Continuous glucose monitoring in older adults with diabetes: Data from the diabetes prospective follow-up (DPV) registry.

AIMS: To analyse predictors for continuous glucose monitoring (CGM) use in people with diabetes aged ≥60 years using insulin therapy and to assess the rates of CGM use during recent years (2019-2021). RESEARCH DESIGN AND METHODS: Prospective study including 6849 individuals with diabetes and insulin therapy (type 2 diabetes: n = 5320; type 1 diabetes: n = 1529) aged ≥60 years. Data from 129 treatment centres were retrieved from the Diabetes Prospective Follow-up Registry (DPV) in March 2023. RESULTS: Sensor use in individuals aged ≥60 years has increased in type 1 (2019: 28%, 2020: 39%, 2021: 45%) and type 2 diabetes (2019: 10%, 2020: 16%, 2021: 18%). Predictors for sensor use in older individuals with type 1 diabetes are younger age and CSII use (p < 0.001). Predictors in older individuals with type 2 diabetes are younger age, longer diabetes duration, higher BMI and CSII use (p < 0.001). CONCLUSIONS: CGM has become more common in older adults with diabetes and will presumably increase further. Age is a predictor for sensor use in older adults with diabetes. Age-related physical barriers and insufficient usability of devices, lack of interest in technologies, but possibly also effects of prejudice on the grounds of age may contribute to this finding.

Identification with Characters of a National Narrative Health Communication Campaign Targeting Type 2 Diabetes.

Type 2 diabetes mellitus (T2DM) has a high prevalence in Germany. Tailored health communication campaigns are part of preventing T2DM at a societal level, with narrative approaches as a promising communication strategy. The aim of this study was to qualitatively examine identification with characters as a potential narrative effect mechanism within a national T2DM communication campaign (Slogan: "Diabetes - not only a question of type"). In doing so, characters' liking and perceived similarity were explored as antecedents of identification. For this purpose, nine focus groups comprising a total of 76 participants diagnosed with T2DM were conducted. Two of these focus groups consisted entirely of participants of Turkish descent. An assessment was developed to measure the extent to which participants liked, perceived themselves to be similar to, and identified with different characters presented via three videoclip formats (live action, animated cartoons, and celebrity testimonials) from a national diabetes communication campaign. Live action and celebrity testimonial characters were mostly perceived as likeable. However, level of identification was low, and participants felt an overall lack of similarity regarding both personal and disease-related characteristics as compared to these characters. Animated cartoons were perceived as less stigmatizing, but also as less engaging. The study indicates that liking without a feeling of similarity to a character is not sufficient to elicit identification. Further, the reinforcement of harmful T2DM stereotypes should be avoided in health communications to prevent reactance and to increase generalizability.

Diabetes technologies in people with type 1 diabetes mellitus and disordered eating: A systematic review on continuous subcutaneous insulin infusion, continuous glucose monitoring and automated insulin delivery.

AIMS: In this systematic review, we aimed (1) to identify and describe research investigating the use of advanced diabetes technologies (continuous subcutaneous insulin infusion, CSII; continuous glucose monitoring, CGM; automated insulin delivery, AID) in people with type 1 diabetes (T1DM) and disordered eating and (2) to discuss potential (dis)advantages of diabetes technology use in this population, derived from previous research. METHODS: We conducted a systematic literature search in two electronic databases for English articles published between 2000 and 2020 addressing eating disorders and/or dysfunctional eating behaviours and diabetes technology use in children, adolescents and adults with T1DM (PROSPERO ID CRD42020160244). RESULTS: Of 70 publications initially identified, 17 were included. Overall, evidence on the use of diabetes technologies in people with T1DM and disordered eating is scarce. The majority of the studies reports findings on CSII in people with T1DM and dysfunctional eating behaviours or eating disorders. Findings predominantly stem from observational data and are, in most cases, secondary findings of the respective studies. Providing the greatest flexibility in diabetes management, CSII may have benefits in disordered eating. CGM data may complement the diagnostic process of disordered eating with a physiological indicator of insulin restriction (i.e. time spent in hyperglycaemia). CONCLUSIONS: Results on possible (dis)advantages of diabetes technology use in people with T1DM and disordered eating are based on observational data, small pilot trials and anecdotical evidence from case reports. Prospective data from larger samples are needed to reliably determine potential effects of diabetes technology on disordered eating in T1DM.

