Improved Glycemic Control With a Digital Health Intervention in Adults With Type 2 Diabetes: Retrospective Study

Effect of Multimodal App-Based Interventions on Glycemic Control in Patients With Type 2 Diabetes: Systematic Review and Meta-Analysis

BACKGROUND

Digital technologies for type 2 diabetes mellitus (T2DM) care hold great potential to improve patients' health in the long term. Only a subset of telemedicine offerings are digital interventions that meet the criteria for prescribable digitale Gesundheitsanwendung (digital health apps; DiGAs) in Germany. Digital treatments further provide vast amounts of patient data that are important to generate evidence.

OBJECTIVE

This systematic review aims to analyze the efficacy of multimodal digital therapies that mainly meet the DiGA criteria for patients with T2DM and to elicit the potential of such therapies. This includes evidence from randomized controlled trials (RCTs) as well as from real-world data. The outcome of interest was a reduction in glycated hemoglobin (hemoglobin A1c [HbA1c]; long-term blood glucose measurements).

METHODS

A systematic literature search was conducted in the literature bases PubMed, LIVIVO, and Cochrane, based on the predefined PICO (Population; Intervention; Control; Outcome) scheme. Identified studies were assessed for risk of bias, pragmatism, and overall quality of evidence. Meta-analyses were conducted for between group differences using RCTs only, and for within-group differences using RCTs and non-RCTs, to examine the effect of the interventions on HbA1c.

RESULTS

In total, 795 records were identified, of which 24 were eligible for this systematic review and 23 studies were eligible for the meta-analysis. The results of the meta-analyses showed significant and clinically relevant reductions in HbA1c in patients with T2DM. Regarding the between-group difference for HbA1c reduction, the pooled effect of the RCTs showed a reduction of -0.36% (95% CI -0.59% to -0.14%; P<.001), favoring app-based interventions. The average mean within-group reduction in HbA1c was -0.79 (95% CI -1.02 to -0.55), with no significant difference between RCTs (-0.69, 95% CI -1.13 to -0.24) and non-RCTs (-0.87, 95% CI -1.16 to -0.57; P<.01, differences between RCTs and RCTs P=.44). A pragmatism rating showed that both study types were on average (very) pragmatic, that is, close to usual care. However, the overall quality of evidence was low to very low.

CONCLUSIONS

This systematic review shows that digital therapies that mainly meet the DiGA criteria can effectively improve HbA1c in patients with T2DM. The integration of digital health care into usual care holds great potential and should be considered as a complementary option to usual care in the future.

TRIAL REGISTRATION

PROSPERO CRD42023440203; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=440203.

Recommendations for improving accessibility of digital health interventions for cardiometabolic disease for ethnically diverse populations

Digital health interventions (DHIs), such as apps, websites and wearables, are being presented as solutions or enablers to manage the burden of cardiometabolic disease in healthcare. However, the potential benefits of DHIs may not be reaching the most in-need populations, who may face intersecting barriers to accessing health services and digital solutions. The Digital Interventions for South Asians in Cardiometabolic Disease (DISC) study used a mixed-method approach to focus on people of a South Asian background, a high-risk group for cardiometabolic disease. A one-day workshop was held in May 2023 with key stakeholders, including people with lived experience, health professionals, technology innovators and policymakers (n = 34), to develop recommendations arising from the DISC study findings. Discussions covered four areas: actions to support individuals to access and benefit from DHIs; translating learning about inclusive design into practice; the role of regulation and evaluation to improve inclusivity of DHIs used within the health service; and improving quality of data collection and use to reduce inequalities related to digital health and cardiometabolic disease. Our recommendations align with recent national strategies and provide specific examples of actions that can be taken to address digital inequalities for ethnic minority populations.

Optimizing glycemic control in type 2 diabetes: the impact of the GLIDE program's personalized digital health intervention

Background

The integration of digital health applications into type 2 diabetes mellitus (T2DM) management presents promising opportunities for optimizing glycemic control, enhancing adherence, and improving health outcomes. MyTatva's Glycemic Lifestyle Intervention in Diabetes Empowerment (GLIDE) program, which integrates dietary and exercise regimens, cognitive behavioral therapy (CBT), and Internet of Things (IoT) devices, potentiates this approach. This study aimed to evaluate the effectiveness of the GLIDE program's personalized, comprehensive approach in improving glycemic control over 90 days among T2DM patients.

Methods

During the study period, 30 diabetic patients completed their GLIDE journey with expert dieticians, physiotherapists, and behavior therapists. Each patient received a personalized root cause analysis based on lifestyle assessment and disease-specific parameters. Statistical analysis was conducted using a paired t-test on the deidentified HbA1c, FBS, and PPBS data at baseline and post-intervention.

Results

Throughout the study, 27 patients actively adhered to the GLIDE program. All the parameters showed statistically significant (p<0.05) changes post-intervention. HbA1c decreased by 11.79% from 8.43% ± 1.32 to 7.44% ± 0.64. Significant reductions were observed in PPBS (47.7%), decreasing from 260.89 mg/dL ± 36.31 to 136.27 mg/dL± 6.36, compared to FBS (31.1%), which decreased from 8.43 mg/dL± 1.32 to 7.44 mg/dL± 0.64.

