JMIR DiabetesPub Date : 2022-11-18DOI: 10.2196/38869
Elena Toschi, Christine Slyne, Katie Weinger, Sarah Sy, Kayla Sifre, Amy Michals, DaiQuann Davis, Rachel Dewar, Astrid Atakov-Castillo, Saira Haque, Stirling Cummings, Stephen Brown, Medha Munshi
{"title":"Use of Telecommunication and Diabetes-Related Technologies in Older Adults With Type 1 Diabetes During a Time of Sudden Isolation: Mixed Methods Study.","authors":"Elena Toschi, Christine Slyne, Katie Weinger, Sarah Sy, Kayla Sifre, Amy Michals, DaiQuann Davis, Rachel Dewar, Astrid Atakov-Castillo, Saira Haque, Stirling Cummings, Stephen Brown, Medha Munshi","doi":"10.2196/38869","DOIUrl":"https://doi.org/10.2196/38869","url":null,"abstract":"<p><strong>Background: </strong>The COVID-19 lockdown imposed a sudden change in lifestyle with self-isolation and a rapid shift to the use of technology to maintain clinical care and social connections.</p><p><strong>Objective: </strong>In this mixed methods study, we explored the impact of isolation during the lockdown on the use of technology in older adults with type 1 diabetes (T1D).</p><p><strong>Methods: </strong>Older adults (aged ≥65 years) with T1D using continuous glucose monitoring (CGM) participated in semistructured interviews during the COVID-19 lockdown. A multidisciplinary team coded the interviews. In addition, CGM metrics from a subgroup of participants were collected before and during the lockdown.</p><p><strong>Results: </strong>We evaluated 34 participants (mean age 71, SD 5 years). Three themes related to technology use emerged from the thematic analysis regarding the impact of isolation on (1) insulin pump and CGM use to manage diabetes, including timely access to supplies, and changing Medicare eligibility regulations; (2) technology use for social interaction; and (3) telehealth use to maintain medical care. The CGM data from a subgroup (19/34, 56%; mean age 74, SD 5 years) showed an increase in time in range (mean 57%, SD 17% vs mean 63%, SD 15%; P=.001), a decrease in hyperglycemia (>180 mg/dL; mean 41%, SD 19% vs mean 35%, SD 17%; P<.001), and no change in hypoglycemia (<70 mg/dL; median 0.7%, IQR 0%-2% vs median 1.1%, IQR 0%-4%; P=.40) during the lockdown compared to before the lockdown.</p><p><strong>Conclusions: </strong>These findings show that our cohort of older adults successfully used technology during isolation. Participants provided the positive and negative perceptions of technology use. Clinicians can benefit from our findings by identifying barriers to technology use during times of isolation and developing strategies to overcome these barriers.</p>","PeriodicalId":52371,"journal":{"name":"JMIR Diabetes","volume":"7 4","pages":"e38869"},"PeriodicalIF":0.0,"publicationDate":"2022-11-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9678329/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9150189","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":"Analyzing User Engagement Within a Patient-Reported Outcomes Texting Tool for Diabetes Management: Engagement Phenotype Study.","authors":"Soumik Mandal, Hayley M Belli, Jocelyn Cruz, Devin Mann, Antoinette Schoenthaler","doi":"10.2196/41140","DOIUrl":"https://doi.org/10.2196/41140","url":null,"abstract":"<p><strong>Background: </strong>Patient-reported outcomes (PROs) capture patients' views on their health conditions and its management, and are increasingly used in clinical trials, including those targeting type 2 diabetes (T2D). Mobile health (mHealth) tools offer novel solutions for collecting PRO data in real time. Although patients are at the center of any PRO-based intervention, few studies have examined user engagement with PRO mHealth tools.</p><p><strong>Objective: </strong>This study aimed to evaluate user engagement with a PRO mHealth tool for T2D management, identify patterns of user engagement and similarities and differences between the patients, and identify the characteristics of patients who are likely to drop out or be less engaged with a PRO mHealth tool.