Mobile Delivery of the Diabetes Prevention Program in People With Prediabetes: Randomized Controlled Trial

Beneficial Effects of the Ketogenic Diet on Nonalcoholic Fatty Liver Disease (NAFLD/MAFLD)

The prevalence of nonalcoholic fatty liver disease (NAFLD) is likely to be approaching 38% of the world's population. It is predicted to become worse and is the main cause of morbidity and mortality due to hepatic pathologies. It is particularly worrying that NAFLD is increasingly diagnosed in children and is closely related, among other conditions, to insulin resistance and metabolic syndrome. Against this background is the concern that the awareness of patients with NAFLD is low; in one study, almost 96% of adult patients with NAFLD in the USA were not aware of their disease. Thus, studies on the therapeutic tools used to treat NAFLD are extremely important. One promising treatment is a well-formulated ketogenic diet (KD). The aim of this paper is to present a review of the available publications and the current state of knowledge of the effect of the KD on NAFLD. This paper includes characteristics of the key factors (from the point of view of NAFLD regression), on which ketogenic diet exerts its effects, i.e., reduction in insulin resistance and body weight, elimination of fructose and monosaccharides, limitation of the total carbohydrate intake, anti-inflammatory ketosis state, or modulation of gut microbiome and metabolome. In the context of the evidence for the effectiveness of the KD in the regression of NAFLD, this paper also suggests the important role of taking responsibility for one's own health through increasing self-monitoring and self-education.

Effectiveness of mobile health intervention for non alcoholic fatty liver disease- A meta analysis of randomized controlled trials

INTRODUCTION

Non-alcoholic fatty liver disease (NAFLD) is the most common cause of chronic liver disease worldwide. Lifestyle modification is the mainstay of management, however, most patients find it difficult to significantly modify their lifestyle. Mobile health is an innovative healthcare system that has an established role in treating chronic diseases like asthma, cancer and cardiovascular disease. Hence, we conducted an updated meta analysis to evaluate the efficacy of mobile health intervention (mHI) for NAFLD.

METHODS

Literature search of five electronic databases was performed from the inception of the paper till 15th May, 2024. Studies were included if they met the inclusion criteria; Randomized controlled trials evaluating use of mHI along with standard care in comparison to standard care only for patients with NAFLD over 18 years. Primary outcomes of interest included changes in weight, body mass index (BMI), and liver markers from baseline to post intervention. Risk of bias was evaluated using the Cochrane bias assessment tool while the Mantel-Haenszel Random-effects model on Review manager was used to pool outcomes.

RESULTS

Outcomes were pooled from 7 RCTs comprising a total of 621 participants. There was a significant decrease in weight (P < 0.0001), aspartate aminotransferase (AST) (P = 0.002) and alkaline aminotransferase (ALT) (P = 0.0009) from baseline to follow-up in the intervention group as compared to the control group. However, the reduction in BMI was found to be non-significant (P = 0.64).

CONCLUSION

Our meta analysis reports that mHI plays an important role in significantly reducing weight and liver markers in patients with NAFLD. Considering that the improvement of these factors plays a key role in the management of the disease, mHI could be the key towards paving better outcomes for patients with NAFLD.

Cost-effectiveness analysis of a digital diabetes-prevention programme versus an in-person diabetes-prevention programme in people with prediabetes in the United States

AIM

To assess the cost-effectiveness of a digital diabetes prevention programme (d-DPP) compared with a diabetes prevention programme (DPP) for preventing type 2 diabetes (T2D) in individuals with prediabetes in the United States.

METHODS

A Markov cohort model was constructed, simulating a 10-year period starting at the age of 45 years, with a societal and healthcare sector perspective. The effectiveness of the d-DPP intervention was evaluated using a meta-analysis, with that of the DPP as the comparator. The initial cycle represented the treatment period, and transition probabilities for the post-treatment period were derived from a long-term lifestyle intervention meta-analysis. The onset of T2D complications was estimated using microsimulation. Quality-adjusted life years (QALYs) were calculated based on health utility measured by short form (SF)-12 scores, and a willingness-to-pay threshold of $100 000 per QALY gained was applied.

RESULTS

The d-DPP intervention resulted in cost savings of $3,672 from a societal perspective and $2,990 from a healthcare sector perspective and a gain of 0.08 QALYs compared with the DPP. The dropout rate was identified as a significant factor influencing the results. Probabilistic sensitivity analysis showed that the d-DPP intervention was preferred in 85.8% in the societal perspective and 85.2% in the healthcare sector perspective.

CONCLUSIONS

The d-DPP is a cost-effective alternative to in-person lifestyle interventions for preventing the development of T2D among individuals with prediabetes in the United States.

Evaluation of a mobile behavior change program for weight loss in breast cancer survivors

Post-diagnosis weight gain is common in early-stage breast cancer and is associated with increased risk of recurrence and mortality. Intentional weight loss is difficult to maintain, and digital lifestyle interventions may provide a scalable approach to address this challenge. In this prospective single-arm study (ClinicalTrials.gov NCT04753268; February 15, 2021), key eligibility criteria included: stage I-III breast cancer, body mass index (BMI) ≥ 27.5 kg/m2, and completion of cancer treatment ≥6 months before study enrollment. Participants were provided with a behavioral change mobile application (Noom®). The primary endpoint was a change in self-reported weight from baseline to 26 weeks. Secondary endpoints included engagement, changes in physical activity, dietary patterns, and patient-reported outcomes (PRO). In total, 31 patients were enrolled (mean age 56.8 ± 9.9, mean baseline BMI 33.5 kg/m2 ± 6.5). The mean weight change was -4.8 kg ( ± 4.4, P < 0.001), mean percent weight change was -5.6% ( ± 5.0%); 11/31 patients (35.5%) lost ≥5% of their initial weight. Metrics of digital application engagement associated with weight loss ≥5% included articles read (P = 0.012), weights logged (P = 0.006), food records logged (P = 0.001), messages sent (P = 0.001), and application open count (P = 0.014). Significant increases were seen in mean daily step count (P = 0.004), GPAQ scores (P = 0.002), and Body Image Scale scores (P < 0.001). Mean energy intake remained consistently in a calorie-restricted range of 1300-1400 kcal/day. In this study, breast cancer survivors were highly engaged with a behavioral change smartphone application which led to clinically significant weight loss, increased physical activity, maintenance of an energy-restricted diet, and improvements in body image.

Role of telemedicine in the management of obesity: State-of-the-art review

Obesity is a worsening public health epidemic that remains challenging to manage. Obesity substantially increases the risk of cardiovascular diseases and presents a significant financial burden on the healthcare system. Digital health interventions, specifically telemedicine, may offer an attractive and viable solution for managing obesity. During the COVID-19 pandemic, the need for a safer alternative to in-person visits led to the increased popularity of telemedicine. Multiple studies have tested the efficacy of telemedicine modalities, including digital coaching via videoconferencing sessions, e-health monitoring using wearable devices, and asynchronous forms of communication such as online chatrooms with counselors. In this review, we discuss the available evidence for telemedicine interventions in managing obesity, review current challenges and barriers to using telemedicine, and outline future directions to optimize the management of patients with obesity using telemedicine.

Smartphone Applications to Prevent Type 2 Diabetes: A Systematic Review and Meta-Analysis

INTRODUCTION

Evidence supporting the use of apps for lifestyle behavior change and diabetes prevention in people at high risk of diabetes is lacking. The aim of this systematic review was to determine the acceptability and effectiveness of smartphone applications (apps) for the prevention of type 2 diabetes.

METHODS

PubMed, Embase, CINAHL and PsychInfo were searched from 2008 to 2023. Included studies involved adults at high risk of developing diabetes evaluating an app intervention with the aim of preventing type 2 diabetes. Random-effects meta-analyses were conducted for weight loss, body mass index (BMI), glycated hemoglobin, and waist circumference. Narrative synthesis was conducted for all studies, including qualitative studies exploring user perspectives.

RESULTS

Twenty-four studies (n=2,378) were included in this systematic review, including 9 randomized controlled trials (RCTs) with an average duration of 6 months, 10 quasi-experimental and 7 qualitative studies. Socially disadvantaged groups were poorly represented. Six RCTs were combined in meta-analyses. Apps were effective at promoting weight loss [mean difference (MD) -1.85; 95% CI -2.90 to -0.80] and decreasing BMI [MD -0.90, 95% CI -1.53 to -0.27], with no effect on glycated hemoglobin and waist circumference. No studies reported on diabetes incidence. Qualitative studies highlighted the need for app personalization.

DISCUSSION

Smartphone apps have a promising effect on preventing type 2 diabetes by supporting weight loss. Future robust trials should include diverse populations in co-design and evaluation of apps and explore the role of artificial intelligence in further personalizing interventions for higher engagement and effectiveness.

Effectiveness of artificial intelligence vs. human coaching in diabetes prevention: a study protocol for a randomized controlled trial

BACKGROUND

Prediabetes is a highly prevalent condition that heralds an increased risk of progression to type 2 diabetes, along with associated microvascular and macrovascular complications. The Diabetes Prevention Program (DPP) is an established effective intervention for diabetes prevention. However, participation in this 12-month lifestyle change program has historically been low. Digital DPPs have emerged as a scalable alternative, accessible asynchronously and recognized by the Centers for Disease Control and Prevention (CDC). Yet, most digital programs still incorporate human coaching, potentially limiting scalability. Furthermore, existing effectiveness results of digital DPPs are primarily derived from per protocol, longitudinal non-randomized studies, or comparisons to control groups that do not represent the standard of care DPP. The potential of an AI-powered DPP as an alternative to the DPP is yet to be investigated. We propose a randomized controlled trial (RCT) to directly compare these two approaches.

METHODS

This open-label, multicenter, non-inferiority RCT will compare the effectiveness of a fully automated AI-powered digital DPP (ai-DPP) with a standard of care human coach-based DPP (h-DPP). A total of 368 participants with elevated body mass index (BMI) and prediabetes will be randomized equally to the ai-DPP (smartphone app and Bluetooth-enabled body weight scale) or h-DPP (referral to a CDC recognized DPP). The primary endpoint, assessed at 12 months, is the achievement of the CDC's benchmark for type 2 diabetes risk reduction, defined as any of the following: at least 5% weight loss, at least 4% weight loss and at least 150 min per week on average of physical activity, or at least a 0.2-point reduction in hemoglobin A1C. Physical activity will be objectively measured using serial actigraphy at baseline and at 1-month intervals throughout the trial. Secondary endpoints, evaluated at 6 and 12 months, will include changes in A1C, weight, physical activity measures, program engagement, and cost-effectiveness. Participants include adults aged 18-75 years with laboratory confirmed prediabetes, a BMI of ≥ 25 kg/m2 (≥ 23 kg/m2 for Asians), English proficiency, and smartphone users. This U.S. study is conducted at Johns Hopkins Medicine in Baltimore, MD, and Reading Hospital (Tower Health) in Reading, PA.