Conclusions

The effectiveness of the GLIDE program is based on a comprehensive root cause analysis approach. The detailed analysis of the patient's clinical journey by health experts at regular intervals enables precise goal management, resulting in expected outcomes for better glycemic control. Therefore, personalized digital health plans are vital for achieving clinically significant changes.

Addressing disparities in the long-term mortality risk in individuals with non-ST segment myocardial infarction (NSTEMI) by diabetes mellitus status: a nationwide cohort study

AIMS/HYPOTHESIS

The aim of this study was to investigate how diabetes mellitus affects longer term outcomes in individuals presenting to hospital with non-ST segment elevation myocardial infarction (NSTEMI).

METHODS

We analysed data from 456,376 adults hospitalised between January 2005 and March 2019 with NSTEMI from the UK Myocardial Ischaemia National Audit Project (MINAP) registry, linked with Office for National Statistics death reporting. We compared outcomes and quality of care by diabetes status.

RESULTS

Individuals with diabetes were older (median age 74 vs 73 years), were more often of Asian ethnicity (13% vs 4%) and underwent revascularisation (percutaneous coronary intervention or coronary artery bypass graft surgery) (38% vs 40%) less frequently than those without diabetes. The mortality risk for those with diabetes compared with those without was significantly higher at 30 days (HR 1.19, 95% CI 1.15, 1.23), 1 year (HR 1.28, 95% CI 1.26, 1.31), 5 years (HR 1.36, 95% CI 1.34, 1.38) and 10 years (HR 1.39, 95% CI 1.36, 1.42). In individuals with diabetes, higher quality inpatient care, assessed by opportunity-based quality indicator (OBQI) score category ('poor', 'fair', 'good' or 'excellent'), was associated with lower mortality rates compared with poor care (good: HR 0.74, 95% CI 0.73, 0.76; excellent: HR 0.69, 95% CI 0.68, 0.71). In addition, compared with poor care, excellent care in the diabetes group was associated with the lowest mortality rates in the diet-treated and insulin-treated subgroups (diet-treated: HR 0.64, 95% CI 0.61, 0.68; insulin-treated: HR 0.69, CI 0.66, 0.72).

CONCLUSION/INTERPRETATION

Individuals with diabetes experience disparities during inpatient care following NSTEMI. They have a higher risk of long-term mortality than those without diabetes, and higher quality inpatient care may lead to better long-term survival.

Uptake of Digital Health Interventions for Cardiometabolic Disease in British South Asian Individuals: Think Aloud Study

Background

Digital health interventions (DHIs) could support prevention and management of cardiometabolic disease. However, those who may benefit most often experience barriers to awareness and adoption of these interventions.

Objective

Among South Asian individuals, we evaluated user experience of DHIs for prevention and management of cardiometabolic disease, aiming to understand barriers and facilitators to initial and ongoing use.

Methods

Among South Asian individuals recruited via primary care, community organizations, and snowball methods (n=18), we conducted "think-aloud" interviews using a reflective and reactive approach. Participants included nonusers, as well as those that used a range of DHIs as part of monitoring and improving their health. Participants were asked to think aloud while completing a task they routinely do in a familiar DHI, as well as while setting up and completing a search task in a novel DHI; they were encouraged to behave as if unobserved.

Results

Lack of cultural specificity was highlighted as reducing relevance and usability, particularly relating to dietary change. Preferred features reflected individual health beliefs and behaviors, digital skills, and trust in DHIs. For example, tracking blood glucose was considered by some to be positive, while for others it caused distress and anxiety. Similarly, some users found the novel DHI to be extremely simple to set up and use, and others grew frustrated navigating through initial interfaces. Many participants raised concerns about data privacy and needing to agree to terms and conditions that they did not understand. Participants expressed that with information and support from trusted sources, they would be interested in using DHIs as part of self-management.

Conclusions

DHIs may support South Asians to prevent and manage cardiometabolic disease, but it is important to consider the needs of specific user groups in DHI development, design, and implementation. Despite motivation to make health changes, digital barriers are common. Cultural appropriateness and trusted sources (such as health care providers and community organizations) have roles in increasing awareness and enabling individuals to access and use DHIs.

Long-Term Glycemic Control Improvement After the Home and Self-Care Program for Patients With Type 1 Diabetes: Real-World-Based Cohort Study

BACKGROUND

The prevalence of type 1 diabetes (T1D) is increasing worldwide, with a much higher proportion of adult patients. However, achieving stable glycemic control is difficult in these patients.

OBJECTIVE

After periodic implementation of structured education for patients with T1D through the Home and Self-Care Program, a pilot home health care project promoted by the Korean government, we evaluated the program's effects on glycemic control.

METHODS

This study was conducted from April 2020 to March 2023. We analyzed 119 participants with T1D aged >15 years. Nursing and nutrition education were provided separately up to 4 times per year, with physician consultation up to 6 times per year. A distinguishing feature of this study compared with previous ones was the provision of remote support using a general-purpose smartphone communication app offered up to 12 times annually on an as-needed basis to enhance the continuity of in-person education effects. Patients were followed up on at average intervals of 3 months for up to 24 months. The primary end point was the mean difference in glycated hemoglobin (HbA1c) at each follow-up visit from baseline. For continuous glucose monitoring (CGM) users, CGM metrics were also evaluated.

