Journal of Diabetes Science and Technology最新文献

{"title":"The Needle Shield Size and Applied Force of Subcutaneous Autoinjectors Significantly Influence the Injection Depth.","authors":"Anne-Sofie Madsen Staples, Mette Poulsen, Kezia Ann Friis Præstmark, Thomas Sparre, Marie Sand Traberg","doi":"10.1177/19322968241231996","DOIUrl":"10.1177/19322968241231996","url":null,"abstract":"<p><strong>Background: </strong>This study examines how shield-triggered autoinjectors (AIs), for subcutaneous drug delivery, affect injection depth. It focuses on shield size and applied force, parameters that could potentially lead to inadvertent intramuscular (IM) injections due to tissue compression.</p><p><strong>Method: </strong>A blinded ex-vivo study was performed to assess the impact of shield size and applied force on injection depth. Shields of 15, 20, and 30 mm diameters and forces from 2 to 10 N were investigated. The study involved 55 injections in three Landrace, Yorkshire, and Duroc (LYD) pigs, with injection depths measured with computed tomography (CT). An in-vivo study, involving 20 injections in three LYD pigs, controlled the findings, using fluoroscopy (FS) videos for depth measurement.</p><p><strong>Results: </strong>The CT study revealed that smaller shield sizes significantly increased injection depth. With a 15 mm diameter shield, 10 N applied force, and 5 mm needle protrusion, the injection depth exceeded the needle length by over 3 mm. Injection depth increased with higher applied forces until a plateau was reached around 8 N. Both applied force and size were significant factors for injection depth (analysis of variance [ANOVA], <i>P</i> < .05) in the CT study. The FS study confirmed the ex-vivo findings in an in-vivo setting.</p><p><strong>Conclusions: </strong>The study demonstrates that shield size has a greater impact on injection depth than the applied force. While conducted in porcine tissue, the study provides useful insights into the relative effects of shield size and applied force. Further investigations in humans are needed to confirm the predicted injection depths for AIs.</p>","PeriodicalId":15475,"journal":{"name":"Journal of Diabetes Science and Technology","volume":" ","pages":"1317-1325"},"PeriodicalIF":3.7,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11571378/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139931416","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":"Accuracy and Functionality of Select Continuous Glucose Monitoring Systems Are Not Impacted by Implantable Cardioverter Defibrillator Devices.","authors":"Dylan Lazar, Michael Tao, William Matievich, Kevin Kastanos, Timothy C Dunn","doi":"10.1177/19322968241260038","DOIUrl":"10.1177/19322968241260038","url":null,"abstract":"<p><strong>Background: </strong>Increasing numbers of individuals with diabetes are adopting use of continuous glucose monitoring (CGM) in their daily self-management. Many of these individuals have advanced heart disease. Implantable cardioverter defibrillator (ICD) devices can effectively reduce arrhythmic death and all-cause mortality in individuals with advanced heart disease. However, the potential impact of ICD devices on CGM system accuracy and functionality has not been well studied.</p><p><strong>Methods: </strong>This evaluation assessed whether FreeStyle Libre (FL) CGM systems can coexist and function within the same patient in the presence of wireless interference devices, including current ICD devices. Interferer sources included Wi-Fi devices, Bluetooth devices, cellular mobile devices, implantable medical devices, Bluetooth Low-Energy (BLE) devices, BLE accessory devices and BLE mobile devices, and ICD-programmer interferers. Five testing methodologies were used to evaluate the accuracy and functionality of the CGM systems when exposed to ICD functions: high-energy emergency shocking, pacing modes, anti-tachycardia pacing mode (ATP), and DC Fibber mode.</p><p><strong>Results: </strong>All acceptance criteria and testing requirements were met for the CGM and ICD system for wireless coexistence evaluation.</p><p><strong>Conclusions: </strong>Our findings demonstrated that coexisting ICD devices and FL CGM systems provide safe and effective wireless communications with functional and accurate transfer of data during scenarios expected in clinical use.</p>","PeriodicalId":15475,"journal":{"name":"Journal of Diabetes Science and Technology","volume":" ","pages":"1385-1391"},"PeriodicalIF":3.7,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11571575/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141440542","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":"Accuracy and Feasibility of Using a Smartphone Application for Carbohydrate Counting Versus Traditional Carbohydrate Counting for Adults With Insulin-Treated Diabetes.","authors":"Mohammad Shehab, Robert M Cohen, Bonnie Brehm, Tamilyn Bakas","doi":"10.1177/19322968241248606","DOIUrl":"10.1177/19322968241248606","url":null,"abstract":"<p><strong>Background: </strong>Patients with insulin-treated diabetes struggle with performing accurate carbohydrate counting for proper blood glucose control. Little is known about the comparative accuracy and feasibility of carbohydrate counting methods.