DISCUSSION

Prediabetes is a significant public health issue, necessitating scalable interventions for the millions affected. Our pragmatic clinical trial is unique in directly comparing a fully automated AI-powered approach without direct human coach interaction. If proven effective, it could be a scalable, cost-effective strategy. This trial will offer vital insights into both AI and human coach-based behavioral change strategies in real-world clinical settings.

TRIAL REGISTRATION

ClinicalTrials.gov NCT05056376. Registered on September 24, 2021, https://clinicaltrials.gov/study/NCT05056376.

Digital interventions for self-management of prediabetes: A scoping review

BACKGROUND

Rates of prediabetes, which can lead to type 2 diabetes, are increasing worldwide. Interventions for prediabetes mainly focus on lifestyle changes to diet and exercise. While these interventions are effective, they are often delivered face-to-face, which may pose a barrier to those with limited access to healthcare. Given the evidence for digital interventions addressing other noncommunicable diseases, these may also be effective for prediabetes self-management. The aim of this scoping review was to assess the breadth of evidence around digital interventions for prediabetes self-management.

METHODS

We developed a targeted search strategy and relevant studies were identified through searches conducted in four bibliographic databases (Medline, Embase, PsycInfo, and Scopus). Published studies were eligible if they included a digital intervention to support adults aged 18+ with prediabetes self-management. Titles and abstracts were first screened for relevance by one researcher. Full texts of selected records were assessed against the review criteria independently by two researchers for inclusion in the final analysis.

RESULTS

Twenty-nine studies were included, of which nine were randomised controlled trials. Most efficacy studies reported significant changes in at least one primary and/or secondary outcome, including participants' glycaemic control, weight loss and/or physical activity levels. About one-third of studies reported mixed outcomes or early significant outcomes that were not sustained at long-term follow-up. Interventions varied in length, digital modalities, and complexity. Delivery formats included text messages, mobile apps, virtually accessible dietitians/health coaches, online peer groups, and web-based platforms. Approximately half of studies assessed participant engagement/acceptability outcomes.

CONCLUSION

Whilst the evidence here suggests that digital interventions to support prediabetes self-management are acceptable and have the potential to reduce one's risk of progression to type 2 diabetes, more research is needed to understand which interventions, and which components specifically, have the greatest reach to diverse populations, are most effective at promoting user engagement, and are most effective in the longer term.

Lifestyle Intervention With Smartphone App and isCGM for People at High Risk of Type 2 Diabetes: Randomized Trial

AIMS

Although conventional interventions for people at high risk of developing type 2 diabetes are usually conducted face-to-face, such interventions are burdensome for health care providers. We developed a lifestyle intervention program combining lifestyle coaching via a smartphone application augmented by intermittently scanned continuous glucose monitoring without burdening health care providers. Its effectiveness for glycemic control and body weight reduction in people at risk of type 2 diabetes was investigated.

MATERIALS AND METHODS

For this 12-week randomized unblinded trial with offline recruitment, participants with a hemoglobin A1c level of 5.6% to 6.4% or a fasting blood glucose of 110 to 125 mg/dL and body mass index (BMI) >23 kg/m2 but <40 kg/m2 were randomly assigned to the intervention group (App) and control group (C). The primary endpoint was the difference in time in range of blood glucose between 70 and 140 mg/dL (3.9-7.8 mmol/L) before and after the study period between the 2 groups.

RESULTS

Among 168 patients (mean age, 48.1 years; mean BMI, 26.6 kg/m2; and male, 80.4%), 82 and 86 were assigned to the App group and C group, respectively. After 12 weeks, time in range of blood glucose at 70 to 140 mg/dL significantly improved in the App group compared with the C group (-2.6 minutes/day vs +31.5 minutes/day, P = .03). Changes in time above range did not differ, whereas time below range (blood glucose <70 mg/dL; +23.5 minutes/day vs -8.9 minutes/day, P = .02) improved in the App group. BMI (-0.26 vs -0.59, P = .017) was reduced in the App group compared with the C group.

CONCLUSION

Intervention with a smartphone app and intermittently scanned continuous glucose monitoring increased glycemic control accompanied by decreased carbohydrate intake and weight loss. Further trials are needed to confirm whether these interventions can reduce incident type 2 diabetes.

A Digitally Enabled Combined Lifestyle Intervention for Weight Loss: Pilot Study in a Dutch General Population Cohort

BACKGROUND

Overweight and obesity rates among the general population of the Netherlands keep increasing. Combined lifestyle interventions (CLIs) focused on physical activity, nutrition, sleep, and stress management can be effective in reducing weight and improving health behaviors. Currently available CLIs for weight loss (CLI-WLs) in the Netherlands consist of face-to-face and community-based sessions, which face scalability challenges. A digitally enabled CLI-WL with digital and human components may provide a solution for this challenge; however, the feasibility of such an intervention has not yet been assessed in the Netherlands.

OBJECTIVE

The aim of this study was two-fold: (1) to determine how weight and other secondary cardiometabolic outcomes (lipids and blood pressure) change over time in a Dutch population with overweight or obesity and cardiometabolic risk participating in a pilot digitally enabled CLI-WL and (2) to collect feedback from participants to guide the further development of future iterations of the intervention.

METHODS

Participants followed a 16-week digitally enabled lifestyle coaching program rooted in the Fogg Behavior Model, focused on nutrition, physical activity, and other health behaviors, from January 2020 to December 2021. Participants could access the digital app to register and track health behaviors, weight, and anthropometrics data at any time. We retrospectively analyzed changes in weight, blood pressure, and lipids for remeasured users. Surveys and semistructured interviews were conducted to assess critical positive and improvement points reported by participants and health care professionals.

RESULTS

Of the 420 participants evaluated at baseline, 53 participated in the pilot. Of these, 37 (70%) were classified as overweight and 16 (30%) had obesity. Mean weight loss of 4.2% occurred at a median of 10 months postintervention. The subpopulation with obesity (n=16) showed a 5.6% weight loss on average. Total cholesterol decreased by 10.2% and low-density lipoprotein cholesterol decreased by 12.9% on average. Systolic and diastolic blood pressure decreased by 3.5% and 7.5%, respectively. Participants identified the possibility of setting clear action plans to work toward and the multiple weekly touch points with coaches as two of the most positive and distinctive components of the digitally enabled intervention. Surveys and interviews demonstrated that the digital implementation of a CLI-WL is feasible and well-received by both participants and health care professionals.

CONCLUSIONS

Albeit preliminary, these findings suggest that a behavioral lifestyle program with a digital component can achieve greater weight loss than reported for currently available offline CLI-WLs. Thus, a digitally enabled CLI-WL is feasible and may be a scalable alternative to offline CLI-WL programs. Evidence from future studies in a Dutch population may help elucidate the mechanisms behind the effectiveness of a digitally enabled CLI-WL.

Multimodal digital phenotyping of diet, physical activity, and glycemia in Hispanic/Latino adults with or at risk of type 2 diabetes

Digital phenotyping refers to characterizing human bio-behavior through wearables, personal devices, and digital health technologies. Digital phenotyping in populations facing a disproportionate burden of type 2 diabetes (T2D) and health disparities continues to lag compared to other populations. Here, we report our study demonstrating the application of multimodal digital phenotyping, i.e., the simultaneous use of CGM, physical activity monitors, and meal tracking in Hispanic/Latino individuals with or at risk of T2D. For 14 days, 36 Hispanic/Latino adults (28 female, 14 with non-insulin treated T2D) wore a continuous glucose monitor (CGM) and a physical activity monitor (Actigraph) while simultaneously logging meals using the MyFitnessPal app. We model meal events and daily digital biomarkers representing diet, physical activity choices, and corresponding glycemic response. We develop a digital biomarker for meal events that differentiates meal events into normal and elevated categories. We examine the contribution of daily digital biomarkers of elevated meal event count and step count on daily time-in-range 54-140 mg/dL (TIR54-140) and average glucose. After adjusting for step count, a change in elevated meal event count from zero to two decreases TIR54-140 by 4.0% (p = 0.003). An increase in 1000 steps in post-meal step count also reduces the meal event glucose response by 641 min mg/dL (p = 0.0006) and reduces the odds of an elevated meal event by 55% (p < 0.0001). The proposed meal event digital biomarkers may provide an opportunity for non-pharmacologic interventions for Hispanic/Latino adults facing a disproportionate burden of T2D.

Effectiveness of a group-based Diabetes Prevention Education Program (DiPEP) in a population with pre-diabetes: a cluster randomised controlled trial in Nepal

Background

Although several lifestyle intervention studies have been conducted in low/middle-income countries, there were no such studies in Nepal. Therefore, a group-based culturally tailored Diabetes Prevention Education Program (DiPEP) was conducted recently. The study aimed to evaluate the effect of DiPEP in glycated haemoglobin (HbA1c), weight, waist circumference, physical activity and diet among population with pre-diabetes.

Method

A two-arm cluster randomised controlled trial was conducted in 12 clusters of two urban areas in Nepal. The DiPEP was a 6 month intervention (four 1-hour weekly educational sessions and 5 months of follow-up by community health workers/volunteers (CHW/Vs)). A postintervention assessment was done after 6 months. Linear mixed model was used to estimate the mean difference in primary outcome (HbA1c) and secondary outcomes (weight, waist circumference, physical activity and diet) between intervention and control arms, adjusted for baseline measure.

Results

In intention-to-treat analysis with a total of 291 participants, the estimated mean difference in HbA1c was found to be 0.015 percentage point (95% CI -0.074 to 0.104) between the intervention arm and the control arm, while it was -0.077 (95% CI -0.152 to -0.002) among those who attended at least 3 out of 4 educational sessions. The estimated mean difference in weight (in participants who attended ≥1 educational session) was -1.6 kg (95% CI -3.1 to -0.1). A significantly lower grain consumption was found in intervention arm (-39 g/day, 95% CI -65 to -14) compared with the control arm at postintervention assessment.

