This Review summarises the research into five common mental health problems that can affect adults living with type 1 diabetes, type 2 diabetes, or gestational diabetes: fear of hypoglycaemia, diabetes distress, depression, disordered eating, and sleep disorders. Mental health problems are common among adults with diabetes and can substantially decrease the quality of life and self-care, and increase the risk of adverse health outcomes, such as high HbA1c, comorbidities, and premature mortality. Many mental health problems are bi-directionally linked to diabetes. Randomised controlled trials have shown that psychological interventions are effective in reducing symptoms in the short term, including cognitive behavioural therapy, mindfulness-based cognitive therapy, and stepped care, which can also be offered digitally as a first step. However, diabetes distress, depression, and other mental health problems are known to recur and the longer-term outcomes of prevention or treatments are unclear. In general, mental health problems are understudied in diabetes, particularly gestational diabetes. People with diabetes want to talk with their diabetes health professionals about the emotional side of living with and managing diabetes. These findings support the integration of routine monitoring and psychological support into clinical practice. Health-care policy makers should ensure that diabetes health-care professionals are well equipped to discuss mental health and refer to appropriate digital health tools and mental health specialists when needed.

Usage of diabetes technology by people living with diabetes does help them a lot with their daily diabetes management burden. Evidence for the efficacy of using systems for continuous glucose monitoring, automated insulin delivery, and so on has largely been derived from randomized controlled trials, which are pivotal for regulatory approvals and reimbursement decisions. However, evidence obtained from real-world usage of technology is crucial as it confirms the benefits also under such conditions. Data obtained from a detailed survey answered by health care professionals and people living with diabetes provides further insights into the reality of usage. They also help to understand the hurdles in daily life and what can be done to overcome these. In this special theme issue, a set of specific topics is addressed that are of academic and clinical importance: dropouts from automated insulin delivery systems, technology use in people living with type 2 diabetes, technology and aging, smart insulin pens, and green diabetes. The data basis for the analysis presented in these manuscripts is from Germany, Austria, and Switzerland. In the future, data from other European Countries will complement the insights gained. This will help to understand the similarities and differences between these countries, which have specific differences in their health care systems. This can lead to subsequent activities in the different countries to improve the clinical care of people living with diabetes.

Postoperative Komplikationen und Mortalität stellen weltweit eine große Belastung dar. Menschen mit Diabetes machen rund 15–25

BACKGROUND:The number of adults with diabetes and older age is increasing, yet little is known about age-related differences in real-world diabetes technology use. This analysis examines how uptake, clinical outcomes, and user experience vary across age groups in people with type 1 or type 2 diabetes. METHODS:Self-reported data from 2056 individuals with diabetes in Germany, Austria, and Switzerland who completed the diabetes technology report 2024/2025 survey were analyzed. Age-related trends in the use of continuous glucose monitoring (CGM), continuous subcutaneous insulin infusion (CSII), and automated insulin delivery (AID) were assessed using generalized additive and segmented logistic regression models. Outcomes included HbA1c, diabetes distress (PAID-5), severe hypoglycemia (SH), and, among AID users, satisfaction. RESULTS:Among people with type 1 diabetes, CGM usage was consistently high across age groups (eg, 94% in 20-29 years; 92% in ≥70 years). Automated insulin delivery usage peaked in adolescents (81% in 10-19 years) and declined to 36% in adults ≥70 years. In type 2 diabetes, CGM use increased with age (48% in 35-44 years; 72% in ≥70 years). The HbA1c remained stable over the age span (±0.25%). Diabetes distress declined with age (Problems Areas in Diabetes Ouestionnaire - 5 Items (PAID-5): 7.8 in <30 vs 4.2 in ≥70 years). The risk of SH did not increase with age; among CSII users, older participants had lower odds of SH (OR 0.03, p = .001). Automated insulin delivery satisfaction was highest in adults aged 60 to 69 years (88.7/100) and lowest in adolescents (79.1/100). CONCLUSIONS:Diabetes technologies are widely used and well tolerated across age groups. Older adults benefit comparably, but barriers to AID use remain.

