JMIR Diabetes最新文献

Background: Making lifestyle changes is an essential element of abdominal obesity (AO) reduction. To support lifestyle modification and self-management, we developed an information and communication technology-based self-management system-DialBeticsLite-with a fully automated dietary evaluation function for the treatment of AO.

Objective: The objective of this study was to evaluate the preliminary efficacy and feasibility of DialBeticsLite among Japanese office workers with AO.

Methods: A 2- to 3-month prospective single-arm pilot intervention study was designed to assess the effects of the intervention using DialBeticsLite. The information and communication technology system was composed of 4 modules: data transmission (body weight, blood pressure, blood glucose, and pedometer count); data evaluation; exercise input; and food recording and dietary evaluation. Eligible participants were workers who were aged ≥20 years and with AO (waist circumference ≥85 cm for men and ≥90 cm for women). Physical parameters, blood tests, nutritional intake, and self-care behavior were compared at baseline and after the intervention.

Results: A total of 48 participants provided completed data for analysis, which yielded a study retention rate of 100%. The average age was 46.8 (SD 6.8) years, and 92% (44/48) of participants were male. The overall average measurement rate of DialBeticsLite, calculated by dividing the number of days with at least one measurement by the number of days of the intervention, was 98.6% (SD 3.4%). In total, 85% (41/48) of the participants reported that their participation in the study helped them to improve their lifestyle. BMI, waist circumference, and visceral fat area decreased significantly after the intervention (P<.001). In addition, the daily calorie intake reduced significantly (P=.02). There was a significant improvement in self-care behavior in terms of exercise and diet (P=.001).

Conclusions: Using DialBeticsLite was shown to be a feasible and potentially effective method for reducing AO by providing users with a motivational framework to evaluate their lifestyle behaviors.

Background: Developments and evolutions in the information and communication technology sector have provided a solid foundation for the emergence of mobile health (mHealth) in recent years. The cornerstone to management of gestational diabetes mellitus (GDM) is the self-management of glycemic indices, dietary intake, and lifestyle adaptations. Given this, it is readily adaptable to incorporation of remote monitoring strategies involving mHealth solutions.

Objective: We sought to examine and assess the available smartphone apps which enable self-monitoring and remote surveillance of GDM with a particular emphasis on the generation of individualized patient feedback.

Methods: Five databases were searched systematically for any studies evaluating mHealth-supported smartphone solutions for GDM management from study inception until January 2022. The studies were screened and assessed for eligibility of inclusion by 2 independent reviewers. Ultimately, 17 studies were included involving 1871 patients across 11 different countries. The PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews) conceptual framework was adhered to for data extraction and categorization purposes.

Results: All studies analyzed as part of this review facilitated direct uploading of data from the handheld glucometer to the downloaded patient-facing smartphone app. Glycemic data were captured by all studies and were reassuringly found to be either improved or noninferior to extant models of hospital-based care. Feedback was delivered in either an automated fashion through in-app communication from the health care team or facilitated through bidirectional communication with the app and hospital portal. Although resource utilization and cost-effective analyses were reported in some studies, the results were disparate and require more robust analysis. Where patient and staff satisfaction levels were evaluated, the response was overwhelmingly positive for mHealth smartphone-delivered care strategies. Emergency cesarean section rates were reduced; however, elective cesarean sections were comparatively increased among studies where the mode of delivery was assessed. Most reviewed studies did not identify any differences in maternal, perinatal, or neonatal health when app-based care was compared with usual in-person review.

Conclusions: This comprehensive scoping review highlights the feasibility, reliability, and acceptability of app-assisted health care for the management of GDM. Although further exploration of the economic benefit is required prior to implementation in a real-world clinical setting, the prospect of smartphone-assisted health care for GDM is hugely promising.

Background: 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.

Objective: 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).

Methods: 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.

Results: 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.

Conclusions: 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.

Background: 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.

Objective: 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.

Methods: 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.

Results: 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.

Conclusions: 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

Background: Patients with type 2 diabetes mellitus (T2DM) having elevated levels of blood glucose and glycated hemoglobin (HbA_1c) 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.

Objective: 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.

Methods: 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_1c≥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_1c, 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.

Results: 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_1c, 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/m² (P=.06), respectively. Among the participants showing improvement in the HbA_1c value at the end of 12 weeks (responders), the mean change in HbA_1c, 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/m² (P=.007), respectively. There was an increase in HOMA-IR values for the overall study population (0.54, P=.29). HbA_1c response showed a significant association with a baseline HbA_1c level ≥7.5%, no prior history of smoking, and no prior COVID-19 infection, as well as with higher levels of program engagement.

Conclusions: A digital therapeutic intervention when used alongside standard medications significantly reduces HbA_1c, FBG, and PPBG levels in patients with T2DM.

Background: 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.

Objective: 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.

Methods: An observational study of adults with T1D who used Loop was performed. An assessment of glycemic and safety outcomes, HbA_1c, 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.

Results: 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_1c 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_1c 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).

Conclusions: 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.

Background: 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.

Objective: 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.

Methods: 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.

Results: 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.

Conclusions: 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

Background: Diabetes is a major health care problem, reaching epidemic numbers worldwide. Reducing hemoglobin A_1c (HbA_1c) 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.

Objective: 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.

Methods: 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_1c 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_1c≤7.5% with a ≥0.5% reduction in HbA_1c at week 24.

Results: 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_1c≤7.5% (64% vs 24%; P=.02) or HbA_1c≤8% (85% vs 53%; P=.02). The mean HbA_1c 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.

Conclusions: 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.

Background: 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.

Objective: 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.

Methods: Diabetes and prediabetes participants (N=171) with a median age of 52 years, BMI of 29.3 kg/m², and glycated hemoglobin (HbA_1c) level of 6.5% and who were being assigned the Nutritionist Buddy Diabetes app were included. Body weight and HbA_1c 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_1c change.

Results: 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_1c 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.

Conclusions: Higher app engagement led to greater weight loss and HbA_1c reduction among adults with overweight or obesity with type 2 diabetes or prediabetes.

Trial registration: Australian New Zealand Clinical Trials Registry (ANZCTR) ACTRN12617001112358; https://anzctr.org.au/Trial/Registration/TrialReview.aspx?ACTRN=12617001112358.

Background: 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.

Objective: 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.

Methods: 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.

Results: 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.

Conclusions: 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.