JMIR Diabetes最新文献

{"title":"Toward a Clinically Actionable, Electronic Health Record-Based Machine Learning Model to Forecast 90-Day Change in Hemoglobin A_1c in Youth With Type 1 Diabetes: Feasibility and Model Development Study.","authors":"Erin M Tallon, David D Williams, Cintya Schweisberger, Colin Mullaney, Brent Lockee, Diana Ferro, Craig A Vandervelden, Mitchell S Barnes, Angelica Cristello Sarteau, Anna R Kahkoska, Susana R Patton, Sanjeev Mehta, Ryan McDonough, Marcus Lind, Leonard D'Avolio, Mark A Clements","doi":"10.2196/69142","DOIUrl":"10.2196/69142","url":null,"abstract":"<p><strong>Background: </strong>Clinicians currently lack an effective means for identifying youth with type 1 diabetes (T1D) who are at risk for experiencing glycemic deterioration between diabetes clinic visits. As a result, their ability to identify youth who may optimally benefit from targeted interventions designed to address rising glycemic levels is limited. Although electronic health records (EHR)-based risk predictions have been used to forecast health outcomes in T1D, no study has investigated the potential for using EHR data to identify youth with T1D who will experience a clinically significant rise in glycated hemoglobin (HbA1c) ≥0.3% (approximately 3 mmol/mol) between diabetes clinic visits.</p><p><strong>Objective: </strong>We aimed to evaluate the feasibility of using routinely collected EHR data to develop a machine learning model to predict 90-day unit-change in HbA1c (in % units) in youth (aged 9-18 y) with T1D. We assessed our model's ability to augment clinical decision-making by identifying a percent change cut point that optimized identification of youth who would experience a clinically significant rise in HbA1c.</p><p><strong>Methods: </strong>From a cohort of 2757 youth with T1D who received care from a network of pediatric diabetes clinics in the Midwestern United States (January 2012-August 2017), we identified 1743 youth with 9643 HbA1c observation windows (ie, 2 HbA1c measurements separated by 70-110 d, approximating the 90-day time interval between routine diabetes clinic visits). We used up to 5 years of youths' longitudinal EHR data to transform 17,466 features (demographics, laboratory results, vital signs, anthropometric measures, medications, diagnosis codes, procedure codes, and free-text data) for model training. We performed 3-fold cross-validation to train random forest regression models to predict 90-day unit-change in HbA1c(%).</p><p><strong>Results: </strong>Across all 3 folds of our cross-validation model, the average root-mean-square error was 0.88 (95% CI 0.85-0.90). Predicted HbA1c(%) strongly correlated with true HbA1c(%) (r=0.79; 95% CI 0.78-0.80). The top 10 features impacting model predictions included postal code, various metrics related to HbA1c, and the frequency of a diagnosis code indicating difficulty with treatment engagement. At a clinically significant percent rise threshold of ≥0.3% (approximately 3 mmol/mol), our model's positive predictive value was 60.3%, indicating a 1.5-fold enrichment (relative to the observed frequency that youth experienced this outcome [3928/9643, 40.7%]). Model sensitivity and positive predictive value improved when thresholds for clinical significance included smaller changes in HbA1c, whereas specificity and negative predictive value improved when thresholds required larger changes in HbA1c.</p><p><strong>Conclusions: </strong>Routinely collected EHR data can be used to create an ML model for predicting unit-change in HbA1c between diabetes clinic visits amo","PeriodicalId":52371,"journal":{"name":"JMIR Diabetes","volume":"10 ","pages":"e69142"},"PeriodicalIF":2.6,"publicationDate":"2025-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12463387/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145151962","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":"Digital Innovation and Integrated Care in People With Diabetes in Western Sydney: Retrospective Cohort Study.","authors":"Ummul Mahfuza, Gideon Meyerowitz-Katz, Riham Abdulla Rasheed, Helen Dick, Glen Maberly, Rajini Jayaballa","doi":"10.2196/64832","DOIUrl":"10.2196/64832","url":null,"abstract":"<p><strong>Background: </strong>The COVID-19 pandemic catalyzed the adoption of digital technologies in health care. This study assesses a digital-first integrated care model for type 2 diabetes management in Western Sydney, using continuous glucose monitoring (CGM) and virtual Diabetes Case Conferences (DCC) involving the patient, general practitioner (GP), diabetes specialist, and diabetes educator at the same time.</p><p><strong>Objective: </strong>This study aims to assess the effectiveness of the innovative diabetes clinics in Western Sydney.</p><p><strong>Methods: </strong>In 2020, a total of 833 new patients with type 2 diabetes were seen at Western Sydney Diabetes (WSD) clinics. An early cohort of 103 patients was evaluated before and after participation in virtual DCC, incorporating CGM data analysis, digital educational resources, and remote consultations with a diabetes multidisciplinary team. Assessments were conducted at baseline and 3-4 months post DCC.