Background: The rapid rise of diabetes technology has markedly improved glycemic outcomes, quality of life, and empowerment of people living with diabetes (PwD). However, the increased use of devices such as continuous glucose monitoring systems, insulin pumps, and smart pens has also introduced significant environmental concerns, contributing to waste from plastic, electronics (e-waste) and packaging, and greenhouse gas emissions. Methods: In this paper, we describe results from an online survey conducted in Germany, Austria, and Switzerland, between November and December 2024, focused on the level of concern PwD have, regarding the environmental impacts of single-use medical device, supplies and packaging, resulting from diabetes treatment, and whether these considerations influence technology choices. Results: Among 1934 PwD surveyed, 1332 (69%) favored more reusable devices, and 865 (45%) expressed concern about packaging waste. However, environmental factors ranked far below safety, effectiveness, and usability when selecting diabetes technologies. Conclusions: Expecting PwD to drive substantial environmental improvements is therefore neither realistic nor fair given prevailing priorities on safety and outcomes. Meaningful progress toward greener diabetes care will depend on manufacturers, policymakers, and healthcare systems embracing eco-design, establishing recycling infrastructure, and integrating sustainability into regulatory and reimbursement frameworks. Only through coordinated efforts can optimal diabetes management be achieved alongside environmental stewardship.

Rapid changes in diabetes therapy combined with limitations of traditional methodological approaches challenge the field of psychosocial research to adequately capture the experiences of people with diabetes. This narrative review provides an overview of emerging qualitative and quantitative approaches that can advance the study of psychosocial aspects of diabetes. We searched PubMed and Google Scholar for English-language articles regarding novel qualitative and quantitative methodologies. Emerging qualitative methodologies aim to increase the transferability of lived experiences to other contexts and populations by employing novel ways to stimulate interactions and using digital tools. Culturally sensitive methods (e.g. yarning) and the use of pictures (e.g. photovoice) and storytelling methods (e.g. story completion) can capture more diverse experiences and sensitive topics while being able to minimise social desirability. Online qualitative surveys can increase the reach while artificial intelligence (AI) can be implemented in qualitative research protocols. Emerging quantitative methodologies aim to better understand dynamic within-person processes. With repeated daily smartphone-based assessments (e.g. ecological momentary assessment) and passive sensor-based data collections (e.g. digital phenotyping), intensive longitudinal data can be collected that allow for n-of-1 trials, especially in combination with continuous glucose monitoring. Quantitative data can also be used to identify clusters/subgroups of people with shared experiences. Innovative digital twin technology and AI offer intriguing possibilities that can advance the field towards precision mental health care. Several innovative methodologies (will) enrich our understanding of psychosocial aspects in diabetes. To fully capitalise on these methodologies, co-design and mixed methods approaches are necessary.

Aims:To develop and evaluate the German versions of the Diabetes Stigma Assessment Scales for type 1 (DSAS-1) and type 2 diabetes (DSAS-2). Methods:The questionnaires were translated using a standardized translation and back-translation procedure. Adults with type 1 (N=636) and type 2 diabetes (N=177) completed the DSAS-1 and DSAS-2 via an online panel. Factor analyses, internal consistency (Cronbach's α), and correlations with convergent measures and discriminant constructs were conducted to assess reliability and validity. Results:For the DSAS-1, the expected three-factor structure was confirmed; for the DSAS-2, a two-factor solution emerged, although a forced three-factor analysis supported the original structure with minor cross-loadings. Scale consistencies were excellent (DSAS-1: 0.94, DSAS-2: 0.95, and subscales: 0.86-0.93). Both scales showed good concurrent, convergent and discriminant validity. The DSAS-2 showed stronger associations with weight self-stigma and self-esteem than the DSAS-1, consistent with its focus on internalized stigma. Three in four persons (type 1 diabetes: 74% and type 2 diabetes: 72%) endorsed at least one stigma item, mostly related to "blame and judgement." Conclusions:Diabetes stigma constitutes an important psychosocial problem. The German DSAS-1and DSAS-2 are reliable, valid instruments for assessing diabetes stigma. Blame and judgement appeared as the most common form of stigma experienced in this sample.

