Efficacy of a Digital Diabetes Logbook for People With Type 1, Type 2, and Gestational Diabetes: Results From a Multicenter, Open-Label, Parallel-Group, Randomized Controlled Trial.

BACKGROUND: In a randomized controlled trial, the efficacy of a digital diabetes diary regarding a reduction of diabetes distress was evaluated. METHODS: A randomized controlled trial with a 12-week follow-up was conducted in 41 study sites across Germany. Key eligibility criteria were a diagnosis of type 1, type 2, or gestational diabetes and regular self-monitoring of blood glucose. Participants were randomly assigned (2:1 ratio) to either use the digital diabetes logbook (mySugr PRO), or to the control group without app use. The primary outcome was the reduction in diabetes distress at the 12-week follow-up. All analyses were based on the intention-to-treat population with all randomized participants. The trial was registered at the German Register for Clinical Studies (DRKS00022923). RESULTS: Between February 11, 2021, and June 24, 2022, 424 participants (50% female, 50% male) were included, with 282 being randomized to the intervention group (66.5%) and 142 to the control group (33.5%). A total of 397 participants completed the trial (drop-out rate: 6.4%). The median reduction in diabetes distress was 2.41 (interquartile range [IQR]: -2.50 to 8.11) in the intervention group and 1.25 (IQR: -5.00 to 7.50) in the control group. The model-based adjusted between-group difference was significant (-2.20, IQR: -4.02 to -0.38, P = .0182) favoring the intervention group. There were 27 adverse events, 17 (6.0%) in the intervention group, and 10 (7.0%) in the control group. CONCLUSIONS: The efficacy of the digital diabetes logbook was demonstrated regarding improvements in mental health in people with type 1, type 2, and gestational diabetes.

Person-reported outcomes in diabetes care: What are they and why are they so important?

In this review, we aim to show how person-reported outcomes (PROs) and person-reported experiences (PREs) can significantly contribute to the way diabetes care is delivered, the involvement of people with diabetes in diabetes care, and the collaboration between health care professionals and people with diabetes. This review focuses on the definition and measurement of PROs and PREs, the importance of PROs and PREs for person-centred diabetes care, and integrating the perspectives of people with diabetes in the evaluation of medical, psychological and technological interventions. PROs have been increasingly accepted by Health Technology Assessment bodies and are therefore valued in the context of reimbursement decisions and consequently by regulators and other health care stakeholders for the allocation of health care resources. Furthermore, the review identified current challenges to the assessment and use of PROs and PREs in clinical care and research. These challenges relate to the combination of questionnaires and ecological momentary assessment for measuring PROs and PREs, lack of consensus on a core outcome set, limited sensitivity to change within many measures and insufficient standardization of what can be considered a minimal clinically important difference. Another issue that has not been sufficiently addressed is the involvement of people with diabetes in the design and development of measures to assess PROs and PREs.

More Frequent Use of Glucose Alarms Is Associated with Continuous Glucose Monitoring-Specific Diabetes Education: Findings from the Dia·Link Diabetes Panel.

The associations of continuous glucose monitoring (CGM)-specific diabetes education with real-world utilization of glucose alerts and alarms were assessed in current CGM-users with type 1 or type 2 diabetes. A cross-sectional online survey was conducted in Germany assessing utilization (use and responses) of different alerts and alarms. Ordinal logistic regression analyses were conducted to analyze associations between utilization and participation in CGM-specific education. Data from 453 participants were analyzed (86.2% type 1 diabetes). Participants who received CGM-specific education were more likely to regularly use low-glucose alerts (odds ratio [OR] = 5.43, P < 0.001), low-glucose alarms (OR = 2.03, P = 0.027), and rate of change alerts (OR = 4.20, P = 0.009), and were more likely to immediately react to low-glucose alerts (OR = 5.23, P < 0.001) and rate of change alerts (OR = 3.75, P = 0.018). CGM-specific education has the potential to increase utilization of and response to alerts and alarms. This may help to implement more preventive elements regarding glucose management in everyday life.

