JMIR Diabetes最新文献

{"title":"Data, Process, and Data-Driven Representations of Digital Twins in Diabetes: Scoping Review.","authors":"Beyza Cinar, Louisa van den Boom, Maria Maleshkova","doi":"10.2196/91729","DOIUrl":"10.2196/91729","url":null,"abstract":"<p><strong>Background: </strong>Diabetes is a chronic metabolic condition characterized by impaired blood glucose regulation. It is often linked to serious health complications and comorbidities that significantly affect quality of life, requiring effective management, continuous monitoring, and advanced data analytics. Notably, tailored diabetes management can be enhanced by digital twins (DTs), which serve as adaptive digital representations of patients, using clinical, physiological, and lifestyle data.</p><p><strong>Objective: </strong>This review explores diabetes-related DTs by examining their patient representation levels. We aim to synthesize the current state of the art and outline the foundations of a holistic, multilevel, multifunctional personalized DT for diabetes management.</p><p><strong>Methods: </strong>We investigate requirements for a personalized holistic DT and classify existing approaches into three representation levels: (1) data representation, involving structured, context-aware, and AI-ready data architectures that support data analysis, enable semantic interoperability, relationship extraction, and real-time bidirectional data exchange between patient and virtual replica. (2) Process representation, primarily based on mechanistic models simulating glucose-insulin-meal and exercise-glucose dynamics. (3) Data-driven representation, focusing on individualization through predictive modeling of disease onset, adverse events, and the generation of explainable, personalized recommendations. The literature is synthesized to provide a holistic, multilevel perspective on DTs, and to identify research gaps.</p><p><strong>Results: </strong>DTs accompany patients throughout their lifecycle and span a wide range of use cases, from long-term disease prediction to timely prediction of severe events. However, personalized DTs remain at an early stage of development. Most existing systems primarily function as simulation tools and lack comprehensive integration of data, processes, and data-driven representations. Key gaps include limited use of standardized semantic data models and ontologies, insufficient real-time bidirectional architectures, and fragmented integration of mechanistic and machine learning models, which are often treated as independent rather than complementary components.</p><p><strong>Conclusions: </strong>Although DTs hold substantial potential to advance personalized diabetes care, current implementations remain fragmented and incomplete. Future research should prioritize the development of holistic, multilevel DTs that integrate interoperable data infrastructures, mechanistic simulations, and data-driven models into cohesive, personalized systems capable of supporting lifelong disease management.</p>","PeriodicalId":52371,"journal":{"name":"JMIR Diabetes","volume":"11 ","pages":"e91729"},"PeriodicalIF":2.9,"publicationDate":"2026-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13646445/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149129054","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"An eHealth-Delivered Total Diet Replacement Intervention for Type 2 Diabetes Remission: Single-Arm Pilot Study.","authors":"Youssef Chninou, Johannes Edholm, Jenny Engvall, Sofia Wahlqvist, Claudia Schien, Anna Winkvist, Julia Otten","doi":"10.2196/93074","DOIUrl":"10.2196/93074","url":null,"abstract":"<p><strong>Background: </strong>The 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.</p><p><strong>Objective: </strong>This 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.</p><p><strong>Methods: </strong>This 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 below 6.5% without glucose-lowering medication, from baseline to 6 months. A 75 g oral glucose tolerance test and indirect calorimetry were performed at baseline and at 6 months to assess resting energy expenditure (REE) and respiratory quotient (RQ).</p><p><strong>Results: </strong>Ten 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; <i>P</i>=.005) kg, and glycated hemoglobin decreased by 1.0% (SD 0.8%<i>; P</i>=.008). Daily home measurements showed a marked reduction in fasting glucose within the first week of the intervention. Median REE decreased by 19% (IQR 17%-22%), while median fasting RQ increased by 15% (IQR 5%-27%) and median post-glucose-load RQ increased by 12% (IQR 9%-18%) at 6 months.</p><p><strong>Conclusions: </strong>In 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.