Associations of Time in Range and Other Continuous Glucose Monitoring-Derived Metrics With Well-Being and Patient-Reported Outcomes: Overview and Trends.

Time in glucose ranges is increasingly relevant for research and clinical practice. Whereas the clinical validity of these metrics has been demonstrated with regard to long-term complications, their associations with patient-reported outcomes such as well-being, diabetes distress, and fear of hypoglycemia remain an open research question. This article reviews existing evidence on links between times in glycemic ranges and patient-reported outcomes. It also describes a novel research approach of using ecological momentary assessment to analyze on a more granular level in real time possible associations of these parameters of glycemic control and patient-reported outcomes. Such an approach could further our understanding of how glucose and patient-reported outcomes may be interconnected.

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.

Fear of Hypoglycemia and Diabetes Distress: Expected Reduction by Glucose Prediction.

BACKGROUND: Extended glucose predictions are novel in diabetes management. Currently, there is no solution widely available. People with diabetes mellitus (DM) are offered features like trend arrows and limited predictions linked to predefined situations. Thus, the impact of extended glucose predictions on the burden of diabetes and person-reported outcomes (PROs) is unclear. METHODS: In this online survey, 206 people with type 1 and type 2 diabetes (T1D and T2D), 70.9% and 29.1%, respectively, who participated in the dia·link online panel and were current continuous glucose monitoring (CGM) users, were presented with different scenarios of hypothetical extended glucose predictions. They were asked to imagine how low glucose predictions of 30 minutes and overnight as well as glucose predictions up to 2 hours would influence their diabetes management. Subsequently, they completed the Hypoglycemia Fear Survey II (HFS-II) and the T1 Diabetes Distress Scale (T1-DDS) by rating each item on a 5-point scale (-2: strong deterioration to +2: strong improvement) according to the potential change due to using glucose predictions. RESULTS: For all glucose prediction periods, 30 minutes, up to 2 hours, and at nighttime, the surveyed participants expected moderate improvements in both fear of hypoglycemia (HFS-II: 0.57 ± 0.49) and overall diabetes distress (T1-DDS = 0.44 ± 0.49). The T1-DDS did not differ for type of therapy or diabetes. CONCLUSIONS: People with T1D and T2D would see glucose predictions as a potential improvement regarding reduced fear of hypoglycemia and diabetes distress. Therefore, glucose predictions represent a value for them in lowering the burden of diabetes and its management.

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.

Cognitive reappraisal in mHealth interventions to foster mental health in adults: a systematic review and meta-analysis.

Background: An increasing number of mHealth interventions aim to contribute to mental healthcare of which interventions that foster cognitive reappraisal may be particularly effective. Objectives: To evaluate the efficacy of mHealth interventions enhancing cognitive reappraisal to improve mental health in adult populations. Methods: The literature search (four databases) yielded 30 eligible randomized controlled trials (comprising 3,904 participants). We performed a multi-level meta-analysis to examine differences between intervention and comparator conditions at post-intervention assessment. Moderator analyses were conducted for potential moderator variables (e.g., type of comparators). Results: Most interventions were CBT-based with other training components in addition to cognitive reappraisal. We found preliminary evidence for a small to medium effect favouring mHealth interventions to enhance cognitive reappraisal over comparators, M(SMD) = 0.34, p = .002. When analysing single symptoms, there was evidence for a small to medium effect of mHealth interventions on anxiety and depressive symptoms, but not for psychological distress and well-being. All analyses showed substantial heterogeneity. Moderator analyses revealed evidence for more favourable effects in studies with passive comparators. There was an overall high risk of bias in most of the studies. Conclusions: We found preliminary evidence for a small to medium effect of mHealth interventions including a cognitive reappraisal component to improve mental health. However, most of the interventions were complex (i.e., reappraisal was provided alongside other components), which prevents us from examining reappraisal-specific effects beyond general mental health promotion in mHealth. Dismantling studies examining the effects of single intervention components are warranted to corroborate these promising results. Systematic Review Registration: https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=142149, identifier [CRD42019142149].