Explaining improvement in diabetes distress: a longitudinal analysis of the predictive relevance of resilience and acceptance in people with type 1 diabetes.

AIMS: To analyze if midterm improvement in diabetes distress can be explained by resilience, diabetes acceptance, and patient characteristics. METHODS: N = 179 adults with type 1 diabetes were enrolled during their stay at a tertiary diabetes center (monocentric enrolment) and followed up over three months in a prospective, observational study ('DIA-LINK1'). Improvement in diabetes distress was assessed as reduction in the Problem Areas in Diabetes Scale score from baseline to follow-up. Resilience (Resilience Scale-13), acceptance (Diabetes Acceptance Scale), and patient characteristics were analyzed as predictors of improvement in diabetes distress using hierarchical multiple regression. RESULTS: Greater reductions in diabetes distress were significantly explained by lower diabetes acceptance at baseline (ß = -0.34, p < 0.01), while resilience, diabetes complications, and other person-related variables were not significantly related to changes in diabetes distress (all p > 0.05). When change in diabetes acceptance from baseline to follow-up was added to the model, improved diabetes distress was explained by increasing diabetes acceptance (ß = 0.41, p < 0.01) and a shorter duration of diabetes (ß = -0.18, p = 0.03), while baseline diabetes acceptance was no longer significantly associated (ß = -0.14, p > 0.05). CONCLUSIONS: Diabetes acceptance is inversely related to diabetes distress, and increasing acceptance explained greater improvement in diabetes distress. These findings suggest that increasing diabetes acceptance may facilitate the reduction of diabetes distress. Treatment approaches targeting acceptance might be useful for the mental healthcare of people with type 1 diabetes and clinically elevated diabetes distress.

Counting the Minutes: Perceived Diabetes Mental Load and its Associations With Technology Use and Mental Disorders.

Little is known about mental load in people with diabetes and associations with demographic, clinical, and treatment characteristics, such as the use of diabetes technologies. To explore perceived mental load, 503 adults with diabetes answered the one-item survey "How much time (in minutes) would you spontaneously estimate that you spend each day thinking about your diabetes?" Mental load estimations varied widely within the sample and between subgroups. Perceived mental load was higher in type 1 diabetes than in type 2 diabetes, higher in women than in men and increased with treatment intensity (ie, insulin therapy, technology use) and the number of mental disorders. Further research may explore associations with diabetes-related distress and determine whether (perceived) mental load has relevance in technology use.

Use of smartphone application versus written titration charts for basal insulin titration in adults with type 2 diabetes and suboptimal glycaemic control (My Dose Coach): multicentre, open-label, parallel, randomised controlled trial.

Background: The majority of people with type 2 diabetes who require insulin therapy use only basal insulin in combination with other anti-diabetic agents. We tested whether using a smartphone application to titrate insulin could improve glycaemic control in people with type 2 diabetes who use basal insulin. Methods: This was a 12-week, multicentre, open-label, parallel, randomised controlled trial conducted in 36 diabetes practices in Germany. Eligible participants had type 2 diabetes, a BMI ≥25.0 kg/m2, were on basal insulin therapy or were initiating basal insulin therapy, and had suboptimal glycaemic control (HbA1c >7.5%; 58.5 mmol/mol). Block randomisation with 1:1 allocation was performed centrally. Participants in the intervention group titrated their basal insulin dose using a smartphone application (My Dose Coach) for 12 weeks. Control group participants titrated their basal insulin dose according to a written titration chart. The primary outcome was the baseline-adjusted change in HbA1c at 12 weeks. The intention-to-treat analysis included all randomised participants. Results: Between 13 July 2021 and 21 March 2022, 251 study participants were randomly assigned (control group: n = 123; intervention group: n = 128), and 236 completed the follow-up phase (control group: n = 119; intervention group: n = 117). Regarding the HbA1c a model-based adjusted between-group difference of -0.31% (95% CI: 0.01%-0.69%; p = 0.0388) in favour of the intervention group was observed. There were 30 adverse events reported: 16 in the control group, 14 in the intervention group. Of these, 15 adverse events were serious. No event was considered to be related to the investigational device. Interpretation: Study results suggest that utilizing this digital health smartphone application for basal insulin titration may have resulted in a comparatively greater reduction in HbA1c levels among individuals with type 2 diabetes, as compared to basal insulin titration guided by a written titration schedule. No negative effect on safety outcomes was observed. Funding: Sanofi-Aventis Deutschland GmbH.

