Engagement and outcomes in a digital Diabetes Prevention Program: 3-year update

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.

Experiences of online group support for engaging and supporting participants in the National Health Service Digital Diabetes Prevention Programme: A qualitative interview study

OBJECTIVES

The National Health Service Digital Diabetes Prevention Programme is a nine-month behavioural intervention for adults in England at risk of type 2 diabetes. This qualitative study aimed to explore how service users engaged with the group support available within the programme.

METHODS

The majority of participants (n = 33), all service users, were interviewed twice via telephone, at 2-4 months into the programme, and at the end of the programme at 8-10 months. Semi-structured interviews covered participants' experiences of online group support functions and how such groups served as a route of support to aid participants' behavioural changes. Data were analysed using manifest thematic analysis.

RESULTS

The majority of participants valued the format of closed group chats, which provided an interactive platform to offer and receive support during their behaviour change journey. However, engagement with group chats reduced over time, and some participants did not find them useful when there was a lack of common interests within the group. Health coaches helped to promote engagement and build rapport among participants within the group chats. Participants reported mixed experiences of discussion forums.

CONCLUSIONS

Programme developers should consider how to optimise online group support to help service users make behavioural changes, in terms of format, participant composition and use of health coach moderators. Further research is required to better understand who might benefit most from 'group chat' or 'discussion forum' support. Health coach moderation of online support groups is likely to facilitate engagement.

Augmenting K-Means Clustering With Qualitative Data to Discover the Engagement Patterns of Older Adults With Multimorbidity When Using Digital Health Technologies: Proof-of-Concept Trial

BACKGROUND

Multiple chronic conditions (multimorbidity) are becoming more prevalent among aging populations. Digital health technologies have the potential to assist in the self-management of multimorbidity, improving the awareness and monitoring of health and well-being, supporting a better understanding of the disease, and encouraging behavior change.

OBJECTIVE

The aim of this study was to analyze how 60 older adults (mean age 74, SD 6.4; range 65-92 years) with multimorbidity engaged with digital symptom and well-being monitoring when using a digital health platform over a period of approximately 12 months.

METHODS

Principal component analysis and clustering analysis were used to group participants based on their levels of engagement, and the data analysis focused on characteristics (eg, age, sex, and chronic health conditions), engagement outcomes, and symptom outcomes of the different clusters that were discovered.

RESULTS

Three clusters were identified: the typical user group, the least engaged user group, and the highly engaged user group. Our findings show that age, sex, and the types of chronic health conditions do not influence engagement. The 3 primary factors influencing engagement were whether the same device was used to submit different health and well-being parameters, the number of manual operations required to take a reading, and the daily routine of the participants. The findings also indicate that higher levels of engagement may improve the participants' outcomes (eg, reduce symptom exacerbation and increase physical activity).

CONCLUSIONS

The findings indicate potential factors that influence older adult engagement with digital health technologies for home-based multimorbidity self-management. The least engaged user groups showed decreased health and well-being outcomes related to multimorbidity self-management. Addressing the factors highlighted in this study in the design and implementation of home-based digital health technologies may improve symptom management and physical activity outcomes for older adults self-managing multimorbidity.

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.

Weight loss and lifestyle change among high-risk individuals enrolled in a digital diabetes prevention program: A longitudinal study of private and public health insurance members in Western New York

Weight loss is critical to reduce diabetes risk. Diabetes Prevention Programs (DPPs) are effective for weight loss, although less is known about digital DPPs. This study explores the association between Brook+, a 52-week digital DPP, and weight loss. This longitudinal observational study uses a sample of 5,516 private, Medicare, and Medicaid health insurance members from Western New York enrolled into Brook+ between December 2020 and December 2022. We used multivariable generalized linear regression models to estimate the association between completion of the Brook+ program, overall and stratified by health insurance type, and 5% weight loss using odds ratios (OR) and 95% confidence intervals (CI), adjusted for age and gender. We also estimated average weight loss from baseline associated with high engagement with the program using adjusted linear regression models. In the pooled sample, those who completed the Brook + program had 21% increased odds of 5% weight loss (OR = 1.21 95% CI: (1.02 - 1.44)). Among users enrolled in private, Medicare, and Medicaid health insurance, program completion was associated with 21%, 33%, and 13% increased odds of 5% weight loss, compared to those who did not complete Brook+. Interacting with health coaches, increased physical activity, and meal logging were all significant predictors of weight loss. Our results suggest that digital DPPs are promising for large-scale diabetes prevention via weight loss and lifestyle change.

Privacy Concerns in Group Format Lifestyle Interventions for Obesity

BACKGROUND

Group format weight loss interventions have benefits over individual format, but privacy concerns may limit their uptake.

METHOD

In this study, adults with obesity and interest in losing weight were recruited nationally online and randomly assigned to view one of eight videos describing a hypothetical, group behavioral weight loss intervention. Based on three fully crossed factors, the videos varied on privacy features of intervention (present or not); matching participants to group based on weight loss barriers (matched or not); and intervention format (online or in-person). Participants rated their willingness to join, privacy concerns, and perceived effectiveness of these interventions. They further reported preference for individual or group format interventions and reason for preferences.

RESULTS

Description of privacy features, matching of participants, and format did not affect willingness to join, privacy concerns, or perceived effectiveness of the intervention. Privacy concerns were associated with lower willingness to join and lower perceived intervention effectiveness, and greater social anxiety and weight stigma. More participants preferred individual over group format (40.1% vs 33.9%; 26% selected neither) and preference for individual format was associated with greater privacy concerns.

CONCLUSION

Strategies to address privacy concerns in group-based interventions warrant further attention.

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.

Design and Early Use of the Nationally Implemented Healthier You National Health Service Digital Diabetes Prevention Programme: Mixed Methods Study

BACKGROUND

The Healthier You National Health Service Digital Diabetes Prevention Programme (NHS-digital-DPP) is a 9-month digital behavior change intervention delivered by 4 independent providers that is implemented nationally across England. No studies have explored the design features included by service providers of digital diabetes prevention programs to promote engagement, and little is known about how participants of nationally implemented digital diabetes prevention programs such as this one make use of them.

OBJECTIVE

This study aimed to understand engagement with the NHS-digital-DPP. The specific objectives were to describe how engagement with the NHS-digital-DPP is promoted via design features and strategies and describe participants' early engagement with the NHS-digital-DPP apps.

METHODS

Mixed methods were used. The qualitative study was a secondary analysis of documents detailing the NHS-digital-DPP intervention design and interviews with program developers (n=6). Data were deductively coded according to an established framework of engagement with digital health interventions. For the quantitative study, anonymous use data collected over 9 months for each provider representing participants' first 30 days of use of the apps were obtained for participants enrolled in the NHS-digital-DPP. Use data fields were categorized into 4 intervention features (Track, Learn, Coach Interactions, and Peer Support). The amount of engagement with the intervention features was calculated for the entire cohort, and the differences between providers were explored statistically.

RESULTS

Data were available for 12,857 participants who enrolled in the NHS-digital-DPP during the data collection phase. Overall, 94.37% (12,133/12,857) of those enrolled engaged with the apps in the first 30 days. The median (IQR) number of days of use was 11 (2-25). Track features were engaged with the most (number of tracking events: median 46, IQR 3-22), and Peer Support features were the least engaged with, a median value of 0 (IQR 0-0). Differences in engagement with features were observed across providers. Qualitative findings offer explanations for the variations, including suggesting the importance of health coaches, reminders, and regular content updates to facilitate early engagement.