</p><p><strong>Purpose: </strong>The purpose of this study was to determine whether carbohydrate counting using a smartphone application is more accurate and feasible than a traditional method.Theoretical/conceptual framework:Based on a conceptual model derived from the Technology Acceptance Model, feasibility was defined as usefulness, ease of use, and behavioral intention to use each method.</p><p><strong>Methods: </strong>A standardized meal was presented to 20 adults with insulin-treated diabetes who counted carbohydrates using traditional and smartphone methods. Accuracy was measured by comparing carbohydrate counting estimates with the standardized meal values. Perceived feasibility (usefulness, ease of use, behavioral intention) was measured using rating forms derived from the Technology Acceptance Model.</p><p><strong>Results: </strong>The number of training and estimation minutes were significantly higher for the traditional method than the smartphone method (<i>Z</i> = -3.83, <i>P</i> < .05; <i>Z</i> = -2.30, <i>P</i> < .05). The traditional method took an additional 1.4 minutes for estimation and 12.5 minutes for training. There were no significant differences in accuracy between traditional and smartphone methods for carbohydrate counting (Wilcoxon signed-rank test, <i>Z</i> = -1.10, <i>P</i> = .28). There were no significant differences between traditional and smartphone methods for feasibility (usefulness, <i>Z</i> = -.10, <i>P</i> = .95; ease of use, <i>Z</i> = -.36, <i>P</i> = .72; or behavioral intention, <i>Z</i> = -.94, <i>P</i> = .35).</p><p><strong>Conclusion: </strong>While both traditional and smartphone methods were found to be similar in terms of accuracy and feasibility, the smartphone method took less time for training and for carbohydrate estimation.</p>","PeriodicalId":15475,"journal":{"name":"Journal of Diabetes Science and Technology","volume":" ","pages":"1302-1309"},"PeriodicalIF":3.7,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11571717/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140849328","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":"Characteristics Associated With Elevated Time Below Range in Elderly Patients With Type 1 Diabetes Using an Automated Insulin Delivery System.","authors":"Ana María Gómez Medina, Darío A Parra Prieto, Diana Cristina Henao Carrillo, Claudia Milena Gómez, Oscar Mauricio Muñoz Velandia, Sandra Caicedo, Alfonso Luis Kerguelen Villadiego, Luis Miguel Rodríguez Hortúa, Oscar David Lucero Pantoja, Mauricio Uribe Valencia, María Margarita García Guete, Sofia Robledo Gómez, Martin Rondón Sepúlveda","doi":"10.1177/19322968241232659","DOIUrl":"10.1177/19322968241232659","url":null,"abstract":"<p><strong>Background: </strong>This study investigated the characteristics associated with an increased risk of hypoglycemia, in elderly patients with type 1 diabetes mellitus (T1D) using automated insulin delivery (AID) systems.</p><p><strong>Methods: </strong>Cross-sectional observational study including patients >60 years, using sensor-augmented insulin pump therapy with predictive low-glucose management (SAPT-PLGM), hybrid closed-loop (HCL), and advanced hybrid closed-loop (AHCL), for more than three months. A geriatric assessment was performed, and body composition was determined to investigate its association with achieving time below range (TBR) <70 mg/dL goals.</p><p><strong>Results: </strong>The study included 59 patients (47.5% of men, mean age of 67.6 years, glycated hemoglobin [HbA1c] of 7.5 ± 0.6%, time in range (TIR) 77.8 ± 9.9%). Time below range <70 and <54 mg/dL were 2.2 ± 2.3% and 0.4 ± 0.81%, respectively. Patients with elevated TBR <70 mg/dL (>1%) had higher HbA1c levels, lower TIR, elevated time above range (TAR), and high glycemic variability. Regarding body composition, greater muscle mass, grip strength, and visceral fat were associated with a lower TBR <70 mg/dL. These factors were independent of the type of technology used, but TIR was higher when using AHCL systems compared with SAPT-PLGM and HCL systems.</p><p><strong>Conclusions: </strong>In elderly patients treated with AID systems with good functional status, lower lean mass, lower grip strength, and lower visceral fat percentage were associated with TBR greater than 1%, regardless of the device used. A similar finding along was found with CGM indicators such as higher HbA1c levels, lower TIR, higher TAR, and higher CV. Geriatric assessment is crucial for personalizing patient management.</p>","PeriodicalId":15475,"journal":{"name":"Journal of Diabetes Science and Technology","volume":" ","pages":"1286-1292"},"PeriodicalIF":3.7,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11571305/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140174915","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":"Behavioral Intervention Functions in Type 2 Diabetes Apps: Literature Review.","authors":"Elia Gabarron, Pietro Randine, Eirik Årsand","doi":"10.1177/19322968241305646","DOIUrl":"10.1177/19322968241305646","url":null,"abstract":"<p><strong>Background: </strong>As type 2 diabetes (T2D) is expected to increase, self-management becomes more crucial. Mobile apps are increasingly supporting self-management with tasks like blood glucose monitoring and medication management. Understanding the behavioral intervention functions used by diabetes apps today, is essential for improving future apps and systems for diabetes management.