</p><p><strong>Methods: </strong>We extracted user engagement data from an ongoing clinical trial that tested the efficacy of a PRO mHealth tool designed to improve hemoglobin A1c levels in patients with uncontrolled T2D. To date, 61 patients have been randomized to the intervention, where they are sent 6 PRO text messages a day that are relevant to T2D self-management (healthy eating and medication adherence) over the 12-month study. To analyze user engagement, we first compared the response rate (RR) and response time between patients who completed the 12-month intervention and those who dropped out early (noncompleters). Next, we leveraged latent class trajectory modeling to classify patients from the completer group into 3 subgroups based on similarity in the longitudinal engagement data. Finally, we investigated the differences between the subgroups of completers from various cross-sections (time of the day and day of the week) and PRO types. We also explored the patient demographics and their distribution among the subgroups.</p><p><strong>Results: </strong>Overall, 19 noncompleters had a lower RR to PRO questions and took longer to respond to PRO questions than 42 completers. Among completers, the longitudinal RRs demonstrated differences in engagement patterns over time. The completers with the lowest engagement showed peak engagement during month 5, almost at the midstage of the program. The remaining subgroups showed peak engagement at the beginning of the intervention, followed by either a steady decline or sustained high engagement. Comparisons of the demographic characteristics showed significant differences between the high engaged and low engaged subgroups. The high engaged completers were predominantly older, of Hispanic descent, bilingual, and had a graduate degree. In comparison, the low engaged subgroup was composed mostly of African American patients who reported the lowest annual income, with one of every 3 patients earning less than US $20,000 annually.</p><p><strong>Conclusions: </strong>There are discernible engagement phenotypes based on individual PRO responses, and their patterns vary in the timing of peak engagement and demographics. Future studies c","PeriodicalId":52371,"journal":{"name":"JMIR Diabetes","volume":" ","pages":"e41140"},"PeriodicalIF":0.0,"publicationDate":"2022-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9706388/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"40684905","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}
JMIR DiabetesPub Date : 2022-10-31DOI: 10.2196/41401
Rajeev Chawla, Shalini Jaggi, Amit Gupta, Ganapathi Bantwal, Suhas Patil
{"title":"Clinical Utility of a Digital Therapeutic Intervention in Indian Patients With Type 2 Diabetes Mellitus: 12-Week Prospective Single-Arm Intervention Study.","authors":"Rajeev Chawla, Shalini Jaggi, Amit Gupta, Ganapathi Bantwal, Suhas Patil","doi":"10.2196/41401","DOIUrl":"https://doi.org/10.2196/41401","url":null,"abstract":"<p><strong>Background: </strong>Patients with type 2 diabetes mellitus (T2DM) having elevated levels of blood glucose and glycated hemoglobin (HbA<sub>1c</sub>) are at higher risk of macro- and microvascular complications. Nonetheless, the goal of achieving glycemic control cannot be met with the use of pharmacotherapy alone. The recent emergence of digital therapeutic tools has shown the possibility of improving the modifiable risk factors and self-management of diabetes.</p><p><strong>Objective: </strong>The aim of this study was to examine the clinical utility of a digital therapeutic intervention as an add-on therapy to achieve glycemic control in patients with T2DM.</p><p><strong>Methods: </strong>This was a 12-week prospective, single-arm digital intervention study in patients with T2DM receiving regular antidiabetic treatment. The eligibility criteria included male and female patients with HbA<sub>1c</sub>≥6.5%, functional English literacy, and a mobile phone capable of running the intervention app. Outcome measures of the study were mean changes in HbA<sub>1c</sub>, fasting blood glucose (FBG), postprandial blood glucose (PPBG), BMI, and Homeostatic Model Assessment for Insulin Resistance (HOMA-IR) index at the end of 12 weeks.