CONCLUSIONS

Almost all participants in the NHS-digital-DPP started using the apps. Differences across providers identified by the mixed methods analysis provide the opportunity to identify features that are important for engagement with digital health interventions and could inform the design of other digital behavior change interventions.

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.

Lifestyle change program engagement in real-world clinical practice: a mixed-methods analysis

Participant engagement in structured lifestyle change programs (LCPs) is essential for adopting behaviors that promote weight loss; however, the challenges to, and facilitators that promote, engagement with such programs are not well understood. We conducted a mixed-methods study among real-world LCP participants to assess factors associated with program engagement and to examine the reasons for withdrawal. Using electronic health records (EHR), we identified LCP eligible participants between 2010 and 2017. Multivariable logistic regression was used to assess associations between program engagement and baseline characteristics. Semi-structured interviews with LCP participants were conducted and thematically analyzed to examine reasons for withdrawal. A total of 1,813 LCP participants were included. The median number of sessions attended was 10 of 21-25 sessions. Highest LCP engagement was associated with factors potentially related to self-efficacy/motivation, such as older age, higher baseline weight, prior healthcare utilization and an absence of a history of smoking or depression. Engagement was also negatively associated with being Non-Hispanic Black versus White. The qualitative analysis of the interviews revealed four general themes pertaining to participants' withdrawal: competing priorities, perceived program effectiveness, characteristics of the program, and facilitator-related factors. Taken together, results from this mixed-methods study suggest that motivation and self-efficacy are important for program engagement; future LCP enhancements should incorporate flexible formats that may help participants manage competing priorities and maximize personal and cultural relevance for all racial/ethnic groups, especially those who have not benefitted fully. Furthermore, participants should be encouraged to set realistic goals to manage expectations.

Measuring Engagement with Mental Health and Behavior Change Interventions: an Integrative Review of Methods and Instruments

BACKGROUND

Engagement is a complex construct consisting of behavioral, cognitive, and affective dimensions, making engagement a difficult construct to measure. This integrative review aims to (1) present a multidisciplinary overview of measurement methods that are currently used to measure engagement with adult mental health and behavior change interventions, delivered in-person, blended, or digitally, and (2) provide a set of recommendations and considerations for researchers wishing to study engagement.

METHODS

We used an integrative approach and identified original studies and reviews on engagement with mental health or behavior change interventions that were delivered in-person, digitally, or blended.

RESULTS

Forty articles were analyzed in this review. Common methods to assess engagement were through objective usage data, questionnaire-based data, and qualitative data, with objective usage data being used most frequently. Based on the synthesis of engagement measures, we advise researchers to (1) predefine the operationalization of engagement for their specific research context, (2) measure behavioral, cognitive, and affective dimensions of engagement in all cases, and (3) measure engagement over time.

CONCLUSIONS

Current literature shows a bias towards behavioral measures of engagement in research, as most studies measured engagement exclusively through objective usage data, without including cognitive and affective measures of engagement. We hope that our recommendations will help to reduce this bias and to steer engagement research towards an integrated approach.

Influences on Patient Uptake of and Engagement With the National Health Service Digital Diabetes Prevention Programme: Qualitative Interview Study

BACKGROUND

Digital diabetes prevention programs (digital-DPPs) are being implemented as population-based approaches to type 2 diabetes mellitus prevention in several countries to address problems with the uptake of traditional face-to-face diabetes prevention programs. However, assessments of digital-DPPs have largely focused on clinical outcomes and usability among those who have taken them up, whereas crucial information on decision-making about uptake (eg, whether a user downloads and registers on an app) and engagement (eg, the extent of use of an app or its components over time) is limited. Greater understanding of factors that influence uptake and engagement decisions may support large-scale deployments of digital-DPPs in real-world settings.

OBJECTIVE

This study aimed to explore the key influences on uptake and engagement decisions of individuals who were offered the National Health Service Healthier You: Digital Diabetes Prevention Programme (NHS-digital-DPP).

METHODS

A qualitative interview study was conducted using semistructured interviews. Participants were adults, aged ≥18 years, diagnosed with nondiabetic hyperglycemia, and those who had been offered the NHS-digital-DPP. Recruitment was conducted via 4 providers of the NHS-digital-DPP and 3 primary care practices in England. Interviews were conducted remotely and were guided by a theoretically informed topic guide. Analysis of interviews was conducted using an inductive thematic analysis approach.

RESULTS

Interviews were conducted with 32 participants who had either accepted or declined the NHS-digital-DPP. In total, 7 overarching themes were identified as important factors in both decisions to take up and to engage with the NHS-digital-DPP. These were knowledge and understanding, referral process, self-efficacy, self-identity, motivation and support, advantages of digital service, and reflexive monitoring. Perceptions of accessibility and convenience of the NHS-digital-DPP were particularly important for uptake, and barriers in terms of the referral process and health care professionals' engagement were reported. Specific digital features including health coaches and monitoring tools were important for engagement.

CONCLUSIONS

This study adds to the literature on factors that influence the uptake of and engagement with digital-DPPs and suggests that digital-DPPs can overcome many barriers to the uptake of face-to-face diabetes prevention programs in supporting lifestyle changes aimed at diabetes prevention.

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.

Testing a very low-carbohydrate adaption of the Diabetes Prevention Program among adults with prediabetes: study protocol for the Lifestyle Education about prediabetes (LEAP) trial

BACKGROUND

The Center for Disease Control and Prevention's National Diabetes Prevention Program (NDPP) aims to help individuals with prediabetes avoid progression to type 2 diabetes mellitus (T2DM) through weight loss. Specifically, the NDPP teaches individuals to follow a low-fat, calorie-restricted diet and to engage in regular physical activity to achieve ≥ 5% body weight loss. Most NDPP participants, however, do not achieve this weight loss goal, and glycemic control remains largely unchanged. One promising opportunity to augment the NDPP's weight loss and glycemic effectiveness may be to teach participants to follow a very low-carbohydrate diet (VLCD), which can directly reduce post-prandial glycemia and facilitate weight loss by reducing circulating insulin and enabling lipolysis. To date, there have been no high-quality, randomized controlled trials to test whether a VLCD can prevent progression to T2DM among individuals with prediabetes. The aim of this study is to test the effectiveness of a VLCD version the NDPP (VLC-NDPP) versus the standard NDPP. We hypothesize the VLC-NDPP will demonstrate greater improvements in weight loss and glycemic control.

METHODS

We propose to conduct a 12-month, 1:1, randomized controlled trial that will assign 300 adults with overweight or obesity and prediabetes to either the NDPP or VLC-NDPP. The primary outcome will be glycemic control as measured by change in hemoglobin A1c (HbA1c) from baseline to 12 months. Secondary outcomes will include percent body weight change and changes in glycemic variability, inflammatory markers, lipids, and interim HbA1c. We will evaluate progression to T2DM and initiation of anti-hyperglycemic agents. We will conduct qualitative interviews among a purposive sample of participants to explore barriers to and facilitators of dietary adherence. The principal quantitative analysis will be intent-to-treat using hierarchical linear mixed effects models to assess differences over time.

DISCUSSION

The NDPP is the dominant public health strategy for T2DM prevention. Changing the program's dietary advice to include a carbohydrate-restricted eating pattern as an alternative option may enhance the program's effectiveness. If the VLC-NDPP shows promise, this trial would be a precursor to a multi-site trial with incident T2DM as the primary outcome.