</p><p><strong>Objective: </strong>To analyze the behavioral intervention functions used in apps for managing T2D that integrate the three main elements: medication management, nutrition tracking, and blood glucose management.</p><p><strong>Methods: </strong>We conducted a literature review on T2D diabetes apps using SCOPUS, PubMed, and PsycINFO. After screening and removing duplicates, we analyzed app details and behavioral intervention functions based on the Behavior Change Wheel (BCW) framework.</p><p><strong>Results: </strong>We reviewed 644 scientific publications describing diabetes apps in clinical studies, narrowing it down to 20 studies, including 16 unique apps, after screening and exclusions. These studies were published between 2016 and 2024. Among the identified apps, automatic processing of medication data was reported in one study, while blood glucose data were automatically processed in 13 studies. Nutrition data processing varied. Most apps used <i>Enablement</i> and <i>Persuasion</i> as behavioral intervention functions, with <i>Education</i> and <i>Training</i> reported less frequently. <i>Environmental Restructuring, Incentivization, Coercion, Restriction</i>, and <i>Modeling</i> were not reported as being used in any studies.</p><p><strong>Conclusions: </strong>This review shows that while <i>Enablement</i> and <i>Persuasion</i> are common, other behavioral intervention functions seem to be underused or underreported. Future research could explore the potential of integrating additional behavioral intervention functions to enhance diabetes app efficacy and users' self-management.</p>","PeriodicalId":15475,"journal":{"name":"Journal of Diabetes Science and Technology","volume":" ","pages":"1183-1195"},"PeriodicalIF":3.7,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11664556/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142877345","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 Personalized Decision Support Systems for Type 1 Diabetes: Integrating Psychobehavioral Factors and Glycemic Control.","authors":"Mohammadreza Ganji, Leela Krishna Chaitanya Koravi, Marc Breton, Chiara Fabris","doi":"10.1177/19322968251359641","DOIUrl":"10.1177/19322968251359641","url":null,"abstract":"<p><strong>Background: </strong>While novel technologies have improved glycemic control in type 1 diabetes (T1D), their design is often glucose-centric and overlooks critical psychobehavioral elements such as individual treatment preferences and therapeutic goals. This article presents an algorithm development framework and study layout aimed at incorporating psychobehavioral factors into the design of technology for the management of T1D.</p><p><strong>Methods/design: </strong>A decision support system (DSS) was engineered at the University of Virginia providing therapeutic advice to individuals with T1D regarding optimal insulin dosing parameters, bolus calculation, safe undertaking of physical activity, and risk for hypoglycemia during the day as well as at bedtime. To accommodate individual preferences as to how the therapeutic advice is delivered, the DSS was designed with two possible operating modalities: <i>prescriptive</i>-offering optimized therapeutic recommendations for structured guidance, and <i>informative</i>-providing users with actionable insights to support informed decision-making. To test the DSS, a randomized crossover clinical trial design is described, where participants are sequentially exposed to each modality in random order. Throughout the study, glycemic control is captured by continuous glucose monitors, while patient-reported outcomes are assessed through psychometric evaluations.</p><p><strong>Conclusion: </strong>This work introduces a novel framework for the design of personalized DSS technology capable of tailoring the delivery mode of therapeutic insights to each user's preferences. By integrating psychobehavioral factors into algorithm design, this work seeks to advance the development of adaptive, user-centric technologies that can enhance both clinical outcomes and patient quality of life.</p>","PeriodicalId":15475,"journal":{"name":"Journal of Diabetes Science and Technology","volume":" ","pages":"1172-1182"},"PeriodicalIF":3.7,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144775561","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"User Perceptions of Behavioral Change Strategies in Diabetes Apps: Feedback From Online Support Groups.","authors":"Eirik Årsand, Elia Gabarron, Pietro Randine","doi":"10.1177/19322968251343918","DOIUrl":"10.1177/19322968251343918","url":null,"abstract":"<p><strong>Background: </strong>Behavioral change strategies are used in mobile health applications to help individuals manage chronic conditions like diabetes. However, there is limited research on user preferences and perceptions regarding these strategies in the context of diabetes management apps. This study aimed to investigate the preferences of individuals with diabetes and their relatives concerning behavioral intervention functions used in mobile health apps to enhance the design and effectiveness of future applications.