Conclusion

Although compliance was affected by COVID-19, individuals who participated in ≥3 educational sessions had significant reduction in HbA1c and those who attended ≥1 educational session had significant weight reduction. Grain intake was significantly reduced among the intervention arm than the control arm. Hence, group-based lifestyle intervention programmes involving CHW/vs is recommended for diabetes prevention.

Trial registration number

NCT04074148.

Changes in Prediabetes Status Among Adults During a 6-Month Randomized Placebo-controlled Supplement Trial With Nutrition and Lifestyle Counselling and 6-Month Follow-up

OBJECTIVES

In this work, we present an exploratory within-trial analysis of the changing prevalence of prediabetes in response to nutrition and lifestyle counselling provided as part of a randomized placebo-controlled supplement trial with follow-up. We aimed to identify factors associated with changing glycemia status.

METHODS

Participants (n=401) in this clinical trial were adults with a body mass index (BMI) of ≥25 kg/m2 and prediabetes (defined by the American Diabetes Association as a fasting plasma glucose [FPG] of 5.6 to 6.9 mmol/L or a glycated hemoglobin [A1C] of 5.7% to 6.4%) within 6 months before trial entry. The trial consisted of a 6-month randomized intervention with 2 dietary supplements and/or placebo. At the same time, all participants received nutrition and lifestyle counselling. This was followed by a 6-month follow-up. Glycemia status was assessed at baseline and at 6 and 12 months.

RESULTS

At baseline, 226 participants (56%) met a threshold for prediabetes, including 167 (42%) with elevated FPG and 155 (39%) with elevated A1C. After the 6-month intervention, the prevalence of prediabetes decreased to 46%, driven by a reduction in prevalence of elevated FPG to 29%. The prevalence of prediabetes then increased to 51% after follow-up. Risk of prediabetes was associated with older age (odds ratio [OR], 1.05; p<0.01), BMI (OR, 1.06; p<0.05), and male sex (OR, 1.81; p=0.01). Participants who reverted to normoglycemia had greater weight loss and lower baseline glycemia.

CONCLUSIONS

Glycemia status can fluctuate over time and improvements can be gained from lifestyle interventions, with certain factors associated with a higher likelihood of reverting to normoglycemia.

Weight loss maintenance after a digital commercial behavior change program (Noom Weight): Observational cross-sectional survey study

Background

Behavioral weight loss programs often lead to significant short-term weight loss, but long-term weight maintenance remains a challenge. Most weight maintenance data come from clinical trials, in-person programs, or general population surveys, but there is a need for better understanding of long-term weight maintenance in real-world digital programs.

Methods

This observational survey study examined weight maintenance reported by individuals who had used Noom Weight, a digital commercial behavior change program, and identified factors associated with greater weight maintenance. The cross-sectional survey was completed by 840 individuals who had lost at least 10% of their body weight using Noom Weight 6-24 months prior.

Results

The study found that 75% of individuals maintained at least 5% weight loss after 1 year, and 49% maintained 10% weight loss. On average, 65% of initial weight loss was maintained after 1 year and 57% after 2 years. Habitual behaviors, such as healthy snacking and exercise, were associated with greater weight maintenance, while demographic factors were not.

Conclusion

This study provides real-world data on the long-term weight maintenance achieved using a fully digital behavioral program. The results suggest that Noom Weight is associated with successful weight maintenance in a substantial proportion of users. Future research will use a randomized controlled trial to track weight maintenance after random assignment and at a 2 year follow-up.

Effectiveness of the Telemedical Lifestyle Intervention Program TeLIPro for Improvement of HbA1c in Type 2 Diabetes: A Randomized-Controlled Trial in a Real-Life Setting

The effectiveness of the multimodal Telemedical Lifestyle Intervention Program (TeLIPro) was proven in the advanced stages of type 2 diabetes mellitus (T2DM). Since its therapeutic potential focusing on telemedical coaching without using a formula diet is unknown, we evaluated improvements in HbA1c, HbA1c normalisation rate, cardiometabolic risk factors, quality-of-life, and eating behaviour in real life. In this randomized-controlled trial, AOK Rhineland/Hamburg insured T2DM patients (n = 1163) were randomized (1:1) into two parallel groups, and 817 received the allocated intervention. In addition to routine care, all participants got scales, step counters, and access to an online portal. The TeLIPro group additionally received equipment for self-monitoring of blood glucose and telemedical coaching. Data were collected at baseline, after 6 and 12 months of intervention as well as after a 6-month follow-up. The primary endpoint after 12 months was (i) the estimated treatment difference (ETD) in HbA1c change and (ii) the HbA1c normalisation rate in those with diabetes duration < 5 years. The TeLIPro group demonstrated significantly stronger improvements in HbA1c (ETD -0.4% (-0.5; -0.2); p < 0.001), body weight, body-mass-index, quality-of-life, and eating behaviour, especially in T2DM patients with diabetes duration ≥ 5 years (ETD -0.5% (-0.7; -0.3); p < 0.001). The HbA1c normalisation rate did not significantly differ between groups (25% vs. 18%). Continuous addition of TeLIPro to routine care is effective in improving HbA1c and health-related lifestyle in T2DM patients with longer diabetes duration in real life.

Engagement with a nationally-implemented digital behaviour change intervention: Usage patterns over the 9-month duration of the National Health Service Digital Diabetes Prevention Programme

Background

Digital behaviour change interventions may offer a scalable way to promote weight loss by increasing physical activity and improving diet. However, user engagement is necessary for such benefits to be achieved. There is a dearth of research that assesses engagement with nationally implemented digital programmes offered in routine practice. The National Health Service Digital Diabetes Prevention Programme (NHS-DDPP) is a nine-month digital behaviour change intervention delivered by independent providers for adults in England who are at high risk of developing type 2 diabetes. This study reports engagement with the NHS-DDPP for users enrolled onto the programme over the nine-month duration.

Methods

Anonymous usage data was obtained for a cohort of service users (n = 1826) enrolled on the NHS-DDPP with three independent providers, between December 2020 and June 2021. Usage data were obtained for time spent in app, and frequency of use of NHS-DDPP intervention features in the apps including self-monitoring, goal setting, receiving educational content (via articles) and social support (via health coaches and group forums), to allow patterns of usage of these key features to be quantified across the nine-month intervention. Median usage was calculated within nine 30-day engagement periods to allow a longitudinal analysis of the dose of usage for each feature.

Results

App usage declined from a median of 32 min (IQR 191) in month one to 0 min (IQR 14) in month nine. Users self-monitored their behaviours (e.g., physical activity and diet) a median of 117 times (IQR 451) in the apps over the nine-month programme. The open group discussion forums were utilised less regularly (accessed a median of 0 times at all time-points). There was higher engagement with some intervention features (e.g., goal setting) when support from a health coach was linked to those features.

Conclusions

App usage decreased over the nine-month programme, although the rate at which the decrease occurred varied substantially between individuals and providers. Health coach support may promote engagement with specific intervention features. Future research should assess whether engagement with particular features of digital diabetes prevention programmes is associated with outcomes such as reduced bodyweight and HbA1c levels.

The Effect of Including eHealth in Dietary Interventions for Patients with Type 2 Diabetes with Overweight or Obesity: A Systematic Review

eHealth has a growing impact on the delivery of healthcare, making health systems more efficient. This study examined the effect of dietary interventions using eHealth compared to face-to-face contact in patients with (pre-) type 2 diabetes (T2D) and who are overweight/obese. Literature databases were searched upon November 2022. Inclusion criteria: randomized controlled trial; duration ≥ 6 months; involving dietary interventions; performed in adults with (pre-) T2D and who are overweight/obese; using eHealth compared to face-to-face contact; and report outcomes on weight loss, glycemic regulation, and/or cost-effectiveness. Selection of articles was performed manually and using ASReviewLab. Fifteen studies were included for data extraction, investigating a wide variety of eHealth interventions. Seven studies reporting on weight loss showed a significant between-group difference (-1.18 to -5.5 kg); five studies showed a trend in favor of the eHealth programs. Eleven studies reported on HbA1c; three found a significant between-group difference (-0.23 to -0.70%) in favor of the eHealth programs and six studies showed non-significant improvements. Interaction with healthcare professionals led to better results of the dietary interventions. Two studies reported incomplete data on cost-effectiveness. In conclusion, eHealth shows better results of dietary interventions in (pre-) T2D patients compared to face-to-face, especially when combined with interaction with healthcare professionals.

The Impact of a Digital Weight Loss Intervention on Health Care Resource Utilization and Costs Compared Between Users and Nonusers With Overweight and Obesity: Retrospective Analysis Study

BACKGROUND

The Noom Weight program is a smartphone-based weight management program that uses cognitive behavioral therapy techniques to motivate users to achieve weight loss through a comprehensive lifestyle intervention.

OBJECTIVE

This retrospective database analysis aimed to evaluate the impact of Noom Weight use on health care resource utilization (HRU) and health care costs among individuals with overweight and obesity.

METHODS

Electronic health record data, insurance claims data, and Noom Weight program data were used to conduct the analysis. The study included 43,047 Noom Weight users and 14,555 non-Noom Weight users aged between 18 and 80 years with a BMI of ≥25 kg/m² and residing in the United States. The index date was defined as the first day of a 3-month treatment window during which Noom Weight was used at least once per week on average. Inverse probability treatment weighting was used to balance sociodemographic covariates between the 2 cohorts. HRU and costs for inpatient visits, outpatient visits, telehealth visits, surgeries, and prescriptions were analyzed.

RESULTS

Within 12 months after the index date, Noom Weight users had less inpatient costs (mean difference [MD] -US $20.10, 95% CI -US $30.08 to -US $10.12), less outpatient costs (MD -US $124.33, 95% CI -US $159.76 to -US $88.89), less overall prescription costs (MD -US $313.82, 95% CI -US $565.42 to -US $62.21), and less overall health care costs (MD -US $450.39, 95% CI -US $706.28 to -US $194.50) per user than non-Noom Weight users. In terms of HRU, Noom Weight users had fewer inpatient visits (MD -0.03, 95% CI -0.04 to -0.03), fewer outpatient visits (MD -0.78, 95% CI -0.93 to -0.62), fewer surgeries (MD -0.01, 95% CI -0.01 to 0.00), and fewer prescriptions (MD -1.39, 95% CI -1.76 to -1.03) per user than non-Noom Weight users. Among a subset of individuals with 24-month follow-up data, Noom Weight users incurred lower overall prescription costs (MD -US $1139.52, 95% CI -US $1972.21 to -US $306.83) and lower overall health care costs (MD -US $1219.06, 95% CI -US $2061.56 to -US $376.55) per user than non-Noom Weight users. The key differences were associated with reduced prescription use.