TRIAL REGISTRATION

NCT05235425. Registered February 11, 2022.

Economic evaluation of using polygenic risk score to guide risk screening and interventions for the prevention of type 2 diabetes in individuals with high overall baseline risk

Type 2 diabetes (T2D) with increasing prevalence is a significant global public health challenge. Obesity, unhealthy diet, and low physical activity are one of the major determinants of the rise in T2D prevalence. In addition, family history and genetic risk of diabetes also play a role in the process of developing T2D. Therefore, solutions for the early identification of individuals at high risk for T2D for early targeted detection of T2D, prevention, and intervention are highly preferred. Recently, novel genomic-based polygenic risk scores (PRSs) have been suggested to improve the accuracy of risk prediction supporting the targeting of preventive interventions to those at highest risk for T2D. Therefore, the aim of the present study was to assess the cost-utility of an additional PRS testing information (as a part of overall risk assessment) followed by a lifestyle intervention and an additional medical therapy when estimated 10-year overall risk for T2D exceeded 20% among Finnish individuals screened as at the high-risk category (i.e., 10%–20% 10-year overall risk of T2D) based on traditional risk factors only. For a cost-utility analysis, an individual-level state-transition model with probabilistic sensitivity analysis was constructed. A 1-year cycle length and a lifetime time horizon were applied in the base-case. A 3% discount rate was used for costs and QALYs. Cost-effectiveness acceptability curve (CEAC) and estimates for the expected value of perfect information (EVPI) were calculated to assist decision makers. The use of the targeted PRS strategy reclassified 12.4 percentage points of individuals to be very high-risk individuals who would have been originally classified as high risk using the usual strategy only. Over a lifetime horizon, the targeted PRS was a dominant strategy (i.e., less costly, more effective). One-way and scenario sensitivity analyses showed that results remained dominant in almost all simulations. However, there is uncertainty, since the probability (EVPI) of cost-effectiveness at a WTP of 0€/QALY was 63.0% (243€) indicating the probability that the PRS strategy is a dominant option. In conclusion, the results demonstrated that the PRS provides moderate additional value in Finnish population in risk screening leading to potential cost savings and better quality of life when compared with the current screening methods for T2D risk.

Innovations in Cardio-oncology Resulting from the COVID-19 Pandemic

The COVID pandemic has transformed our approach to patient care, research, and training in cardio-oncology. While the early phases of the COVID pandemic were exceptionally frightening, we now can reflect on the innovative changes that brought more effective and patient-centered care to our doorsteps: expansion of telemedicine, integration of digital health, wider adoption of cardiac biomarkers, consolidation, and coordination of cardio-oncology testing. Normally, it takes years for health care systems to adopt new technology or modify patient care pathways; however, COVID pushed healthcare providers and the health systems to change at warp speed. All of these innovations have improved our efficacy and provided a more “patient-centered” approach for our cardio-oncology patients. The changes we have made in cardio-oncology will likely remain well beyond the pandemic and continue to grow improving the cardiovascular care of oncology patients.

The economic imperatives for technology enabled wellness centered healthcare

A 2020 World Health Organization report underscored the impact of rising healthcare spending globally and questioned the long-term economic sustainability of current funding models. Increases in costs associated with care of late-stage irreversible diseases and the increasing prevalence of debilitating neurodegenerative disorders, coupled with increases in life expectancy are likely to overload the healthcare systems in many nations within the next decade if not addressed. One option for sustainability of the healthcare system is a change in emphasis from illness to wellness centered care. An attractive model is the P4 (Predictive, Preventative, Personalized and Participatory) medicine approach. Recent advances in connected health technology can help accelerate this transition; they offer prediction, diagnosis, and monitoring of health-related parameters. We explain how to integrate such technologies with conventional approaches and guide public health policy toward wellness-based care models and strategies to relieve the escalating economic burdens of managed care.

Adaptation of diabetes prevention program for Chinese Americans - a qualitative study

BACKGROUND

Studies have demonstrated that a culturally and linguistically tailored Diabetes Prevention Program (DPP) can be effective in reducing diabetes risk in Chinese Americans. The purpose of this study was to explore the cultural and linguistic acceptability of the Centers for Disease Control and Prevention's Prevent T2 curriculum in an online format in the Chinese American community in New York City (NYC).

METHODS

Three focus groups among a total of 24 Chinese Americans with prediabetes and one community advisory board (CAB) meeting with 10 key stakeholders with expertise in diabetes care and lifestyle interventions were conducted. Each focus group lasted approximately 1 to 1.5 h. All groups were moderated by a bilingual moderator in Chinese. The sessions were audiotaped, transcribed and translated to English for analysis. Using Atlas.ti software and open coding techniques, two researchers analyzed transcripts for thematic analysis.

RESULTS

Five key themes were identified: barriers to behavioral changes, feedback on curriculum content and suggestions, web-based intervention acceptability, web-based intervention feasibility, and web-based intervention implementation and modifications. Participants with prediabetes were found to have high acceptability of web-based DPP interventions. Suggestions for the curriculum included incorporating Chinese American cultural foods and replacing photos of non-Asians with photos of Asians. Barriers included lack of access to the internet, different learning styles and low technology self-efficacy for older adults.

CONCLUSION

Although the acceptability of web-based DPP in the Chinese American community in NYC is high, our focus group findings indicated that the major concern is lack of internet access and technical support. Providing support, such as creating an orientation manual for easy online program access for future participants, is important.

A Mobile Health-Based Disease Management Program Improves Blood Pressure in People With Multiple Lifestyle-Related Diseases at Risk of Developing Vascular Disease ― A Retrospective Observational Study ―

Background: The overlap of multiple lifestyle-related diseases increases the risk of vascular diseases. This study investigated the effects of a mobile health (mHealth)-based disease management program on blood pressure and the safety of this program in people with multiple lifestyle-related diseases at risk of developing vascular disease.

Methods and Results: This retrospective observational study was conducted using secondary data collected by PREVENT Inc. People with a full history of hypertension, diabetes, and dyslipidemia and who participated in a 6-month mHealth-based disease management program were included in the study. The primary outcome was blood pressure. Adverse events during the program were investigated to evaluate safety. In total, 125 participants (mean [±SD] age 55.3±6.2 years) were examined. Systolic and diastolic blood pressure were significantly lower after the intervention than at baseline (systolic blood pressure, 128.0±12.3 vs. 131.9±12.7 mmHg [P<0.001]; diastolic blood pressure, 81.2±9.3 vs. 83.6±8.9 mmHg; P=0.003). No serious adverse events occurred during the program.

Conclusions: The present results indicate that the mHealth-based disease management program may reduce blood pressure in people with multiple lifestyle-related diseases at risk of developing vascular disease and that the program is safe. These findings will help shape future health instructions using mHealth-based interventions.

Uptake and impact of the English National Health Service digital diabetes prevention programme: observational study

INTRODUCTION

'Healthier You', the National Health Service (NHS) diabetes prevention programme (DPP) offers adults in England at high risk of type 2 diabetes (T2DM) an evidence-based behavioral intervention to prevent or delay T2DM onset. This study assesses the impact of a pilot digital stream of the DPP (DDPP) on glycated hemoglobin (HbA1c) and weight.