Emotional distress and cardiovascular disease risk among participants enrolled in the Glycemia Reduction Approaches in Diabetes: A Comparative Effectiveness (GRADE) study.

AIMS: People with type 2 diabetes (T2DM) have an increased risk of cardiovascular disease (CVD). We examined depressive symptoms (DS) and diabetes distress (DD) in relation to the estimated 10-year risk of CVD in adults with T2DM enrolled in the GRADE Emotional Distress Substudy. METHODS: Linear regression models examined the associations of baseline DS and DD with estimated 10-year risk of CVD using the Atherosclerotic Cardiovascular Disease (ASCVD) risk score, adjusting for age, sex, race/ethnicity, education, income, diabetes duration, diabetes-related complications, and HbA1c. RESULTS: A total of 1,605 GRADE participants were included: 54% Non-Latino (NL) White, 18% Latino, 19% NL-Black, 66% male, mean age 57.5 (SD = 10.25) years, diabetes duration 4.2 (SD = 2.8) years, and HbA1c 7.5% (SD = 0.5%). After incorporating covariates, only DS, especially cognitive-affective symptoms, were associated with ASCVD risk (estimate = 0.15 [95% CI: 0.04, 0.025], p = 0.006). Higher DS remained significantly associated with higher ASCVD risk when adding DD to covariates (estimate = 0.19 [95% CI: 0.07, 0.30], p = 0.002). DD was not associated with ASCVD risk when accounting for covariates. CONCLUSIONS: Depressive symptoms, particularly cognitive-affective symptoms, are associated with increased 10-year predicted ASCVD risk among adults with early T2DM. Diabetes distress is not significantly associated with the predicted ASCVD risk when accounting for covariates.

Assessing fear of complications in people with type 1 and type 2 diabetes with the Fear of Diabetes Complications Questionnaire.

OBJECTIVE: Fear of diabetes complications (FDC) is a common source of emotional distress in people with diabetes across types and treatments and may affect health outcomes. To assess FDC, the Fear of Diabetes Complications Questionnaire (FDCQ) was developed. This study evaluates the FDCQ's German version in people with type 1 diabetes (T1D) and type 2 diabetes (T2D). METHOD: A German version of the FDCQ was developed and administered as part of four different studies sampling people with T1D and T2D. Measurement properties were evaluated across studies using factor analyses, reliability estimates, and associations of the measure within a network of variables. A cutoff criterion for elevated FDC was derived. A short form scale was also developed. RESULTS: High reliability and validity were supported. FDC as measured by the FDCQ was independently associated with higher diabetes distress and depressive symptoms. A cut-off score for elevated FDC was set at ≥30 in the 15-item FDCQ. Elevated FDCQ scores were detected in 36% of participants in secondary diabetes care and up to 46% of those in tertiary care. CONCLUSIONS: FDC is prevalent in people with T1D and T2D and associated with diabetes distress and depressive symptoms. The FDCQ is a reliable and valid tool for assessing FDC in research and practice. It may help identify persons in need of tailored education and care and monitor effects following treatment. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Assessing Barriers and Adherence to Insulin Injection Technique in People With Diabetes: Development and Validation of New Assessment Tools.