Disordered eating behaviours and eating disorders in adults with type 1 diabetes (DEBBI): rational and design of an observational longitudinal online study.

INTRODUCTION: Disordered eating behaviours (DEB) and eating disorders (ED) are among the most common mental health comorbidities of type 1 diabetes. However, research on diabetes-specific risk and protective factors is limited. To this end, comprehensive characterisations of DEB and ED in type 1 diabetes, as well as longitudinal research on the course of DEB and ED, are needed to gain more insight. The 'Disordered eating behaviours and eating disorders in diabetes type I' (DEBBI) study aims to describe DEB/ED and their correlates in people with type 1 diabetes, to identify key diabetes-specific, psychosocial risk and protective factors, and to describe the course of DEB over time. METHODS AND ANALYSIS: The DEBBI study is a longitudinal online survey with follow-up assessments after 6, 12 and 18 months, targeted at adults who have been diagnosed with type 1 diabetes for at least 12 months. The survey covers data on diabetes diagnosis and self-management (eg, diabetes treatment and complications), lifestyle (eg, eating habits, physical activity), psychosocial well-being (eg, anxiety, depressive symptoms) and demographic and medical information. It includes validated instruments and self-generated items. One key aspect of the data analysis will be latent profile analyses to determine latent subtypes of DEB manifestation in people with type 1 diabetes and their courses over time, including data on the clinical picture and symptoms, behaviours and diabetes-specific complications. ETHICS AND DISSEMINATION: The study protocol was approved by the Ethics Committee of the State Medical Chamber of Rhineland-Palatine, Germany (ID 2021-16040). Participants give informed written consent before starting the survey. The DEBBI study will provide more clarity in the so far inconsistent empirical evidence base and will help to inform research on prevention and intervention strategies that are tailored to diabetes-specific needs. TRIAL REGISTRATION NUMBER: The study is registered with DRKS German Clinical Trials Register (DRKS00028833).

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.

[Depressive disorders: An often underestimated comorbidity in diabetes]. / Depressive Störungen: Eine oft unterschätzte Komorbidität bei Diabetes.

People with diabetes often have a depressive disorder in addition to diabetes, which makes therapy more difficult and worsens the prognosis of the disease. Depression is an often underestimated risk factor in the context of diabetes. The aim of this article is to illustrate the significance of depression in diabetes for the course of the disease and to provide an overview of the most important diagnostic and therapeutic recommendations for practice.

Gamification and Behavior Change Techniques in Diabetes Self-Management Apps.

BACKGROUND: Diabetes management apps may have positive effects on diabetes self-management. It remains unclear, however, which app features are particularly effective and encourage sustained app usage. Behavior change techniques (BCTs) and gamification are promising approaches to improve user engagement. However, little is known about the frequency BCTs and gamification techniques (GTs) are actually used. This app review aims to provide an overview of BCTs and GTs in current diabetes management apps. METHODS: Google's Play Store was searched for applications using a broad search strategy (keyword: "diabetes"). We limited our research to freely available apps. A total of 56 apps matched the inclusion criteria and were reviewed in terms of the features they offer to support self-management. We used a taxonomy comprising 29 BCTs and 17 GTs to evaluate the applications. Two independent raters tested and evaluated each app. RESULTS: Interrater agreement was high (ICC = .75 for BCTs; ICC = .90 for GTs). An average of 7.4 BCTs (SD = 3.1) and an average of 1.4 out of 17 GTs (SD = 1.6) were implemented in each app. Five out of 29 BCTs accounted for 55.8% of the BCTs identified in total. The GT most often identified was "feedback" and accounted for 50% of the GTs. CONCLUSIONS: The potential of BCTs and GTs in diabetes management apps has not been fully exploited yet. Only very restricted sets of BCTs and gamification features were implemented. Systematic research on the efficacy of specific BCTs and GTs is needed to provide further guidance for app design.