RESEARCH DESIGN AND METHODS

A service evaluation employing prospectively collected data in a prospective cohort design in nine NHS local pilot areas across England. Participants were adults with non-diabetic hyperglycemia (NDH) (HbA1c 42-47 mmol/mol or fasting plasma glucose 5.5-6.9 mmol/L) in the 12 months prior to referral. The DDPP comprised five digital health interventions (DHI). Joint primary outcomes were changes in HbA1c and weight between baseline and 12 months. HbA1c and weight readings were recorded at referral (baseline) by general practices, and then at 12-month postregistration. Demographic data and service variables were collected from the DHI providers.

RESULTS

3623 participants with NDH registered for the DDPP and of these, 2734 (75%) were eligible for inclusion in the analyses. Final (12-month) follow-up data for HbA1c were available for 1799 (50%) and for weight 1817 (50%) of registered participants. Mean change at 12 months was -3.1 (-3.4 to -2.8) kg, p<0.001 for weight and -1.6 (-1.8 to -1.4) mmol/mol, p<0.001 for HbA1c. Access to peer support and a website and telephone service was associated with significantly greater reductions in HbA1c and weight.

CONCLUSIONS

Participation in the DDPP was associated with clinically significant reductions in weight and HbA1c. Digital diabetes prevention can be an effective and wide-reaching component of a population-based approach to addressing type 2 diabetes prevention.

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.

Digitally Supported Lifestyle Intervention to Prevent Type 2 Diabetes Through Healthy Habits: Secondary Analysis of Long-Term User Engagement Trajectories in a Randomized Controlled Trial

BACKGROUND

Digital health interventions may offer a scalable way to prevent type 2 diabetes (T2D) with minimal burden on health care systems by providing early support for healthy behaviors among adults at increased risk for T2D. However, ensuring continued engagement with digital solutions is a challenge impacting the expected effectiveness.

OBJECTIVE

We aimed to investigate the longitudinal usage patterns of a digital healthy habit formation intervention, BitHabit, and the associations with changes in T2D risk factors.

METHODS

This is a secondary analysis of the StopDia (Stop Diabetes) study, an unblinded parallel 1-year randomized controlled trial evaluating the effectiveness of the BitHabit app alone or together with face-to-face group coaching in comparison with routine care in Finland in 2017-2019 among community-dwelling adults (aged 18 to 74 years) at an increased risk of T2D. We used longitudinal data on usage from 1926 participants randomized to the digital intervention arms. Latent class growth models were applied to identify user engagement trajectories with the app during the study. Predictors for trajectory membership were examined with multinomial logistic regression models. Analysis of covariance was used to investigate the association between trajectories and 12-month changes in T2D risk factors.

RESULTS

More than half (1022/1926, 53.1%) of the participants continued to use the app throughout the 12-month intervention. The following 4 user engagement trajectories were identified: terminated usage (904/1926, 46.9%), weekly usage (731/1926, 38.0%), twice weekly usage (208/1926, 10.8%), and daily usage (83/1926, 4.3%). Active app use during the first month, higher net promoter score after the first 1 to 2 months of use, older age, and better quality of diet at baseline increased the odds of belonging to the continued usage trajectories. Compared with other trajectories, daily usage was associated with a higher increase in diet quality and a more pronounced decrease in BMI and waist circumference at 12 months.

CONCLUSIONS

Distinct long-term usage trajectories of the BitHabit app were identified, and individual predictors for belonging to different trajectory groups were found. These findings highlight the need for being able to identify individuals likely to disengage from interventions early on, and could be used to inform the development of future adaptive interventions.

TRIAL REGISTRATION

ClinicalTrials.gov NCT03156478; https://clinicaltrials.gov/ct2/show/NCT03156478.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

RR2-10.1186/s12889-019-6574-y.

Implementation of Diabetes Prevention in Health Care Organizations: Best Practice Recommendations

Approximately 1 in 3 American adults has prediabetes, a condition characterized by blood glucose levels that are above normal, not in the type 2 diabetes ranges, and that increases the risk of developing type 2 diabetes. Evidence-based treatments can be used to prevent or delay type 2 diabetes in adults with prediabetes. The American Medical Association (AMA) has collaborated with health care organizations across the country to build sustainable diabetes prevention strategies. In 2017, the AMA formed the Diabetes Prevention Best Practices Workgroup (DPBP) with representatives from 6 health care organizations actively implementing diabetes prevention. Each organization had a unique strategy, but all included the National Diabetes Prevention Program lifestyle change program as a core evidence-based intervention. DPBP established the goal of disseminating best practices to guide other health care organizations in implementing diabetes prevention and identifying and managing patients with prediabetes. Workgroup members recognized similarities in some of their basic steps and considerations and synthesized their practices to develop best practice recommendations for 3 strategy maturity phases. Recommendations for each maturity phase are classified into 6 categories: (1) organizational support; (2) workforce and funding; (3) promotion and dissemination; (4) clinical integration and support; (5) evaluation and outcomes; (6) and program. As the burden of chronic disease grows, prevention must be prioritized and integrated into health care. These maturity phases and best practice recommendations can be used by any health care organization committed to diabetes prevention. Further research is suggested to assess the impact and adoption of diabetes prevention best practices.

A 12-Month Follow-Up of the Effects of a Digital Diabetes Prevention Program (VP Transform for Prediabetes) on Weight and Physical Activity Among Adults With Prediabetes: Secondary Analysis

Background

The prevalence of diabetes is increasing rapidly. Previous research has demonstrated the efficacy of a diabetes prevention program (DPP) in lifestyle modifications that can prevent or delay the onset of type 2 diabetes among individuals at risk. Digital DPPs have the potential to use technology, in conjunction with behavior change science, to prevent prediabetes on a national and global scale.

Objective

The aim of this study is to investigate the effects of a digital DPP (Virgin Pulse [VP] Transform for Prediabetes) on weight and physical activity among participants who had completed 12 months of the program.

Methods

This study was a secondary analysis of retrospective data of adults with prediabetes who were enrolled in VP Transform for Prediabetes for 12 months of the program. The program incorporates interactive mobile computing, remote monitoring, an evidence-based curriculum, behavior tracking tools, health coaching, and online peer support to prevent or delay the onset of type 2 diabetes.

Results

The sample (N=1095) was comprised of people with prediabetes who completed at least 9 months of the VP Transform for Prediabetes program. Participants were 67.7% (n=741) female, with a mean age of 53.6 (SD 9.75) years. After 12 months, participants decreased their weight by an average of 10.9 lbs (5.5%; P<.001) and increased their physical activity by 91.2 (P<.001) minutes.

Conclusions

These results suggest that VP Transform for Prediabetes is effective at preventing type 2 diabetes through a significant reduction in body weight and increase of physical activity. Furthermore, these results suggest that the DPP remains effective 12 months after beginning the program. A prospective randomized controlled clinical study is warranted to validate these findings.

Evaluating the Implementation of a Digital Diabetes Prevention Program in an Integrated Health Care Delivery System Among Older Adults: Results of a Natural Experiment

The purpose of this natural experiment study was to assess the effectiveness of a 12-month digital Diabetes Prevention Program (DPP) for adults aged 65-75 years with prediabetes and obesity within a large, integrated health care system. Adjusting for propensity scores and covariates, patients who enrolled and participated in the digital DPP had a mean weight loss of 8.6 lb over 12 months and 5.7 lb by 24 months, compared with a steady, minimal weight loss of 1.3 lb over 12 months and 2.8 lb by 24 months among patients not enrolled. There was a significant difference in mean change in A1C between enrolled and nonenrolled patients over 12 months (-0.10%), but not by 24 months (-0.06%). Digital DPP appears to be an effective weight loss option and potential diabetes prevention intervention for older adults at high risk for type 2 diabetes.