RESULTS

The mean HbA1c level of study participants was 8.6% at baseline (mean duration of T1D 10.02, SD 16.10 y). The HbA1c level reduction in participants who received at least 1 structured educational session went from 1.63% (SD 2.03%; P<.001; adjustment model=1.69%, 95% CI 1.24%-2.13% at the first follow-up visit) to 1.23% (SD 1.31%; P=.01; adjustment model=1.28%, 95% CI 0.78%-1.79% at the eighth follow-up visit). In the adjustment model, the actual mean HbA1c values were maintained between a minimum of 7.33% (95% CI 7.20%-7.46% at the first follow-up visit) and a maximum of 7.62% (95% CI 7.41%-7.82% at the sixth follow-up visit). Among CGM users, after at least 1 session, the mean time in the target range was maintained between 61.59% (adjusted model, 95% CI 58.14%-65.03% at the second follow-up visit) and 54.7% (95% CI 50.92%-58.48% at the eighth follow-up visit), consistently staying above 54.7% (corresponding to an HbA1c level of <7.6%). The mean time below the target range (TBR) also gradually improved to the recommended range (≤4% for TBR of <70 mg/dL and ≤1% for TBR of <54 mg/dL).

CONCLUSIONS

The Home and Self-Care Program protocol for glycemic control in patients with T1D is effective, producing significant improvement immediately and long-term maintenance effects, including on CGM indexes.

Walking away from depression: the mediating role of walking activity in depression impacting blood glucose levels of people with diabetes or prediabetes

Introduction

Depression can exacerbate diabetes by impairing self-care behaviors and increasing the risk of complication; however, the underlying mechanism is still unclear. Given the suggested associations between walking activity, depression status, and blood glucose levels this study explores the intricate relationship between depression and blood glucose (BG) control, with a focus on walking activity as a behavioral mediator. The purpose of this study is to examine walking activity's mediating role in depression's impact on BG levels, investigating and validating the non-linear association between BG levels and walking activity. This retrospective real-world study demonstrates the potential of regular walking activity as a simple and accessible intervention to mitigate the negative effects of depression on BG levels in T2D and prediabetes.

Methods

A cohort of 989 users with T2D and prediabetes, who regularly tracked their steps levels and BG levels for 12 months using the Dario digital health platform was evaluated. The mediating role of the monthly average number of steps on the relationship between the self-reported depression status and lagged monthly average BG was assessed. Additionally, the association between monthly walking activity and monthly average BG was tested using a piecewise linear mixed effects model.

Results

Users with self-reported depression demonstrated increased BG levels compared to users without depression (B=8.00, P=.01). The association between depression and monthly average number of steps was significant (B=-.27, P<.005) and monthly average number of steps significantly predicted the following months' average BG (B=-.81, P=.001), adjusting for depression. The monthly average number of steps significantly mediated the effect of self-reported depression on the following month's average BG (M=.22, P<.005). Further sensitivity analysis demonstrated model robustness over various periods. Finally, non-linear dynamics of walking activity over time was validated using unseen data showing a decrease in monthly average BG for users with over an average of 400 steps per day (B=-1.87, P<.01).

Discussion

This study shows how regular walking may reduce the negative impact of depression on BG levels in people with T2D. Our findings advocate for the integration of walking activity into treatment protocols as a cost-effective, accessible intervention strategy to improve glycemic management and depressive symptoms in this population.

Automated Personalized Self-care Program for Patients With Type 2 Diabetes Mellitus: A Pilot Trial

PURPOSE

Providing continuous self-care support to the growing diabetes population is challenging. Strategies are needed to enhance engagement in self-care, utilizing innovative technologies for personalized feedback. This study aimed to assess the feasibility of the Automated Personalized Self-Care program among type 2 diabetes patients and evaluate its preliminary effectiveness.

METHODS

A parallel randomized pilot trial with qualitative interviews occurred from May 3, 2022, to September 27, 2022. Participants aged 40-69 years with type 2 diabetes and HbA1c ≥ 7.0% were recruited. The three-month program involved automated personalized goal setting, education, monitoring, and feedback. Feasibility was measured by participants' engagement and intervention usability. Preliminary effectiveness was examined through self-care self-efficacy, self-care behaviors, and health outcomes. Qualitative interviews were conducted with the intervention group.

RESULTS

A total of 404 patients were screened. Out of the 61 eligible patients, 32 were enrolled, resulting in a recruitment rate of 52.5%. Retention rates at three months were 84.2% and 84.6% in the intervention and control groups, respectively. Among the intervention group, 81.3% satisfied adherence criteria. Mobile application's usability scored 66.25, and participants' satisfaction was 8.06. Intention-to-treat analysis showed improvements in self-measured blood glucose testing, grain intake, and HbA1c in the intervention group. Qualitative content analysis identified nine themes.

CONCLUSION

Feasibility of the program was verified. A larger randomized controlled trial is needed to determine its effectiveness in self-care self-efficacy, self-care behaviors, and health outcomes among type 2 diabetes patients. This study offers insights for optimizing future trials assessing clinical effectiveness.