</p><p><strong>Results: </strong>A total of 128 participants completed the study period of 12 weeks. There were 54.7% (70/128) men and 45.3% (58/128) women with a mean age of 48.48 years (SD 10.27). At the end of 12 weeks, the mean change in HbA<sub>1c</sub>, FBG, PPBG, and BMI for the overall study population was -0.84% (P<.001), -8.39 mg/dl (P=.02), -14.97 mg/dl (P<.001), and -0.24 kg/m<sup>2</sup> (P=.06), respectively. Among the participants showing improvement in the HbA<sub>1c</sub> value at the end of 12 weeks (responders), the mean change in HbA<sub>1c</sub>, FBG, PPBG, and BMI was -1.24% (P<.001), -12.42 mg/dl (P=.003), -21.45 mg/dl (P<.001), and -0.34 kg/m<sup>2</sup> (P=.007), respectively. There was an increase in HOMA-IR values for the overall study population (0.54, P=.29). HbA<sub>1c</sub> response showed a significant association with a baseline HbA<sub>1c</sub> level ≥7.5%, no prior history of smoking, and no prior COVID-19 infection, as well as with higher levels of program engagement.</p><p><strong>Conclusions: </strong>A digital therapeutic intervention when used alongside standard medications significantly reduces HbA<sub>1c</sub>, FBG, and PPBG levels in patients with T2DM.</p>","PeriodicalId":52371,"journal":{"name":"JMIR Diabetes","volume":" ","pages":"e41401"},"PeriodicalIF":0.0,"publicationDate":"2022-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9664320/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"33502802","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}
JMIR DiabetesPub Date : 2022-10-24DOI: 10.2196/40326
Amy E Morrison, Kimberley Chong, Valerie Lai, Kate Farnsworth, Peter A Senior, Anna Lam
{"title":"Improved Glycemia and Quality of Life Among Loop Users: Analysis of Real-world Data From a Single Center.","authors":"Amy E Morrison, Kimberley Chong, Valerie Lai, Kate Farnsworth, Peter A Senior, Anna Lam","doi":"10.2196/40326","DOIUrl":"10.2196/40326","url":null,"abstract":"<p><strong>Background: </strong>Despite do-it-yourself automated insulin delivery being an unapproved method of insulin delivery, an increasing number of people with type 1 diabetes (T1D) worldwide are choosing to use Loop, a do-it-yourself automated insulin delivery system.</p><p><strong>Objective: </strong>In this study, we aimed to assess glycemic outcomes, safety, and the perceived impact on quality of life (QOL) in a local Edmonton cohort of known Loop users.</p><p><strong>Methods: </strong>An observational study of adults with T1D who used Loop was performed. An assessment of glycemic and safety outcomes, HbA<sub>1c</sub>, time in range, hospital admissions, and time below range compared users most recent 6 months of Loop use, with their prior regulatory approved insulin delivery method. QOL outcomes were assessed using Insulin Dosing Systems: Perceptions, Ideas, Reflections, and Expectations, diabetes impact, and device satisfaction measures (with maximum scores of 100, 10, and 10, respectively) and semistructured interviews.</p><p><strong>Results: </strong>The 24 adults with T1D who took part in this study 16 (67%) were female, with a median age of 33 (IQR 28-45) years, median duration of diabetes of 22 (IQR 17-32) years, median pre-Loop HbA<sub>1c</sub> of 7.9% (IQR 7.6%-8.3%), and a median duration of Loop use of 18 (IQR 12-25) months. During Loop use, the participants had median (IQR) values of 7.1% (6.5%-7.5%), 54 mmol (48-58) for HbA<sub>1c</sub> and 76.5% (64.6%-81.9%) for time in range, which were a significant improvement from prior therapy (P=.001 and P=.005), with a nonsignificant reduction in time below range; 3.0 to 3.9 mmol/L (P=.17) and <3 mmol/L (P=.53). Overall, 2 episodes of diabetic ketoacidosis occurred in a total of 470 months of Loop use, and no severe hypoglycemia occurred. The positive impact of Loop use on QOL was explored in qualitative analysis and additionally demonstrated through a median Insulin Dosing Systems: Perceptions, Ideas, Reflections, and Expectations score of 86 (IQR 79-95), a median diabetes impact score of 2.8 (IQR 2.1-3.9), and a median device satisfaction score of 9 (IQR 8.2-9.4).</p><p><strong>Conclusions: </strong>This local cohort of people with T1D demonstrated a beneficial effect of Loop use on both glycemic control and QOL, with no safety concerns being highlighted.</p>","PeriodicalId":52371,"journal":{"name":"JMIR Diabetes","volume":" ","pages":"e40326"},"PeriodicalIF":0.0,"publicationDate":"2022-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9641512/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"40585012","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}