CONCLUSIONS

Noom Weight use is associated with lower HRU and costs than non-Noom Weight use, with potential cost savings of up to US $1219.06 per user at 24 months after the index date. These findings suggest that Noom Weight could be a cost-effective weight management program for individuals with overweight and obesity. This study provides valuable evidence for health care providers and payers in evaluating the potential benefits of digital weight loss interventions such as Noom Weight.

The Association Between Goal Setting and Weight Loss: Prospective Analysis of a Community Weight Loss Program

BACKGROUND

Goal setting aids health-related behavior changes; however, the influence of different types of goals on weight loss remains unclear.

OBJECTIVE

We aimed to investigate the association of 3 aspects of goal setting with weight and program dropout over a 24-week period.

METHODS

This study was a prospective longitudinal analysis of participants in a 12-week digital behavioral weight loss program. Weight and engagement data for eligible participants (N=36,794) were extracted from the database. Eligible participants were adults in the United Kingdom who had enrolled in the program, had a BMI ≥25 kg/m², and a weight reading recorded at baseline. Three aspects of goal setting were self-reported at enrollment: weight loss motivation (appearance, health, fitness, or self-efficacy), overall goal preference (low, medium, or high), and percentage weight loss goal (<5%, 5%-10%, or >10%). Weight was measured at 4, 12, and 24 weeks. Mixed models for repeated measures were used to explore the association between goals and weight across the 24-week period. To measure sustained weight change, the primary outcome was weight at 24 weeks. We explored dropout rates over the 24-week period by goal and whether engagement mediated the association between goals and weight loss.

RESULTS

Of the 36,794 participants (mean 46.7, SD 11.1 years; 33,902/36,794, 92.14% female) included in the cohort, 13.09% (n=4818) reported weight at 24 weeks. Most participants set goals of 5%-10% weight loss (23,629/36,794, 64.22%), but setting goals for >10% was associated with greater weight loss (mean difference 5.21 kg, 95% CI 5.01-5.41; P<.001). There was no difference between goals of 5%-10% and <5% (mean difference 0.59 kg, 95% CI 0.00-1.18; P=.05). Appearance was the most prevalent motivational factor (14,736/36,794, 40.05%), but health and fitness were associated with greater weight losses (mean difference health vs appearance 1.40 kg, 95% CI 1.15-1.65; P<.001 and mean difference fitness vs appearance 0.38 kg, 95% CI 0.05-0.70; P=.03). Goal preference had no association with weight. Engagement was an independent predictor of weight loss but not a mediator of the effect of goal setting. At 24 weeks, those who set goals of >10% were less likely to drop out compared with 5%-10% goals (odds ratio [OR] 0.40, 95% CI 0.38-0.42; P<.001); those who liked to set overall high goals were more likely to drop out compared with medium goals (OR 1.20, 95% CI 1.11-1.29; P<.001); and those motivated by fitness or health were less likely to drop out compared with appearance (OR 0.92, 95% CI 0.85-0.995; P=.04 and OR 0.84, 95% CI 0.78-0.89; P<.001, respectively).

CONCLUSIONS

Setting higher weight loss goals and being motivated by health or fitness were associated with greater weight loss and lower likelihood of dropout. Randomized trials for setting these types of goals are required to confirm causality.

Cost and cost-effectiveness analysis of a digital diabetes prevention program: results from the PREDICTS trial

Although technology-assisted diabetes prevention programs (DPPs) have been shown to improve glycemic control and weight loss, information are limited regarding relevant costs and their cost-effectiveness. To describe a retrospective within-trial cost and cost-effectiveness analysis (CEA) to compare a digital-based DPP (d-DPP) with small group education (SGE), over a 1-year study period. The costs were summarized into direct medical costs, direct nonmedical costs (i.e., times that participants spent engaging with the interventions), and indirect costs (i.e., lost work productivity costs). The CEA was measured by the incremental cost-effectiveness ratio (ICER). Sensitivity analysis was performed using nonparametric bootstrap analysis. Over 1 year, the direct medical costs, direct nonmedical costs, and indirect costs per participant were $4,556, $1,595, and $6,942 in the d-DPP group versus $4,177, $1,350, and $9,204 in the SGE group. The CEA results showed cost savings from d-DPP relative to SGE based on a societal perspective. Using a private payer perspective for d-DPP, ICERs were $4,739 and $114 to obtain an additional unit reduction in HbA1c (%) and weight (kg), and were $19,955 for an additional unit gain of quality-adjusted life years (QALYs) compared to SGE, respectively. From a societal perspective, bootstrapping results indicated that d-DPP has a 39% and a 69% probability, at a willingness-to-pay of $50,000/QALY and $100,000/QALY, respectively, of being cost-effective. The d-DPP was cost-effective and offers the prospect of high scalability and sustainability due to its program features and delivery modes, which can be easily translated to other settings.

Effects of a digital diabetes prevention program on cardiovascular risk among individuals with prediabetes

OBJECTIVE

To examine changes in cardiovascular disease (CVD) risk outcomes of overweight/obese adults with prediabetes.

METHODS

Using data from a randomized control trial of digital diabetes prevention program (d-DPP) with 599 participants. We applied the atherosclerotic CVD (ASCVD) risk calculator to predict 10-year CVD risk for d-DPP and small education (comparison) groups. Between-group risk changes at 4 and 12 months were compared using a repeated measures linear mixed-effect model. We examined within-group differences in proportion of participants over time for specific CVD risk factors using generalized estimating equations.

RESULTS

We found no differences between baseline 10-year ASCVD risk. Relative to the comparison group, the d-DPP group experienced greater reductions in predicted 10-year ASCVD risk at each follow-up visit and a significant group difference at 4 months (-0.96%; 95% confidence interval: -1.58%, -0.34%) (but not at 12 months). Additionally, we observed that the d-DPP group experienced a decreased proportion of individuals with hyperlipidemia (18% and 16% from baseline to 4 and 12 months), high-risk total cholesterol (8% from baseline to 12 months), and being insufficiently active (26% and 22% from baseline to 4 and 12 months at follow-up time points.

CONCLUSIONS

Our findings suggest that a digitally adapted DPP may promote the prevention of cardiometabolic disease among overweight/obese individuals with prediabetes. However, given the lack of maintenance of effect on ASCVD risk at 12 months, there may also be a need for additional interventions to sustain the effect detected at 4 months.

Mobile health lifestyle intervention program leads to clinically significant loss of body weight in patients with NASH

BACKGROUND AIMS

Lifestyle intervention remains the foundation of clinical care for patients with NASH; however, most patients are unsuccessful in enacting sustained behavioral change. There remains a clear unmet need to develop lifestyle intervention programs to support weight loss. Mobile health (mHealth) programs offer promise to address this need, yet their efficacy remains unexplored.

APPROACH RESULTS

We conducted a 16-week randomized controlled clinical trial involving adults with NASH. Patients were randomly assigned (1:1 ratio) to receive Noom Weight (NW), a mHealth lifestyle intervention program, or standard clinical care. The primary end point was a change in body weight. Secondary end points included feasibility (weekly app engagement), acceptability (>50% approached enrolled), and safety. Of 51 patients approached, 40 (78%) were randomly assigned (20 NW and 20 standard clinical care). NW significantly decreased body weight when compared to standard clinical care (-5.5 kg vs. -0.3 kg, p = 0.008; -5.4% vs. -0.4%, p = 0.004). More NW subjects achieved a clinically significant weight loss of ≥5% body weight (45% vs. 15%, p = 0.038). No adverse events occurred, and the majority (70%) of subjects in the NW arm met the feasibility criteria.

CONCLUSIONS

This clinical trial demonstrated that NW is not only feasible, acceptable, and safe but also highly efficacious because this mHealth lifestyle intervention program led to significantly greater body weight loss than standard clinical care. Future large-scale studies are required to validate these findings with more representative samples and to determine if mHealth lifestyle intervention programs can lead to sustained, long-term weight loss in patients with NASH.

The Efficacy of Mobile Applications for Weight Loss

Purpose of Review

A variety of mobile-based applications aimed at weight loss have become popular in recent years. This review describes the features and effectiveness of mobile weight loss apps.

Recent Findings

Overall, mobile apps can help patients lose weight either as well as or better than traditional paper-and-pencil weight loss interventions and often better than minimal intervention control groups. Mobile apps promote multiple strategies, including self-monitoring of diet, exercise, and weight, as well as social support and educational content. Significant variation exists in app types, which makes it difficult to conclude which features drive program effectiveness. Intervention success varies based on patients’ level of engagement with the app. There is a deficit of apps and app-based studies of older, less tech-savvy adults, ethnic/racial minorities, and low-income individuals, as well as longer-term studies.

Summary

Mobile apps can successfully help patients lose weight and represent a cost-effective, accessible alternative to intensive in-person weight loss programs. More research is needed into their long-term potential, especially for hard-to-reach populations.

Analyzing the Effectiveness of mHealth to Manage Diabetes Mellitus Among Adults Over 50: A Systematic Literature Review

Purpose

A total of 537 million suffered from diabetes mellitus in 2021, and the aging of the population will not abate this number in the future. Diabetes predisposes people to ailments and doubles the risk of COVID-19 mortality. mHealth has shown promise to help manage diabetes. The aim of this review is to objectively analyze research from the last 2.5 years to assess effectiveness where mHealth has been used as an intervention to help manage diabetes in older patients. We also analyzed patient satisfaction, quality, and barriers to adoption of mHealth to manage diabetes.

Patients and Methods

No human subjects were involved in this review. We queried four research databases for mHealth to manage diabetes in older adults. We conducted the review based on the Kruse Protocol for writing as systematic review and we reported our findings in accordance with PRISMA (2020).

