Digital Diabetes Prevention Research Articles

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

To assess the cost-effectiveness of a digital diabetes prevention programme (d-DPP) compared with a diabetes prevention programme (DPP) for preventing type 2 diabetes (T2D) in individuals with prediabetes in the United States. A Markov cohort model was constructed, simulating a 10-year period starting at the age of 45 years, with a societal and healthcare sector perspective. The effectiveness of the d-DPP intervention was evaluated using a meta-analysis, with that of the DPP as the comparator. The initial cycle represented the treatment period, and transition probabilities for the post-treatment period were derived from a long-term lifestyle intervention meta-analysis. The onset of T2D complications was estimated using microsimulation. Quality-adjusted life years (QALYs) were calculated based on health utility measured by short form (SF)-12 scores, and a willingness-to-pay threshold of $100 000 per QALY gained was applied. The d-DPP intervention resulted in cost savings of $3,672 from a societal perspective and $2,990 from a healthcare sector perspectiveand a gain of 0.08 QALYs compared with the DPP. The dropout rate was identified as a significant factor influencing the results. Probabilistic sensitivity analysis showed that the d-DPP intervention was preferred in 85.8% in the societal perspective and 85.2% in the healthcare sector perspective. The d-DPP is a cost-effective alternative to in-person lifestyle interventions for preventing the development of T2D among individuals with prediabetes in the United States.

Feasibility of Fit24, a Digital Diabetes Prevention Program for Hispanic Adolescents: Qualitative Evaluation Study.

Digital health interventions are promising for reaching and engaging high-risk youth in disease prevention opportunities; however, few digital prevention interventions have been developed for Hispanic youth, limiting our knowledge of these strategies among this population. This study qualitatively assessed the feasibility and acceptability of Fit24, a 12-week goal-setting intervention that uses a Fitbit watch (Fitbit Inc) and theoretically grounded SMS text messages to promote physical activity and sleep among Hispanic adolescents (aged between 14 and 16 years) with obesity. After completing the intervention, a subsample of youth (N=15) participated in an in-depth interview. We categorized the themes into dimensions based on participant perspectives using the Practical, Robust Implementation, and Sustainability Model (PRISM) framework. Participants shared positive perceptions of wearing the Fitbit and receiving SMS text messages. Youth were highly engaged in monitoring their behaviors and perceived increased activity and sleep. Almost all youth organically received social support from a peer or family member and suggested the use of a group chat or team challenge for integrating peers into future interventions. However, most youth also expressed the need to take personal responsibility for the change in their behavior. Barriers that impacted the feasibility of the study included the skin-irritating material on the Fitbit watch band and environmental barriers (eg, lack of resources and school schedules), that limited participation in activity suggestions. Additionally, sync issues with the Fitbit limited the transmission of data, leading to inaccurate feedback. Fit24 is a promising approach for engaging Hispanic youth in a diabetes prevention program. Strategies are needed to address technical issues with the Fitbit and environmental issues such as message timing. While integrating peer social support may be desired by some, peer support strategies should be mindful of youth's desire to foster personal motivation for behavior change. Findings from this study will inform future diabetes prevention trials of Fit24 and other digital health interventions for high-risk pediatric populations.

Effects of Early-Program Physical Activity Lessons on Daily Active Minutes in a Digital Diabetes Prevention Program

ABSTRACT Background Reducing sedentary behavior and increasing physical activity have important benefits for type 2 diabetes prevention and risk reduction. Purpose To evaluate the immediate impact of completing educational lessons about physical activity within a fully digital diabetes prevention program (DPP) on the daily activity levels of participants with overweight or obesity and at risk for type 2 diabetes. Methods This study compared the pre-post change in daily active minutes of participants between two groups, 1. Completers, or participants who completed physical activity lessons 2 and 3 of the DPP and 2. Starters, or a propensity-matched control group who initiated the program but did not complete lessons 2 and 3 within the first month. Results We observed a significant difference in the change in daily active minutes between groups (U = 636742.5, p ≤ .0001). Completers increased their daily active minutes between baseline and the end of the first month (Mean = 7.1 minutes, SE = 0.7) while Starters decreased (Mean = –25.4 minutes; SE = 1.0). Discussion Targeted educational lessons about physical activity coupled with self-monitoring and automated coaching promoted daily physical activity among participants in a digital DPP. Translation to Health Education Practice Health educators may use digitally delivered educational lessons about physical activity to facilitate immediate changes in daily active behaviors.