</p><p><strong>Results: </strong>The integration of CGM and virtual consultations significantly improved glycemic control. Hemoglobin A_1c (HbA_1c) levels decreased notably from 9.6% to 8.2% (average reduction of 1.4%; 95% CI 1.03-1.82; P<.001). Time in range (TIR) as measured by CGM increased substantially from 46% to 73% (95% CI 20-32; P<.001), and the glucose management indicator (GMI) improved from 7.9% to 7% (average reduction of 0.9%; 95% CI 0.55-1.2; P<.001). Despite no significant change in the total daily insulin dose, the proportion of patients on insulin therapy rose from 27% to 39% (P<.001), indicating more targeted and effective diabetes management.</p><p><strong>Conclusions: </strong>Our findings demonstrate the effectiveness of a digitally enabled integrated care model in managing type 2 diabetes. The use of CGM technology, complemented by virtual DCCs and digital educational tools, not only facilitated better disease management and patient engagement but also empowered primary care providers with advanced management capabilities. This digital approach addresses traditional barriers in diabetes care, highlighting the potential for scalable, technology-driven solutions in chronic disease management.</p>","PeriodicalId":52371,"journal":{"name":"JMIR Diabetes","volume":"10 ","pages":"e64832"},"PeriodicalIF":2.6,"publicationDate":"2025-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12466306/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145042158","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 innovative insulin dose self-titration toolkit for adults living with type 2 diabetes mellitus.","authors":"Nadin Abbas, Heather Lochnan, Sandhya Goge, Annie Garon-Mailer, Cathy J Sun","doi":"10.2196/75903","DOIUrl":"10.2196/75903","url":null,"abstract":"<p><strong>Unstructured: </strong>To encourage insulin dose self-titration by adults living with type 2 diabetes, we developed an innovative bilingual toolkit comprised of a personalized action plan and educational videos.</p>","PeriodicalId":52371,"journal":{"name":"JMIR Diabetes","volume":" ","pages":""},"PeriodicalIF":2.6,"publicationDate":"2025-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145440001","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":"The Role of Community Health Workers in Improving Diabetes Device Use Among Youth With Type 1 Diabetes: A Web-Based Qualitative Study Using Human-Centered Design With Clinicians.","authors":"Charlotte Wang Chen, Alexa Jacqueline Durante, Margaret Grace Maynard, Marina Reznik, Lori Laffel, Shivani Agarwal","doi":"10.2196/76387","DOIUrl":"10.2196/76387","url":null,"abstract":"<p><strong>Background: </strong>Inequity in diabetes technology use persists among Black and Hispanic youth with type 1 diabetes (T1D). Community health workers (CHWs) can address social and clinical barriers to diabetes device use. However, more information is needed on clinicians' perceptions to inform the development of a CHW model for youth with T1D.</p><p><strong>Objective: </strong>This study aimed to identify barriers to diabetes technology use and cocreate solutions in collaboration with diabetes and school-based clinicians serving Black and Hispanic youth with T1D.</p><p><strong>Methods: </strong>Using human-centered design, the study team conducted 2-hour web-based workshops with clinicians from a diabetes clinic or school-based clinics at a safety net hospital in the Bronx, New York. The workshops promoted active ideation of barriers and co-design of a CHW intervention prototype to address self-reported challenges. Workshops were analyzed using a qualitative inductive approach.</p><p><strong>Results: </strong>A total of 17 participants completed the human-centered design workshops and surveys. Of these, 11 (65%) were clinicians from the diabetes clinic and 6 (35%) were school-based clinicians from elementary, middle, and high schools in the Bronx. A total of 4 workshops were conducted. The perceived diabetes device barriers for youth with T1D and their families by participants were general health-related social needs (HRSNs) and diabetes technology-specific HRSNs that interfered with technology uptake, such as housing and financial insecurity, as well as digital social needs; and difficulty navigating health care systems, insurance, and pharmacy benefits due to the high level of care coordination required by caregivers. In addition, the participants identified barriers that interfered with their ability to support youth with T1D with diabetes technology, such as limited support for using diabetes technology in school and lack of time and technology support to troubleshoot problems in diabetes clinics. Ways in which a CHW could help mitigate these barriers include (1) identifying and addressing HRSNs by directing patients to appropriate resources; (2) providing peer support for caregivers to navigate diabetes device logistics; (3) acting as a school liaison to improve communication and coordination between caregivers, schools, and diabetes clinicians; and (4) offering administrative support to offload the logistical burden of clinicians.