Results

Thirty research articles from 11 countries were analyzed. Five interventions of mHealth were identified. Of these mHealth Short Message service (SMS) helped change behavior and encouraged self-care. mHealth SMS coupled with telemedicine for coaching showed positive effects on weight loss, BMI, diet, exercise, HbA1C, disease awareness, blood pressure, cholesterol, medication adherence, and foot care.

Conclusion

mHealth SMS coupled with telemedicine for coaching shows the greatest promise for educating, changing behavior, and realizing positive outcomes across a broad spectrum of health factors. The largest drawback is the cost of acquiring equipment and training users.

Predictive capacity of COVID-19-related risk beliefs on weight management behaviors on a commercial weight loss program and speed of COVID-19 vaccination uptake: prospective cohort study

BACKGROUND

Recent work has shown that obesity may be a risk factor for severe COVID-19. However, it is unclear to what extent individuals have heard or believe this risk factor information, and how these beliefs may predict their preventive behaviors (e.g., weight management behaviors or COVID-19 preventive behaviors). Previous work has primarily looked at overall risk likelihood perceptions (i.e., not about obesity as a risk factor) within general populations of varying weight and concentrated on COVID-19-related preventive behaviors. Therefore, this prospective cohort study explored whether beliefs about obesity as a risk factor and overall risk likelihood perceptions predicted weight management and COVID-19 preventive behaviors over the next 16 weeks in individuals with obesity or overweight.

METHODS

Participants were 393 individuals in the US who joined a commercial weight management program in January, 2021. We leveraged the mobile program's automatic measurement of real-time engagement in weight management behaviors (e.g., steps taken), while surveys measured risk beliefs at baseline as well as when individuals received COVID-19 vaccination doses (asked monthly) over the next 16 weeks. Mixed effects models predicted engagement and weight loss each week for 16 weeks, while ordinal logistic regression models predicted the month that individuals got vaccinated against COVID-19.

RESULTS

We found that belief in obesity as a risk factor at baseline significantly predicted greater engagement (e.g., steps taken, foods logged) in program-measured weight management behaviors over the next 16 weeks in models adjusted for baseline BMI, age, gender, and local vaccination rates (minimally adjusted) and in models additionally adjusted for demographic factors. Belief in obesity as a risk factor at baseline also significantly predicted speed of COVID-19 vaccination uptake in minimally adjusted models but not when demographic factors were taken into account. Exposure to obesity risk factor information at baseline predicted greater engagement over 16 weeks in minimally adjusted models.

CONCLUSIONS

The results highlight the potential utility of effective education to increase individuals' belief in obesity risk factor information and ultimately promote engagement or faster vaccination. Future research should investigate to what extent the results generalize to other populations.

An early interactive human coaching via a mobile application to improve quality of life in patients who underwent gastrectomy for gastric cancer: Design and protocol of a randomized controlled trial

BACKGROUND

After gastrectomy, patients may experience the postgastrectomy syndrome and face difficulties adapting to everyday diet. Recently, human health coaching via a mobile application (app) has been used for obese patients or patients with chronic diseases, with significant improvements in clinical outcomes. The aim of this study is to evaluate and compare the effects of human health coaching via a mobile app and conventional face-to-face counseling in patients who underwent gastrectomy for gastric cancers.

METHODS

This study is a single-institution, prospective randomized controlled trial comparing the mobile health and face-to-face counselling groups. After randomization, participants assigned to the mobile health coaching group will receive health coaching via a mobile app for 3 months after discharge, and the assigned coaches will provide personalized advice based on the self-recorded health data. Participants in the face-to-face group will have 1- and 3-months postoperative dietary consultations with a clinical dietitian. The primary endpoint is the food restriction score on the European Organization for Research and Treatment of Cancer Quality of Life Questionnaire-STO22, and secondary endpoints included all other quality of life scale scores and nutritional parameters. The calculated sample size is 180, and the outcomes will be measured until 1-year post-surgery.

SIGNIFICANCE

This study will show the efficacy of human health coaching via a mobile app on dietary adaptation in patients who underwent gastrectomy. A relational approach based on personal data and timely intervention using a mobile platform could reduce patients' trial and error and improve quality of life.

TRIAL REGISTRATION

ClinicalTrials.gov, NCT04394585, Registered 19 May, 2020 -Retrospectively registered, http://clinicaltrials.gov/ct2/show/NCT040394585.

The Use of Mobile Health Interventions for Outcomes among Middle-Aged and Elderly Patients with Prediabetes: A Systematic Review

BACKGROUND

There are currently limited systematic reviews of mobile health interventions for middle-aged and elderly patients with prediabetes from trial studies. This review aimed to gather and analyze information from experimental studies investigating the efficacy of mobile health usability for outcomes among middle-aged and elderly patients with prediabetes.

METHODS

We conducted a literature search in five databases: Clinicaltrials.gov, the International Clinical Trials Registry Platform (ICTRP), PubMed, ProQuest, and EBSCO, with a date range of January 2007 to July 2022 written in English, following a registered protocol on PROSPERO (CRD42022354351). The quality and possibility of bias were assessed using the Jadad score. The data extraction and analysis were conducted in a methodical manner.

RESULTS

A total of 25 studies were included in the qualitative synthesis, with 19 studies using randomized trial designs and 6 studies with non-randomized designs. The study outcomes were the incidence of diabetes mellitus, anthropometric measures, laboratory examinations, measures of physical activity, and dietary behavior. During long-term follow-up, there was no significant difference between mobile health interventions and controls in reducing the incidence of type 2 diabetes. The findings of the studies for weight change, ≥3% and ≥5% weight loss, body mass index, and waist circumference changes were inconsistent. The efficacy of mobile health as an intervention for physical activity and dietary changes was lacking in conclusion. Most studies found that mobile health lacks sufficient evidence to change hbA1c. According to most of these studies, there was no significant difference in blood lipid level reduction.

CONCLUSIONS

The use of mobile health was not sufficiently proven to be effective for middle-aged and elderly patients with prediabetes.

Weight loss in a digital app-based diabetes prevention program powered by artificial intelligence

Objective

The National Diabetes Prevention Program (DPP) reduces diabetes incidence and associated medical costs but is typically staffing-intensive, limiting scalability. We evaluated an alternative delivery method with 3933 members of a program powered by conversational Artificial Intelligence (AI) called Lark DPP that has full recognition from the Centers for Disease Control and Prevention (CDC).

Methods

We compared weight loss maintenance at 12 months between two groups: 1) CDC qualifiers who completed ≥4 educational lessons over 9 months (n  =  191) and 2) non-qualifiers who did not complete the required CDC lessons but provided weigh-ins at 12 months (n  =  223). For a secondary aim, we removed the requirement for a 12-month weight and used logistic regression to investigate predictors of weight nadir in 3148 members.

Results

CDC qualifiers maintained greater weight loss at 12 months than non-qualifiers (M  =  5.3%, SE  =  .8 vs. M  =  3.3%, SE  =  .8; p  =  .015), with 40% achieving ≥5%. The weight nadir of 3148 members was 4.2% (SE  =  .1), with 35% achieving ≥5%. Male sex (β = .11; P  =  .009), weeks with ≥2 weigh-ins (β = .68; P < .0001), and days with an AI-powered coaching exchange (β = .43; P < .0001) were associated with a greater likelihood of achieving ≥5% weight loss.

Conclusions

An AI-powered DPP facilitated weight loss and maintenance commensurate with outcomes of other digital and in-person programs not powered by AI. Beyond CDC lesson completion, engaging with AI coaching and frequent weighing increased the likelihood of achieving ≥5% weight loss. An AI-powered program is an effective method to deliver the DPP in a scalable, resource-efficient manner to keep pace with the prediabetes epidemic.

A Pilot Study to Examine the Feasibility and Acceptability of a Virtual Adaptation of an In-Person Adolescent Diabetes Prevention Program

BACKGROUND

Rates of prediabetes and type 2 diabetes are alarmingly high among racial/ethnic minority youth. The current study examines the virtual adaptation of an in-person peer-led youth diabetes prevention program.

METHODS

The initial phase involved the study team adapting workshop sessions from an in-person to a virtual format (Zoom). We conducted a 2-h feasibility pilot in December 2020 and implemented the full 12 session pilot program from June to September 2021 with 14 prediabetic adolescents recruited from our hospital-based general pediatric clinic. Weekly sessions were led by trained peer educators and focused on promoting healthy eating and physical activity using behavioral techniques (e.g., goal setting, brainstorming, and problem solving).

RESULTS

The virtual adaptation of our program was shown to be feasible and acceptable among our pilot participants. We were able to deliver the same workshop content and behavioral skills development as the in-person workshop using a variety of Zoom features.

CONCLUSIONS

Our peer-led youth diabetes prevention program was successfully adapted and implemented in a virtual format and was well accepted by at-risk youth. Future research is needed to examine the impact of virtual youth lifestyle interventions on behavioral and clinical outcomes such as weight and diabetes risk.

Pragmatic randomized trial assessing the impact of digital health technology on quality of life in patients with heart failure: Design, rationale and implementation

BACKGROUND

Self-care and patient engagement are important elements of heart failure (HF) care, endorsed in the guidelines. Digital health tools may improve quality of life (QOL) in HF patients by promoting care, knowledge, and engagement. This manuscript describes the rationale and challenges of the design and implementation of a pragmatic randomized controlled trial to evaluate the efficacy of three digital health technologies in improving QOL for patients with HF.

HYPOTHESIS

We hypothesize that digital health interventions will improve QOL of HF patients through the early detection of warning signs of disease exacerbation, the opportunity of self-tracking symptoms, and the education provided, which enhances patient empowerment.

METHODS

Using a fully electronic enrollment and consent platform, the trial will randomize 200 patients across HF clinics in the Yale New Haven Health system to receive either usual care or one of three digital technologies designed to promote self-management and provide critical data to clinicians. The primary outcome is the change in QOL as assessed by the Kansas City Cardiomyopathy Questionnaire at 3 months.

RESULTS

First enrollment occurred in September 2021. Recruitment was anticipated to last 6-8 months and participants were followed for 6 months after randomization. Our recruitment efforts have highlighted the large digital divide in our population of interest.

CONCLUSION

Assessing clinical outcomes, patient usability, and ease of clinical integration of digital technologies will be beneficial in determining the feasibility of the integration of such technologies into the healthcare system.