Leveraging Machine Learning to Develop Digital Engagement Phenotypes of Users in a Digital Diabetes Prevention Program: Evaluation Study.

Digital diabetes prevention programs (dDPPs) are effective "digital prescriptions" but have high attrition rates and program noncompletion. To address this, we developed a personalized automatic messaging system (PAMS) that leverages SMS text messaging and data integration into clinical workflows to increase dDPP engagement via enhanced patient-provider communication. Preliminary data showed positive results. However, further investigation is needed to determine how to optimize the tailoring of support technology such as PAMS based on a user's preferences to boost their dDPP engagement. This study evaluates leveraging machine learning (ML) to develop digital engagement phenotypes of dDPP users and assess ML's accuracy in predicting engagement with dDPP activities. This research will be used in a PAMS optimization process to improve PAMS personalization by incorporating engagement prediction and digital phenotyping. This study aims (1) to prove the feasibility of using dDPP user-collected data to build an ML model that predicts engagement and contributes to identifying digital engagement phenotypes, (2) to describe methods for developing ML models with dDPP data sets and present preliminary results, and (3) to present preliminary data on user profiling based on ML model outputs. Using the gradient-boosted forest model, we predicted engagement in 4 dDPP individual activities (physical activity, lessons, social activity, and weigh-ins) and general activity (engagement in any activity) based on previous short- and long-term activity in the app. The area under the receiver operating characteristic curve, the area under the precision-recall curve, and the Brier score metrics determined the performance of the model. Shapley values reflected the feature importance of the models and determined what variables informed user profiling through latent profile analysis. We developed 2 models using weekly and daily DPP data sets (328,821 and 704,242 records, respectively), which yielded predictive accuracies above 90%. Although both models were highly accurate, the daily model better fitted our research plan because it predicted daily changes in individual activities, which was crucial for creating the "digital phenotypes." To better understand the variables contributing to the model predictor, we calculated the Shapley values for both models to identify the features with the highest contribution to model fit; engagement with any activity in the dDPP in the last 7 days had the most predictive power. We profiled users with latent profile analysis after 2 weeks of engagement (Bayesian information criterion=-3222.46) with the dDPP and identified 6 profiles of users, including those with high engagement, minimal engagement, and attrition. Preliminary results demonstrate that applying ML methods with predicting power is an acceptable mechanism to tailor and optimize messaging interventions to support patient engagement and adherence to digital prescriptions. The results enable future optimization of our existing messaging platform and expansion of this methodology to other clinical domains. ClinicalTrials.gov NCT04773834; https://www.clinicaltrials.gov/ct2/show/NCT04773834. RR2-10.2196/26750.

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

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. The majority of participants (n = 33), all service users, were interviewed twice via telephone, at 2-4months into the programme, and at the end of the programme at 8-10months. 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. 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. 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.

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 insurancemembers 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.

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

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. 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. 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. 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. 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.

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

BackgroundDigital 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. MethodsAnonymous 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. ResultsApp 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. ConclusionsApp 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.

Cost-effectiveness analysis of a digital Diabetes Prevention Program (dDPP) in prediabetic patients.

To assess the cost-effectiveness of a digital Diabetes Prevention Program (dDPP) in preventing type 2 diabetes mellitus among prediabetic patients from a health system perspective over a 10-year time horizon. A Markov cohort model was constructed to assess the cost-effectiveness of dDPP compared to a small group education (SGE) intervention. Transition probabilities for the first year of the model were derived from two clinical trials on dDPP. Transition probabilities for longer-term effects were derived from meta-analyses on lifestyle and Diabetes Prevention Program interventions. Cost and health utilities were derived from published literature. Partial completion of interventions was incorporated to provide a robust prediction of a real-world deployment. Parameter uncertainties were assessed using univariate and probabilistic sensitivity analyses. Cost-effectiveness was measured by an incremental cost-effectiveness ratio (ICER) between dDPP and SGE from a health system perspective over a 10-year time horizon. The dDPP dominated the SGE at the $50,000, $100,000, and $150,000 willingness-to-pay thresholds per quality-adjusted life years (QALYs). The base case analysis at the $100,000 willingness-to-pay threshold (WTP) revealed a dominated ICER, with the SGE costing $1332 more and accruing an average of 0.04 fewer QALYs. Probabilistic sensitivity analysis showed that the dDPP was preferred in 64.4% of simulations across the $100,000 WTP thresholds. The findings comparing a dDPP to an SGE suggest that a dDPP can be cost-effective for patients with a high risk of developing type 2 diabetes.