JMIR DiabetesPub Date : 2022-10-05DOI: 10.2196/34650
Maya Allen-Taylor, Laura Ryan, Kirsty Winkley, Rebecca Upsher
{"title":"Exploring the Experiences and Perspectives of Insulin Therapy in Type 2 Diabetes via Web-Based UK Diabetes Health Forums: Qualitative Thematic Analysis of Threads.","authors":"Maya Allen-Taylor, Laura Ryan, Kirsty Winkley, Rebecca Upsher","doi":"10.2196/34650","DOIUrl":"https://doi.org/10.2196/34650","url":null,"abstract":"<p><strong>Background: </strong>Despite the advent of type 2 diabetes (T2D) remission strategies and novel therapeutic agents, many individuals with T2D will require insulin treatment to achieve target glycemia, with the aim of preventing or delaying diabetes complications. However, insulin refusal and cessation of treatment in this group are common, and their needs are underreported and relatively unexplored.</p><p><strong>Objective: </strong>This study aimed to explore the experiences and perspectives of individuals with T2D for whom insulin therapy is indicated as expressed on web-based health forums, in order to inform the development of evidence-based structured educational and support strategies and improve health care provider awareness.</p><p><strong>Methods: </strong>Retrospective archived forum threads from the 2 largest, freely and publicly accessible diabetes health forums in the United Kingdom were screened over a 12-month period (August 2019-2020). The Diabetes UK and Diabetes.co.uk forums were searched for relevant threads. A total of 3 independent researchers analyzed the forum threads and posts via thematic analysis. Pertinent themes were identified and illustrated by paraphrasing members' quotes to ensure anonymity. A total of 299 posts from 29 threads from Diabetes UK and 295 posts from 28 threads Diabetes.co.uk were analyzed over the study period. In all, 57 threads met the inclusion criteria and were included in the final analysis.</p><p><strong>Results: </strong>Four overarching themes were generated to illustrate the unmet needs that prompted members to seek information, advice, and support regarding insulin therapy outside of their usual care provision via the forums: empowerment through sharing self-management strategies, seeking and providing extended lifestyle advice, relationships with health care professionals, and a source of psychological peer support.</p><p><strong>Conclusions: </strong>This is the first study to collect data from web-based health forums to characterize the experiences and perspectives of people with T2D for whom insulin therapy is indicated. The observed naturalistic conversations have generated useful insights; our findings suggest that there are significant unmet self-management and psychological needs within this group that are not being met elsewhere, prompting the seeking of information and support on the web. These include practical aspects such as insulin injection technique, storage and dose titration, driving and travel considerations, the emerging use of technology, and a strong interest in the effects of extended lifestyle (diet and activity) approaches to support insulin therapy. In addition, problematic relationships with health care professionals appear to be a barrier to effective insulin therapy for some. In contrast, seeking and offering mutually beneficial, practical, and psychological support from peers was viewed as enabling. The study results will help to directly inform insul","PeriodicalId":52371,"journal":{"name":"JMIR Diabetes","volume":" ","pages":"e34650"},"PeriodicalIF":0.0,"publicationDate":"2022-10-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9582920/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"33488326","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}