Evaluating the Implementation of Digital and In-Person Diabetes Prevention Program in a Large, Integrated Health System: Natural Experiment Study Design

INTRODUCTION

Implementation of a Diabetes Prevention Program (DPP) in both in-person and digital health-care settings has been increasing. The purpose of this article is to describe the protocol of a mixed-methods, natural experiment study designed to evaluate the implementation of DPP in a large, integrated health system.

METHODS

Kaiser Permanente Northwest patients who were 19 to 75 years with prediabetes (hemoglobin A1c or glycated hemoglobin, 5.7-6.4) and obesity (body mass index ≥ 30 kg/m2) were invited, via the Kaiser Permanente Northwest patient portal, to participate in the digital (n = 4124) and in-person (n = 2669) DPP during 2016 through 2018. Primary (weight) and secondary (hemoglobin A1c or glycated hemoglobin level) outcome data will be obtained from electronic health records. A cost-effectiveness analysis as well as qualitative interviews with patients (enrolled and not enrolled in the DPP) and stakeholders will be conducted to examine further implementation, acceptability, and sustainability.

CONCLUSION

The mixed-methods, natural experiment design we will use to evaluate Kaiser Permanente Northwest's implementation of the digital and in-person DPP builds on existing evidence related to the effectiveness of these two DPP delivery modes and will contribute new knowledge related to best practices for implementing and sustaining the DPP within large health systems over the long term.

The Relationship Between Weight Loss Outcomes and Engagement in a Mobile Behavioral Change Intervention: Retrospective Analysis

Background

There is large variance in weight loss outcomes of digital behavior change interventions (DBCIs). It has been suggested that different patterns of engagement in the program could be responsible for this variance in outcomes. Previous studies have found that the amount of engagement on DBCIs, such as the number of meals logged or articles read, is positively associated with weight loss.

Objective

This retrospective study extends previous research by observing how important weight loss outcomes (high weight loss: 10% or greater body weight loss; moderate weight loss: between 5% to 10%; stable weight: 0 plus or minus 1%) are associated with engagement on a publicly available mobile DBCI (Noom) from 9 to 52 weeks.

Methods

Engagement and weight data for eligible participants (N=11,252) were extracted from the Noom database. Engagement measures included the number of articles read, meals logged, steps recorded, messages to coach, exercise logged, weigh-ins, and days with 1 meal logged per week. Weight was self-reported on the program. Multiple linear regressions examined how weight loss outcome (moderate and high vs stable) was associated with each engagement measure across 3 study time periods: 9-16 weeks, 17-32 weeks, and 33-52 weeks.

Results

At 9-16 weeks, among the 11,252 participants, 2594 (23.05%) had stable weight, 6440 (57.23%) had moderate weight loss, and 2218 (19.71%) had high weight loss. By 33-52 weeks, 525 (18.21%) had stable weight, 1214 (42.11%) had moderate weight loss, and 1144 (39.68%) had high weight loss. Regression results showed that moderate weight loss and high weight loss outcomes were associated with all engagement measures to a significantly greater degree than was stable weight (all P values <.001). These differences held across all time periods with the exception of exercise for the moderate weight loss category at 1 time period of 33-52 weeks. Exercise logging increased from 9 to 52 weeks regardless of the weight loss group.

Conclusions

Our results suggest that these clinically important weight loss outcomes are related to the number of articles read, meals logged, steps recorded, messages to coach, exercise logged, weigh-ins, and days with 1 meal logged per week both in the short-term and long-term (ie, 1 year) on Noom. This provides valuable data on engagement patterns over time on a self-directed mobile DBCI, can help inform how interventions tailor recommendations for engagement depending on how much weight individuals have lost, and raises important questions for future research on engagement in DBCIs.

Costing a population health management approach for participant recruitment to a diabetes prevention study

Limited research has reported the economic feasibility-from both a research and practice perspective-of efforts to recruit and enroll an intended audience in evidence-based approaches for disease prevention. We aimed to retrospectively assess and estimate the costs of a population health management (PHM) approach to identify, engage, and enroll patients in a Type 1 Hybrid Effectiveness-Implementation (HEI), diabetes-prevention trial. We used activity-based costing to estimate the recruitment costs of a PHM approach integrated within an HEI trial. We took the perspective of a healthcare system that may adopt, and possibly sustain, the strategy in the typical practice. We also estimated replication costs based on how the strategy could be applied in healthcare systems interested in referring patients to a local diabetes prevention program from a payer perspective. The total recruitment and enrollment costs were $360,424 to accrue 599 participants over approximately 15 months. The average cost per screened and enrolled participant was $263 and $620, respectively. Translating to the typical settings, total recruitment costs for replication were estimated as $193,971 (range: $43,827-$210,721). Sensitivity and scenario analysis results indicated replication costs would be approximately $283-$444 per patient enrolled if glucose testing was necessary, based on the Medicare-covered services. From a private payer perspective, and without glucose testing, per-participant assessed costs were estimated at $31. A PHM approach can be used to accrue a large number of participants in a short period of time for an HEI trial, at a comparable cost per participant.

Pharmacy-based screening to detect persons at elevated risk of type 2 diabetes: a cost-utility analysis

Background

Early identification of people at elevated risk of type 2 diabetes (T2D) is an important step in preventing or delaying its onset. Pharmacies can serve as a significant channel to reach these people. This study aimed to assess the potential health economic impact of screening and recruitment services in pharmacies in referring people to preventive interventions.

Methods

A decision analytic model was constructed to perform a cost-utility analysis of the expected national health economic consequences (in terms of costs and quality-adjusted life years, QALYs) of a hypothetical pharmacy-based service where people screened and recruited through pharmacies would participate in a digital lifestyle program. Cost-effectiveness was considered in terms of net monetary benefit (NMB). In addition, social return on investment (SROI) was calculated as the ratio of the intervention and recruitment costs and the net present value of expected savings. Payback time was the time taken to reach the break-even point in savings. In the base scenario, a 20-year time horizon was applied. Probabilistic and deterministic sensitivity analyses were applied to study robustness of the results.

Results

In the base scenario, the expected savings from the pharmacy-based screening and recruitment among the reached target cohort were 255.3 m€ (95% CI − 185.2 m€ to 717.2 m€) in pharmacy visiting population meaning 1412€ (95% CI − 1024€ to 3967€) expected savings per person. Additionally, 7032 QALYs (95% CI − 1344 to 16,143) were gained on the population level. The intervention had an NMB of 3358€ (95% CI − 1397€ to 8431€) using a cost-effectiveness threshold of 50,000 €/QALY. The initial costs were 122.2 m€ with an SROI of 2.09€ (95% CI − 1.52€ to 5.88€). The expected payback time was 10 and 8 years for women and men, respectively. Results were most sensitive for changes in effectiveness of the intervention and selected discount rate.

Conclusions

T2D screening and recruitment to prevention programs conducted via pharmacies was a dominant option providing both cost savings and QALY gains. The highest savings can be potentially reached by targeting recruitment at men at elevated risk of T2D.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12913-021-06948-6.