BACKGROUND: The correct injection technique is crucial for people with insulin therapy. However, barriers to insulin injections exist, which can lead to problems with injections. In addition, injection behavior may deviate from recommendations leading to lower adherence to the correct injection technique. We developed two scales to assess barriers and adherence to the correct technique. METHODS: Two item pools were created to assess barriers to insulin injections (barriers scale) and adherence to the correct technique (adherence scale). In an evaluation study, participants completed the two newly created scales, as well as other questionnaires used for criterion validity. Exploratory factor analysis, correlational analysis, and receiver operating characteristics analysis were computed to analyze the validity of the scales. RESULTS: A total of 313 people with type 1 and type 2 diabetes using an insulin pen for insulin injections participated. For the barriers scale, 12 items were selected achieving a reliability of 0.74. The factor analysis revealed three factors namely emotional, cognitive, and behavioral barriers. For the adherence scale, nine items were selected achieving a reliability of 0.78. Both scales showed significant associations with diabetes self-management, diabetes distress, diabetes acceptance, and diabetes empowerment. Receiver operating characteristics analysis showed significant area under the curves for both scales in classifying people with current skin irritations. CONCLUSIONS: Reliability and validity of the two scales assessing barriers and adherence to insulin injection technique were demonstrated. The two scales can be used in clinical practice to identify persons in need of education in insulin injection technique.

Reduced heart rate variability in people with type 1 diabetes and elevated diabetes distress: Results from the longitudinal observational DIA-LINK1 study.

AIMS: People with type 1 diabetes have a higher risk for cardiovascular disease (CVD). Reduced heart rate variability (HRV) is a clinical marker for CVD. In this observational study using continuous HRV measurement across 26 days, we investigated whether psychological stressors (diabetes distress, depressive symptoms) and glycaemic parameters (hypo- and hyperglycaemic exposure, glycaemic variability and HbA1c ) are associated with lower HRV in people with type 1 diabetes. METHODS: Data from the non-interventional prospective DIA-LINK1 study were analysed. At baseline, depressive symptoms and diabetes distress were assessed. Glucose values and HRV were recorded daily for 26 days using continuous glucose monitoring (CGM) and a wrist-worn health tracker respectively. Multilevel modelling with participant as nesting factor was used to analyse associations between day-to-day HRV and diabetes distress, depressive symptoms and CGM-derived parameters. RESULTS: Data from 149 participants were analysed (age: 38.3 ± 13.1 years, HbA1c : 8.6 ± 1.9%). Participants with elevated diabetes distress had a significantly lower HRV across the 26 days compared to participants without elevated distress (ß = -0.28; p = 0.004). Elevated depressive symptoms were not significantly associated with HRV (ß = -0.18; p = 0.074). Higher daily exposure to hyperglycaemia (ß = -0.44; p = 0.044), higher average exposure to hypoglycaemia (ß = -0.18; p = 0.042) and higher HbA1c (ß = -0.20; p = 0.018) were associated with reduced HRV across the 26 days. Sensitivity analysis with HRV averaged across all days corroborated these results. CONCLUSIONS: Diabetes distress is a clinically meaningful psychosocial stressor that could play a role in the cardiovascular health of people with type 1 diabetes. These findings highlight the need for integrated psychosocial care in diabetes management.

Evaluation of a Digital Health Tool for Titration of Basal Insulin in People With Type 2 Diabetes: Rationale and Design of a Randomized Controlled Trial.

BACKGROUND: Optimal insulin titration is essential in helping people with type 2 diabetes mellitus (T2DM) to achieve adequate glycemic control. Barriers of people with diabetes to implementation of titration include lack of self-efficiency and self-management skills, increased diabetes-related distress, low treatment satisfaction, poor well-being, as well as concerns about hypoglycemia and insulin overdose. My Dose Coach is a digital health tool for optimizing titration of basal insulin that combines a smartphone app for patients with T2DM and a Web portal for health care professionals. METHODS/DESIGN: This is a prospective, open-label, multicenter, randomized controlled parallel study conducted in approximately 50 centers in Germany that are specialized in the treatment of diabetes. Patients in the intervention group will use the titration app and will be registered on the Web portal by their treating physician. Control group patients will continue their current basal insulin titration without using the app. The primary outcome is the mean change in HbA1c levels at the 12-week follow-up. The secondary outcome measures include patient-reported outcomes such as diabetes-related distress, self-management, empowerment, self-efficacy, treatment satisfaction, and psychological well-being as well as fasting blood glucose values. CONCLUSION: This digital health tool has been previously implemented in several independent pilot studies. The findings from this multicenter randomized controlled trial can provide further evidence supporting the effectiveness of this tool in patients with T2DM and serve as a basis for its clinical integration. TRIAL REGISTRATION: German Register for Clinical Studies-DRKS-ID: DRKS00024861.