JMIR DiabetesPub Date : 2022-10-03DOI: 10.2196/40377
Domingo Orozco-Beltrán, Cristóbal Morales, Sara Artola-Menéndez, Carlos Brotons, Sara Carrascosa, Cintia González, Óscar Baro, Alberto Aliaga, Karine Ferreira de Campos, María Villarejo, Carlos Hurtado, Carolina Álvarez-Ortega, Antón Gómez-García, Marta Cedenilla, Gonzalo Fernández
{"title":"Effects of a Digital Patient Empowerment and Communication Tool on Metabolic Control in People With Type 2 Diabetes: The DeMpower Multicenter Ambispective Study.","authors":"Domingo Orozco-Beltrán, Cristóbal Morales, Sara Artola-Menéndez, Carlos Brotons, Sara Carrascosa, Cintia González, Óscar Baro, Alberto Aliaga, Karine Ferreira de Campos, María Villarejo, Carlos Hurtado, Carolina Álvarez-Ortega, Antón Gómez-García, Marta Cedenilla, Gonzalo Fernández","doi":"10.2196/40377","DOIUrl":"https://doi.org/10.2196/40377","url":null,"abstract":"<p><strong>Background: </strong>Diabetes is a major health care problem, reaching epidemic numbers worldwide. Reducing hemoglobin A<sub>1c</sub> (HbA<sub>1c</sub>) levels to recommended targets is associated with a marked decrease in the risk of type 2 diabetes mellitus (T2DM)-related complications. The implementation of new technologies, particularly telemedicine, may be helpful to facilitate self-care and empower people with T2DM, leading to improved metabolic control of the disease.</p><p><strong>Objective: </strong>This study aimed to analyze the effect of a home digital patient empowerment and communication tool (DeMpower App) on metabolic control in people with inadequately controlled T2DM.</p><p><strong>Methods: </strong>The DeMpower study was multicenter with a retrospective (observational: 52 weeks of follow-up) and prospective (interventional: 52 weeks of follow-up) design that included people with T2DM, aged ≥18 and ≤80 years, with HbA<sub>1c</sub> levels ≥7.5% to ≤9.5%, receiving treatment with noninsulin antihyperglycemic agents, and able to use a smartphone app. Individuals were randomly assigned (2:1) to the DeMpower app-empowered group or control group. We describe the effect of empowerment on the proportion of patients achieving the study glycemic target, defined as HbA<sub>1c</sub>≤7.5% with a ≥0.5% reduction in HbA<sub>1c</sub> at week 24.</p><p><strong>Results: </strong>Due to the COVID-19 pandemic, the study was stopped prematurely, and 50 patients (33 in the DeMpower app-empowered group and 17 in the control group) were analyzed. There was a trend toward a higher proportion of patients achieving the study glycemic target (46% vs 18%; P=.07) in the DeMpower app group that was statistically significant when the target was HbA<sub>1c</sub>≤7.5% (64% vs 24%; P=.02) or HbA<sub>1c</sub>≤8% (85% vs 53%; P=.02). The mean HbA<sub>1c</sub> was significantly reduced at week 24 (-0.81, SD 0.89 vs -0.15, SD 1.03; P=.03); trends for improvement in other cardiovascular risk factors, medication adherence, and satisfaction were observed.</p><p><strong>Conclusions: </strong>The results suggest that patient empowerment through home digital tools has a potential effect on metabolic control, which might be even more relevant during the COVID-19 pandemic and in a digital health scenario.</p>","PeriodicalId":52371,"journal":{"name":"JMIR Diabetes","volume":" ","pages":"e40377"},"PeriodicalIF":0.0,"publicationDate":"2022-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9577714/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"40393921","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}
JMIR DiabetesPub Date : 2022-09-30DOI: 10.2196/35039
Su Lin Lim, Melissa Hui Juan Tay, Kai Wen Ong, Jolyn Johal, Qai Ven Yap, Yiong Huak Chan, Genevieve Kai Ning Yeo, Chin Meng Khoo, Alison Yaxley