</p><p><strong>Conclusions: </strong>Important needs related to specialized technology support, enhanced care coordination, family-clinician communication, and administrative task shifting were identified by clinicians to inform a CHW model for youth with T1D. Continued co-design and pilot testing are needed to refine the model.</p>","PeriodicalId":52371,"journal":{"name":"JMIR Diabetes","volume":"10 ","pages":"e76387"},"PeriodicalIF":2.9,"publicationDate":"2025-08-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12426574/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144978091","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":"Assessing the Clinical Feasibility of the DiaFocus System for Integrated Personalized Management of Type 2 Diabetes: 6-Month Pilot Cohort Study.","authors":"Nanna Lind, Per Bækgaard, Jakob E Bardram, Claus Cramer-Petersen, Kirsten Nørgaard, Merete B Christensen","doi":"10.2196/63894","DOIUrl":"10.2196/63894","url":null,"abstract":"&lt;p&gt;&lt;strong&gt;Background: &lt;/strong&gt;Type 2 diabetes (T2D) is a complex, chronic condition that requires ongoing management. An important aspect of effective diabetes management is shared decision-making between the person with diabetes and the health care professionals (HCPs) to tailor individual treatment plans. Personal health technologies can play a crucial role in this collaborative effort by providing tools for monitoring, communication, and education.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Objective: &lt;/strong&gt;This study aims to test the clinical feasibility of DiaFocus, a mobile health system developed for adults with T2D.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Methods: &lt;/strong&gt;This was a single-arm, prospective, 6-month pilot study in a clinical outpatient setting at Steno Diabetes Center Copenhagen, Denmark. The DiaFocus system includes an app for the participants and a web portal for the HCPs. The system collects diabetes-related data, including participant-reported lifestyle surveys, sensor-based measures on physical activity, and participant-selected focus areas, aiming to support communication and shared decision-making at clinical visits. Participants were eligible if they were ≥18 years old, diagnosed with T2D≥12 months, spoke Danish, and had a smartphone (iOS 13+ or Android 8.0+). For each participant, 3 visits and 1 telephone call were scheduled during the 6-month study period. The DiaFocus system's acceptability and feasibility were assessed through retention rates, app usage, participant feedback, and by the CACHET Unified Method for Assessment of Clinical Feasibility (CUMACF) questionnaire. The clinical outcomes were assessed by the following questionnaires: Diabetes Distress Scale (DDS), Perceived Competence for Diabetes (PCDS), Diabetes Treatment Satisfaction Questionnaire (DTSQs+c), hemoglobin A1c levels, and body weight.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Results: &lt;/strong&gt;A total of 17 participants with T2D were included in the study, 15 completed the study, and data were analyzed on an intention-to-treat basis. The median age was 68 (IQR 56-72) years, 12 (71%) were males, the median diabetes duration was 18 (IQR 11-21) years, and the median hemoglobin A1c was 59 (IQR 49-68) mmol/mol. Participants found the DiaFocus system feasible to support diabetes management despite technical problems, and they valued the ability to set focus areas. The most common focus areas were \"blood glucose\" (n=10, 59%) and \"exercise\" (n=9, 53%), but areas such as \"sleep\" and \"mood\" were also used. The CUMACF questionnaire showed that 90% (9/10) of the participants had very favorable views of how easy the system is to understand, learn, and use, and 80% (8/10) of the participants agreed or strongly agreed that the system was useful. Feedback was generally positive, indicating participants would use a refined version. Despite these findings, no statistically significant changes in clinical outcomes were observed throughout the study period using the DiaFocus system.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Conclusions: &lt;/strong&gt;This pilot study d","PeriodicalId":52371,"journal":{"name":"JMIR Diabetes","volume":"10 ","pages":"e63894"},"PeriodicalIF":2.6,"publicationDate":"2025-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12377514/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144978122","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 Novel Mobile Health App to Educate and Empower Young Adults With Type 1 Diabetes to Exercise Safely: Prospective Single-Arm Pre-Post Noninferiority Clinical Trial.","authors":"Vinutha Beliyurguthu Shetty, Rachel Lim, Shaun Teo, Wayne H K Soon, Heather C Roby, Alison G Roberts, Grant J Smith, Paul A Fournier, Timothy W Jones, Elizabeth A Davis","doi":"10.2196/68694","DOIUrl":"10.2196/68694","url":null,"abstract":"<p><strong>Background: </strong>A novel mobile health (mHealth) app \"acT1ve,\" developed using a co-design model, provides real-time support during exercise for young people with type 1 diabetes (T1D).