitative thematic content analysis. Our findings revealed that to be able to succeed with a lifestyle change a focus has to be on a converted way of thinking, managing vulnerability, and achieving an emotional balance. To achieve a sustainable lifestyle change due to obesity in the third age the focus has to be on a health identity instead of a weight identity. Personalised support with enjoyable physical activities should be designed and developed. Strategies for emotional balance based on autonomy and self-empowerment must be included. This knowledge is important when designing support for sustainable change.

The Electronic CardioMetabolic Program (eCMP) for Patients With Cardiometabolic Risk: A Randomized Controlled Trial

Background

Effective lifestyle interventions targeting high-risk adults that are both practical for use in ambulatory care settings and scalable at a population management level are needed.

Objective

Our aim was to examine the potential effectiveness, feasibility, and acceptability of delivering an evidence-based Electronic Cardio-Metabolic Program (eCMP) for improving health-related quality of life, improving health behaviors, and reducing cardiometabolic risk factors in ambulatory care high-risk adults.

Methods

We conducted a randomized, wait-list controlled trial with 74 adults aged ≥18 years recruited from a large multispecialty health care organization. Inclusion criteria were (1) BMI ≥35 kg/m² and prediabetes, previous gestational diabetes and/or metabolic syndrome, or (2) BMI ≥30 kg/m² and type 2 diabetes and/or cardiovascular disease. Participants had a mean age of 59.7 years (SD 11.2), BMI 37.1 kg/m² (SD 5.4) and were 59.5% female, 82.4% white. Participants were randomized to participate in eCMP immediately (n=37) or 3 months later (n=37). eCMP is a 6-month program utilizing video conferencing, online tools, and pre-recorded didactic videos to deliver evidence-based curricula. Blinded outcome assessments were conducted at 3 and 6 months postbaseline. Data were collected and analyzed between 2014 and 2015. The primary outcome was health-related quality of life. Secondary outcomes included biometric cardiometabolic risk factors (eg, body weight), self-reported diet and physical activity, mental health status, retention, session attendance, and participant satisfaction.

Results

Change in quality of life was not significant in both immediate and delayed participants. Both groups significantly lost weight and reduced waist circumference at 6 months, with some cardiometabolic factors trending accordingly. Significant reduction in self-reported anxiety and perceived stress was seen in the immediate intervention group at 6 months. Retention rate was 93% at 3 months and 86% at 6 months post-baseline. Overall eCMP attendance was high with 59.5-83.8% of immediate and delayed intervention participants attending 50% of the virtual stress management and behavioral lifestyle sessions and 37.8-62.2% attending at least 4 out of 7 in-person physical activity sessions. The intervention received high ratings for satisfaction.

Conclusions

The technology-assisted eCMP is a feasible and well-accepted intervention and may significantly decrease cardiometabolic risk among high-risk individuals.

Trial Registration

Clinicaltrials.gov NCT02246400; https://clinicaltrials.gov/ct2/show/NCT02246400 (Archived by WebCite at http://www.webcitation.org/6h6mWWokP)

Effectiveness of an mHealth intervention to improve the cardiometabolic profile of people with prehypertension in low-resource urban settings in Latin America: a randomised controlled trial

BACKGROUND

Poor diet and physical inactivity strongly affect the growing epidemic of cardiovascular disease worldwide. Mobile phone-based health interventions (mHealth) have been shown to help promote weight loss and increase physical activity and are an attractive approach for health-care systems with limited resources. We aimed to assess whether mHealth with advice for lifestyle improvements would reduce blood pressure, promote weight loss, and improve diet quality and physical activity in individuals with prehypertension living in low-resource urban settings in Latin America.