Background: Diabetes technologies, such as continuous glucose monitoring (CGM), insulin pumps, and automated insulin delivery (AID) systems, are increasingly used by people with type 2 diabetes (PWT2D), with growing clinical evidence supporting their therapeutic benefit. To describe the extent of adoption, perceived benefits, and future expectations, both health care professionals (HCPs) and PWT2D data from the dt-report 2025 were analyzed. Methods: From November to December 2025, HCP and PWT2D participated in the dt-report providing their attitudes, expectations, and predictions regarding the use of diabetes technology in type 2 diabetes. Frequencies from specific responses were analyzed. Results: Data from 1078 HCPs and 450 PWT2D from the DACH region were analyzed for questions regarding the use of technology in type 2 diabetes. Continuous glucose monitoring was the most widely endorsed technology across both groups, with 58% of the survey participants using a CGM, and 1% using a pump. Health care professionals estimated 87% of PWT2D on intensive insulin therapy would benefit from CGM and saw indications among non-intensive insulin users (62%) and those on oral therapies (55%). Future use of CGM and AID systems was anticipated by both HCPs and PWT2D, including many currently not using such systems. Smart pens and stand-alone insulin pumps were viewed less favorably. Reported barriers included lack of awareness, reimbursement limitations, digital literacy, and usability concerns. Conclusion: The findings indicate growing openness toward diabetes technologies among PWT2D and broader perceived indications among HCPs. However, uptake remains limited, particularly outside of intensive insulin therapy. These insights are of relevance for future clinical guidance, access strategies, and patient education.

Objective: As part of the 2025 diabetes and technology (dt)-report, this study explored indications for use, barriers to adoption, and perceived functionality of smart pens. Methods: An online survey conducted between November and December 2024 gathered responses from diabetes specialists and diabetes educators (health care professionals [HCPs]) in Germany (DE), Austria (AT), Switzerland (CH), and Spain (ES). Participants estimated the proportion of individuals with diabetes who would benefit from smart pens, rated the significance of specific functions, and evaluated barriers on 5-point scales. Results: The survey included 1294 HCPs (69.2% DE, 9.7% AT, 7.0% CH; 14.1% ES). Current usage of smart pens is estimated at 4% to 15% for people with type 1 diabetes and 3% to 6% for those with type 2 diabetes. However, the indication rate is markedly higher, ranging from 51% to 73% for people with type 1 and up to 69% for those with type 2 with intensive insulin therapy. Most valued features included reminders for missed insulin doses (4.4 ± 0.7), bolus dose suggestions (4.1 ± 0.8), integration with continuous glucose monitoring (CGM) apps (4.1 ± 0.8), and temperature alerts (3.7 ± 1.0). Basal insulin suggestions were considered less important (3.3 ± 1.1). No significant differences were found between physicians and diabetes educators. Major barriers included preference for disposable pens (57%), limited device options (54%), and high cost (53%). Among DE respondents, concerns over cost reimbursement rose compared to the 2024 dt-report. Conclusion: Smart pens are underutilized compared to expectations. Cost and reimbursement remain the predominant barriers, while reminder functionality stands out as the most valued feature.

AIMS:Health-related quality of life (HRQoL) is a key patient-reported outcome in diabetes care, yet the extent to which somatic and psychological factors are associated with HRQoL remains unclear. This study examined how demographic, diabetes-related, medical, and psychological factors were independently associated with HRQoL in adults with diabetes. MATERIALS AND METHODS:A cross-sectional online survey was conducted among adults with diabetes in Germany (September 2024-February 2025). HRQoL was assessed using the EuroQol 5-Dimension 5-Level questionnaire (EQ-5D-5L). Participants also completed the PHQ-8 for depressive symptoms, the problem areas in diabetes (PAID) scale, and the hypoglycaemia fear survey (HFS-II). Clinical variables were self-reported and included diabetes type, duration, HbA1c, body mass index (BMI), and complications. Tobit regression accounted for the censored EQ-5D distribution. Blockwise multivariable models evaluated incremental explained variance across demographic, diabetes-related, comorbidity, and mental-health domains. RESULTS:Of 1581 invitees, 734 completed the EQ-5D (mean age 56 ± 14 years; 73% type I). In multivariable analyses, female sex (β = -0.045), higher BMI (β = -0.029), diabetic foot syndrome (β = -0.078), neuropathy (β = -0.123), and elevated depressive symptoms (β = -0.212), diabetes distress (β = -0.069), and fear of hypoglycaemia (β = -0.085) were all independently associated with lower EQ-5D utilities (p < 0.01). Mental-health variables explained a similar proportion of variance (≈22%) as diabetes-related complications (≈20%). Mental health factors like depression, diabetes distress, and fear of hypoglycaemia showed highly significant associations with reduced HRQoL by up to 27%. CONCLUSIONS:Both diabetes complications and mental health determine HRQoL in people with diabetes. Depression emerged as the strongest independent predictor reducing HRQoL by up to 21%. This underscores the importance of mental health for HRQoL. This findings highlight the relevance of integrating mental health assessment into diabetes management.