</p><p><strong>Objective: </strong>This study aimed to demonstrate the noninferiority of acT1ve compared with \"treatment as usual\" with regard to hypoglycemic events.</p><p><strong>Methods: </strong>Thirty-nine participants living with T1D (age: 17.2, SD 3.3 years; HbA1c: 64, SD 6.0 mmol/mol) completed a 12-week single-arm, pre-post noninferiority study with a follow-up qualitative component. During the intervention, continuous glucose monitoring (CGM) and physical activity were monitored while participants used acT1ve to manage exercise. CGM data were used to assess the number of hypoglycemic events (<3.9 mmol/L for ≥15 minutes) in each phase. Using a mixed effects negative binomial regression, the difference in the rates of hypoglycemia between the preapp and app-use phases was analyzed. Participants completed both a semistructured interview and the user Mobile Application Rating Scale (uMARS) questionnaire postintervention. All interviews were audio-recorded for transcription, and a deductive content analysis approach was used to analyze the participant interviews. The uMARS Likert scores for each subscale (engagement, functionality, esthetics, and information) were calculated and reported as medians with IQRs.</p><p><strong>Results: </strong>The rates of hypoglycemia were similar for both the preapp and app-use phases (0.79 and 0.83 hypoglycemia events per day, respectively). The upper bound of the CI of the hypoglycemia rate ratio met the prespecified criteria for noninferiority (rate ratio=1.06; 95% CI 0.91-1.22). The uMARS analysis showed a high rating (≥4 out of 5) of acT1ve by 80% of participants for both functionality and information, 72% for esthetics, and 63% for overall uMARS rating. Content analysis of the interview transcripts identified 3 main themes: \"Provision of information,\" \"Exercising with the App,\" and \"Targeted Population.\"</p><p><strong>Conclusions: </strong>The mHealth app \"acT1ve,\" which was developed in collaboration with young people with T1D, is functional, acceptable, and safe for diabetes management around exercise. The study supports the noninferiority of acT1ve compared with \"treatment as usual\" with regards to hypoglycemic events.</p>","PeriodicalId":52371,"journal":{"name":"JMIR Diabetes","volume":"10 ","pages":"e68694"},"PeriodicalIF":2.6,"publicationDate":"2025-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12373410/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144978079","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":"Insulin injection technique education and associated factors of knowledge: A cross-sectional survey on knowledge and practice of insulin injection technique education among physicians in Indonesia.","authors":"Ida Ayu Made Kshanti, Nadya Magfira, Anak Agung Arie Widyastuti, Jerry Nasarudin, Marina Epriliawati, Md Ikhsan Mokoagow","doi":"10.2196/65359","DOIUrl":"10.2196/65359","url":null,"abstract":"<p><strong>Background: </strong>Insulin therapy is crucial for type 2 diabetes mellitus management, with increasing usage in Indonesia, and its effectiveness is well-established. However, prescribing insulin poses various challenges that can impact the effectiveness of insulin. Patient education is crucial for the successful implementation of insulin therapy. Proper insulin use remains insufficient in Indonesia.</p><p><strong>Objective: </strong>This study seeks to investigate physicians' knowledge and practice in providing education on insulin use to type 2 diabetes mellitus patients in Indonesia.</p><p><strong>Methods: </strong>This study recruited potential participants (all physicians in Indonesia) through the Internet using a convenience sampling method. The participants were asked to fill out a questionnaire. The questionnaire had 32 questions divided into 4 sections, comprising demographics and clinical practice, practice of insulin education, Indonesian insulin injection technique guideline, and knowledge of insulin injection technique. The instrument used in this study was developed based on the Pedoman Teknik Menyuntik Insulin Indonesia (PTMII), which was adapted from the international consensus by the Forum for Injection Technique and Therapy Expert Recommendations (FITTER). The survey lasted from February to March 2021. Data was analysed using Kruskal-Wallis tests.