TRIAL REGISTRATION

Clinical Research Information Service, KCT0008202 (registration date: 17 February 2023).

The Impact of Intervention Design on User Engagement in Digital Therapeutics Research: Factorial Experiment With a Mixed Methods Study

BACKGROUND

User engagement is crucial for digital therapeutics (DTx) effectiveness; due to variations in the conceptualization of engagement and intervention design, assessment and retention of engagement remain challenging.

OBJECTIVE

We investigated the influence of the perceived acceptability of experimental intervention components and satisfaction with core intervention components in DTx on user engagement, while also identifying potential barriers and facilitators to user engagement.

METHODS

We conducted a mixed methods study with a 2 × 2 factorial design, involving 12 outpatients with atopic dermatitis. Participants were randomized into 4 experimental groups based on push notification ("basic" or "advanced") and human coach ("on" or "off") experimental intervention components. All participants engaged in self-monitoring and learning courses as core intervention components within an app-based intervention over 8 weeks. Data were collected through in-app behavioral data, physician- and self-reported questionnaires, and semistructured interviews assessed at baseline, 4 weeks, and 8 weeks. Descriptive statistics and thematic analysis were used to evaluate user engagement, perceived acceptability of experimental intervention components (ie, push notification and human coach), satisfaction with core intervention components (ie, self-monitoring and learning courses), and intervention effectiveness through clinical outcomes.

RESULTS

The primary outcome indicated that group 4, provided with "advanced-level push notifications" and a "human coach," showed higher completion rates for self-monitoring forms and learning courses compared to the predetermined threshold of clinical significance. Qualitative data analysis revealed three key themes: (1) perceived acceptability of the experimental intervention components, (2) satisfaction with the core intervention components, and (3) suggestions for improvement in the overall intervention program. Regarding clinical outcomes, the Perceived Stress Scale and Dermatology Life Quality Index scores presented the highest improvement in group 4.

CONCLUSIONS

These findings will help refine the intervention and inform the design of a subsequent randomized trial to test its effectiveness. Furthermore, this design may serve as a model for broadly examining and optimizing overall engagement in DTx and for future investigation into the complex relationship between engagement and clinical outcomes.

TRIAL REGISTRATION

Clinical Research Information Service KCT0007675; http://tinyurl.com/2m8rjrmv.

Long-Term Results of a Digital Diabetes Self-Management and Education Support Program Among Adults With Type 2 Diabetes: A Retrospective Cohort Study

PURPOSE

The purpose of this study is to examine the long-term impact of a digital diabetes self-management education and support (DSMES) program on A1C among adults with type 2 diabetes (T2DM).

METHODS

Data analyzed were from a retrospective cohort of commercially insured members with T2DM enrolled in the Omada for Diabetes program between January 1, 2019, and January 31, 2022 (n = 1,322). Linear mixed models measured changes in A1C and weight across 12 months (collected at baseline and every 3 months over 1 year) overall and stratified by A1C at baseline (≥8% vs <8%).

RESULTS

On average, members were 53.5 years old, 56.9% female, and 71.5% White, with a mean baseline body mass index (BMI) of 36.9 and A1C of 7.6%. Members with baseline A1C ≥8% demonstrated clinically and statistically significant adjusted mean reductions in A1C during follow-up, from 9.48% at baseline to 7.33%, 7.57%, 7.59%, and 7.47% at 3, 6, 9, and 12 months, respectively. Those with A1C <8% maintained glycemic stability (6.73%, 6.50%, 6.54%, 6.62%, and 6.51%, respectively). Collectively, members experienced a -1.17 kg/m2 mean reduction in BMI over 12 months.

CONCLUSIONS

This study provides real-world evidence that members with elevated baseline A1C (≥8%) enrolled in a digital DSMES program experienced clinically meaningful and statistically significant reductions in A1C. Those with baseline A1C within goal treatment range (<8%) maintained glycemic stability over 1 year. The findings support existing evidence that scalable digital DSMES solutions can help individuals with T2DM manage their condition.

An Overview of Pharmaceutical Care in Type II Diabetes Mellitus Patients: Current Position and Prospects

Diabetes mellitus is an ongoing disease that is related to a high mortality rate due to severe complications. Diabetes mellitus type 2 (DMT2) is a persistent metabolic deficiency and its prevalence has been increasing consistently worldwide. As a result, it is rapidly turning into a plague in some parts of the world, and the number of people affected is expected to double in the following decade due to an increase in the maturing populace, adding to the overall existing importance for medical service providers, particularly in the underdeveloped nations. Extensive diabetes care is an intricate task that takes a whole group of medical care experts, including drug specialists, to provide multidisciplinary care for the patients. The duty of drug experts has changed significantly in recent years, changing from conventional drug dispensing in the drug store to patient- centered clinical support services. Upgrading the medication treatment to accomplish better remedial results without causing drug-related issues has been considered the essential objective of treatment for diabetic patients. This review discusses the healthcare needs of patients with T2DM, the current evidence for the role of pharmacists in diabetes care, and insight into the upcoming role of pharmacists in its management. The advanced role of clinical pharmacists in diabetes control through drug treatment, diabetes care centers, and diabetes health counselor schooling, is also discussed in this review.