Background: Automated insulin delivery (AID) systems improve glycemic control and reduce treatment burden in people with type 1 diabetes, yet their uptake remains suboptimal in many countries. Understanding barriers to the usage of AID systems from the health care professional (HCP) perspective is essential to support wider adoption. Methods: Physicians and diabetes educators/nurses were invited to complete an online survey assessing the current use of diabetes technology as well as attitudes and barriers to AID and insulin pump therapy. The survey was conducted from October to December 2022. A network analysis was conducted to analyze the associations between different barriers to usage of AID systems and insulin pumps. Results: Data from 594 HCPs (220 physicians and 374 diabetes educators/nurses) were analyzed. In 2022, HCPs estimated that 11% of their patients with type 1 diabetes used an AID system. They reported that 20% to 27% of eligible patients refuse to use an AID system; 5% to 7% of the users of an AID system stopped using it. The majority of HCPs (68.4% and 60.7%) reported an increased need for education. The most important barriers to start using an AID system were a lack of training and education materials, body image issues, overload, and insufficient training of the members of the diabetes team. Conclusions: There was a sharp increase in AID use in Germany from 2019 to 2022. The results highlight the need for adequate training materials for people with diabetes and the diabetes team.

The aim of the study was to examine the course of diabetes distress and depressive symptoms and their predictors of incidence and remission in individuals with type 1 and type 2 diabetes. Data were collected every 6 months over a 24 month period. Participants (n=654) completed measures of diabetes distress (Problem Areas in Diabetes Scale) and depressive symptoms (Patient Health Questionnaire 8). Cox proportional hazards models were applied to examine predictors of incidence and remission, considering demographic, clinical and psychosocial factors. All predictors were assessed at baseline, except for HbA1c, which was modelled as a time-varying covariate. Diabetes distress showed cumulative incident cases in 21

Aims Continuous glucose monitoring (CGM) is now standard of care for insulin-treated people with diabetes (PwD) and expanding to broader patient groups. Barriers to CGM-related training and awareness among healthcare professionals (HCPs) in different roles should be removed to allow broader access to CGM. We developed a role-based competency framework that stratifies CGM-related knowledge and skills for HCPs interacting with PwD who use CGM. Methods A multidisciplinary, international panel of CGM-experienced clinicians and diabetes educators developed the competence framework. Draft competencies were derived from published guidance, reviewed and refined, then organized into domains and mapped to four responsibility levels. Results The framework comprises four levels (awareness, competence, expertise, leadership) across the domains of system knowledge, clinical application, special situations and leadership. Levels are defined by a HCP’s role rather than professional title. For each level, the framework specifies core knowledge, skills and appropriate referral strategies. The resulting structure helps to reduce implementation barriers and aligns level-specific training with defined clinical responsibilities and tailored referral pathways. Conclusions This consensus-driven, role-oriented framework offers a pragmatic structure for CGM-related education by mapping competencies to different roles and skills, thus enabling HCPs to introduce CGM as a meaningful benefit for both themselves and PwD.

Background: Automated insulin delivery (AID) systems can significantly improve glycemic outcomes in people with type 1 diabetes (PWT1D). Despite their clinical efficacy, little is known about their uptake in clinical care, or about the perspectives and experiences of health care professionals (HCPs) and people with diabetes (PWD) with this relatively new technology. Furthermore, research is limited on broader populations, such as people with type 2 diabetes (PWT2D) and cross-country comparisons. Methods: This study analyzes data from the dt-report 2025, a multinational online survey of PWD and HCPs from Germany, Austria, Switzerland, and Spain, which was conducted at the end of 2024. The surveys assessed, among others, AID relevance, indications, barriers, daily use, satisfaction, and support needs. Results: In total, 1294 HCPs and 2535 PWD from Germany, Austria, Switzerland, and Spain took part. Health care professionals identified fully closed-loop systems as the most promising future therapy. While 90% of PWT1D were seen as candidates for AID therapy, 55% of PWT2D on intensified insulin therapy were also considered likely to benefit. Nonetheless, 22% of eligible PWD rejected AID, citing device burden and general concerns regarding its usability. Health care professionals reported a discontinuation rate of 8%. Satisfaction with AID was generally high. Regression analyses identified technical problems, lack of trust, and unrealistic expectations as significant predictors of lower satisfaction and poorer management in PWD. Conclusion: Despite increasing user rates of AID systems, a significant proportion reports problems in managing this technology or aborting its use. Addressing reasons for this may increase the uptake in clinical care. There was also a positive view of HCPs on AID use in PWT2D.