</p><p><strong>Methods: </strong>An online survey was conducted to gather sociodemographic information, details about diabetes diagnoses, and the target group's preferences for the use of nine main behavioral change strategies, possible to include in mobile health apps. Participants were asked to rate their agreement with specific statements related to each of the nine strategies on a three-point scale: \"Agree,\" \"Don't know,\" or \"Disagree.\" Recruitment efforts targeted 12 diabetes support groups on Facebook.</p><p><strong>Results: </strong>A total of 107 responses were received, all from Norwegian Facebook groups. The most valued behavior intervention function for diabetes apps was enablement, where 85% of the respondents wanted app functions based on this. Second, environmental restructuring received 70.1% votes, followed by incentivization and training, with 68.2% and 67.3%, respectively.</p><p><strong>Conclusions: </strong>We identified that the users in this survey preferred more, and other behavior change strategies that were identified were used in a recent review. We conclude that more awareness is needed among app developers of preferences among end users.</p>","PeriodicalId":15475,"journal":{"name":"Journal of Diabetes Science and Technology","volume":" ","pages":"1239-1246"},"PeriodicalIF":3.7,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12104217/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144142750","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":"Assessment of Glycemic Control Using Continuous Glucose Monitoring During Hospitalization and After Discharge for Older Adults.","authors":"Sriya Kantipudi, Thaer Idrees, Iris Castro-Revoredo, Priya Vellanki, Eduard Castejon-Rosales, Kenneth Petty, Limin Peng, Guillermo E Umpierrez","doi":"10.1177/19322968251332656","DOIUrl":"10.1177/19322968251332656","url":null,"abstract":"","PeriodicalId":15475,"journal":{"name":"Journal of Diabetes Science and Technology","volume":" ","pages":"1427-1428"},"PeriodicalIF":3.7,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11993542/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144021010","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":"Glycemic Fluctuations in Healthy Pediatric Residents During 24-Hr Emergency Shifts: A Hidden Metabolic Risk for Health Care Workers.","authors":"Anastasia Proimou, Georgia Sotiriou, Paraskevi Panagopoulou, Zoi Tsimtsiou, Athanasios Christoforidis","doi":"10.1177/19322968251352554","DOIUrl":"10.1177/19322968251352554","url":null,"abstract":"","PeriodicalId":15475,"journal":{"name":"Journal of Diabetes Science and Technology","volume":" ","pages":"1421-1422"},"PeriodicalIF":3.7,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12206223/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144528211","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":"Benefits of Usability Evaluation in the Development Process of Diabetes Technologies Using the Example of a Continuous Glucose Monitoring System Prototype.","authors":"Anne Beltzer, Julia Kölle, Marta Gil Miró, Stefan Pleus, Collin Krauss, Cornelia Haug, Elvis Safary, Beatrice Vetter, Guido Freckmann","doi":"10.1177/19322968241238146","DOIUrl":"10.1177/19322968241238146","url":null,"abstract":"<p><strong>Background: </strong>Usability engineering analyzes the interaction between the intended users and a device. Its implementation is mandatory for manufacturers to obtain regulatory approval for the European market. The aim of this evaluation was assessing the role of usability testing in the development process. For this purpose, a continuous glucose monitoring (CGM) device under development was investigated to determine whether it could be used safely and effectively by the intended users.</p><p><strong>Methods: </strong>Conduct of the usability testing was based on the international standard IEC 62366-1. Medical device use of CGM-experienced and non-experienced users (n = 15 each) was observed without initial training in use scenarios containing 18 tasks. The success rate of task completion was determined and the System Usability Scale (SUS) score was calculated from a questionnaire. A prototype of the FiberSense CGM System (EyeSense GmbH, Großostheim, Germany), comprising of a single-use sensor and a reusable detector, was investigated.</p><p><strong>Results: </strong>Most use errors made by both user groups were related to ease of handling of the reusable detectors. The SUS scores achieved in this study were below the pre-defined SUS score acceptance criterion of ≥68. The most frequently mentioned reason for use errors was an incomprehensible and non-chronological instructions for use (IFU).</p><p><strong>Conclusions: </strong>The evaluation provides valuable insights on how to improve usability of the prototype device and demonstrates the value of conducting structured usability testing prior to product finalization. The results reflected areas for improvement of the user interface, mainly by restructuring the IFU, provision of an additional leaflet, and device training prior to use.</p>","PeriodicalId":15475,"journal":{"name":"Journal of Diabetes Science and Technology","volume":" ","pages":"1293-1301"},"PeriodicalIF":3.7,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11572192/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140110413","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}