Rural/urban disparities in access to the National Diabetes Prevention Program

Residents of rural communities generally have limited access to preventive health services such as lifestyle programs for weight management. In 2009, the U.S. Congress authorized the Centers for Disease Control and Prevention (CDC) to partner with local community organizations to disseminate the Diabetes Prevention Program (DPP), an evidence-based lifestyle intervention for weight management. Given that the National DPP (NDPP) was designed to broaden nationwide access to weight-loss treatment for adults at high risk for developing diabetes, the present study examined the implementation of the NDPP in rural and urban counties across the USA. The names and locations of NDPP community partnership sites were collected from the CDC website and cross-referenced with the U.S. Census Bureau's classification of counties as rural versus urban. Results showed that overall 27.9% of the 3,142 counties in the USA contained one or more NDPP partnership sites. However, significantly fewer rural counties had access to a NDPP site compared with urban counties (14.6% vs. 48.4%, respectively, p < .001). This disparity was evident across all types of partnership sites (ps < .001). These findings indicate that implementation of the NDPP has expanded the overall availability of evidence-based weight-management programs across the USA. However, this increase has been disproportionately greater for urban counties versus rural counties, thereby widening the rural/urban disparity in access to preventive health services. Alternative dissemination strategies that address the special barriers to implementation faced by rural communities are needed to increase access to the NDPP.

Identifying critical features of type two diabetes prevention interventions: A Delphi study with key stakeholders

Aims

This study aims to identify critically important features of digital type two diabetes mellitus (T2DM) prevention interventions.

Methods

A stakeholder mapping exercise was undertaken to identify key end-user and professional stakeholders, followed by a three-round Delphi procedure to generate and evaluate evidence statements related to the critical elements of digital T2DM prevention interventions in terms of product (intervention), price (funding models/financial cost), place (distribution/delivery channels), and promotion (target audiences).

Results

End-user (n = 38) and professional (n = 38) stakeholders including patients, dietitians, credentialed diabetes educators, nurses, medical doctors, research scientists, and exercise physiologists participated in the Delphi study. Fifty-two critical intervention characteristics were identified. Future interventions should address diet, physical activity, mental health (e.g. stress, diabetes-related distress), and functional health literacy, while advancing behaviour change support. Programs should be delivered digitally or used multiple delivery modes, target a range of population subgroups including children, and be based on collaborative efforts between national and local and government and non-government funded organisations.

Conclusions

Our findings highlight strong support for digital health to address T2DM in Australia and identify future directions for T2DM prevention interventions. The study also demonstrates the feasibility and value of stakeholder-led intervention development processes.

Reach, engagement and effectiveness of in-person and online lifestyle change programs to prevent diabetes

BACKGROUND

COVID-19 has accelerated interest in and need for online delivery of healthcare. We examined the reach, engagement and effectiveness of online delivery of lifestyle change programs (LCP) modelled after the Diabetes Prevention Program (DPP) in a multistate, real-world setting.

METHODS

Longitudinal, non-randomized study comparing online and in-person LCP in a large multistate sample delivered over 1 year. Sample included at-risk adults (n = 26,743) referred to online (n = 9) and in-person (n = 11) CDC-recognized LCP from a multi-state registry (California, Florida and Colorado) between 2015 and 2018. The main outcome was effectiveness (proportion achieving > 5% weight loss) at one-year. Our secondary outcomes included reach (proportion enrolled among referred) and engagement (proportion ≥ 9 sessions by week 26). We used logistic regression modelling to assess the association between participant- and setting -level characteristics with meaningful weight loss.

RESULTS

Online LCP effectiveness was lower, with 23% of online participants achieving > 5% weight loss, compared with 35% of in-person participants (p < 0.001). More adults referred to online programs enrolled (56% vs 51%, p < 0.001), but fewer engaged at 6-months (attendance at ≥9 sessions 46% vs 66%, p < 0.001) compared to in-person participants.

CONCLUSIONS

Compared to adults referred to in-person LCP, those referred to online LCP were more likely to enroll and less likely to engage. Online participants achieved modest meaningful weight loss. Online delivery of LCP is an attractive strategy to deliver and scale DPP, particularly with social distancing measures currently in place. However, it is unclear how to optimize delivery models for maximal impact given trade-offs in reach and effectiveness.

Commercial Weight Loss Programs in the Management of Obesity: an Update

PURPOSE OF REVIEW

Comprehensive lifestyle programs are cornerstones of obesity management, but clinician referrals may be limited by program availability. Commercial weight loss programs may be an alternative, but clinicians may be unaware of their efficacy and safety. This review describes the evidence for commercial programs, particularly 12-month weight loss, among individuals with obesity.

RECENT FINDINGS

Several programs are concordant with evidence-based recommendations (i.e., lower-calorie diet, increased physical activity, and behavioral strategies). Among the guideline-concordant programs, National Diabetes Prevention Program, WW, Jenny Craig, Medifast, and OPTIFAST have demonstrated 12-month weight loss efficacy and safety. While other programs show promise, more evidence is needed before clinician referral may be recommended. Clinical practice guidelines support referrals to commercial weight loss programs that have peer-reviewed evidence to support their efficacy and safety. Clinicians should consider the available evidence, patient preference, and cost when considering referrals to these programs for weight management.

Feasibility and Adoption of a Focused Digital Wellness Program in Older Adults

Digital health programs offer numerous psychological and physical health benefits. To date, digital programs have been aimed broadly at younger participants, yet older individuals may also benefit. Our study sought to demonstrate user feasibility and satisfaction in a digital wellness program for older adults. We conducted a retrospective analysis of 140 participants in a digital health wellness application that integrated guided exercises, nutrition planning and health education. Primary outcomes were active participant retention, engagement in the mobile program and user satisfaction as operationalized by NPS scores. Among 140 participants, median age was 59.82 (50–80), 61% female, in a sample taken in the United States. Engagement was high and sustained, with more than 65% participants engaged, operationalized as at least completing one task activity a month over 17 weeks. Participants were also satisfied with the program, reporting NPS scores of 43 on day 30 of the program. Secondary health outcomes included 3.44 pound weight change during the first month. User feasibility and satisfaction was demonstrated in a sample of older participants for this novel digital health wellness program. Future work focused on older adult users may result in improvements in patient health outcomes and improved preventive medicine strategies.

Effectiveness of eHealth Nutritional Interventions for Middle-Aged and Older Adults: Systematic Review and Meta-analysis

BACKGROUND

The risk of development of chronic diseases related to poor nutrition increases with age. In the face of an aging population, it is important for health care sectors to find solutions in delivering health services efficiently and effectively to middle-aged and older adults.

OBJECTIVE

The aim of this systematic review and meta-analysis was to consolidate the literature that reported the effectiveness of eHealth apps in delivering nutritional interventions for middle-aged and older adults.

METHODS

A literature search from five databases (PubMed, CINAHL, Cochrane, Web of Science, and Global Health) from the past 5 years was performed. Studies were selected for inclusion that used eHealth to deliver nutritional interventions to adults aged 40 years and above, and reported health and behavioral outcomes. Two independent reviewers searched for research articles and assessed the eligibility of studies to be included in the review. A third reviewer resolved disagreements on study inclusion. We also assessed the quality of the included studies using the CONSORT 2010 checklist.

RESULTS

A total of 70 studies were included for analysis. The study quality ranged from 44% to 85%. The most commonly used eHealth intervention type was mobile apps (22/70, 31%). The majority of studies (62/70, 89%) provided multicomponent health interventions, which aimed to improve nutrition and other health behaviors (eg, exercise, smoking cessation, medication adherence). Meta-analysis results indicated high and significant heterogeneity; hence, conclusions based on these results should be considered with caution. Nonetheless, the results generally showed that eHealth interventions improved anthropometric and clinical outcomes, but not behavioral outcomes such as fruit and vegetable consumption.

