Norbert Hermanns

Aims/hypothesis: The aims were to: (1) analyse the day-to-day mechanisms through which daily diabetes-specific negative emotional experiences (burdens) accumulate and potentially affect emotional well-being; and (2) identify the specific triggers of these dynamics in people with type 1 and type 2 diabetes. Methods: Data were derived from three prospective observational studies employing ecological momentary assessment for up to 17 days. Multilevel vector autoregression models were used to estimate within-person temporal networks of nine daily diabetes-specific burdens. Out-strength and in-strength indices quantified each variable’s role as a trigger (i.e. influencing others) or receiver (i.e. being influenced by others). Individual network density was computed to characterise how strongly daily burdens predicted one another. Logistic regression models tested whether these dynamic features predicted questionnaire-assessed incidence and remission of elevated diabetes distress and depressive symptoms at follow-up. Results: Among 741 participants (50.1% with type 2 diabetes, 50.7% male, aged [mean ± SD] 50.4±14.2 years, HbA _1c [mean ± SD] 65±18.6 mmol/mol [8.1±1.7%]), ‘feelings of guilt’ regarding suboptimal self-management emerged as the most significant trigger of other negative emotional experiences/burdens. In type 1 diabetes, greater ‘feelings of guilt’ on one day were temporally associated with increased levels of ‘feeling alone’ (β=0.09, p p =0.016), ‘feeling restricted’ (β=0.05, p =0.015) and ‘feeling burdened by hyperglycaemia’ (β=0.05, p =0.030) on the following day. In type 2 diabetes, ‘feelings of guilt’ functioned primarily as a receiver. Greater ‘feelings of guilt’ on one day were predicted by ‘feeling alone’ (β=−0.07, p =0.016) and ‘feeling burdened by hypoglycaemia’ (β=0.04, p =0.017) on the previous day. Higher individual network density predicted greater odds of incident elevated diabetes distress (OR 1.50, p =0.025) and depressive symptoms (OR 2.08, p <0.001), with ‘feelings of guilt’ and ‘feeling restricted’ as the most relevant predictors. Conclusions/interpretation: The results provide evidence of how daily diabetes-specific burdens can accumulate and potentially affect the course of emotional well-being. Feeling guilty regarding diabetes self-management may play a central role and represent an important clinical target as well as outcome. Trial registration: ClinicalTrials.gov NCT03811132, NCT04438018, NCT05548699.

Diabetes distress is the emotional burden that arises from living with, and self-managing, diabetes. The aim of this clinical guideline is to optimise the assessment and management of diabetes distress among adults with type 1 diabetes or type 2 diabetes, promoting consistent, person-centred care. The guideline was developed using the EASD Standard Operating Procedure, GRADE methodology and RIGHT reporting standards. A multidisciplinary Guideline Development Panel, including lived experience experts, formulated clinical questions using the PICOT framework. Two clinical questions were addressed: (1) optimal approaches and timing for identifying and exploring diabetes distress; (2) the effectiveness of psychological, psychoeducational, educational, peer support and technology-based interventions for reducing diabetes distress. Good Practice Statements on assessment were informed by de novo realist reviews. GRADE recommendations on management were derived from a commissioned systematic review and meta-analyses of RCTs. For adults with type 1 diabetes or type 2 diabetes, eight Good Practice Statements emphasise routine discussion of emotional well-being, use of validated tools, ongoing monitoring, collaborative care planning, documentation and availability of psychological support. For adults with type 1 diabetes, conditional GRADE recommendations support psychological interventions, continuous glucose monitoring and automated insulin delivery systems for reducing diabetes distress. For adults with type 2 diabetes, conditional GRADE recommendations support psychological, psychoeducational and educational interventions for reducing diabetes distress. The strengths of this guideline include its rigorous methodology and strong stakeholder engagement. Limitations include the scarcity of high-quality trials, particularly in low- and middle-income countries, and exclusion of non-randomised evidence. Implementation will require training and system-level support for integration into routine care, in addition to dissemination through peer-reviewed publications and open access formats. Graphical Abstract