Weight Loss in a Digital Diabetes Prevention Program for People in Health Professional Shortage and Rural Areas.

Individuals with prediabetes living in hard-to-reach and underserved areas experience barriers to accessing traditional in-person preventive health services. The National Diabetes Prevention Program (DPP) is a preventive health care program designed to reduce the risk of developing type 2 diabetes. Although there have been increasing numbers of remote DPPs accessible, there are little data on the clinical outcomes of digital DPPs for members living in hard-to-reach and underserved areas. This study assessed whether living in a designated Health Professional Shortage Area (HPSA) and a rural versus urban area impacted the weight loss of N = 7266 members of a fully digital program called Lark DPP. Secondary analyses included between-group comparisons of program retention and member characteristics, demographics, and socioeconomics. Percent weight loss did not differ by HPSA (P = 0.16) or rural/urban status (P = 0.15), despite greater potential barriers for members residing in HPSAs (eg, highest starting body mass index, lowest income, lowest education). Mean percent weight loss for members residing in an HPSA and rural area was mean (M) = 4.75%, standard error (SE) = 0.09; for members in a non-HPSA, rural area M = 4.96%, SE = 0.16; for members in an HPSA, urban area M = 4.55%, SE = 0.13; and for members in a non-HPSA, urban area M = 4.77%, SE = 0.13. Members of a fully digital DPP achieved weight loss that did not differ by HPSA or urban/rural designation. Fully digital programs offer a solution to reduce the risk of type 2 diabetes in areas where residents may not otherwise have access to diabetes prevention services.

Description of the nationally implemented National Health Service digital diabetes prevention programme and rationale for its development: mixed methods study

BackgroundThe National Health Service (NHS) Digital Diabetes Prevention Programme (DDPP) is a behaviour change programme for adults in England who are at high risk of developing type 2 diabetes. Four independent providers deliver the NHS-DDPP following a competitive tendering process. Although providers work to a single service specification, there is potential for some variation in the service across providers. This study (1) assesses fidelity of the structural features of the design of the NHS-DDPP compared to the service specification, (2) describes the structural features of delivery of the NHS-DDPP as implemented (3) reports developers’ views on how the structural components of the NHS-DDPP were developed and why changes were made following implementation.MethodsUsing mixed methods, we conducted a document review of providers’ NHS-DDPP design and delivery documentation, and extracted information using the Template for Intervention Description and Replication checklist, which was adapted to capture features of digital delivery. Documentation was supplemented by content analysis of interviews with 12 health coaches involved in delivering the NHS-DDPP. Semi-structured interviews were also conducted with 6 programme developers employed by the digital providers.ResultsProvider plans for the NHS-DDPP show relatively high fidelity to the NHS service specification. Despite this, there was wide variation in structural features of delivery of the NHS-DDPP across providers, particularly for delivery of ‘support’ (e.g. use, dose and scheduling of health coaching and/or group support). Interviews with developers of the programmes showed that much of this variation is likely to be attributable to the origin of each provider’s programme, which was usually a pre-existing programme that was adapted to conform to the NHS-DDPP service specification. The NHS-DDPP is continually improved and developed based on user experience feedback and research conducted by the providers.ConclusionIndirect evidence suggests that variation in delivery of support could affect effectiveness of the NHS-DDPP. A priority for future research is ascertaining whether the variation in delivery of the NHS-DDPP across providers is related to any differences in health outcomes. It is recommended that future rounds of commissioning the NHS-DDPP pre-specify the type of support participants should receive, including expected dose and scheduling.

Weight loss and modeled cost savings in a digital diabetes prevention program.