Emotional distress, self-management, and glycemic control among participants enrolled in the glycemia reduction approaches in diabetes: A comparative effectiveness (GRADE) study.

OBJECTIVE: We examined emotional distress in relation to metformin adherence, overall diabetes self-management, and glycemic control among adults with early type 2 diabetes (T2DM) enrolled in the GRADE study. METHODS: Linear regression models examined cross-sectional associations of baseline depression symptoms and diabetes distress with adherence to metformin, self-management, and HbA1c, adjusting for covariates. Cognitive-affective (e.g., sadness) and somatic (e.g., sleep/appetite disturbance) depression symptoms and diabetes distress subscales were also examined. RESULTS: This substudy of 1,739 GRADE participants (56 % Non-Hispanic White, 18 % Non-Hispanic Black, 17 % Hispanic, 68 % male, mean[SD] age = 57.96[10.22] years, diabetes duration = 4.21[2.81] years, and HbA1c = 7.51[0.48]) found that the prevalence of clinically significant depression and diabetes distress was 8.7 % and 25 %, respectively. Fully adjusted models showed that depression symptoms were associated with lower self-management (p < 0.0001); this effect was only significant for somatic symptoms. Diabetes distress was associated with lower adherence (p = 0.0001) and self-management (p < 0.0001); effects were significant for all subscales, except physician-related distress. No significant relationships of total depression symptom severity or diabetes distress with HbA1c were found. CONCLUSIONS: Depression symptoms and diabetes distress were robustly associated with problematic diabetes self-management among participants in GRADE. These findings highlight the need for routine assessment of depression symptoms and diabetes distress early in T2DM care.

Time With Diabetes Distress and Glycemia-Specific Distress: New Patient-Reported Outcome Measures for the Psychosocial Burden of Diabetes Using Ecological Momentary Assessment in an Observational Study.

OBJECTIVE: To estimate time with diabetes distress using ecological momentary assessment (EMA) in people with type 1 diabetes and analyze its associations with glycemic management based on continuous glucose monitoring (CGM). RESEARCH DESIGN AND METHODS: We used EMA to assess diabetes distress in a sample of recently hospitalized adults with type 1 diabetes once a day for 17 consecutive days in an ambulatory setting. Additionally, participants were asked daily about hypoglycemia distress (<70 mg/dL [3.9 mmol/L]), hyperglycemia distress (>180 mg/dL [10 mmol/L]), and variability distress (glucose fluctuations). Per person, the percentage of days with elevated distress was calculated (time with distress). Multilevel regression was used to analyze daily associations of distress ratings with CGM-derived parameters. EMA-derived associations between diabetes distress and glycemic outcomes were compared with questionnaire-derived associations. RESULTS: Data of 178 participants were analyzed. Participants spent a mean (SD) of days in a state of diabetes distress, 54.6 ± 26.0% in hyperglycemia distress, 45.2 ± 27.5% in variability distress, and 23.0 ± 19.3% in hypoglycemia distress. In multilevel analyses, higher daily ratings of diabetes distress were significantly associated with hyperglycemia (ß = 0.41). Results showed high between-person variability as explanation of variance of the models ranged between 22.2 and 98.8%. EMA-derived diabetes distress showed a significant association with mean glucose (r = 0.25), while questionnaire-based diabetes distress did not (r = 0.10). Prospectively, time with diabetes distress was associated with HbA1c at the 3-month follow-up (r = 0.27), while questionnaire-based distress showed no association (r = 0.11). CONCLUSIONS: Time with distress as assessed with EMA showed a comparative advantage over distress as determined by questionnaire-based assessment of diabetes distress regarding associations with glycemic management.