METHODS

In this parallel-group, randomised controlled trial, we recruited individuals (aged 30-60 years) with systolic blood pressure between 120 and 139 mm Hg, diastolic blood pressure between 80 and 89 mm Hg, or both from health-care centres, workplaces, and community centres in low-resource urban settings in Argentina, Guatemala, and Peru. Participants were randomly assigned to receive either monthly motivational counselling calls and weekly personalised text messages to their mobile phones about diet quality and physical activity for 12 months, or usual care. Randomisation was stratified by country, and we applied minimisation by sex and age groups. Study personnel collecting and analysing data were masked to group assignment. The primary outcomes were mean between-group differences in the changes in systolic and diastolic blood pressure from baseline to 12 months in an intention-to-treat analysis of all participants who completed assessments at 12 months. Secondary outcome measures were changes in bodyweight, waist circumference, and self-reported target behaviours from baseline to 12 months. The trial is registered with ClinicalTrials.gov, number NCT01295216.

FINDINGS

Between March 1, 2012, and Nov 30, 2012, we randomly assigned 637 participants to receive intervention (n=316) or usual care (n=321). 266 (84%) participants in the intervention group and 287 (89%) in the control group were assessed at 12 months. The intervention did not affect change in systolic blood pressure (mean net change -0·37 mm Hg [95% CI -2·15 to 1·40]; p=0·43) or diastolic blood pressure (0·01 mm Hg [-1·29 to 1·32]; p=0·99) compared with usual care. However, we noted a significant net reduction in bodyweight (-0·66 kg [-1·24 to -0·07]; p=0·04) and intake of high-fat and high-sugar foods (-0·75 [-1·30 to -0·20]; p=0·008) in the intervention group compared with the control group. In a prespecified subanalysis, we found that participants in the intervention group who received more than 75% of the calls (nine or more, from a maximum of 12) had a greater reduction of bodyweight (-4·85 [-8·21 to -1·48]) and waist circumference (-3·31 [-5·95 to -0·67]) than participants in the control group. Additionally, participants in the intervention group had an increase in the intake of fruits and vegetables and a decrease in diets high in sodium, fat, and simple sugars relative to participants in the control group. However, we found no changes in systolic blood pressure, diasatolic blood pressure, or physical activity in the group of participants who received more than 75% of the calls compared with the group who received less than 50% of the calls.

INTERPRETATION

Our mHealth-based intervention did not result in a change in blood pressure that differed from usual care, but was associated with a small reduction in bodyweight and an improvement in some dietary habits. We noted a dose-response effect, which signals potential opportunities for larger effects from similar interventions in low-resource settings. More research is needed on mHealth, particularly among people who are poor and disproportionally affected by the cardiovascular disease epidemic and who need effective and affordable interventions to help bridge the equity gap in the management of cardiometabolic risk factors.

FUNDING

National Heart, Lung, and Blood Institute (US National Institutes of Health) and the Medtronic Foundation.

Diabetes Prevention and Weight Loss with a Fully Automated Behavioral Intervention by Email, Web, and Mobile Phone: A Randomized Controlled Trial Among Persons with Prediabetes

BACKGROUND

One-third of US adults, 86 million people, have prediabetes. Two-thirds of adults are overweight or obese and at risk for diabetes. Effective and affordable interventions are needed that can reach these 86 million, and others at high risk, to reduce their progression to diagnosed diabetes.

OBJECTIVE

The aim was to evaluate the effectiveness of a fully automated algorithm-driven behavioral intervention for diabetes prevention, Alive-PD, delivered via the Web, Internet, mobile phone, and automated phone calls.

METHODS

Alive-PD provided tailored behavioral support for improvements in physical activity, eating habits, and factors such as weight loss, stress, and sleep. Weekly emails suggested small-step goals and linked to an individual Web page with tools for tracking, coaching, social support through virtual teams, competition, and health information. A mobile phone app and automated phone calls provided further support. The trial randomly assigned 339 persons to the Alive-PD intervention (n=163) or a 6-month wait-list usual-care control group (n=176). Participants were eligible if either fasting glucose or glycated hemoglobin A1c (HbA1c) was in the prediabetic range. Primary outcome measures were changes in fasting glucose and HbA1c at 6 months. Secondary outcome measures included clinic-measured changes in body weight, body mass index (BMI), waist circumference, triglyceride/high-density lipoprotein cholesterol (TG/HDL) ratio, and Framingham diabetes risk score. Analysis was by intention-to-treat.