</p>","PeriodicalId":52371,"journal":{"name":"JMIR Diabetes","volume":"11 ","pages":"e93074"},"PeriodicalIF":2.9,"publicationDate":"2026-10-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13641317/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149118368","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Real-Time Psychological Factors Using Ecological Momentary Assessment With Continuous Glucose Monitoring in Diabetes Mellitus: Scoping Review.","authors":"Kara Mizokami-Stout, Kira Voelker, Melissa DeJonckheere, Lynn Ang, Evan L Reynolds, Joyce M Lee, Rodica Pop-Busui, Brian C Callaghan, Emily Hirschfeld, Jennifer J Iyengar, Dana Albright","doi":"10.2196/87688","DOIUrl":"https://doi.org/10.2196/87688","url":null,"abstract":"&lt;p&gt;&lt;strong&gt;Background: &lt;/strong&gt;Ecological 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.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Objective: &lt;/strong&gt;This scoping review aims to summarize the objectives, methodologies, and outcomes of studies analyzing concurrent biopsychosocial EMA and CGM data in diabetes.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Methods: &lt;/strong&gt;This 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.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Results: &lt;/strong&gt;Of 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.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Conclusions: &lt;/strong&gt;This 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 under","PeriodicalId":52371,"journal":{"name":"JMIR Diabetes","volume":"11 ","pages":"e87688"},"PeriodicalIF":2.9,"publicationDate":"2026-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13626547/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149118373","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"SMARTCLOTH-Odyssey for Nutrition Education in Type 1 Diabetes: Development and Acceptability Study of a Gamified Web-Based Platform for Diabetes Nurse Educators Using a Human-Centered Design Approach.","authors":"Guillermo Molina-Recio, Ana-Belen Ariza-Jimenez, Alberto Membrillo-Del Pozo, Sandra Zafrilla-Sanchez, Jose Alvarez-Moral, Jose-Luis Velez-Leon, Rosa Gonzalez-Illanes, Rafael Molina-Luque","doi":"10.2196/79648","DOIUrl":"10.2196/79648","url":null,"abstract":"<p><strong>Background: </strong>The onset of type 1 diabetes mellitus (T1DM) in adolescence represents a challenge for patients, families, and health care professionals. Diabetes nurse educators identify a lack of adolescent-friendly educational resources, especially in nutrition education. Digital technology offers an opportunity to develop innovative tools to address these needs from a user-centered approach.</p><p><strong>Objective: </strong>We aimed to design and evaluate the acceptability of the SMARTCLOTH-Odyssey platform, an interactive web tool designed to support diabetes nurse educators in delivering nutrition education based on carbohydrate counting to adolescents with recent T1DM, evaluated from the perspective of nurse educators.</p><p><strong>Methods: </strong>A mixed study was carried out in three phases: (1) qualitative analysis through two focus groups with nurse educators in the Andalusian Community to identify barriers and needs; (2) development of the digital tool following a human-centered design methodology, incorporating narrative and gamified elements; and (3) quantitative evaluation of acceptability through an ad hoc questionnaire applied to 40 professionals who tested the platform.</p><p><strong>Results: </strong>Participants highlighted the lack of homogeneous and adapted debut materials, and the need for emotionally sensitive and visually appealing tools. SMARTCLOTH-Odyssey was rated positively in terms of usefulness, clarity, and clinical applicability. A total of 97.5% (39/40) felt it could facilitate nutrition education, and 90% (36/40) said they would use it in their practice. The platform was perceived as intuitive, innovative, and adapted to the characteristics of the adolescent patient.</p><p><strong>Conclusions: </strong>SMARTCLOTH-Odyssey constitutes a viable and well-valued proposal by nurse educators. It has the potential to improve nutrition education from the diagnosis of T1DM. Its participatory development reinforces its applicability and sustainability in real clinical contexts.</p>","PeriodicalId":52371,"journal":{"name":"JMIR Diabetes","volume":"11 ","pages":"e79648"},"PeriodicalIF":2.9,"publicationDate":"2026-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13614223/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149065906","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Toward Robust AI-Assisted Dietary Assessment for Diabetes Self-Management: Quantifying and Decomposing Large Language Model Prediction Variability From Meal Images.","authors":"Zhaohua Wang, Daniel Lane, Kayo Waki","doi":"10.2196/102715","DOIUrl":"10.2196/102715","url":null,"abstract":"<p><strong>Unlabelled: </strong>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.