Effectiveness of a Digital Health Application for the Treatment of Diabetes Type II-A Pilot Study

(1) Background: This study aimed at providing preliminary evidence for mebix, an app-based treatment program for patients with diabetes mellitus type II. The main target was to show a positive healthcare impact as defined by improved blood glucose control, i.e., reduced HbA1c values. (2) Methods: For this, a 3-month, prospective, open-label trial with an intraindividual control group was conducted. Participants received the mebix intervention for 3 months. HbA1c values were observed every 3 months: retrospectively, at baseline, and 3 months after the start of using the app. Additionally, weight and patients' reported outcomes (well-being, diabetes-related distress, and self-management) were assessed. Data generated within the app were summarized and analyzed (steps, physical activity, fulfilled tasks, and food logs). (3) Results: After the usage of mebix for 3 months, participants significantly reduced their HbA1c levels (-1.0 ± 0.8%). Moreover, improvements in weight, well-being, and self-management as well as a reduction in diabetes-related distress were observed. App-generated data mainly supported the other main finding, that higher baseline HbA1c values lead to higher reductions. Overall, the study provided preliminary evidence that mebix can help patients improve metabolic and psychological health outcomes.

Impact of a Combined Continuous Glucose Monitoring-Digital Health Solution on Glucose Metrics and Self-Management Behavior for Adults With Type 2 Diabetes: Real-World, Observational Study

BACKGROUND

The BlueStar (Welldoc) digital health solution for people with diabetes incorporates data from multiple devices and generates coaching messages using artificial intelligence. The BlueStar app syncs glucose data from the G6 (Dexcom) real-time continuous glucose monitoring (RT-CGM) system, which provides a glucose measurement every 5 minutes.

OBJECTIVE

The objective of this real-world study of people with type 2 diabetes (T2D) using the digital health solution and RT-CGM was to evaluate change in glycemic control and engagement with the program over 3 months.

METHODS

Participants were current or former enrollees in an employer-sponsored health plan, were aged 18 years or older, had a T2D diagnosis, and were not using prandial insulin. Outcomes included CGM-based glycemic metrics and engagement with the BlueStar app, including logging medications taken, exercise, food details, blood pressure, weight, and hours of sleep.

RESULTS

Participants in the program that met our analysis criteria (n=52) were aged a mean of 53 (SD 9) years; 37% (19/52) were female and approximately 50% (25/52) were taking diabetes medications. The RT-CGM system was worn 90% (SD 8%) of the time over 3 months. Among individuals with suboptimal glycemic control at baseline, defined as mean glucose >180 mg/dL, clinically meaningful improvements in glycemic control were observed, including reductions in a glucose management indicator (-0.8 percentage points), time above range 181-250 mg/dL (-4.4 percentage points) and time above range >250 mg/dL (-14 percentage points; all P<.05). Time in range 70-180 mg/dL also increased by 15 percentage points (P=.016) in this population, which corresponds to an increase of approximately 3.5 hours per day in the target range. Over the 3-month study, 29% (15/52) of participants completed at least one engagement activity per week. Medication logging was completed most often by participants (23/52, 44%) at a rate of 12.1 (SD 0.8) events/week, and this was closely followed by exercise and food logging.

CONCLUSIONS

The combination of an artificial intelligence-powered digital health solution and RT-CGM helped people with T2D improve their glycemic outcomes and diabetes self-management behaviors.

A Randomised Control Trial to Explore the Impact and Efficacy of the Healum Collaborative Care Planning Software and App on Condition Management in the Type 2 Diabetes Mellitus Population in NHS Primary Care

INTRODUCTION

Effective and scalable solutions to support management of Type 2 Diabetes (T2D) at a distance are a priority for health systems worldwide. The use of personalised care planning has been shown to be effective at improving the health outcomes and the experience of care amongst people with T2D and other long-term health conditions. Here we describe a specific example of such an intervention.

METHODS

The sample comprised 197 participants with T2D randomised to either the active intervention group with digital health planning (App + usual care), with 115 participants, or the control group (usual care), with 82 participants. We analysed data in relation to changes in body mass index (BMI) and glycated haemoglobin (HbA1c) over a 6-month follow-up period. We also analysed responses to questionnaires sent out and held interviews with participants that were in the active treatment group and therefore had a care plan created and access to an app.

RESULTS

The active treatment group had significant reductions in HbA1c (p < 0.01) and BMI (p < 0.037) vs the control group (no significant change). The average percentage change in HbA1c for the treatment group over 6 months was - 7.4% (± SE 1.4%), compared with 1.8% (± SE 2.1%) for the control group. The average percentage change in BMI for the treatment group was - 0.7% (± SE 0.4%) and it was - 0.2% (± SE 0.5%) for the control group. A higher percentage of the active treatment group reduced their HbA1c and BMI than the control group. For HbA1c, 72.4% of the active treatment group reduced their HbA1c, compared to 41.5% of the control group. For BMI, 52.7% of the active treatment group experienced a reduction, compared to 42.9% for the control group. Self-measured quality of life (QoL) improved for patients in the active treatment group, shown by an increase in their pre-trial to post-trial EQ-5D-5L rating by an average of 0.0464 (± SE 0.0625), compared to a decrease of 0.0086 (± SE 0.0530) for the control group. The average EQ VAS score also increased pre- to post-trial for the active treatment group, on average by 8.2%, whereas it decreased by an  average of - 2.8% for the control group.