CONCLUSIONS

The use of eHealth apps to deliver health interventions has been increasing in recent years, and these apps have the potential to deliver health services to a larger group of people. Our findings showed that the effectiveness of eHealth apps to deliver health interventions for middle-aged to older adults was supported by the improvement of anthropometric and clinical outcomes. Future work could aim to develop research frameworks in administering eHealth interventions to address heterogeneity in this field of research.

Future and Development Direction of Digital Healthcare

OBJECTIVES

Digital healthcare is expected to play a pivotal role in patient-centered healthcare. It empowers patients by informing, communicating, and motivating them. However, a pragmatic evaluation of the present status of digital healthcare has not been presented; therefore, we aimed to examine the status of digital healthcare in Korea.

METHODS

This article discusses digital healthcare, examples of assessment in Korea and other countries, the implications of past examples, and future directions for development.

RESULTS

Over the years, various clinical studies have used clinical evidence to assess the feasibility of digital healthcare. If feasible, it is actually clinically effective. If it is effective, can it be commercialized at an acceptable cost? These questions have been investigated in various evidence-based studies. In addition, great efforts are being made to secure ample evidence to assess various aspects of digital healthcare, such as safety, quality, end-user experience, and equity.

CONCLUSIONS

Digital healthcare requires a deep understanding of both the technical and medical aspects. To strengthen the competence of the medical aspect, medical staff, patients, and the government must work together with continuous interest in this goal.

Return on Investment: Medical Savings of an Employer-Sponsored Digital Intensive Lifestyle Intervention, Weight Loss

OBJECTIVE

This study aimed to determine the medical cost impact and return on investment (ROI) of a large, commercial, digital, weight-management intensive lifestyle intervention (ILI) program (Real Appeal).

METHODS

Participants in this program were compared with a control group matched by age, sex, geographic region, health risk, baseline medical costs, and chronic conditions. Medical costs were defined as the total amount paid for all medical expenses, inclusive of both the insurers' and the study participants' responsibility.

RESULTS

In the 3 years following program registration, the intent-to-treat (ITT) cohort had significantly lower medical expenditures than the matched controls, with an average of -$771 or 12% lower costs (P = 0.002). Among 4,790 ITT participants, a total savings of $3,693,090 compared with total program costs of $1,639,961 translated into a 2.3:1 ROI. Program completers (n = 3,990), who attended more sessions than the overall ITT group, had greater mean weight loss (-4.4%), greater cost savings (-$956 or 14%), and an ROI of 2.0:1 over the 3-year time frame compared with matched controls.

CONCLUSIONS

The findings demonstrated that the digital weight-management ILI was associated with a significantly positive ROI. Employers and payers willing to cover the cost of an ILI that produces both weight loss and demonstrated cost benefits can improve health and save money for their population with overweight or obesity.

Why digital health trials can fail: Lessons learned from a randomized trial of health coaching and virtual cardiac rehabilitation

Background

Methods

Results

Conclusion

Digital Coaching Strategies to Facilitate Behavioral Change in Type 2 Diabetes: A Systematic Review

CONTEXT

In this systematic review, we focus on the clinical impact of digital tools for providing health coaching, education, and facilitating behavior in patients with prediabetes or type 2 diabetes. Our approach was designed to provide insights for clinicians and health care systems that are considering adopting such digital tools.

EVIDENCE ACQUISITION

We searched the CINAHL, Scopus, and Ovid/MEDLINE databases using PRISMA guidelines for studies that reported digital coaching strategies for management and prevention of type 2 diabetes published from January 2014 to June 2019. Articles were reviewed by 2 independent blinded reviewers. Twenty-one articles met inclusion criteria.

EVIDENCE SYNTHESIS

We found that 20 of 21 studies in our analysis showed statistically significant improvements in at least one measure of diabetes control including HbA1c, weight loss, fasting blood glucose, and BMI. Studies that reported weight loss percentage from baseline at 1 year reported values ranging from -3.04% to -8.98%, similar to outcomes with traditional coaching in the Diabetes Prevention Program (N = 4). Additionally, all studies that included a comparison group of in-person or telephone-based coaching showed statistically better or similar outcomes in the digital coaching group (N = 5).

CONCLUSIONS

The evidence reported in this systematic review suggests that digital health coaching offers a promising strategy for long-term management and prevention of type 2 diabetes in diverse populations with similar benefits to in-person or telephone-based health coaching. We argue that, with the potential to treat large numbers of individuals in diverse geographic locations, digital coaching offers a promising solution to the rapid increase in diabetes prevalence.

A web-based intervention to increase weight loss treatment initiation: results of a cluster randomized feasibility and acceptability trial

Evidence-based behavioral weight loss treatment is under-utilized. To increase initiation of treatment, we developed a single-session, online, primary care-based intervention ("mobilization tool"). We evaluated the mobilization tool's acceptability for primary care patients with obesity, trial design feasibility, and signal of an effect of the tool on treatment initiation. In this cluster randomized feasibility trial, primary care providers (PCPs) were randomized to a mobilization tool or comparator tool arm. Patients with obesity and a scheduled appointment with a randomized PCP were assigned to complete the mobilization or comparator tool prior to their appointment. The online mobilization tool asks patients to answer questions about a variety of weight-related topics and then provides automated, tailored feedback that addresses psychosocial determinants of weight loss treatment initiation. The comparator tool provided a nontailored description of treatments. All participants were offered free enrollment in behavioral weight loss treatments. Six PCPs were randomized. Sixty patients (57% female; 66% white; aged 55 ± 13 years) participated in this study of 296 contacted for eligibility evaluation (20.2%). Six-month follow-up assessments were completed by 65% (22/34) of the mobilization and 73% (19/26) of comparator tool participants. Participants completing the acceptability survey reported that the mobilization tool was usable, enjoyable, informative, and useful. Weight loss treatment was initiated by 59% (n = 19) of mobilization and 33% (n = 8) of comparator tool participants. The mobilization tool shows promise for increasing treatment initiation among primary care patients, which may increase population weight loss. Trial Registration: Clinicaltrials.gov identifier: NCT02708121.

Protocol for a feasibility and early efficacy study of the Comprehensive Lifestyle Improvement Program for Prostate Cancer-2 (CLIPP2)

Background

Although androgen deprivation therapy (ADT) for prostate cancer demonstrates improved overall and disease-free survival, it is associated with adverse effects such as obesity and metabolic syndrome that increase risk of cardiometabolic disease and diabetes type 2. ADT also leads to fatigue, depression and erectile dysfunction, which reduce quality of life (QoL). Lifestyle modification has shown promise in reducing obesity, metabolic syndrome and diabetes type 2 in other disease types. However, there is a paucity of data regarding the utility of lifestyle modification in men receiving ADT for prostate cancer.

Methods

The primary aim of the Comprehensive Lifestyle Improvement Program for Prostate Cancer-2 (CLIPP2) is to test the feasibility of conducting a 24-week lifestyle modification intervention in men on ADT for prostate cancer. Additionally, it will also determine the effect of this intervention on weight loss, cardiometabolic markers (secondary aim and markers of interest: serum glucose, insulin resistance, hemoglobin A1C and lipid panel), and QoL (tertiary aim). The intervention will be delivered weekly via telephone for the first 10 weeks and bi-weekly for the remaining 14 weeks. Questionnaires and serum samples will be collected at baseline, week 12, and week 24. Anthropometric measurements will be collected at baseline, week 6, week 12, week 18 and week 24.