</p>","PeriodicalId":52371,"journal":{"name":"JMIR Diabetes","volume":"11 ","pages":"e102715"},"PeriodicalIF":2.9,"publicationDate":"2026-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13544413/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148892961","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Implementing Diabetic Eye Care in Rural Primary Care Through Teleophthalmology and Pop-Up Clinics: Mixed Methods Study.","authors":"Nisha G Arya, Victoria Koltchine, Talia C Gearinger, Sherianne Buehler, Reza Yousefi-Nooraie, Rajeev S Ramchandran","doi":"10.2196/106290","DOIUrl":"10.2196/106290","url":null,"abstract":"&lt;p&gt;&lt;strong&gt;Background: &lt;/strong&gt;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.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Objective: &lt;/strong&gt;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.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Methods: &lt;/strong&gt;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.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Results: &lt;/strong&gt;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.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Conclusions: &lt;/strong&gt;Primary care-based eye programs in rural settings preferentially reached socially v","PeriodicalId":52371,"journal":{"name":"JMIR Diabetes","volume":"11 ","pages":"e106290"},"PeriodicalIF":2.9,"publicationDate":"2026-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13541231/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148889222","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Social Media Discussions of Anti-Diabetic Drugs and the Popularity of GLP-1 Therapies: Content Analysis.","authors":"Chloe Stallion, Tamkeen Khan, Christian Guerrero, Stavros Tsipas, Gregory Wozniak","doi":"10.2196/87590","DOIUrl":"10.2196/87590","url":null,"abstract":"<p><strong>Background: </strong>The clinical use of antidiabetic drugs (ADDs) has gained prominent public visibility due to the Food and Drug Administration (FDA) expansion of glucagon-like peptide-1 receptor agonists (GLP-1 RAs) in recent years; these drugs are now widely prescribed for weight loss. This shift is reflected in online public discourse.</p><p><strong>Objective: </strong>This study aimed to analyze the current online public discourse surrounding ADDs, with an emphasis on perceptions of insulin versus noninsulin therapies and the increasing prominence of weight loss-associated medications.</p><p><strong>Methods: </strong>We conducted a retrospective analysis of 23,580 English-language posts from the United States in 2023, using Boolean keyword searches to examine conversations about insulin-inclusive, with or without weight loss terms, and insulin-exclusive, with or without weight loss terms. We analyzed the volume and sentiment of online conversations regarding ADDs, frequency of drug mentions, proportion of posts by self-identified physicians, and thematic analysis of patient and clinician concerns.</p><p><strong>Results: </strong>A total of 26,832 initial posts were collected in 2023. After post validation, 23,580 posts remained as the study sample size. Of the 23,580 posts, 4.6% (1087/23,580) mentioned insulin, and 95.4% (n=22,493) did not mention insulin. Semaglutide-containing drugs such as Ozempic and Mounjaro were the most referenced medications, particularly in weight-loss contexts. Weight loss conversations made up the majority of online posts. Conversations about insulin were marginal compared with conversations that did not mention insulin online. Only 7% to 10% of posts came from self-identified physicians. Key themes included drug accessibility, off-label use for weight management, concerns about supply shortages, insurance coverage, and growing calls for holistic care. Notably, public perspectives favored the dual efficacy of medications like Ozempic in managing diabetes and promoting weight loss.</p><p><strong>Conclusions: </strong>The discourse on ADDs is dominated by weight loss-oriented therapies, with GLP-1 RAs driving much of the engagement. This surveillance paper illustrates the current state of public health interests around antidiabetic medications associated with weight loss and raises concerns regarding equitable access for patients with diabetes. These findings underscore the need for updated clinical guidance on necessary lifestyle behaviors for antidiabetic medication use and ongoing monitoring of public opinions regarding chronic disease management medications.</p>","PeriodicalId":52371,"journal":{"name":"JMIR Diabetes","volume":"11 ","pages":"e87590"},"PeriodicalIF":2.9,"publicationDate":"2026-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13515349/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148882695","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The Emotional Burden and Behavioral Impacts of Alarms and Alerts Across the Spectrum of Diabetes Technology Use: a Cross-Sectional Study.","authors":"Estelle Everett, Erin Shaw, Bryan Escobar Barrios, Beatrice Brumley, Kyrstin Lane, Tannaz Moin, Lauren E Wisk","doi":"10.2196/97122","DOIUrl":"https://doi.org/10.2196/97122","url":null,"abstract":"&lt;p&gt;&lt;strong&gt;Background: &lt;/strong&gt;Continuous glucose monitors (CGMs), sensor-augmented pumps (SAPs), and automated insulin delivery (AID) systems have substantially improved glycemic outcomes for people with type 1 diabetes (T1D). However, these technologies also generate frequent alarms and alerts that may contribute to emotional burden, alarm fatigue, and maladaptive behavioral responses. Despite increasing recognition of alarm-related distress, little is known about how alarm burden differs across contemporary diabetes technologies.