</p><p><strong>Results: </strong>A total of 823 participants were included in the analysis. A total of 680 out of 823 participants (82.6%) had given insulin education to patients at least once during the last 30 days. However, only 479 out of 823 participants (58.2%) used specific guidelines in their practice, with only 280 out of 823 participants (34.0%) aware of the Indonesian guidelines. Eight hundred and fifteen out of 823 participants (99.0%) agreed that insulin injection techniques would affect clinical results. The median score of knowledge about insulin injection techniques was 7 (interquartile range 2) among the study participants, indicating good knowledge. The profession was the only statistically significant variable associated with knowledge scores, with the highest median score held by consultants in endocrinology, metabolism & diabetes, and the lowest by other doctors (P <.001).</p><p><strong>Conclusions: </strong>Most physicians in this study had given education to their patients. However, there was still a gap between the guidelines and the practice of insulin education, as shown by the lack of awareness and a fair level of knowledge about the Indonesian guidelines.</p><p><strong>Clinicaltrial: </strong></p>","PeriodicalId":52371,"journal":{"name":"JMIR Diabetes","volume":" ","pages":""},"PeriodicalIF":2.6,"publicationDate":"2025-08-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145001932","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":"Exploring Desired Features of Mobile Health Apps for Patients With Diabetes to Enhance Engagement and Self-Management: Qualitative Study.","authors":"Arkers Kwan Ching Wong, Ying Nan, Bing Xiang Yang, Yanqun Liu","doi":"10.2196/69176","DOIUrl":"10.2196/69176","url":null,"abstract":"<p><strong>Background: </strong>Diabetes mellitus (DM) is a chronic condition requiring effective self-management to maintain glycemic control and prevent complications. Mobile health (mHealth) apps offer potential solutions by providing real-time monitoring, personalized feedback, and educational resources. However, their long-term adoption is hindered by a lack of user involvement in the development process and insufficient cultural adaptation. This study aims to explore the perspectives of patients with DM in Hong Kong on the functionalities and features of mHealth apps, highlighting the importance of tailoring these apps to meet local cultural needs.</p><p><strong>Objective: </strong>The objective of this study is to understand the views of patients with DM on the development of mHealth apps and the demand for app functions in order to provide a basis for the development of DM prevention apps.</p><p><strong>Methods: </strong>This descriptive qualitative study conducted semi-structured interviews with 10 patients with DM attending a District Health Centre in Hong Kong in May 2024, using a purposive sampling strategy. The transcribed data were analyzed by the inductive content analytical method, and themes were extracted with the aid of NVivo (version 15.0; QSR International) software.</p><p><strong>Results: </strong>In total, 7 key themes were identified: accurate information resources, automatic tracking and monitoring of health metrics, reminders, personalized customization options, intuitive usability, efficient data-sharing capabilities, and interactive design. Additionally, the study emphasizes the importance of cultural adaptation and the potential of artificial intelligence-enabled mHealth apps to enhance personalized information delivery. Ensuring the credibility and professionalism of information sources is also essential.</p><p><strong>Conclusions: </strong>The results provide valuable insights for enhancing the self-management capabilities of patients with DM and inform the future development of mHealth apps focused on DM prevention.</p>","PeriodicalId":52371,"journal":{"name":"JMIR Diabetes","volume":"10 ","pages":"e69176"},"PeriodicalIF":2.6,"publicationDate":"2025-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12352858/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144857021","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":"Development of a Smartphone App for Women Living With Gestational Diabetes Mellitus: Qualitative Study.","authors":"Catherine Knight-Agarwal, Mary Bushell, Mary-Ellen Hooper, Natasha JoJo, Marjorie Atchan, Alison Shield, Angela Douglas, Abu Saleh, Masoud Mohammadian, Irfan Khan, Cheuk Chan, Nico Rovira Iturrieta, Emily Murphy, Tanishta Arza, Deborah Davis","doi":"10.2196/65328","DOIUrl":"10.2196/65328","url":null,"abstract":"<p><strong>Background: </strong>Gestational diabetes mellitus (GDM), a type of blood glucose intolerance or hyperglycemia that occurs during pregnancy, is a common condition increasing in prevalence both globally and in Australia. Mobile health apps have been shown to be a useful resource for women with type 1 diabetes and could successfully contribute to GDM management by facilitating healthy behaviors.</p><p><strong>Objective: </strong>This study aimed to seek the perspectives of health care consumers (HCCs) and health professionals (HPs) regarding the development of a smartphone app for women living with GDM.