{"title":"Association Between Mobile Health App Engagement and Weight Loss and Glycemic Control in Adults With Type 2 Diabetes and Prediabetes (D'LITE Study): Prospective Cohort Study.","authors":"Su Lin Lim, Melissa Hui Juan Tay, Kai Wen Ong, Jolyn Johal, Qai Ven Yap, Yiong Huak Chan, Genevieve Kai Ning Yeo, Chin Meng Khoo, Alison Yaxley","doi":"10.2196/35039","DOIUrl":"https://doi.org/10.2196/35039","url":null,"abstract":"<p><strong>Background: </strong>Mobile health apps are increasingly used as early intervention to support behavior change for diabetes prevention and control, with the overarching goal of lowering the overall disease burden.</p><p><strong>Objective: </strong>This prospective cohort study conducted in Singapore aimed to investigate app engagement features and their association with weight loss and improved glycemic control among adults with diabetes and prediabetes from the intervention arm of the Diabetes Lifestyle Intervention using Technology Empowerment randomized controlled trial.</p><p><strong>Methods: </strong>Diabetes and prediabetes participants (N=171) with a median age of 52 years, BMI of 29.3 kg/m<sup>2</sup>, and glycated hemoglobin (HbA<sub>1c</sub>) level of 6.5% and who were being assigned the Nutritionist Buddy Diabetes app were included. Body weight and HbA<sub>1c</sub> were measured at baseline, 3 months, and 6 months. A total of 476,300 data points on daily app engagement were tracked via the backend dashboard and developer's report. The app engagement data were analyzed by quartiles and weekly means expressed in days per week. Linear mixed model analysis was used to determine the associations between the app engagements with percentage weight and HbA<sub>1c</sub> change.</p><p><strong>Results: </strong>The median overall app engagement rate was maintained above 90% at 6 months. Participants who were actively engaged in ≥5 app features were associated with the greatest overall weight reduction of 10.6% from baseline (mean difference -6, 95% CI -8.9 to -3.2; P<.001) at 6 months. Adhering to the carbohydrate limit of >5.9 days per week and choosing healthier food options for >4.3 days per week had the most impact, eliciting weight loss of 9.1% (mean difference -5.2, 95% CI -8.2 to -2.2; P=.001) and 8.8% (mean difference -4.2, 95% CI -7.1 to -1.3; P=.005), respectively. Among the participants with diabetes, those who had a complete meal log for >5.1 days per week or kept within their carbohydrate limit for >5.9 days per week each achieved greater HbA<sub>1c</sub> reductions of 1.2% (SD 1.3%; SD 1.5%), as compared with 0.2% (SD 1%; SD 0.6%). in the reference groups who used the features <1.1 or ≤2.5 days per week, respectively.</p><p><strong>Conclusions: </strong>Higher app engagement led to greater weight loss and HbA<sub>1c</sub> reduction among adults with overweight or obesity with type 2 diabetes or prediabetes.</p><p><strong>Trial registration: </strong>Australian New Zealand Clinical Trials Registry (ANZCTR) ACTRN12617001112358; https://anzctr.org.au/Trial/Registration/TrialReview.aspx?ACTRN=12617001112358.</p>","PeriodicalId":52371,"journal":{"name":"JMIR Diabetes","volume":"7 3","pages":"e35039"},"PeriodicalIF":0.0,"publicationDate":"2022-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9568822/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"40385880","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}
JMIR DiabetesPub Date : 2022-07-28DOI: 10.2196/28153
Hessah Alaslawi, Ilhem Berrou, Abdullah Al Hamid, Dari Alhuwail, Zoe Aslanpour
{"title":"Diabetes Self-management Apps: Systematic Review of Adoption Determinants and Future Research Agenda.","authors":"Hessah Alaslawi, Ilhem Berrou, Abdullah Al Hamid, Dari Alhuwail, Zoe Aslanpour","doi":"10.2196/28153","DOIUrl":"https://doi.org/10.2196/28153","url":null,"abstract":"<p><strong>Background: </strong>Most diabetes management involves self-management. Effective self-management of the condition improves diabetes control, reduces the risk of complications, and improves patient outcomes. Mobile apps for diabetes self-management (DSM) can enhance patients' self-management activities. However, they are only effective if clinicians recommend them, and patients use them.