RESULTS

Participants' mean age was 55 (SD 8.9) years, mean BMI was 31.2 (SD 4.4) kg/m(2), and 68.7% (233/339) were male. Mean fasting glucose was in the prediabetic range (mean 109.9, SD 8.4 mg/dL), whereas the mean HbA1c was 5.6% (SD 0.3), in the normal range. In intention-to-treat analyses, Alive-PD participants achieved significantly greater reductions than controls in fasting glucose (mean -7.36 mg/dL, 95% CI -7.85 to -6.87 vs mean -2.19, 95% CI -2.64 to -1.73, P<.001), HbA1c (mean -0.26%, 95% CI -0.27 to -0.24 vs mean -0.18%, 95% CI -0.19 to -0.16, P<.001), and body weight (mean -3.26 kg, 95% CI -3.26 to -3.25 vs mean -1.26 kg, 95% CI -1.27 to -1.26, P<.001). Reductions in BMI, waist circumference, and TG/HDL were also significantly greater in Alive-PD participants than in the control group. At 6 months, the Alive-PD group reduced their Framingham 8-year diabetes risk from 16% to 11%, significantly more than the control group (P<.001). Participation and retention was good; intervention participants interacted with the program a median of 17 (IQR 14) of 24 weeks and 71.1% (116/163) were still interacting with the program in month 6.

CONCLUSIONS

Alive-PD improved glycemic control, body weight, BMI, waist circumference, TG/HDL ratio, and diabetes risk. As a fully automated system, the program has high potential for scalability and could potentially reach many of the 86 million US adults who have prediabetes as well as other at-risk groups.

TRIAL REGISTRATION

Clinicaltrials.gov NCT01479062; https://clinicaltrials.gov/ct2/show/NCT01479062 (Archived by WebCite at http://www.webcitation.org/6bt4V20NR).

A web- and mobile phone-based intervention to prevent obesity in 4-year-olds (MINISTOP): a population-based randomized controlled trial

BACKGROUND

Childhood obesity is an increasing health problem globally. Overweight and obesity may be established as early as 2-5 years of age, highlighting the need for evidence-based effective prevention and treatment programs early in life. In adults, mobile phone based interventions for weight management (mHealth) have demonstrated positive effects on body mass, however, their use in child populations has yet to be examined. The aim of this paper is to report the study design and methodology of the MINSTOP (Mobile-based Intervention Intended to Stop Obesity in Preschoolers) trial.

METHODS/DESIGN

A two-arm, parallel design randomized controlled trial in 300 healthy Swedish 4-year-olds is conducted. After baseline measures, parents are allocated to either an intervention- or control group. The 6- month mHealth intervention consists of a web-based application (the MINSTOP app) to help parents promote healthy eating and physical activity in children. MINISTOP is based on the Social Cognitive Theory and involves the delivery of a comprehensive, personalized program of information and text messages based on existing guidelines for a healthy diet and active lifestyle in pre-school children. Parents also register physical activity and intakes of candy, soft drinks, vegetables as well as fruits of their child and receive feedback through the application. Primary outcomes include body fatness and energy intake, while secondary outcomes are time spent in sedentary, moderate, and vigorous physical activity, physical fitness and intakes of fruits and vegetables, snacks, soft drinks and candy. Food and energy intake (Tool for Energy balance in Children, TECH), body fatness (pediatric option for BodPod), physical activity (Actigraph wGT3x-BT) and physical fitness (the PREFIT battery of five fitness tests) are measured at baseline, after the intervention (six months after baseline) and at follow-up (12 months after baseline).

DISCUSSION

This novel study will evaluate the effectiveness of a mHealth program for mitigating gain in body fatness among 4-year-old children. If the intervention proves effective it has great potential to be implemented in child-health care to counteract childhood overweight and obesity.

TRIAL REGISTRATION

ClinicalTrials.gov NCT02021786 ; 20 Dec 2013.