</p><p><strong>Methods: </strong>A co-design process with 4 distinct phases underpinned the development of SugarMumma. Phase 1 involved a nonsystematic literature search followed by the creation of an app functions wish list. In phase 2, semistructured interviews with HCCs and HPs were undertaken and then thematically analyzed. In phase 3, a prototype was designed based on social cognitive theory and stakeholder recommendations. Agile project management methodology was used, followed by \"user acceptance testing.\" During phase 4, a second round of individual interviews was undertaken with HCCs and HPs. The same qualitative methods outlined in phase 2 were used.</p><p><strong>Results: </strong>In phase 2, individual and didactic interviews were undertaken with HCCs (n=2) and HPs (n=6). Two overarching themes encompassing recommendations for app development emerged: (1) functionality and (2) individualized care. SugarMumma was created in phase 3. Phase 4 involved a second round of individual interviews with HCCs (n=1) and HPs (n=5), resulting in the final theme (3) future directions.</p><p><strong>Conclusions: </strong>With increasing numbers of people using smartphones, mobile health apps can help manage chronic conditions such as GDM. SugarMumma was designed following extensive stakeholder input. Good functionality, regular notifications, appealing visual aids, positive feedback, relevant dietary advice, and exporting information to HPs are important features to include.</p>","PeriodicalId":52371,"journal":{"name":"JMIR Diabetes","volume":"10 ","pages":"e65328"},"PeriodicalIF":2.6,"publicationDate":"2025-08-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12338752/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144823178","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 Nurse-Led Telemonitoring Approach in Diabetes During the COVID-19 Pandemic: Prospective Cohort Study.","authors":"Stephanie A Noonan, Amanda L Gauld, Maria I Constantino, Margaret J McGill, Timothy L Middleton, Ian D Caterson, Luigi N Fontana, Stephen M Twigg, Ted Wu, Raaj Kishore Biswas, Jencia Wong","doi":"10.2196/68214","DOIUrl":"10.2196/68214","url":null,"abstract":"<p><strong>Background: </strong>The utility of a nurse-led telemonitoring approach (NLTA) is yet to be firmly established in diabetes management.</p><p><strong>Objective: </strong>This study aims to examine the effect of a 12-month proactive NLTA on metabolic and psychological health indices in individuals with diabetes during the COVID-19 pandemic, and to evaluate it as a new diabetes model of care.</p><p><strong>Methods: </strong>The telemonitoring study group (TSG; n=91) comprised adults who had attended an Australian tertiary hospital diabetes center between January 2019 and March 2020. Telehealth surveillance contact with a diabetes nurse educator was subsequently maintained at approximately 3-month intervals over 12 months. Prospective surveillance measures included glycated hemoglobin A1c (HbA1c%), weight, adherence to healthy behaviors, and patient-reported outcomes of diabetes distress, anxiety, and depression using validated instruments. Metabolic changes were compared retrospectively with a comparison group who had not received telemonitoring contact during the study period (non-TSG; n=115).</p><p><strong>Results: </strong>The average participant age was 57.2 (SD 15) years; 63% (129/206) were male, 48% (99/206) had type 1 diabetes, 50% (104/206) had type 2 diabetes, and the mean HbA1c% was 8.1% (SD 1.4%). At the end of the 12-month study, the relative percentage reduction in unadjusted HbA1c% for the TSG cohort was significantly greater than that observed in the non-TSG cohort (4% vs 1%; P=.04). Following adjustment for baseline HbA1c%, a significant improvement in HbA1c% was observed in the TSG (P=.048) but not in the non-TSG (P=.61). TSG participants were 40% less likely (odds ratio 0.6, 95% CI 0.5-0.7) to experience an unfavorable rise in HbA1c% compared to non-TSG participants, after adjusting for sex, age, prepandemic HbA1c%, ethnicity, diabetes type, and diabetes duration. The NLTA facilitated assessments of psychological risk, with elevated depression, anxiety and diabetes distress scores significantly increased in women and youth <30 years of age (P<.001). Increasing anxiety measures were observed in those with high baseline anxiety scores (P<.001).</p><p><strong>Conclusions: </strong>A proactive diabetes NLTA is feasible with positive effects on glycemia and the potential to identify those at psychological risk for targeted intervention. In the context of increasing demand for diabetes-related resources, further study of an NLTA model of care is warranted.</p>","PeriodicalId":52371,"journal":{"name":"JMIR Diabetes","volume":"10 ","pages":"e68214"},"PeriodicalIF":2.6,"publicationDate":"2025-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12334113/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144805314","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}