Participation in the National Diabetes Prevention Program (DPP) can improve individual health through reduced risk of type 2 diabetes and save the healthcare system substantial medical costs associated with a diagnosis of type 2 diabetes and its associated complications. There is less evidence of outcomes and cost savings associated with a fully digital delivery of the DPP. This study assessed 13,593 members who provided an initial digital weight and subsequently achieved various weight loss and engagement outcomes during their participation in a digital DPP. Analyzed data included both complete observations and missing observations imputed using maximum likelihood estimation. Findings include members' behavioral correlates of weight loss and a literature-based cost-savings estimate associated with achieving three mutually exclusive weight loss or engagement benchmarks: ≥5% weight loss, >2% but <5% weight loss, and completion of ≥4 educational lessons. 11,976 members (88%) provided a weight after 2months of participation, enabling calculation of their weight nadir. Considering complete data, 97% of members maintained or lost weight. Using the imputed data for these calculations, 32.0% of members achieved ≥5%, 32.4% achieved >2% but <5%, 32.0% maintained ±2%, and 3.6% gained weight. Members who lost the most weight achieved their weight nadir furthest into the program (mean day=189, SE=1.4) and had the longest active engagement (mean days=268, SE=1.4), particularly compared to members who gained weight (mean nadir day=119, SE=3.7; active engagement mean days=199, SE=4.9) (both p≤0.0001). Modeled 1-year cost-savings estimates ranged from $11,229,160 to $12,960,875. Members of a fully digital DPP achieved clinical and engagement outcomes during their participation in the program that confer important health benefits and cost savings.

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

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. 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). 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. 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. 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.

Comparison of weight change between face-to-face and digital delivery of the English National Health service diabetes prevention programme: An exploratory non-inferiority study with imputation of plausible weight outcomes

Worldwide evidence suggests face-to-face diabetes prevention programmes are effective in preventing and delaying the onset of type 2 diabetes by encouraging behaviour change towards weight loss, healthy eating, and increased exercise. There is an absence of evidence on whether digital delivery is as effective as face-to-face. During 2017–18 patients in England were offered the National Health Service Diabetes Prevention Programme as group-based face-to-face delivery, digital delivery (‘digital-only’) or a choice between digital and face-to-face (‘digital-choice’). The contemporaneous delivery allowed for a robust non-inferiority study, comparing face-to-face with digital only and digital choice cohorts.Changes in weight at 6 months were missing for around half of participants. Here we take a novel approach, estimating the average effect in all 65,741 individuals who enrolled in the programme, by making a range of plausible assumptions about weight change in individuals who did not provide outcome data. The benefit of this approach is that it includes everyone who enrolled in the programme, not restricted to those who completed. We analysed the data using multiple linear regression models.Under all scenarios explored, enrolment in the digital diabetes prevention programme was associated with clinically significant reductions in weight which were at least equivalent to weight loss in the face-to-face programme. Digital services can be just as effective as face-to-face in delivering a population-based approach to the prevention of type 2 diabetes. Imputation of plausible outcomes is a feasible methodological approach, suitable for analysis of routine data in settings where outcomes are missing for non-attenders.

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

ObjectiveTo examine changes in cardiovascular disease (CVD) risk outcomes of overweight/obese adults with prediabetes. MethodsUsing data from a randomized control trial of digital diabetes prevention program (d‐DPP) with 599 participants. We applied the atherosclerotic CVD (ASCVD) risk calculator to predict 10-year CVD risk for d‐DPP and small education (comparison) groups. Between-group risk changes at 4 and 12 months were compared using a repeated measures linear mixed-effect model. We examined within-group differences in proportion of participants over time for specific CVD risk factors using generalized estimating equations. ResultsWe found no differences between baseline 10-year ASCVD risk. Relative to the comparison group, the d‐DPP group experienced greater reductions in predicted 10-year ASCVD risk at each follow-up visit and a significant group difference at 4 months (−0.96%; 95% confidence interval: −1.58%, −0.34%) (but not at 12 months). Additionally, we observed that the d‐DPP group experienced a decreased proportion of individuals with hyperlipidemia (18% and 16% from baseline to 4 and 12 months), high-risk total cholesterol (8% from baseline to 12 months), and being insufficiently active (26% and 22% from baseline to 4 and 12 months at follow-up time points. ConclusionsOur findings suggest that a digitally adapted DPP may promote the prevention of cardiometabolic disease among overweight/obese individuals with prediabetes. However, given the lack of maintenance of effect on ASCVD risk at 12 months, there may also be a need for additional interventions to sustain the effect detected at 4 months.