Prevention of type 2 diabetes through remotely-administered lifestyle programs: A systematic review

BACKGROUND

Although effective in reducing the risk of type 2 diabetes (T2D), in-person lifestyle modification programs have been underutilized. To minimize barriers related to convenience and accessibility, recent research has focused on developing virtual or remote interventions that may have comparable or greater efficacy in promoting lifestyle changes and reducing the risk of T2D. We conducted a systematic review to evaluate the efficacy of remotely-administered lifestyle interventions on preventing T2D.

METHODS

We searched an electronic database by using keywords, and a web-based software platform was used to screen articles and extract data in duplicate. We included articles with adolescent/adult participant populations who had prediabetes or were at elevated risk of diabetes, remotely-administered lifestyle interventions on T2D prevention, and changes in glycemic traits. We excluded trials of patients with prevalent T2D, interventions that included medications, and those not relevant to our outcomes of interest.

RESULTS

A total of 8 publications were included in this systematic review. Six papers indicated significant reductions in weight and/or glycemic biomarkers such as HbA1c and fasting glucose. All studies reported that remotely-administered interventions were convenient for participants, and one publication reported that participation of the online DPP group was significantly higher than the in-person DPP.

CONCLUSION

These findings suggest that remotely-administered lifestyle interventions for T2D prevention could be a promising participant-friendly alternative to in-person programs, with efficacy for reducing weight and glycemic biomarkers.

Measurement of Adherence to mHealth Physical Activity Interventions and Exploration of the Factors That Affect the Adherence: Scoping Review and Proposed Framework

BACKGROUND

Mobile health (mHealth) is widely used as an innovative approach to delivering physical activity (PA) programs. Users' adherence to mHealth programs is important to ensure the effectiveness of mHealth-based programs.

OBJECTIVE

Our primary aim was to review the literature on the methods used to assess adherence, factors that could affect users' adherence, and the investigation of the association between adherence and health outcomes. Our secondary aim was to develop a framework to understand the role of adherence in influencing the effectiveness of mHealth PA programs.

METHODS

MEDLINE, PsycINFO, EMBASE, and CINAHL databases were searched to identify studies that evaluated the use of mHealth to promote PA in adults aged ≥18 years. We used critical interpretive synthesis methods to summarize the data collected.

RESULTS

In total, 54 papers were included in this review. We identified 31 specific adherence measurement methods, which were summarized into 8 indicators; these indicators were mapped to 4 dimensions: length, breadth, depth, and interaction. Users' characteristics (5 factors), technology-related factors (12 factors), and contextual factors (1 factor) were reported to have impacts on adherence. The included studies reveal that adherence is significantly associated with intervention outcomes, including health behaviors, psychological indicators, and clinical indicators. A framework was developed based on these review findings.

CONCLUSIONS

This study developed an adherence framework linking together the adherence predictors, comprehensive adherence assessment, and clinical effectiveness. This framework could provide evidence for measuring adherence comprehensively and guide further studies on adherence to mHealth-based PA interventions. Future research should validate the utility of this proposed framework.

Goal language is associated with attrition and weight loss on a digital program: Observational study

Behavioral weight loss reduces risk of weight-related health complications. Outcomes of behavioral weight loss programs include attrition and weight loss. There is reason to believe that individuals' written language on a weight management program may be associated with outcomes. Exploring associations between written language and these outcomes could potentially inform future efforts towards real-time automated identification of moments or individuals at high risk of suboptimal outcomes. Thus, in the first study of its kind, we explored whether individuals' written language in actual use of a program (i.e., outside of a controlled trial) is associated with attrition and weight loss. We examined two types of language: goal setting (i.e., language used in setting a goal at the start of the program) and goal striving (i.e., language used in conversations with a coach about the process of striving for goals) and whether they are associated with attrition and weight loss on a mobile weight management program. We used the most established automated text analysis program, Linguistic Inquiry Word Count (LIWC), to retrospectively analyze transcripts extracted from the program database. The strongest effects emerged for goal striving language. In striving for goals, psychologically distanced language was associated with more weight loss and less attrition, while psychologically immediate language was associated with less weight loss and higher attrition. Our results highlight the potential importance of distanced and immediate language in understanding outcomes like attrition and weight loss. These results, generated from real-world language, attrition, and weight loss (i.e., from individuals' natural usage of the program), have important implications for how future work can better understand outcomes, especially in real-world settings.

Evaluation of an adapted version of the Diabetes Prevention Program for low- and middle-income countries: A cluster randomized trial to evaluate "Lifestyle Africa" in South Africa

BACKGROUND

Low- and middle-income countries (LMICs) are experiencing major increases in diabetes and cardiovascular conditions linked to overweight and obesity. Lifestyle interventions such as the United States National Diabetes Prevention Program (DPP) developed in high-income countries require adaptation and cultural tailoring for LMICs. The objective of this study was to evaluate the efficacy of "Lifestyle Africa," an adapted version of the DPP tailored for an underresourced community in South Africa compared to usual care.

METHODS AND FINDINGS

Participants were residents of a predominantly Xhosa-speaking urban township of Cape Town, South Africa characterized by high rates of poverty. Participants with body mass index (BMI) ≥ 25 kg/m2 who were members of existing social support groups or "clubs" receiving health services from local nongovernmental organizations (NGOs) were enrolled in a cluster randomized controlled trial that compared Lifestyle Africa (the intervention condition) to usual care (the control condition). The Lifestyle Africa intervention consisted of 17 video-based group sessions delivered by trained community health workers (CHWs). Clusters were randomized using a numbered list of the CHWs and their assigned clubs based on a computer-based random allocation scheme. CHWs, participants, and research team members could not be blinded to condition. Percentage weight loss (primary outcome), hemoglobin A1c (HbA1c), blood pressure, triglycerides, and low-density lipoprotein (LDL) cholesterol were assessed 7 to 9 months after enrollment. An individual-level intention-to-treat analysis was conducted adjusting for clustering within clubs and baseline values. Trial registration is at ClinicalTrials.gov (NCT03342274). Between February 2018 and May 2019, 782 individuals were screened, and 494 were enrolled. Participants were predominantly retired (57% were receiving a pension) and female (89%) with a mean age of 68 years. Participants from 28 clusters were allocated to Lifestyle Africa (15, n = 240) or usual care (13, n = 254). Fidelity assessments indicated that the intervention was generally delivered as intended. The modal number of sessions held across all clubs was 17, and the mean attendance of participants across all sessions was 61%. Outcome assessment was completed by 215 (90%) intervention and 223 (88%) control participants. Intent-to-treat analyses utilizing multilevel modeling included all randomized participants. Mean weight change (primary outcome) was -0.61% (95% confidence interval (CI) = -1.22, -0.01) in Lifestyle Africa and -0.44% (95% CI = -1.06, 0.18) in control with no significant difference (group difference = -0.17%; 95% CI = -1.04, 0.71; p = 0.71). However, HbA1c was significantly lower at follow-up in Lifestyle Africa compared to the usual care group (mean difference = -0.24, 95% CI = -0.39, -0.09, p = 0.001). None of the other secondary outcomes differed at follow-up: systolic blood pressure (group difference = -1.36; 95% CI = -6.92, 4.21; p = 0.63), diastolic blood pressure (group difference = -0.39; 95% CI = -3.25, 2.30; p = 0.78), LDL (group difference = -0.07; 95% CI = -0.19, 0.05; p = 0.26), triglycerides (group difference = -0.02; 95% CI = -0.20, 0.16; p = 0.80). There were no unanticipated problems and serious adverse events were rare, unrelated to the intervention, and similar across groups (11 in Lifestyle Africa versus 13 in usual care). Limitations of the study include the lack of a rigorous dietary intake measure and the high representation of older women.

CONCLUSIONS

In this study, we found that Lifestyle Africa was feasible for CHWs to deliver and, although it had no effect on the primary outcome of weight loss or secondary outcomes of blood pressure or triglycerides, it had an apparent small significant effect on HbA1c. The study demonstrates the potential feasibility of CHWs to deliver a program without expert involvement by utilizing video-based sessions. The intervention may hold promise for addressing cardiovascular disease (CVD) and diabetes at scale in LMICs.

TRIAL REGISTRATION

ClinicalTrials.gov NCT03342274.

The digital transformation of hepatology: The patient is logged in

The rise in innovative digital health technologies has led a paradigm shift in health care toward personalized, patient-centric medicine that is reaching beyond traditional brick-and-mortar facilities into patients' homes and everyday lives. Digital solutions can monitor and detect early changes in physiological data, predict disease progression and health-related outcomes based on individual risk factors, and manage disease intervention with a range of accessible telemedicine and mobile health options. In this review, we discuss the unique transformation underway in the care of patients with liver disease, specifically examining the digital transformation of diagnostics, prediction and clinical decision-making, and management. Additionally, we discuss the general considerations needed to confirm validity and oversight of new technologies, usability and acceptability of digital solutions, and equity and inclusivity of vulnerable populations.

Digital Behavior Change Interventions for the Prevention and Management of Type 2 Diabetes: Systematic Market Analysis

BACKGROUND

Advancements in technology offer new opportunities for the prevention and management of type 2 diabetes. Venture capital companies have been investing in digital diabetes companies that offer digital behavior change interventions (DBCIs). However, little is known about the scientific evidence underpinning such interventions or the degree to which these interventions leverage novel technology-driven automated developments such as conversational agents (CAs) or just-in-time adaptive intervention (JITAI) approaches.

OBJECTIVE

Our objectives were to identify the top-funded companies offering DBCIs for type 2 diabetes management and prevention, review the level of scientific evidence underpinning the DBCIs, identify which DBCIs are recognized as evidence-based programs by quality assurance authorities, and examine the degree to which these DBCIs include novel automated approaches such as CAs and JITAI mechanisms.

METHODS

A systematic search was conducted using 2 venture capital databases (Crunchbase Pro and Pitchbook) to identify the top-funded companies offering interventions for type 2 diabetes prevention and management. Scientific publications relating to the identified DBCIs were identified via PubMed, Google Scholar, and the DBCIs' websites, and data regarding intervention effectiveness were extracted. The Diabetes Prevention Recognition Program (DPRP) of the Center for Disease Control and Prevention in the United States was used to identify the recognition status. The DBCIs' publications, websites, and mobile apps were reviewed with regard to the intervention characteristics.