CONCLUSION

These findings point to how the provision of personalised plans of care, support and education linked to a mobile app, can result in HbA1c and BMI reduction for many individuals with T2D. The use of a patient management app as well as a personalised care plan also led to an improvement in patient self-rated QoL and engagement.

The Effectiveness of an eHealth Family-Based Intervention Program in Patients With Uncontrolled Type 2 Diabetes Mellitus (T2DM) in the Community Via WeChat: Randomized Controlled Trial

BACKGROUND

Intervention based on family support and risk perception can enhance type 2 diabetes mellitus (T2DM) patients' self-care activities. In addition, eHealth education is considered to improve family members' support for patients with T2DM. However, there is little evidence from rigorously designed studies on the effectiveness of an intervention combining these approaches.

OBJECTIVE

This randomized controlled trial (RCT) aimed to assess the effectiveness of an eHealth family-based health education intervention for patients with T2DM to improve their glucose control, risk perception, and self-care behaviors.

METHODS

This single-center, 2-parallel-group RCT was conducted between 2019 and 2020. Overall, 228 patients were recruited from Jiading District, Shanghai, and randomly divided into intervention and control groups. The intervention group received an eHealth family intervention based on community management via WeChat, whereas the control group received usual care. The primary outcome was the glycated hemoglobin (HbA1c) level of the patients with T2DM, and the secondary outcomes were self-management behavior (general and specific diet, exercise, blood sugar testing, foot care, and smoking), risk perception (risk knowledge, personal control, worry, optimism bias, and personal risk), and family support (supportive and nonsupportive behaviors). A 2-tailed paired-sample t test was used to compare the participants at baseline and follow-up within the control and intervention groups. An analysis of covariance was used to measure the intervention effect.

RESULTS

In total, 225 patients with T2DM were followed up for 1 year. After intervention, they had significantly lower HbA1c values (β=-.69, 95% CI -0.99 to -0.39; P<.001). They also had improved general diet (β=.60, 95% CI 0.20 to 1.00; P=.003), special diet (β=.71, 95% CI 0.34 to 1.09; P<.001), blood sugar testing (β=.50, 95% CI 0.02 to 0.98; P=.04), foot care (β=1.82, 95% CI 1.23 to 2.42; P<.001), risk knowledge (β=.89, 95% CI 0.55 to 1.24; P<.001), personal control (β=.22, 95% CI 0.12 to 0.32; P<.001), worry (β=.24, 95% CI 0.10 to 0.39; P=.001), optimism bias (β=.26, 95% CI 0.09 to 0.43; P=.003), and supportive behaviors (β=5.52, 95% CI 4.03 to 7.01; P<.001).

CONCLUSIONS

The eHealth family-based intervention improved glucose control and self-care activities among patients with T2DM by aiding the implementation of interventions to improve T2DM risk perceptions among family members. The intervention is generalizable for patients with T2DM using health management systems in community health centers.

TRIAL REGISTRATION

Chinese Clinical Trial Registry ChiCTR1900020736; https://www.chictr.org.cn/showprojen.aspx?proj=31214.

Improvements in Glycemic Control and Depressive Symptoms Among Adults With Type 2 Diabetes: Retrospective Study

BACKGROUND

The prevalence of diabetes remains high, with traditional lifestyle interventions demonstrating limited success in improving diabetes-related outcomes, particularly among individuals with diabetes-related mental health comorbidities. Digital health interventions provide the ability to ease the sustained and rigorous self-management needs associated with diabetes care and treatment. Current interventions though, are plagued by small sample sizes, underpowered pilot studies, and immense heterogeneity in program intervention, duration, and measured outcomes.

OBJECTIVE

Therefore, this work aimed to evaluate the effectiveness of a mobile health diabetes management program on measures of glycemic control in a high-risk population with type 2 diabetes (hemoglobin A1c [HbA1c] ≥8.0%), utilizing a sample of 1128 participants who provided baseline and follow-up data. The sustainability of this change in glycemic control was examined in a subset of participants (n=455) at 6 months and 1 year following program enrollment. A secondary analysis examined changes in glycemic control among a subset of participants with self-reported mild-to-moderate depression at baseline.

METHODS

This study utilized a single-arm, retrospective design. Participants were enrolled in the Vida Health Diabetes Management Program. This app-based intervention utilized one-on-one remote sessions with a health coach, registered dietitian nutritionist, and/or a certified diabetes care and education specialist and structured lessons and tools related to diabetes management and self-care. Participants provided baseline (-365 to 21 days of program enrollment) as well as follow-up (at least 90 days following program enrollment) HbA1c values. Paired t tests were used to evaluate changes in HbA1c between baseline and follow-up time points. The 8-item Patient Health Questionnaire and the 7-item Generalized Anxiety Disorder Scale were utilized to assess self-reported depressive and anxiety symptoms, respectively. Paired t tests and linear regression modeling accounting for pertinent covariates were used to evaluate changes in mental health symptom acuity and their relationship with changes in glycemic control.