Results

We hypothesize that the CLIPP2 intervention will produce a 7% weight loss that will result in improved markers associated with cardiometabolic disease and type 2 diabetes in the study population.

Conclusion

Results will provide insight into the role of lifestyle modification in addressing ADT adverse effects as well as provide preliminary data to inform the development of future lifestyle interventions in this area.

Trial registration

NCT04228055 Clinicaltrials. gov.

A Multilevel Diabetes and CVD Risk Reduction Intervention in African American Churches: Project Faith Influencing Transformation (FIT) Feasibility and Outcomes

Wide-reaching health promotion interventions are needed in influential, accessible community settings to address African American (AA) diabetes and CVD disparities. Most AAs are overweight/obese, which is a primary clinical risk factor for diabetes/CVD. Using a faith-community-engaged approach, this study examined feasibility and outcomes of Project Faith Influencing Transformation (FIT), a diabetes/CVD screening, prevention, and linkage to care pilot intervention to increase weight loss in AA church-populations at 8 months. Six churches were matched and randomized to multilevel FIT intervention or standard education control arms. Key multilevel religiously tailored FIT intervention components included: (a) individual self-help materials (e.g., risk checklists, pledge cards); (b) YMCA-facilitated weekly group Diabetes Prevention Program (DPP) weight loss classes; (c) church service activities (e.g., sermons, responsive readings); and (d) church-community text/voice messages to promote healthy eating and physical activity. Health screenings (e.g., weight, blood pressure, blood glucose) were held during church services to identify participants with diabetes/CVD risks and refer them to their church's DPP class and linkage to care services. Participants (N = 352 church members and community members using churches' outreach ministries) were primarily female (67%) and overweight/obese (87%). Overall, FIT intervention participants were significantly more likely to achieve a > 5 lb weight loss (OR = 1.6; CI = 1.24, 2.01) than controls. Odds of intervention FIT-DPP participants achieving a > 5 lb weight loss were 3.6 times more than controls (p < .07). Exposure to sermons, text/email messages, brochures, commitment cards, and posters was significantly related to > 5 lb. weight loss. AA churches can feasibly assist in increasing reach and impact of diabetes/CVD risk reduction interventions with intensive weight loss components among at risk AA church-populations.

Can you see me? Participant experience of accessing a weight management programme via group videoconference to overcome barriers to engagement

Background

Engagement with conventional weight management group programmes is low.

Objective

To understand participant experience of accessing an adapted programme via videoconference.

Participants

Adults with obesity (BMI ≥ 35kg/m²), referred to an NHS Dietetics service in Wales, were offered a group videoconference weight management programme as an optional alternative to in‐person groups. Thirteen participants (mean age 48.5 ± 20.2 years, 8 female) recruited to two videoconference groups were interviewed.

Study design

A Registered Dietitian delivered a behavioural programme using Skype for Business in 10 sessions over 6 months. Participants joined the groups from any Internet‐connected device with a webcam. Participant perspectives were audiorecorded in one‐to‐one, semi‐structured interviews. Interviews were transcribed verbatim and thematically analysed using self‐determination theory as a theoretical framework.

Results

Ten themes were identified, three relating to service engagement and seven relating to behaviour change facilitation. Key themes in engagement included ‘reduced burden’, described as saving time and travel and ‘reduced threat’ as participants perceived joining a group from home as less daunting compared to attending in‐person. Despite reporting some initial technical difficulties with establishing video and audio connection, participants described beneficial peer support although not physically with other group members.

Conclusion

Accessing a group weight management programme via videoconference may be the preferred option for some participants, overcoming some of the barriers to access to standard in‐person programmes, particularly in rural areas. Participants are able to experience peer support via videoconference. During the COVID‐19 pandemic, weight management programmes could utilize videoconference groups to continue to provide support.

Impact of a Digital Diabetes Prevention Program on Risk Factors for Chronic Disease in a Workforce Cohort

OBJECTIVE

Evaluate the effect of a digital Diabetes Prevention Program (dDPP) on chronic disease risk factors in a workplace population.

METHODS

dDPP participants were employees and spouses with BMI ≥ 24 kg/m and prediabetes or diabetes (n = 84). Annual change in risk factors before and after dDPP were assessed in the dDPP group and in a retrospectively identified matched control group drawn from those who participated in a dDPP after the conclusion of this study (n = 252).

RESULTS

In the dDPP group, body weight, BMI, fasting glucose, triglycerides, total cholesterol and LDL-cholesterol decreased in the post-dDPP period compared with the pre-dDPP period (P < 0.05). In the control group, no difference between the annual change before and after dDPP was observed (P > 0.37).

CONCLUSION

The dDPP was effective in reducing risk factors for chronic disease in a workplace setting.

Developing and testing a discrete event simulation model to evaluate budget impacts of diabetes prevention programs

Type 2 diabetes (T2D) is one of the most rapidly increasing non-communicable diseases worldwide. Lifestyle interventions are effective in preventing T2D but also resource intensive. This study evaluated with discrete event simulation (DES) the relative budget impacts of three hypothetical diabetes prevention programs (DPP), including group-based contact intervention, digital program with human coaching and fully automated program. The data for simulation were derived from research literature and national health and population statistics. The model was constructed using the iGrafx Process for Six Sigma software and simulations were carried out for 10 years. All simulated interventions produced cost savings compared to the situation without any intervention. However, this was a modeling study and future studies are needed to verify the results in real-life. Decision makers could benefit the predictive models regarding the long-term effects of diabetes prevention interventions, but more data is needed in particular on the usage, acceptability, effectiveness and costs of digital intervention tools.

Drivers of weight loss in a CDC-recognized digital diabetes prevention program

INTRODUCTION

To investigate the impact of the digital Livongo Diabetes Prevention Program (DPP) on weight at 12 months, understand participants' self-monitoring behaviors associated with greater weight loss, and evaluate the impact of coaching interactions on more frequent self-monitoring behaviors.

RESEARCH DESIGN AND METHODS

A retrospective analysis was performed using data from 2037 participants enrolled in the Livongo DPP who completed lesson 1 and recorded a starting weight during 2016-2017. Self-monitoring behaviors, including weigh-ins, food logging, activity, and coach-participant interactions, were analyzed at 6 and 12 months. Subgroup analysis was conducted based on those who were highly engaged versus those minimally engaged. Multiple regression analysis was performed using demographic, self-monitoring, and lesson attendance data to determine predictors of weight loss at 12 months and coaching impact on self-monitoring.

RESULTS

Participants had a mean age of 50 years (SD ±12), with a starting weight of 94 kg (SD ±21), were college-educated (78%), and were female (74%). Overall, participants lost on average 5.1% of their starting weight. Highly engaged participants lost 6.6% of starting body weight, with 25% losing ≥10% at 12 months. Logistic regression analysis showed each submitted food log was associated with 0.23 kg (p<0.05) weight loss, each lesson completed was associated with 0.14 kg (p<0.05) weight loss, and a week of 150 active minutes was associated with 0.1 kg (p<0.01) weight loss. One additional coach-participant message each week was associated with 1.4 more food logs per week, 1.6% increase in weeks with four or more weigh-ins, and a 2.7% increase in weeks with 150 min of activity.

CONCLUSIONS

Food logging had the largest impact on weight loss, followed by lesson engagement and physical activity. Future studies should examine further opportunities to deliver nutrition-based content to increase and sustain weight loss for DPP.