RESULTS

The 16 top-funded companies offering DBCIs for type 2 diabetes received a total funding of US $2.4 billion as of June 15, 2021. Only 4 out of the 50 identified publications associated with these DBCIs were fully powered randomized controlled trials (RCTs). Further, 1 of those 4 RCTs showed a significant difference in glycated hemoglobin A1c (HbA1c) outcomes between the intervention and control groups. However, all the studies reported HbA1c improvements ranging from 0.2% to 1.9% over the course of 12 months. In addition, 6 interventions were fully recognized by the DPRP to deliver evidence-based programs, and 2 interventions had a pending recognition status. Health professionals were included in the majority of DBCIs (13/16, 81%,), whereas only 10% (1/10) of accessible apps involved a CA as part of the intervention delivery. Self-reports represented most of the data sources (74/119, 62%) that could be used to tailor JITAIs.

CONCLUSIONS

Our findings suggest that the level of funding received by companies offering DBCIs for type 2 diabetes prevention and management does not coincide with the level of evidence on the intervention effectiveness. There is considerable variation in the level of evidence underpinning the different DBCIs and an overall need for more rigorous effectiveness trials and transparent reporting by quality assurance authorities. Currently, very few DBCIs use automated approaches such as CAs and JITAIs, limiting the scalability and reach of these solutions.

Mobile Health Technology in the Primary Prevention of Type 2 Diabetes: a Systematic Review

PURPOSE OF REVIEW

The objective of this review was to summarize the current scientific evidence of mobile health technology in the primary prevention of type 2 diabetes in patients with prediabetes derived from randomized clinical trials.

RECENT FINDINGS

Few randomized clinical trials are available using mobile health technologies in the prevention of type 2 diabetes. There is heterogeneity in regard to the main study outcomes, duration of interventions, and study findings. Inconsistent findings have been reported whether mobile health technologies are effective in reducing HbA1C levels or the incidence of type 2 diabetes in patients with prediabetes. However, results are promising that mobile health interventions may decrease body weight. Future study may consistently measure changes in glycemic indicators as well as develop elements that better address behavior changes.

Body Positivity and Self-Compassion on a Publicly Available Behavior Change Weight Management Program

According to recent research, body positivity and self-compassion are key outcomes that are tied to better psychological and physical health. To date, it is unclear whether body positivity and self-compassion improve, stay constant, or deteriorate over the course of a weight management program, particularly one that addresses the psychological roots of behavior change. Additionally, beyond controlled settings, there are no studies on body positivity and self-compassion in individuals who choose to join a commercial weight management program. Therefore, this single-arm prospective study examined changes in body positivity and self-compassion from baseline to the 16 week milestone of Noom Weight, a commercial behavior change weight management program informed by acceptance and commitment therapy (ACT), dialectical behavior therapy (DBT), and cognitive behavioral therapy (CBT). We also examined how baseline and over-time changes in body positivity and self-compassion predicted engagement in program-measured relevant behaviors (e.g., exercises logged). Participants were a random subset of individuals who had recently self-enrolled in the program (n = 133). Body positivity and self-compassion were measured via survey at baseline and end of the core program (16 weeks). Self-reported weight and program-recorded engagement were extracted from the program database. Compared to baseline, body appreciation, body image flexibility, self-compassion, and body-focused rumination significantly improved at 16 weeks (all ps < 0.007). Participants lost a statistically significant amount of weight (3.9 kg; t(128)) = 10.64, p < 0.001) by 16 weeks, which was 4.4% body weight. Greater engagement, especially messaging a coach, reading articles, and logging meals, was associated with improvements over time in body appreciation (r = 0.17, p = 0.04), body image flexibility (r = −0.23, p = 0.007), and the brooding component of rumination (r = −0.23, p = 0.007). Greater engagement was also associated with baseline total self-compassion (r = 0.19, p = 0.03) and self-judgment (r = 0.24, p = 0.006). The results suggest that individuals experience improvements in body positivity and self-compassion while learning about ACT, DBT, and CBT through curriculum and coaching in this setting. The results also have important clinical implications, such as the possibility that psychologically-oriented (i.e., ACT, DBT, and CBT-based) weight management could be important to improve body positivity or that baseline self-compassion could be used to target individuals at risk for lower engagement. Future work should investigate these possibilities as well as delineate the causal relationships between body positivity, self-compassion, engagement, and weight loss.

Challenges in Participant Engagement and Retention using Mobile Health Apps: A Literature Review (Preprint)

Background

Mobile health (mHealth) apps are revolutionizing the way clinicians and researchers monitor and manage the health of their participants. However, many studies using mHealth apps are hampered by substantial participant dropout or attrition, which may impact the representativeness of the sample and the effectiveness of the study. Therefore, it is imperative for researchers to understand what makes participants stay with mHealth apps or studies using mHealth apps.

Objective

This study aimed to review the current peer-reviewed research literature to identify the notable factors and strategies used in adult participant engagement and retention.

Methods

We conducted a systematic search of PubMed, MEDLINE, and PsycINFO databases for mHealth studies that evaluated and assessed issues or strategies to improve the engagement and retention of adults from 2015 to 2020. We followed the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. Notable themes were identified and narratively compared among different studies. A binomial regression model was generated to examine the factors affecting retention.

Results

Of the 389 identified studies, 62 (15.9%) were included in this review. Overall, most studies were partially successful in maintaining participant engagement. Factors related to particular elements of the app (eg, feedback, appropriate reminders, and in-app support from peers or coaches) and research strategies (eg, compensation and niche samples) that promote retention were identified. Factors that obstructed retention were also identified (eg, lack of support features, technical difficulties, and usefulness of the app). The regression model results showed that a participant is more likely to drop out than to be retained.

Conclusions

Retaining participants is an omnipresent challenge in mHealth studies. The insights from this review can help inform future studies about the factors and strategies to improve participant retention.

Digital Resilience Biomarkers for Personalized Health Maintenance and Disease Prevention

Health maintenance and disease prevention strategies become increasingly prioritized with increasing health and economic burden of chronic, lifestyle-related diseases. A key element in these strategies is the empowerment of individuals to control their health. Self-measurement plays an essential role in achieving such empowerment. Digital measurements have the advantage of being measured non-invasively, passively, continuously, and in a real-world context. An important question is whether such measurement can sensitively measure subtle disbalances in the progression toward disease, as well as the subtle effects of, for example, nutritional improvement. The concept of resilience biomarkers, defined as the dynamic evaluation of the biological response to an external challenge, has been identified as a viable strategy to measure these subtle effects. In this review, we explore the potential of integrating this concept with digital physiological measurements to come to digital resilience biomarkers. Additionally, we discuss the potential of wearable, non-invasive, and continuous measurement of molecular biomarkers. These types of innovative measurements may, in the future, also serve as a digital resilience biomarker to provide even more insight into the personal biological dynamics of an individual. Altogether, digital resilience biomarkers are envisioned to allow for the measurement of subtle effects of health maintenance and disease prevention strategies in a real-world context and thereby give personalized feedback to improve health.

The Effects of Text Messages for Promoting Physical Activities in Prediabetes: A Randomized Controlled Trial

Objective: To test the effects of text messages for promoting physical activities in people with prediabetes. Methods: This randomized controlled trial was performed in participants with prediabetes. Participants were recruited from a primary care unit. Allocation to the study groups used a stratified block randomization. All participants received physical activity education at baseline. The intervention group additionally received supportive text messages by using mobile phone text messages. Participants were assessed at baseline at 8 and 12 weeks. The primary outcome measure was physical activity energy. Secondary outcomes included weight, body mass index, waist circumstance, and blood pressure. Results: All participants were included in the analyses (n = 324; control: n = 162; intervention: n = 162). Mean physical activity energy was significantly increased in those who received text messages at 8 weeks, increasing 1,590.73 Metabolic Equivalent of Tasks (METs)/min/week (95% confidence interval [CI]: 837.72, 2343.75) in the intervention group and 407.39 METs/min/weeks (95% CI: -267.59, 1082.36) in the control group with an adjusted mean difference of -1,183 METs/min/weeks (95% CI: -2190.11, -176.58, p = 0.02). Over the 12 weeks follow-up period, mean physical activity energy did not differ statistically by group. Mixed-model repeated-measures analysis of the total physical energy revealed no significant differences, with an adjusted mean difference 273.3 METs/min/week (95% CI: -530.64, 1077.21, p = 0.513). However, moderate physical energy was significantly increased to 256.40 METs/min/week (95% CI: 17.20, 495.63, p = 0.040). Conclusion: Text messaging significant in physical activity at the 8-week. But, text messaging no significant in physical activity at 12-week. Further research is needed to identify optimal times to send messages to people with prediabetes. Thai Clinical Trials Registry (TCTR), number: TCTR20200624008.

Evaluation of the Low Carb Program Digital Intervention for the Self-Management of Type 2 Diabetes and Prediabetes in an NHS England General Practice: Single-Arm Prospective Study

Background

Type 2 diabetes mellitus has serious health consequences, including blindness, amputation, and stroke. Researchers and clinicians are increasingly in agreement that type 2 diabetes may be effectively treated with a carbohydrate-reduced diet. Digital apps are increasingly used as an adjunct to traditional health care provisions to support remote self-management of long-term health conditions.

Objective

Our objective was to evaluate the real-world 12-month outcomes of patients prescribed the Low Carb Program digital health intervention at a primary care National Health Service (NHS) site. The Low Carb Program is a nutritionally focused, 12-session, digitally delivered, educational behavior change intervention for glycemic control and weight loss for adults with prediabetes and type 2 diabetes. The program educates and supports sustainable dietary changes focused on carbohydrate restriction by utilizing behavior change techniques, including goal setting, peer support, and behavioral self-monitoring, as well as personalized downloadable resources, including recipes and meal plans tailored to ethnicity, weekly shopping budget, and dietary preferences.

Methods

This study evaluated the real-world outcomes of patients recruited to the Low Carb Program at an NHS general practice in Southport, United Kingdom. All of the NHS patients recruited to the program were diagnosed with type 2 diabetes or prediabetes and were given access to the program at no cost. A total of 45 participants, with a mean age of 54.8 years (SD 13.2), were included in the study. Women made up 42% (19/45) of the sample. The mean hemoglobin A_1c (HbA_1c) of the sample was 56.7 mmol/mol (SD 16.95) and the mean body weight was 89.4 kg (SD 13.8).