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Objective: &lt;/strong&gt;This study evaluated differences in alarm frequency, emotional burden, and behavioral responses to alarms and alerts among adults using CGMs alone, SAP therapy, and AID systems.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Methods: &lt;/strong&gt;We conducted a cross-sectional survey of adults (≥18 years) with T1D receiving care within a large academic health system between August 2024 and March 2025. Eligible participants completed an online survey assessing demographics, diabetes technology use, perceptions of alarm frequency and burden, and responses to alarms and alerts. Participants were categorized as CGM-only, SAP, or AID users. Differences between groups were evaluated using χ2 tests and ANOVA. Ordinal logistic regression models adjusted for age, gender, and diabetes duration were used to examine associations between diabetes technology type and alarm-related outcomes.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Results: &lt;/strong&gt;Among 838 respondents (mean age 46.0, SD 16.6 years; mean diabetes duration 23.0, SD 14.0 years; n=457, 55% women), AID users reported the highest alarm frequency, with 49% (n=252) experiencing alarms several times daily, compared with 35% (n=28) of SAP users and 32% (n=79) of CGM-only users (P&lt;.001). AID users also reported greater alarm disruptiveness, annoyance, and unwanted attention than CGM-only users. Overcorrection of glucose levels in response to alerts was common across all technologies: 44% (n=371) and 50% (n=419) of participants reported sometimes overcorrecting low and high glucose levels, respectively, while 32% (n=265) and 18% (n=147) reported often or always overcorrecting low and high glucose levels, respectively. After adjustment, AID users had greater odds of frequent alarms (odds ratio [OR] 1.98, 95% CI 1.48-2.65), alarm disruptiveness (OR 1.67, 95% CI 1.24-2.25), annoyance (OR 1.65, 95% CI 1.23-2.19), unwanted attention (OR 1.85, 95% CI 1.38-2.47), ignoring alarms (OR 1.86, 95% CI 1.40-2.47), and overcorrecting low glucose levels (OR 1.61, 95% CI 1.20-2.15) compared with CGM-only users. Perceived effectiveness of alarms did not differ by technology type.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Conclusions: &lt;/strong&gt;Although AID systems provide important clinical benefits, they are associated with the greatest alarm and alert burden. Alarm-driven behaviors, including ignoring alerts and overcorrecting glucose levels, represent previously underrecognized consequences of diabetes technology that may diminish user experience","PeriodicalId":52371,"journal":{"name":"JMIR Diabetes","volume":"11 ","pages":"e97122"},"PeriodicalIF":2.9,"publicationDate":"2026-08-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13472229/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148763104","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Promoting Stigma-Free Language in Type 2 Diabetes Care Among Primary Care Clinicians: Randomized Controlled Pilot Trial.","authors":"Kevin L Joiner, Alexandra Agapiou, Alicia Carmichael, Brandon P Labbree, Donna Walter, Houda Tarraf, Medha Raju, Boluwatife Dogari, Nao Hagiwara, Sophia Lin, Richard Gonzalez","doi":"10.2196/95805","DOIUrl":"10.2196/95805","url":null,"abstract":"&lt;p&gt;&lt;strong&gt;Background: &lt;/strong&gt;The American Diabetes Association and the Association of Diabetes Care & Education Specialists recommend person-first, strengths-based, and stigma-free language in diabetes care and education. However, interventions to promote stigma-free language among primary care clinicians remain limited.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Objective: &lt;/strong&gt;This mixed methods pilot study aimed to evaluate the acceptability and preliminary effects of a diabetes stigma-reduction training module for primary care clinicians, designed to increase awareness of language used in clinician-patient interactions and explore changes in attitudes and intentions toward avoiding stigmatizing language.