RESULTS

We observed a significant decrease in HbA1c of -1.35 points between baseline (mean 9.84, SD 1.64) and follow-up (mean 8.48, SD 1.77; t=22.56, P<.001) among this large, high-risk sample. This decrease was sustained up to 1 year following program enrollment. Additionally, a significant relationship between improvements in depressive symptom acuity and improvements in HbA1c was observed (β=-0.74, P=.03).

CONCLUSIONS

This study demonstrates clinically meaningful improvements in glycemic control among participants enrolled in the Vida Health Diabetes Management Program. Additionally, this work presents one of the largest studied samples of participants enrolled in a digital health diabetes management program to date.

Clinical Utility of a Digital Therapeutic Intervention in Indian Patients With Type 2 Diabetes Mellitus: 12-Week Prospective Single-Arm Intervention Study

Background

Patients with type 2 diabetes mellitus (T2DM) having elevated levels of blood glucose and glycated hemoglobin (HbA_1c) are at higher risk of macro- and microvascular complications. Nonetheless, the goal of achieving glycemic control cannot be met with the use of pharmacotherapy alone. The recent emergence of digital therapeutic tools has shown the possibility of improving the modifiable risk factors and self-management of diabetes.

Objective

The aim of this study was to examine the clinical utility of a digital therapeutic intervention as an add-on therapy to achieve glycemic control in patients with T2DM.

Methods

This was a 12-week prospective, single-arm digital intervention study in patients with T2DM receiving regular antidiabetic treatment. The eligibility criteria included male and female patients with HbA_1c≥6.5%, functional English literacy, and a mobile phone capable of running the intervention app. Outcome measures of the study were mean changes in HbA_1c, fasting blood glucose (FBG), postprandial blood glucose (PPBG), BMI, and Homeostatic Model Assessment for Insulin Resistance (HOMA-IR) index at the end of 12 weeks.

Results

A total of 128 participants completed the study period of 12 weeks. There were 54.7% (70/128) men and 45.3% (58/128) women with a mean age of 48.48 years (SD 10.27). At the end of 12 weeks, the mean change in HbA_1c, FBG, PPBG, and BMI for the overall study population was –0.84% (P<.001), –8.39 mg/dl (P=.02), –14.97 mg/dl (P<.001), and –0.24 kg/m² (P=.06), respectively. Among the participants showing improvement in the HbA_1c value at the end of 12 weeks (responders), the mean change in HbA_1c, FBG, PPBG, and BMI was –1.24% (P<.001), –12.42 mg/dl (P=.003), –21.45 mg/dl (P<.001), and –0.34 kg/m² (P=.007), respectively. There was an increase in HOMA-IR values for the overall study population (0.54, P=.29). HbA_1c response showed a significant association with a baseline HbA_1c level ≥7.5%, no prior history of smoking, and no prior COVID-19 infection, as well as with higher levels of program engagement.

Conclusions

A digital therapeutic intervention when used alongside standard medications significantly reduces HbA_1c, FBG, and PPBG levels in patients with T2DM.

Enhancing type 2 diabetes treatment through digital plans of care. First results from the East Cheshire Study of an App to support people in the management of type 2 diabetes

Introduction

The use of personalised care planning has been effective at improving health outcomes for people with long-term health conditions.

Methods

We analysed data in relation to changes in BMI/HbA1c. The sample was made up of (n = 36) participants randomised to either the active intervention group (App+usual care) or the control group (usual care).

Results:

The average HbA1c percentage change for the treatment group was 9.5%, but just −2% for the control (usual care) group (P = 0.015 for the difference). The average percentage change in BMI for the treatment group was −0.4%, but 0.1% for the control group (P = 0.03 for the difference).

Conclusion

These preliminary findings point to how the provision of personalised plans of care, support and education linked to a mobile app, can result in HbA1c and BMI reduction over a 6-month period. While the results are preliminary, they portend the potential for digital plans of care to enhance T2DM management.

Improvements in Depression Outcomes Following a Digital Cognitive Behavioral Therapy Intervention in a Polychronic Population: Retrospective Study

Background

Digital mental health interventions have shown promise in reducing barriers to effective care for depression. Depression and related mental disorders are known to be highly comorbid with common chronic physical conditions, such as obesity and type 2 diabetes. While some research has explored the interaction dynamics of treating populations living with both mental and physical disorders, very little is known about such dynamics in digital care.

Objective

We aimed to examine the effectiveness of a 12-week, therapist-supported, app-based cognitive behavioral therapy program in improving symptoms of depression and anxiety. The studied population included adults with a heavy burden of chronic physical disease, including obesity and type 2 diabetes.

Methods

A total of 1512 participants with at least moderate depression were enrolled. The treatment cohort consisted of 831 (54.96%) participants who completed a follow-up assessment. The program included structured lessons and tools (ie, exercises and practices) and offered one-on-one weekly video counseling sessions with a licensed therapist for 12 weeks and monthly sessions thereafter. The clinically validated 8-item Patient Health Questionnaire (PHQ-8) and the 7-item Generalized Anxiety Disorder scale (GAD-7) were used to assess depression and anxiety, respectively. Linear mixed-effects modeling was employed to examine changes in depression and anxiety over time. Given correlation among various measures of program usage, a composite variable for depth of usage was used to analyze the correlation between usage and changes in depressive symptoms. Body weight changes from baseline were assessed primarily with digitally connected scales.