Results

Of the 45 study participants recruited to the program, all of them (100%) activated their accounts and 37 (82%) individuals reported outcomes at 12 months. All 45 (100%) patients completed at least 40% of the lessons and 32 (71%) individuals completed more than nine out of 12 core lessons of the program. Glycemic control and weight loss improved, particularly for participants who completed more than nine core lessons in the program over 12 months. The mean HbA_1c went from 58.8 mmol/mol at baseline to 54.0 mmol/mol, representing a mean reduction of 4.78 mmol/mol (SD 4.60; t₃₁=5.87; P<.001). Results showed an average total body weight reduction of 4.17%, with an average weight reduction of 3.85 kg (SD 2.49; t₃₁=9.27; P<.001) at the 12-month follow-up point.

Conclusions

A digital app prescribed to adults with type 2 diabetes and prediabetes in a primary care setting supporting a transition to a low-carbohydrate diet has been shown to be effective in improving glycemic control and enabling weight loss. Further research to understand more about factors affecting engagement with the app and further positive health implications would be valuable.

Prevention of Type 2 Diabetes

The global diabetes burden is staggering, and prevention efforts are needed to reduce the impact on individuals and populations. There is strong evidence from efficacy trials showing that lifestyle interventions promoting increased physical activity, improvements in diet, and/or weight loss significantly reduce diabetes incidence and improve cardiometabolic risk factors. Implementation research assessing the feasibility, effectiveness, and cost-effectiveness of delivering these proven programs at the community level has shown success, but more research is needed to overcome barriers to implementation in different settings globally. New avenues of research should be considered to combat this public health issue.

Feasibility of an Interactive Health Coaching Mobile App to Prevent Malnutrition and Muscle Loss in Esophageal Cancer Patients Receiving Neoadjuvant Concurrent Chemoradiotherapy: Prospective Pilot Study

BACKGROUND

Excessive muscle loss is an important prognostic factor in esophageal cancer patients undergoing neoadjuvant chemoradiotherapy (NACRT), as reported in our previous research.

OBJECTIVE

In this pilot study, we prospectively tested the feasibility of a health coaching mobile app for preventing malnutrition and muscle loss in this patient population.

METHODS

Between July 2019 and May 2020, we enrolled 38 male patients with esophageal cancer scheduled for NACRT. For 8 weeks from the start of radiotherapy (RT), the patients used Noom, a health coaching mobile app that interactively provided online advice about food intake, exercise, and weight changes. The skeletal muscle index (SMI) measured based on computed tomography and nutrition-related laboratory markers were assessed before and after RT. We evaluated the changes in the SMI, nutrition, and inflammatory factors between the patient group that used the mobile app (mHealth group) and our previous study cohort (usual care group). Additionally, we analyzed the factors associated with walk steps recorded in the app.

RESULTS

Two patients dropped out of the study (no app usage; treatment changed to a definitive aim). The use (or activation) of the app was noted in approximately 70% (25/36) of the patients until the end of the trial. Compared to the 1:2 matched usual care group by propensity scores balanced with their age, primary tumor location, tumor stage, pre-RT BMI, and pre-RT SMI level, 30 operable patients showed less aggravation of the prognostic nutritional index (PNI) (-6.7 vs -9.8; P=.04). However, there was no significant difference in the SMI change or the number of patients with excessive muscle loss (∆SMI/50 days >10%). In patients with excessive muscle loss, the walk steps significantly decreased in the last 4 weeks compared to those in the first 4 weeks. Age affected the absolute number of walk steps (P=.01), whereas pre-RT sarcopenia was related to the recovery of the reduced walk steps (P=.03).

CONCLUSIONS

For esophageal cancer patients receiving NACRT, a health care mobile app helped nutritional self-care with less decrease in the PNI, although it did not prevent excessive muscle loss. An individualized care model with proper exercise as well as nutritional support may be required to reduce muscle loss and malnutrition.

Comparing Outcomes of a Digital Commercial Weight Loss Program in Adult Cancer Survivors and Matched Controls with Overweight or Obesity: Retrospective Analysis

Maintaining a healthy weight is beneficial for cancer survivors. However, weight loss program effectiveness studies have primarily been in highly controlled settings. This is a retrospective study exploring real-world outcomes (weight loss and program engagement) after use of a digital commercial weight loss program (Noom) in cancer survivors and matched controls. All participants had voluntarily self-enrolled in Noom. Weight and engagement data were extracted from the program. Cancer-related quality of life was secondarily assessed in a one-time cross-sectional survey for survivors. Controls were a sample of Noom users with overweight/obesity who had no history of cancer but 0–1 chronic conditions. Primary outcomes were weight change at 16 weeks and program engagement over 16 weeks. Engagement included frequency of weight, food, and physical activity logging, as well as number of coach messages. Multiple regression controlling for baseline age, gender, engagement, and BMI showed that survivors lost less weight than controls (B = −2.40, s.e. = 0.97, p = 0.01). Survivors also weighed in less (survivors: 5.4 [2.3]; controls: 5.7 [2.1], p = 0.01) and exercised less (survivors: 1.8 [3.2]; controls: 3.2 [4.1], p < 0.001) than controls. However, survivors sent more coach messages (survivors: 2.1 [2.4]; controls: 1.7 [2.0], p < 0.001). Despite controls losing more weight than cancer survivors (−7.0 kg vs. −5.3 kg), survivors lost significant weight in 4 months (M = −6.2%). Cancer survivors can have success on digital commercial programs available outside of a clinical trial. However, they may require additional support to engage in weight management behaviors.

Nutrition in Patients with Type 2 Diabetes: Present Knowledge and Remaining Challenges

Unhealthy behaviours, including diet and physical activity, coupled with genetic predisposition, drive type 2 diabetes (T2D) occurrence and severity; the present review aims to summarise the most recent nutritional approaches in T2D, outlining unmet needs. Guidelines consistently suggest reducing energy intake to counteract the obesity epidemic, frequently resulting in sarcopenic obesity, a condition associated with poorer metabolic control and cardiovascular disease. Various dietary approaches have been proposed with largely similar results, with a preference for the Mediterranean diet and the best practice being the diet that patients feel confident of maintaining in the long term based on individual preferences. Patient adherence is indeed the pivotal factor for weight loss and long-term maintenance, requiring intensive lifestyle intervention. The consumption of nutritional supplements continues to increase even if international societies do not support their systematic use. Inositols and vitamin D supplementation, as well as micronutrients (zinc, chromium, magnesium) and pre/probiotics, result in modest improvement in insulin sensitivity, but their use is not systematically suggested. To reach the desired goals, patients should be actively involved in the collaborative development of a personalised meal plan associated with habitual physical activity, aiming at normal body weight and metabolic control.

Cross-National Outcomes of a Digital Weight Loss Intervention in the United States, Canada, United Kingdom and Ireland, and Australia and New Zealand: A Retrospective Analysis

Mobile health (mHealth) interventions are ubiquitous and effective treatment options for obesity. There is a widespread assumption that the mHealth interventions will be equally effective in other locations. In an initial test of this assumption, this retrospective study assesses weight loss and engagement with an mHealth behavior change weight loss intervention developed in the United States (US) in four English-speaking regions: the US, Australia and New Zealand (AU/NZ), Canada (CA), and the United Kingdom and Ireland (UK/IE). Data for 18,459 participants were extracted from the database of Noom's Healthy Weight Program. Self-reported weight was collected every week until program end (week 16). Engagement was measured using user-logged and automatically recorded actions. Linear mixed models were used to evaluate change in weight over time, and ANOVAs evaluated differences in engagement. In all regions, 27.2–33.2% of participants achieved at least 5% weight loss by week 16, with an average of 3–3.7% weight loss. Linear mixed models revealed similar weight outcomes in each region compared to the US, with a few differences. Engagement, however, significantly differed across regions (P < 0.001 on 5 of 6 factors). Depending on the level of engagement, the rate of weight loss over time differed for AU/NZ and UK/IE compared to the US. Our findings have important implications for the use and understanding of digital weight loss interventions worldwide. Future research should investigate the determinants of cross-country engagement differences and their long-term effects on intervention outcomes.

Self-Reported Nutritional Factors Are Associated with Weight Loss at 18 Months in a Self-Managed Commercial Program with Food Categorization System: Observational Study

Little is known about nutritional factors during weight loss on digital commercial weight loss programs. We examined how nutritional factors relate to weight loss for individuals after 4 and 18 months on a mobile commercial program with a food categorization system based on energy density (Noom). This is a two-part (retrospective and cross-sectional) cohort study. Two time points were used for analysis: 4 months and 18 months. For 4-month analyses, current Noom users who met inclusion criteria (n = 9880) were split into 5% or more body weight loss and stable weight loss (0 ± 1%) groups. Individuals who fell into one of these groups were analyzed at 4 months (n = 3261). For 18-month analyses, individuals from 4-month analyses who were still on Noom 18 months later were invited to take a one-time survey (n = 803). At 18 months 148 participants were analyzed. Noom has a system categorizing foods as low-, medium-, and high-energy-dense. Measures were self-reported proportions of low-, medium-, and high-energy-dense foods, and self-reported nutritional factors (fruit and vegetable intake, dietary quality, nutrition knowledge, and food choice). Nutritional factors were derived from validated survey measures, and food choice from a novel validated computerized task in which participants chose a food they would want to eat right now. ANOVAs compared participants with 5% or more body weight loss and participants with stable weight (0 ± 1%) at 4 months on energy density proportions. Analyses at 18 months compared nutritional factors across participants with >10% (high weight loss), 5–10% (moderate weight loss), and less than 5% body weight loss (low weight loss), and then assessed associations between nutritional factors and weight loss. Individuals with greater weight loss reported consuming higher proportions of low-energy-dense foods and lower proportions of high-energy-dense foods than individuals with less weight loss at 4 months and 18 months (all ps < 0.02). Individuals with greater weight loss had higher fruit and vegetable intake (p = 0.03), dietary quality (p = 0.02), nutrition knowledge (p < 0.001), and healthier food choice (p = 0.003) at 18 months. Only nutrition knowledge and food choice were associated with weight loss at 18 months (B = −19.44, 95% CI: −33.19 to −5.69, p = 0.006; B = −5.49, 95% CI: −8.87 to −2.11, p = 0.002, respectively). Our results highlight the potential influence of nutrition knowledge and food choice in weight loss on a self-managed commercial program. We also found for the first time that in-the-moment inclination towards food even when just depicted is associated with long-term weight loss.