Aims/hypothesis: Diabetes distress refers to the emotional and psychological burden specifically associated with living with and managing diabetes. We aimed to systematically identify, summarise and critically appraise the available evidence from RCTs assessing the efficacy of interventions for reducing diabetes distress among adults with type 1 or type 2 diabetes. Methods: We searched PubMed, the Cochrane Library, APA PsycInfo and CINAHL from inception until 23 September 2024. Studies were eligible if they were RCTs conducted in adults (aged ≥18 years) with type 1 or type 2 diabetes in which the effect of an active intervention on diabetes distress was recorded as a primary or a secondary outcome. Studies with combined populations (e.g. children plus adults) where no separate results were reported for adults were excluded. When possible, we performed a random-effects meta-analysis of the standardised mean difference (SMD) of the endpoint, diabetes distress, measured with a validated questionnaire. We conducted subgroup analyses based on baseline diabetes distress level, intervention delivery method, risk of bias assessment (using the Cochrane RoB2 tool) and trial duration. We used GRADE methodology to assess the certainty of evidence. Results: We included 248 trials, with 59 trials reporting on psychological interventions, 68 on psychoeducational interventions and 121 on miscellaneous interventions (non-psychological or non-psychoeducational, i.e. education without a psychological component, peer support without a psychological component, devices, telehealth, health behaviours and a heterogeneous group of other interventions). In total, 52 trials included participants with type 1 diabetes (including two during pregnancy), 160 included participants with type 2 diabetes, and 36 included mixed/undefined populations of adults with diabetes. The total sample size was 55,497 participants (range 12–4034). The analysed trials were judged to have either some concerns for risk of bias (94 trials) or a high risk of bias (71 trials). Compared with usual care, psychological interventions reduced diabetes distress in adults with type 1 diabetes (SMD −0.22 [95% CI −0.35, −0.08]; N =16; GRADE = low) and type 2 diabetes (SMD −0.31 [95% CI −0.50, −0.13]; N =21; GRADE = very low). Additionally, continuous glucose monitoring (CGM) or intermittently scanned glucose monitoring reduced diabetes distress in adults with type 1 diabetes, compared with standard blood glucose measurement (SMD −0.26 [95% CI −0.41, −0.11]; N =6; GRADE = moderate), while educational interventions reduced diabetes distress in adults with type 2 diabetes, compared with usual care (SMD −0.34 [95% CI −0.56, −0.11]; N =3; GRADE = low). Other comparisons, including those of psychological, psychoeducational, peer support, educational and device-based interventions with various active control interventions or usual care, did not show statistically significant effects. The results did not differ meaningfully across predefined subgroups. The certainty of evidence as assessed by GRADE methodology was moderate, low or very low in two, five and seven comparisons, respectively. No meta-analyses could be conducted for telehealth, health behaviours and the assorted mixed interventions due to heterogeneity or an insufficient number of studies. Conclusions/interpretation: Psychological interventions reduced diabetes distress among adults with type 1 diabetes and those with type 2 diabetes, while devices reduced diabetes distress in adults with type 1 diabetes and education reduced diabetes distress in adults with type 2 diabetes. Most other interventions showed little or no clear effect. Funding: European Association for the Study of Diabetes. Registration: PROSPERO registration no. CRD42024598512.

Background: Patch insulin pumps are often treated as a single class, although fully disposable and semi-reusable designs differ in cost and waste. We evaluated real-world clinical, pharmacoeconomic, and environmental outcomes of a semi-reusable tubeless insulin pump (Microtech Equil™, referred as SR-TIP). Methods: Prospective, multicentre, open-label real-world study in adults with type 1 or type 2 diabetes transitioning from continuous subcutaneous insulin infusion (CSII) or multiple daily injections (MDI). Follow-up was 3 months. Primary endpoints were HbA1c non-inferiority and change in hypoglycaemic event frequency. Secondary endpoints included safety, device deficiencies, patient-reported outcomes (Diabetes Treatment Satisfaction Questionnaire, Device Assessment Questionnaire), monthly disposable treatment costs, and waste based on disposable component counts and material composition. Results: Ninety-seven participants completed follow-up (CSII n = 79; MDI n = 18). HbA1c changes met non-inferiority criteria in both groups. Hypoglycaemic events decreased by 45% in CSII users and 86% in MDI users. Device-related adverse events were infrequent and mainly mild. Among participants previously using fully disposable tubeless pumps, mean monthly disposable treatment costs decreased by €108.6 (p < 0.001). The semi-reusable architecture eliminated routine disposal of batteries/electronic components and reduced overall waste. Conclusions: In routine care, a semi-reusable tubeless pump maintained glycaemic control while reducing hypoglycaemia and disposable costs versus fully disposable patch pumps, with measurable reductions in electronic waste. These data support value-based, sustainable diabetes technology adoption.

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.

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 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: 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.

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.