The Influence of Baseline Hemoglobin A1c on Digital Health Coaching Outcomes in Adults With Type 2 Diabetes: Real-World Retrospective Cohort Study

Digital therapeutics as an emerging new therapy for diabetes mellitus: potentials and concerns

The global burden of controlling and managing diabetes mellitus (DM) is a significant challenge. Despite the advancements in conventional DM therapy, there remain hurdles to overcome, such as enhancing medication adherence and improving patient prognosis. Digital therapeutics (DTx), an innovative digital application, has been proposed to augment the traditional disease management workflow, particularly in managing chronic diseases like DM. Several studies have explored DTx, yielding promising results. However, certain concerns about this innovation persist. In this review, we aim to encapsulate the potential of DTx and its applications in DM management, thereby providing a comprehensive overview of this technique for public health policymakers.

Demystifying diabetes health coaching: A scoping review unveiling the 'who' and 'where' of health coaching for adults with type 2 diabetes

Type 2 diabetes (T2D) is a complex chronic condition that requires ongoing self-management. Diabetes health coaching interventions provide personalized healthcare programming to address physical and psychosocial aspects of diabetes self-management.

AIMS

This scoping review aims to explore the contexts and settings of diabetes health coaching interventions for adults with T2D, using the RE-AIM framework.

METHODS

A search was completed in MEDLINE, PsycINFO, Emcare, Embase and Cochrane. Included citations described adults with exclusively T2D who had received a health coaching intervention. Citations were excluded if they focused on any other types of diabetes or diabetes prevention.

RESULTS

A total of 3418 records were identified through database and manual searches, with 29 citations selected for data extraction. Most health coaching interventions were delivered by health professionals, many employed lay health workers and a few included peer coaches. While many health coaching interventions were delivered remotely, in-person intervention settings were distributed among primary care, community health settings and non-healthcare sites.

CONCLUSION

The findings of this review suggest that diabetes health coaching may be implemented by a variety of providers in different settings. Further research is required to standardize training and implementation of health coaching and evaluate its long-term effectiveness.

Are e-Health Interventions Effective in Reducing Diabetes-Related Distress and Depression in Patients with Type 2 Diabetes? A Systematic Review with Meta-Analysis

Background: e-Health refers to any health care service delivered through the internet or related technologies, to improve quality of life. Despite the increasing use of e-health interventions to manage type 2 diabetes (T2D), there is a lack of evidence about the effectiveness on diabetes distress and depression, which are common issues in those living with T2D. Purpose: To synthesize and determine the effects of e-health interventions on diabetes distress and depression among patients with T2D. Methods: We systematically searched PubMed, Scopus, Cochrane CENTRAL, and Web of Science for randomized controlled trials (RCTs), non-RCTs and observational cohort studies for the effects of e-health interventions on diabetes distress and depression in patients with T2D up to September 14, 2022. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses 2020 recommendations were followed. The risk of bias was assessed according to the Risk-of-Bias 2 tool (RCTs), the Risk Of Bias In Non-randomised Studies-of Interventions (ROBINS-I) (non-RCTs) and the National Institute of Health tool (observational). The standardized mean difference (SMD) and its related 95% confidence intervals (CIs) were estimated with the DerSimonian-Laird method through random-effect models. A pooled raw mean difference (MD) meta-analysis was conducted for RCTs comparing the effects of e-health versus control on diabetes distress screening to display the clinical impact. Results: A total of 41 studies (24 RCTs, 14 non-RCTs, and 3 observational) involving 8,667 individuals were included. The pooled SMD for the effect of e-health versus the control group on diabetes distress was -0.14 (95% CI = -0.24 to -0.04; I2 = 23.9%; n = 10 studies), being -0.06 (95% CI = -0.15 to 0.02; I2 = 7.8%; n = 16 studies) for depression. The pooled raw MD on diabetes distress screening showed a reduction of -0.54 points (95% CI = -0.81 to -0.27; I2 = 85.1%; n = 7 studies). Conclusion: e-Health interventions are effective in diminishing diabetes distress among adults with T2D, inducing clinically meaningful reductions.

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.

Patient-reported outcomes for people with diabetes: what and how to measure? A narrative review

Patient-reported outcomes (PROs) are valuable for shared decision making and research. Patient-reported outcome measures (PROMs) are questionnaires used to measure PROs, such as health-related quality of life (HRQL). Although core outcome sets for trials and clinical practice have been developed separately, they, as well as other initiatives, recommend different PROs and PROMs. In research and clinical practice, different PROMs are used (some generic, some disease-specific), which measure many different things. This is a threat to the validity of research and clinical findings in the field of diabetes. In this narrative review, we aim to provide recommendations for the selection of relevant PROs and psychometrically sound PROMs for people with diabetes for use in clinical practice and research. Based on a general conceptual framework of PROs, we suggest that relevant PROs to measure in people with diabetes are: disease-specific symptoms (e.g. worries about hypoglycaemia and diabetes distress), general symptoms (e.g. fatigue and depression), functional status, general health perceptions and overall quality of life. Generic PROMs such as the 36-Item Short Form Health Survey (SF-36), WHO Disability Assessment Schedule (WHODAS 2.0), or Patient-Reported Outcomes Measurement Information System (PROMIS) measures could be considered to measure commonly relevant PROs, supplemented with disease-specific PROMs where needed. However, none of the existing diabetes-specific PROM scales has been sufficiently validated, although the Diabetes Symptom Self-Care Inventory (DSSCI) for measuring diabetes-specific symptoms and the Diabetes Distress Scale (DDS) and Problem Areas in Diabetes (PAID) for measuring distress showed sufficient content validity. Standardisation and use of relevant PROs and psychometrically sound PROMs can help inform people with diabetes about the expected course of disease and treatment, for shared decision making, to monitor outcomes and to improve healthcare. We recommend further validation studies of diabetes-specific PROMs that have sufficient content validity for measuring disease-specific symptoms and consider generic item banks developed based on item response theory for measuring commonly relevant PROs.

A Pilot Feasibility Study of Digital Health Coaching for Men With Prostate Cancer

PURPOSE

Prostate cancer is the most common cancer among men in the United States. The majority of prostate cancer treatment occurs in the ambulatory setting, and patients and their caregivers take on significant responsibility for monitoring and managing treatment and disease-related toxicity. Digital health coaching has shown promise as a tool to positively influence outcomes. We completed a single-arm pilot study to assess the feasibility of digital health coaching in men with prostate cancer.

METHODS

Men with a history of prostate cancer requiring treatment in the past 2 years were eligible for inclusion. Participants engaged in a 12-week health coaching program, consisting of a combination of at least one telephone call and up to four digital nudges (defined as content delivered via text, e-mail, or app on the basis of the participant's preference) per week. Prostate cancer-specific content addressed one of the following topics each week: fatigue, pain management, healthy eating, exercise, managing incontinence, sexual health, managing stress and anxiety, financial toxicity, goal setting during treatment, managing side effects, communicating with the health care team, and medication adherence. Services were provided at no cost to the participant.

RESULTS

A hundred patients were consented for the study, and 88 enrolled. The feasibility threshold of 60% was met with 63 of the 88 enrolled individuals completing the 3-month program (proportion = 71.6%; 90% CI, 62.6 to 79.4; P = .016).

CONCLUSION

Digital health coaching for men with prostate cancer is feasible. These findings support further evaluation of digital health coaching for men with prostate cancer in larger randomized controlled trials.