Real-Time Continuous Glucose Monitoring Can Predict Severe Hypoglycemia in People with Type 1 Diabetes: Combined Analysis of the HypoDE and DIAMOND Trials.

Objective: We combined data from two landmark trials (DIAMOND and HypoDE) to examine the diagnostic performance of low glucose measurements derived from open and masked continuous glucose monitoring (CGM) to predict the occurrence of future severe hypoglycemia (SH). Methods: We analyzed hypoglycemia parameters (low blood glucose index [LBGI], % <70 mg/dL, 54-69 mg/dL [level 1 hypoglycemia] and <54 mg/dL [level 2 hypoglycemia]) from masked CGM over 14 days during baseline and from open CGM over 14 days after randomization. We used receiver operating characteristics (ROC) curves to evaluate the screening performance of these measures to predict future SH. Positive likelihood ratios were calculated to indicate the overall diagnostic performance of these parameters. Results: Data from 288 individuals with type 1 diabetes (mean age 45.6 ± 12.8 years, diabetes duration 20.7 ± 13.7 years, HbA1c 8.2% ± 1.0%, Hypoglycemia Unawareness Score 3.4 ± 2.1) were analyzed. Area under ROC-curve (AUC) for LBGI and % <70 mg/dL ranged between 0.68 and 0.75, indicating that LBGI and % <70 mg/dL could significantly predict future SH. Significance of AUC regarding % <54 mg/dL were mixed (0.63-0.72). Positive and negative likelihood ratios ranged between 1.82 to 3.40 and 0.56 to 0.32, respectively. Suggested optimal cutoff values were remarkedly lower in open CGM than in masked CGM. Conclusion: These results indicate that CGM-derived hypoglycemic parameters have a good screening performance to significantly predict future clinical hypoglycemia. In addition, this analysis suggests that cutoff values to indicate elevated hypoglycemia risk in the future are substantially lower in open CGM than in masked CGM. ClinicalTrials.gov registration numbers: HypoDE: NCT02671968. DIAMOND: NCT02282397.

Coordination of glucose monitoring, self-care behaviour and mental health: achieving precision monitoring in diabetes.

Monitoring of glucose plays an essential role in the management of diabetes. However, to fully understand and meaningfully interpret glucose levels, additional information on context is necessary. Important contextual factors include data on behaviours such as eating, exercise, medication-taking and sleep, as well as data on mental health aspects such as stress, affect, diabetes distress and depressive symptoms. This narrative review provides an overview of the current state and future directions of precision monitoring in diabetes. Precision monitoring of glucose has made great progress over the last 5 years with the emergence of continuous glucose monitoring (CGM), automated analysis of new glucose variables and visualisation of CGM data via the ambulatory glucose profile. Interestingly, there has been little progress in the identification of subgroups of people with diabetes based on their glycaemic profile. The integration of behavioural and mental health data could enrich such identification of subgroups to stimulate precision medicine. There are a handful of studies that have used innovative methodology such as ecological momentary assessment to monitor behaviour and mental health in people's everyday life. These studies indicate the importance of the interplay between behaviour, mental health and glucose. However, automated integration and intelligent interpretation of these data sources are currently not available. Automated integration of behaviour, mental health and glucose could lead to the identification of certain subgroups that, for example, show a strong association between mental health and glucose in contrast to subgroups that show independence of mental health and glucose. This could inform precision diagnostics and precision therapeutics. We identified just-in-time adaptive interventions as a potential means by which precision monitoring could lead to precision therapeutics. Just-in-time adaptive interventions consist of micro-interventions that are triggered in people's everyday lives when a certain problem is identified using monitored behaviour, mental health and glucose variables. Thus, these micro-interventions are responsive to real-life circumstances and are adaptive to the specific needs of an individual with diabetes. We conclude that, with current developments in big data analysis, there is a huge potential for precision monitoring in diabetes.