Results

Out of 831 participants in the treatment cohort, 74.5% (n=619) showed a clinically significant reduction in depressive symptom severity after 12 weeks, where follow-up PHQ-8 scores had shifted downward by at least one diagnostic category. In total, 67.5% (n=561) of the participants showed a reliable improvement in PHQ-8 scores as measured by the reliable change index. There was an average reduction of 5.9 (SD 5.2) points (P<.001) between baseline and follow-up. Greater program usage was correlated with greater likelihood of reliable improvement in depressive symptoms (odds ratio 1.3, 95% CI 1.1-1.5; P=.002). An exploratory analysis of body weight changes with a multilevel, mixed-effect model suggested that reliable improvement in depressive symptoms at follow-up was associated with significantly greater weight loss at 9 months (β=–1.11, P=.002).

Conclusions

The results provide further support that digital interventions can support clinically meaningful improvements in depression. Some form of synergy in treatment of comorbid depression and obesity or diabetes could be studied in future research. The study was limited by postintervention participant attrition as well as the retrospective observational study design.

Effects of a Novel Blood Glucose Forecasting Feature on Glycemic Management and Logging in Adults With Type 2 Diabetes Using One Drop: Retrospective Cohort Study

Background

Personalized feedback is an effective behavior change technique frequently incorporated into mobile health (mHealth) apps. Innovations in data science create opportunities for leveraging the wealth of user data accumulated by mHealth apps to generate personalized health forecasts. One Drop’s digital program is one of the first to implement blood glucose forecasts for people with type 2 diabetes. The impact of these forecasts on behavior and glycemic management has not been evaluated to date.

Objective

This study sought to evaluate the impact of exposure to blood glucose forecasts on blood glucose logging behavior, average blood glucose, and percentage of glucose points in range.

Methods

This retrospective cohort study examined people with type 2 diabetes who first began using One Drop to record their blood glucose between 2019 and 2021. Cohorts included those who received blood glucose forecasts and those who did not receive forecasts. The cohorts were compared to evaluate the effect of exposure to blood glucose forecasts on logging activity, average glucose, and percentage of glucose readings in range, after controlling for potential confounding factors. Data were analyzed using analysis of covariance (ANCOVA) and regression analyses.

Results

Data from a total of 1411 One Drop users with type 2 diabetes and elevated baseline glucose were analyzed. Participants (60.6% male, 795/1311; mean age 50.2 years, SD 11.8) had diabetes for 7.1 years on average (SD 7.9). After controlling for potential confounding factors, blood glucose forecasts were associated with more frequent blood glucose logging (P=.004), lower average blood glucose (P<.001), and a higher percentage of readings in range (P=.03) after 12 weeks. Blood glucose logging partially mediated the relationship between exposure to forecasts and average glucose.

Conclusions

Individuals who received blood glucose forecasts had significantly lower average glucose, with a greater amount of glucose measurements in a healthy range after 12 weeks compared to those who did not receive forecasts. Glucose logging was identified as a partial mediator of the relationship between forecast exposure and week-12 average glucose, highlighting a potential mechanism through which glucose forecasts exert their effect. When administered as a part of a comprehensive mHealth program, blood glucose forecasts may significantly improve glycemic management among people living with type 2 diabetes.

Understanding the Users with Chronic Pain on AI CBT Mental Health App (Wysa): A Mixed-Methods Retrospective Observational Study (Preprint)

Background

Digital health interventions can bridge barriers in access to treatment among individuals with chronic pain.

Objective

This study aimed to evaluate the perceived needs, engagement, and effectiveness of the mental health app Wysa with regard to mental health outcomes among real-world users who reported chronic pain and engaged with the app for support.

Methods

Real-world data from users (N=2194) who reported chronic pain and associated health conditions in their conversations with the mental health app were examined using a mixed methods retrospective observational study. An inductive thematic analysis was used to analyze the conversational data of users with chronic pain to assess perceived needs, along with comparative macro-analyses of conversational flows to capture engagement within the app. Additionally, the scores from a subset of users who completed a set of pre-post assessment questionnaires, namely Patient Health Questionnaire-9 (PHQ-9) (n=69) and Generalized Anxiety Disorder Assessment-7 (GAD-7) (n=57), were examined to evaluate the effectiveness of Wysa in providing support for mental health concerns among those managing chronic pain.

Results

The themes emerging from the conversations of users with chronic pain included health concerns, socioeconomic concerns, and pain management concerns. Findings from the quantitative analysis indicated that users with chronic pain showed significantly greater app engagement (P<.001) than users without chronic pain, with a large effect size (Vargha and Delaney A=0.76-0.80). Furthermore, users with pre-post assessments during the study period were found to have significant improvements in group means for both PHQ-9 and GAD-7 symptom scores, with a medium effect size (Cohen d=0.60-0.61).

Conclusions

The findings indicate that users look for tools that can help them address their concerns related to mental health, pain management, and sleep issues. The study findings also indicate the breadth of the needs of users with chronic pain and the lack of support structures, and suggest that Wysa can provide effective support to bridge the gap.