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Methods: &lt;/strong&gt;Twenty-one primary care clinicians completed either a stigma-reduction training module (n=12) or an active control condition (n=9). Both conditions included a standardized patient encounter, an educational video, and a guided self-reflection activity. The stigma-reduction training module included diabetes-specific content on stigmatizing language and person-first, strengths-based alternatives. Theory of Planned Behavior domain measures were administered before and immediately after the assigned condition. Attitudes and intentions were assessed precondition and postcondition. Acceptability was evaluated using a postcondition survey and semistructured qualitative interviews. Repeated-measures ANOVA was used to assess between-group changes over time, and a qualitative descriptive approach was used to explore clinicians' perceptions.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Results: &lt;/strong&gt;Clinicians who received the stigma-reduction training module demonstrated significantly greater improvement in attitudes toward avoiding stigmatizing language compared with clinicians in the active control condition, with mean attitude scores increasing by 1.19 (SD 0.68) points versus 0.21 (SD 0.44) points, respectively. A significant condition × time interaction was observed (F1,19=14.27; P=.001, partial η2=0.43, Cohen d=1.67). The between-group difference in intention change was not statistically significant, with mean intention scores increasing by 0.69 (SD 1.08) points in the stigma-reduction training module condition versus 0.02 (SD 0.90) points in the active control condition (F1,19=2.33; P=.14, partial η2=0.11, Cohen d=0.67). Acceptability ratings were higher for the stigma-reduction training module than for the active control condition for clarity (mean 6.17, SD 0.72 vs mean 4.44, SD 1.74; P=.02), helpfulness (mean 6.08, SD 1.00 vs mean 4.56, SD 1.59; P=.03), and likelihood of recommendation (mean 6.25, SD 0.87 vs mean 4.56, SD 1.67; P=.02). The qualitative findings suggested that clinicians perceived the stigma-reduction training module as actionable, relevant to primary care, and useful for promoting self-reflection about habitual language use. The active control condition was generally perceived as a useful refresher but less novel and impactful.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Conc","PeriodicalId":52371,"journal":{"name":"JMIR Diabetes","volume":"11 ","pages":"e95805"},"PeriodicalIF":2.9,"publicationDate":"2026-08-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13460796/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148714492","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Serious Digital Game (SugarVita) to Support Diabetes Self-Management: Pilot Randomized Controlled Trial.","authors":"Edouard Reinders, Elma Cruts-Van de Meulengraaf, Ryan De Vries, Natal van Riel, Pieter Van Gorp, Jeanne Dieleman, Pleun Wouters-van Poppel, Harm Haak","doi":"10.2196/99345","DOIUrl":"10.2196/99345","url":null,"abstract":"<p><strong>Background: </strong>Serious digital games have been proposed as a novel approach to support diabetes education and self-management, but evidence regarding their effectiveness remains limited.</p><p><strong>Objective: </strong>This study aimed to evaluate the effects of SugarVita, a serious game for people with type 2 diabetes, on diabetes-related knowledge, self-confidence, and self-management. Secondary outcomes included hemoglobin A1c (HbA1c), engagement, and user evaluation.</p><p><strong>Methods: </strong>In this pilot randomized controlled trial, 30 adults with type 2 diabetes were randomized to SugarVita plus standard care or standard care alone for 8 weeks. Outcomes were assessed before and after the intervention using validated questionnaires and laboratory HbA1c values. Within-group changes were analyzed using Wilcoxon signed-rank tests and between-group differences using Mann-Whitney U tests. Bonferroni correction was applied for multiple primary outcomes.</p><p><strong>Results: </strong>No statistically significant between-group differences were observed for diabetes-related knowledge, self-confidence, or self-management after correction for multiple testing. Both groups showed numerical improvements over time. HbA1c decreased significantly within the intervention group (median 73.0, IQR 70.8-81.5 to median 64.5, IQR 60.8-72.0 mmol/mol; P=.007), whereas no significant change was observed in the control group. Greater total playtime was moderately associated with HbA1c reduction. User evaluations indicated high perceived educational value.</p><p><strong>Conclusions: </strong>Participants reported positive experiences with SugarVita and perceived the game as educational and user-friendly. No statistically significant between-group differences were observed for the primary outcomes. These findings support the feasibility and acceptability of SugarVita as a digital educational intervention and warrant further evaluation in larger studies.</p>","PeriodicalId":52371,"journal":{"name":"JMIR Diabetes","volume":"11 ","pages":"e99345"},"PeriodicalIF":2.9,"publicationDate":"2026-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13451009/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148690204","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}