What behaviour change technique content is offered to service users of the nationally implemented English NHS Digital Diabetes Prevention Programme: Analysis of multiple sources of intervention content

The National Health Service Digital Diabetes Prevention Programme (NHS-DDPP) is a behavioural intervention for adults in England at risk of developing Type 2 diabetes, rolled out nationally via independent providers and their digital partners. The NHS England programme specification indicated 19 behaviour change techniques (BCTs) which should be present in the intervention, including BCTs to support self-regulation. A previous evaluation of the face-to-face service found an under-delivery of some self-regulatory BCTs. This study assessed whether those 19 BCTs were offered in the different interventions delivered by four digital providers.A cross-sectional analysis of BCT content in the NHS-DDPP was elicited from the following sources: (a) online platforms (e.g. apps), (b) educational materials, and (c) health coaching (assessed via interviews with health coaches and audio-recorded telephone consultations). All materials were coded using the Behaviour Change Technique Taxonomy v1.A total of 17, 15, 15 and 14 of the 19 specified BCTs were identified across the four digital provider programmes. A mean proportion of 43% of specified BCTs were present via providers’ apps, 74% via educational materials, and 62% via health coaching. An additional 41 BCTs were included in at least one of the four providers’ programmes.Fidelity of BCT content in the NHS-DDPP was better than previously identified for the face-to-face DPP service. However, BCTs were offered via multiple modalities, thus the degree to which users engage with the modalities will impact on their exposure to BCTs and likely effectiveness of the digital programme.

How the Behavior Change Content of a Nationally Implemented Digital Diabetes Prevention Program Is Understood and Used by Participants: Qualitative Study of Fidelity of Receipt and Enactment.

The National Health Service Digital Diabetes Prevention Programme (NHS-DDPP) is a program for adults in England at risk of developing type 2 diabetes mellitus (T2DM). It is based on NHS England specifications that stipulate specific behavior change techniques (BCTs), that is, active ingredients to produce behavior change to target diet and physical activity. Now rolled out nationally, the NHS-DDPP is being delivered by 4 independent providers as a 9-month intervention via apps, educational material, and remote health coaching. To optimize effectiveness, participants need to be able to understand and use behavior change content (eg, goal setting and problem solving) of an intervention delivered to them digitally. Previous research has shown that people benefit from support to aid the understanding and use of BCTs. The objectives of this qualitative study were to evaluate how participants in the NHS-DDPP understand and use BCT content, investigate how participants describe the role of health coaches in supporting their behavior change, and examine how the understanding and use of behavior change content of the NHS-DDPP varies across providers. In total, 45 service users were interviewed twice by telephone at 2 to 4 months into, and at the end of, the program. Topics included participants' understanding and use of key BCTs to support self-regulation (eg, goal setting) and the support they received via the program. Transcripts were analyzed thematically, informed by the framework method. Participants described their understanding and use of some behavior change content of the program as straightforward: use of BCTs (eg, self-monitoring of behavior) delivered digitally via provider apps. Participants valued the role of health coaches in supporting their behavior change through the emotional support they offered and their direct role in delivery and application of some BCTs (eg, problem solving) to their specific circumstances. Participants expressed frustration over the lack of monitoring or feedback regarding their T2DM risk within the program. Variations in the understanding and use of behavior change content of the NHS-DDPP were present across provider programs. Health coaches' support in delivery of key components of the program seems to be pivotal. To improve the understanding and use of BCTs in digital interventions, it is important to consider routes of delivery that offer additional interactive human support. Understanding of some self-regulatory BCTs may benefit from this support more than others; thus, identifying the optimal mode of delivery for behavior change content is a priority for future research. The NHS-DDPP could be improved by explicitly setting out the need for health coaches to support understanding of some self-regulatory BCT content such as problem solving in the service specification and amending the discharge process so that knowledge of any change in T2DM risk is available to participants.

Cost Savings and Reduced Health Care Utilization Associated with Participation in a Digital Diabetes Prevention Program in an Adult Workforce Population.