</p><p><strong>Objective: </strong>This study aimed to explore the determinants of DSM apps' use by patients and their recommendations by health care professionals (HCPs). It also outlines the future research agenda for using DSM apps in diabetes care.</p><p><strong>Methods: </strong>We systematically reviewed the factors affecting the adoption of DSM apps by both patients and HCPs. Searches were performed using PubMed, Scopus, CINAHL, Cochrane Central, ACM, and Xplore digital libraries for articles published from 2008 to 2020. The search terms were diabetes, mobile apps, and self-management. Relevant data were extracted from the included studies and analyzed using a thematic synthesis approach.</p><p><strong>Results: </strong>A total of 28 studies met the inclusion criteria. We identified a range of determinants related to patients' and HCPs' characteristics, experiences, and preferences. Young female patients were more likely to adopt DSM apps. Patients' perceptions of the benefits of apps, ease of use, and recommendations by patients and other HCPs strongly affect their intention to use DSM apps. HCPs are less likely to recommend these apps if they do not perceive their benefits and may not recommend their use if they are unaware of their existence or credibility. Young and technology-savvy HCPs were more likely to recommend DSM apps.</p><p><strong>Conclusions: </strong>Despite the potential of DSM apps to improve patients' self-care activities and diabetes outcomes, HCPs and patients remain hesitant to use them. However, the COVID-19 pandemic may hasten the integration of technology into diabetes care. The use of DSM apps may become a part of the new normal.</p>","PeriodicalId":52371,"journal":{"name":"JMIR Diabetes","volume":"7 3","pages":"e28153"},"PeriodicalIF":0.0,"publicationDate":"2022-07-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9377471/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"40554555","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}
JMIR DiabetesPub Date : 2022-07-26DOI: 10.2196/33401
Audrey White, David Bradley, Elizabeth Buschur, Cara Harris, Jacob LaFleur, Michael Pennell, Adam Soliman, Kathleen Wyne, Kathleen Dungan
{"title":"Effectiveness of a Diabetes-Focused Electronic Discharge Order Set and Postdischarge Nursing Support Among Poorly Controlled Hospitalized Patients: Randomized Controlled Trial.","authors":"Audrey White, David Bradley, Elizabeth Buschur, Cara Harris, Jacob LaFleur, Michael Pennell, Adam Soliman, Kathleen Wyne, Kathleen Dungan","doi":"10.2196/33401","DOIUrl":"10.2196/33401","url":null,"abstract":"<p><strong>Background: </strong>Although the use of electronic order sets has become standard practice for inpatient diabetes management, there is limited decision support at discharge.</p><p><strong>Objective: </strong>In this study, we assessed whether an electronic discharge order set (DOS) plus nurse follow-up calls improve discharge orders and postdischarge outcomes among hospitalized patients with type 2 diabetes mellitus.</p><p><strong>Methods: </strong>This was a randomized, open-label, single center study that compared an electronic DOS and nurse phone calls to enhanced standard care (ESC) in hospitalized insulin-requiring patients with type 2 diabetes mellitus. The primary outcome was change in glycated hemoglobin (HbA<sub>1c</sub>) level at 24 weeks after discharge. The secondary outcomes included the completeness and accuracy of discharge prescriptions related to diabetes.</p><p><strong>Results: </strong>This study was stopped early because of feasibility concerns related to the long-term follow-up. However, 158 participants were enrolled (DOS: n=82; ESC: n=76), of whom 155 had discharge data. The DOS group had a greater frequency of prescriptions for bolus insulin (78% vs 44%; P=.01), needles or syringes (95% vs 63%; P=.03), and glucometers (86% vs 36%; P<.001). The clarity of the orders was similar. HbA<sub>1c</sub> data were available for 54 participants in each arm at 12 weeks and for 44 and 45 participants in the DOS and ESC arms, respectively, at 24 weeks. The unadjusted difference in change in HbA<sub>1c</sub> level (DOS - ESC) was -0.6% (SD 0.4%; P=.18) at 12 weeks and -1.1% (SD 0.4%; P=.01) at 24 weeks. The adjusted difference in change in HbA<sub>1c</sub> level was -0.5% (SD 0.4%; P=.20) at 12 weeks and -0.7% (SD 0.4%; P=.09) at 24 weeks. The achievement of the individualized HbA<sub>1c</sub> target was greater in the DOS group at 12 weeks but not at 24 weeks.