Psychosocial Impact of the COVID-19 Pandemic on People With Type 1 Diabetes: Results of an Ecological Momentary Assessment Study.

Aims: Psychological distress due to living with diabetes, demanding self-management tasks, impacts on life, and risks of complications is common among people living with diabetes. COVID-19 could pose a new additional risk factor for psychological distress in this group. This study aimed to analyze levels of COVID-19-related burdens and fears, variables explaining these levels, and associations with the concurrent 7-day COVID-19 incidence in people with type 1 diabetes (T1D). Methods: A total of 113 people with T1D (58% women; age: 42.3 ± 9.9 years) participated in an ecological momentary assessment (EMA) study between December 2020 and March 2021. The participants reported daily levels of COVID-19-related burdens and fears over 10 consecutive days. Global ratings of COVID-19-related burdens and fears were assessed using questionnaires, as were current and previous levels of diabetes distress (PAID), acceptance (DAS), fear of complications (FCQ), depressive symptoms (CES-D), and diabetes self-management (DSMQ). Current levels of diabetes distress and depressive symptoms were compared with pre-pandemic ratings gained during an earlier study phase. Associations between burdens and fears, psychosocial and somatic aspects, and the concurrent 7-day incidence rate were analyzed using multilevel regression. Results: Diabetes distress and depressive symptoms reported during the pandemic were comparable to pre-pandemic levels (PAID: p = .89; CES-D: p = .38). Daily EMA ratings reflected relatively low mean COVID-19-related burdens and fears in everyday life. However, there was substantial day-to-day variation per person indicating higher burdens on specific days. Multilevel analyses showed that daily COVID-19-related burdens and fears were significantly predicted by pre-pandemic levels of diabetes distress and diabetes acceptance but were not associated with the concurrent 7-day incidence rate nor with demographic and medical variables. Conclusions: This study observed no increase in diabetes distress and depressive symptoms during the pandemic in people with T1D. The participants reported low to moderate levels of COVID-19-related burdens. COVID-19-related burdens and fears could be explained by pre-pandemic levels of diabetes distress and acceptance but not by demographic and clinical risk variables. The findings suggest that mental factors may constitute stronger predictors of COVID-19-related burdens and fears than objective somatic conditions and risks in middle-aged adults with T1D.

Level of Digitalization in Germany: Results of the Diabetes Digitalization and Technology (D.U.T) Report 2020.

BACKGROUND: New diagnostic and therapeutic technologies are increasingly changing the treatment of people with diabetes (PWD), along with increased usage of digital tools. To date, however, there is little data to which level and how diabetologists and PWD implement digitalization. Also, not much is known about the view of diabetologists on the current status and future developments in this respect. METHOD: In an online survey, diabetologists working in clinics and practices across Germany provided responses regarding their view on digitalization and the adoption of new technologies in diabetology to 56 questions. These comments reflect the opinion of several experts about the current importance and use of specific digital/technological topics. RESULTS: Overall, 326 diabetologists took part in the survey. They reported a positive attitude (75.8%) toward new technologies and digitalization, and they see more advantages rather than disadvantages. Younger age of the diabetologists was significantly associated with a more positive attitude (r = -0.176; P < .01), and there was no gender effect (P = .738). On average, in each practice, 5.5% of PWD are using an insulin pump for therapy, 4.8% a real-time continuous glucose monitoring system, 16.9% an intermittent scanning continuous glucose monitoring system, and 0.3% an automated insulin delivery (AID) system. With respect to digitalization, the three most important current topics are software for glucose data analysis (average rank on a scale from one to six, with one being the most important: 2.4), compatibility with other systems (2.9), and AID systems (3.8)). CONCLUSIONS: This survey, which is going to be repeated annually, showed that the diabetologists who participated predominantly have a positive attitude toward new technologies and digital applications and were aware of the associated advantages. However, perceived disadvantages need to be addressed to enable wider adoption of new technologies and digital solutions.