Abstract BackgroundThe Diabetes Remission Clinical Trial (DiRECT) demonstrated that remission of type 2 diabetes can be achieved through substantial weight loss using a total diet replacement (TDR) intervention combined with structured support. Whether this approach can be delivered exclusively via eHealth has not been well studied. ObjectiveThis pilot study aimed to evaluate whether a TDR intervention delivered solely via eHealth could induce clinically meaningful weight loss and achieve type 2 diabetes remission. MethodsThis was a single-arm, nonblinded, single-center pilot study conducted at the clinical research facilities of Umeå University Hospital. Individuals with type 2 diabetes diagnosed within the past 6 years were included. Participants followed a TDR (~850 kcal/d) for 12 weeks, and then gradually reintroduced food, with a total study duration of 6 months. Diabetes medications were discontinued at the start of the study. Daily body weight and fasting glucose were measured at home and transmitted to the study team via connected devices. All clinical support was delivered through video calls and chat. The 2 prespecified coprimary outcomes were a reduction in weight of 15 kg or more and remission of diabetes, defined as glycated hemoglobin ResultsTen participants (mean age 58.5, SD 7.4 y; mean BMI 35.3, SD 5.9 kg/m²; n=9 men and n=1 woman) were enrolled. After 6 months, 6 of 10 participants achieved the prespecified coprimary outcome of ≥15 kg weight loss, and all 10 participants achieved the prespecified coprimary outcome of diabetes remission. Mean weight loss was 16.9 (SD 5.4; P; P ConclusionsIn this pilot study, an eHealth-delivered TDR intervention was associated with substantial weight loss and diabetes remission at 6 months without the use of glucose-lowering medication. These findings support further evaluation of fully eHealth-delivered dietary interventions in larger and longer-term randomized controlled trials.
Abstract BackgroundEcological momentary assessment (EMA) is a tool that captures emotional states, experiences, and behaviors in real or near-real time. Concurrent EMA and continuous glucose monitoring (CGM) data can provide an in-depth understanding of the impacts of psychosocial factors on momentary glucose levels. However, study methodology varies widely for EMA and CGM data collection and analysis. ObjectiveThis scoping review aims to summarize the objectives, methodologies, and outcomes of studies analyzing concurrent biopsychosocial EMA and CGM data in diabetes. MethodsThis study was conducted following the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) guidelines. Original research studies evaluating participants with diabetes, with concurrent collection and analysis of EMA and CGM data, were included in this review. A total of 782 studies were identified from PubMed, Embase, and EBSCOhost from May 2009 to December 2025. From these, duplicates, non-original research articles, and articles not measuring concurrent EMA and CGM data were excluded, resulting in a total of 19 studies included in this review. Methodological data were abstracted and summarized, including study characteristics, EMA protocols and outcomes, CGM outcomes, and integrated EMA and CGM study objectives. Methodological gaps across the included studies were identified and summarized. ResultsOf the 19 studies, 16 primarily recruited adult populations, and the majority of these studies (n=14, 74%) included participants with type 1 diabetes. The median EMA delivery duration was 14 days (range 3‐18 days), with a median of 5.5 prompts delivered per day (range 1‐28). EMA outcomes included a variety of biopsychosocial factors (emotion, self-care behaviors, interpersonal interactions, symptoms, and cognition). Seventy-four percent analyzed blinded CGM data over a median of 14 (range 3‐18) days. Forty-two percent used nonstandardized CGM glucose outcomes (postprandial glucose, eating patterns, and hypoglycemic events). Integrated EMA and CGM data analysis answered a broad array of study objectives, including the impact of psychosocial factors on momentary glucose metrics; the influence of momentary glucose on emotional states, mood, personal behaviors, sleep, and cognition, or vice versa; and study protocol or mobile app optimization, among others. Methodological gaps included lack of standardization of EMA and CGM outcomes, duration of data capture, reporting of statistical analyses, and study population. ConclusionsThis review provides a detailed summary of the methodology and outcomes of original research articles using combined EMA and blood glucose data measured via CGM. These combined methods allow for an opportunity to elucidate relationships between psychosocial factors and momentary glucose, an understanding of which is imperative for the development of future psychological and behavioral interventions in diabetes. However, standardization of protocols and expansion of participant populations for future EMA and CGM data collection and analysis are needed to ensure data accuracy, reproducibility, and generalizability.
Abstract Nutrient estimation from meal images by multimodal large language models can support diabetes self-management, but its robustness is limited by variability driven by both sensitivity to visual presentation and inherent model instability. Accounting for and mitigating this variability is essential for robust AI-assisted dietary assessment.
Abstract Background Diabetic retinopathy is the leading cause of blindness in US adults. Fewer than half of patients with diabetes in rural areas complete the recommended screening that could prevent blindness. Store-and-forward teleophthalmology and mobile pop-up eye clinics have each been shown to improve screening access, but studies examining the implementation of both modalities within the same rural primary care system are lacking. Objective This study aimed to identify multilevel facilitators and barriers to implementing teleophthalmology and pop-up eye clinics for diabetic eye care in 2 rural primary care clinics in upstate New York. Methods We conducted a mixed methods implementation study with prospective semistructured interviews and retrospective, descriptive electronic health record data at 2 university-affiliated primary care clinics classified as “isolated rural,” guided by the Consolidated Framework for Implementation Research (CFIR). Electronic health record data from 885 adults with diabetes were used to characterize patient demographics and eye care use. Patients were categorized into 3 groups: eye exam with an eye doctor (n=586), on-site primary care–based eye exam (n=91; teleophthalmology n=39 and pop-up clinic n=52), or no recent eye exam (n=208). Semistructured interviews were conducted with 20 patients (n=5 per subgroup) and 14 staff members (primary care clinicians, optometrists, and administrative personnel), purposively sampled to capture diverse perspectives across eye care pathways and roles. Interviews were coded using CFIR domains and analyzed thematically until no new themes emerged. Results Patients in the on-site primary care eye exam group were the most socially disadvantaged, with the lowest proportions reporting no transportation needs (42/91, 46.2%), no housing instability (28/91, 30.8%), and no food insecurity (36/91, 39.6%). Over 18 months, 58.4% (52/89) of scheduled pop-up clinic appointments were completed, and 92.3% (36/39) of teleophthalmology images were gradable. Pop-up clinics detected higher rates of diabetic retinopathy (11/52, 21.2% vs 3/39, 7.7%), cataract (29/52, 55.8% vs 3/39, 7.7%), and reduced visual acuity (23/52, 44.2% vs 11/39, 28.2%) than teleophthalmology. Qualitative analysis revealed that patients viewed both modalities as a convenient “one-stop shop” and valued trust in primary care staff. Staff identified complementary barriers: training and workflow complexity for teleophthalmology, and underutilization and scheduling challenges for pop-up clinics. Implementation champions across roles proposed an integrated workflow in which same-day teleophthalmology becomes a default component of annual diabetes visits, with targeted referral to pop-up clinics for patients with abnormal findings. Conclusions Primary care–based eye programs in rural settings preferentially reached socially vulnerable patients with diabetes and detected substantial unmet eye pathology. However, operating teleophthalmology and pop-up clinics as separate programs led to inefficiencies in both programs. A stakeholder-driven integrated model embedding teleophthalmology into routine diabetes care, with targeted pop-up clinic referrals, may improve the reach, efficiency, and sustainability of diabetic eye screening in rural populations.