</p><p><strong>Conclusions: </strong>An intervention that included a DOS plus a postdischarge nurse phone call resulted in more complete discharge prescriptions. The assessment of postdischarge outcomes was limited, owing to the loss of the long-term follow-up, but it suggested a possible benefit in glucose control.</p><p><strong>Trial registration: </strong>ClinicalTrials.gov NCT03455985; https://clinicaltrials.gov/ct2/show/NCT03455985.</p>","PeriodicalId":52371,"journal":{"name":"JMIR Diabetes","volume":"7 3","pages":"e33401"},"PeriodicalIF":0.0,"publicationDate":"2022-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9364166/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"40625016","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":"Type 1 Diabetes Hypoglycemia Prediction Algorithms: Systematic Review.","authors":"Stella Tsichlaki, Lefteris Koumakis, Manolis Tsiknakis","doi":"10.2196/34699","DOIUrl":"https://doi.org/10.2196/34699","url":null,"abstract":"<p><strong>Background: </strong>Diabetes is a chronic condition that necessitates regular monitoring and self-management of the patient's blood glucose levels. People with type 1 diabetes (T1D) can live a productive life if they receive proper diabetes care. Nonetheless, a loose glycemic control might increase the risk of developing hypoglycemia. This incident can occur because of a variety of causes, such as taking additional doses of insulin, skipping meals, or overexercising. Mainly, the symptoms of hypoglycemia range from mild dysphoria to more severe conditions, if not detected in a timely manner.</p><p><strong>Objective: </strong>In this review, we aimed to report on innovative detection techniques and tactics for identifying and preventing hypoglycemic episodes, focusing on T1D.</p><p><strong>Methods: </strong>A systematic literature search following the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines was performed focusing on the PubMed, GoogleScholar, IEEEXplore, and ACM Digital Library to find articles on technologies related to hypoglycemia detection in patients with T1D.</p><p><strong>Results: </strong>The presented approaches have been used or devised to enhance blood glucose monitoring and boost its efficacy in forecasting future glucose levels, which could aid the prediction of future episodes of hypoglycemia. We detected 19 predictive models for hypoglycemia, specifically on T1D, using a wide range of algorithmic methodologies, spanning from statistics (1.9/19, 10%) to machine learning (9.88/19, 52%) and deep learning (7.22/19, 38%). The algorithms used most were the Kalman filtering and classification models (support vector machine, k-nearest neighbors, and random forests). The performance of the predictive models was found to be satisfactory overall, reaching accuracies between 70% and 99%, which proves that such technologies are capable of facilitating the prediction of T1D hypoglycemia.</p><p><strong>Conclusions: </strong>It is evident that continuous glucose monitoring can improve glucose control in diabetes; however, predictive models for hypo- and hyperglycemia using only mainstream noninvasive sensors such as wristbands and smartwatches are foreseen to be the next step for mobile health in T1D. Prospective studies are required to demonstrate the value of such models in real-life mobile health interventions.</p>","PeriodicalId":52371,"journal":{"name":"JMIR Diabetes","volume":"7 3","pages":"e34699"},"PeriodicalIF":0.0,"publicationDate":"2022-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9353679/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"40610969","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}