BackgroundThough in-person delivery of the Diabetes Prevention Program (DPP) has demonstrated medical cost savings, the economic impact of digital programs is not as well understood.ObjectiveThis study examines the impact of a digital DPP program on reducing all-cause health care costs and utilization among 2027 adult participants at 12 months.MethodsA longitudinal, observational analysis of health care claims data was conducted on a workforce population who participated in a digital diabetes prevention program. Differences in utilization and costs from the year prior to program delivery through 1 year after enrollment were calculated using medical claims data for digital DPP participants compared to a propensity matched cohort in a differences-in-differences model.ResultsAt 1 year, the digital DPP population had a reduction in all-cause health care spend of US$1169 per participant relative to the comparison group (P = 0.01), with US$699 of that savings coming from reduced inpatient spend (P = 0.001). Cost savings were driven by fewer hospital admissions and shorter length of stay (P < 0.001). No other significant results in cost differences were detected. There was a trend toward savings extending into the second year, but the savings did not reach statistical significance.ConclusionsThese results demonstrated significant short-term health care cost savings at 1 year associated with digital DPP program delivery.

Mental health diagnosis attenuates weight loss among older adults in a digital diabetes prevention program.

Diabetes Prevention Programs (DPP) are effective at reducing diabetes incidence via clinically significant weight loss. Co-morbid mental health condition(s) may reduce the effect of DPP administered in-person and telephonically but this has not been assessed for digital DPP. This report examines the moderating effect of mental health diagnosis on weight change among individuals who enrolled in digital DPP (enrollees) at 12 and 24months. Secondary analysis of prospective, electronic health record data from a study of digital DPP among adults (N=3904) aged 65-75 with prediabetes (HbA1c 5.7%-6.4%) and obesity (BMI ≥30kg/m2). Mental health diagnosis only moderated the effect of digital DPP on weight change during the first 7months (p=0.003) and the effect attenuated at 12 and 24months. Results were unchanged after adjusting for psychotropic medication use. Among those without a mental health diagnosis, digital DPP enrollees lost more weight than non-enrollees: -4.17kg (95% CI, -5.22 to -3.13) at 12months and -1.88kg (95% CI, -3.00 to -0.76) at 24months, whereas among individuals with a mental health diagnosis, there was no difference in weight loss between enrollees and non-enrollees at 12 and 24months (-1.25kg [95% CI, -2.77 to 0.26] and 0.02kg [95% CI, -1.69-1.73], respectively). Digital DPP appears less effective for weight loss among individuals with a mental health condition, similar to prior findings for in-person and telephonic modalities. Findings suggest a need for tailoring DPP to address mental health conditions.

Costs and Cost-Effectiveness of Implementing a Digital Diabetes Prevention Program in a Large, Integrated Health System.

BackgroundThe Diabetes Prevention Program (DPP) has been translated into digital formats. We report an economic evaluation of a digital DPP implemented in a large, integrated health care system. MethodsPatients (n = 4148) were invited to participate in digital DPP based on clinical characteristics (HbA1c 5.7%-6.4% and body mass index ≥ 30 kg/m2) assessed using electronic medical record data. Using a propensity score we matched (1:1) enrolled and not enrolled patients for a total of 784. We identified high-risk patients (ie, above the 50th percentile of risk; n = 202) by calculating each patient's 2-year of developing diabetes. We report the cost of the intervention and the costs of medical care over 12- and 24-month follow-up, and the incremental cost-effectiveness ratio as the cost per additional kilogram weight loss at 24 months. ResultsAt 12 months, enrolled patients had lower total costs ($6,926, 95% CI $5,681-$8,171) than not enrolled patients ($7,538, 95% CI $6,293-$8,783). This pattern attenuated slightly at 24 months (enrolled = $16,255, 95% CI $14,097-$18,412; not enrolled = $16,688, 95% CI $14,531-$18,846). We found an incremental cost-effectiveness ratio of $81.92 per additional kilogram weight loss. For high-risk patients, the digital DPP group had, on average, lower costs and greater weight loss. We found a 55% chance of the digital DPP program being cost-effective at a willingness-to-pay of $150 per additional kilogram of weight loss; at the same willingness-to-pay, there is a 60% chance in the high-risk subgroup. Limitations include the nonrandomized design and potential volunteer bias. ConclusionDigital DPP had a favorable cost-effectiveness profile compared to other lifestyle interventions.