Perceived glucose levels matter more than CGM-based data in predicting diabetes distress in type 1 or type 2 diabetes: a precision mental health approach using n-of-1 analyses.

AIMS/HYPOTHESIS: Diabetes distress is one of the most frequent mental health issues identified in people with type 1 and type 2 diabetes. Little is known about the role of glucose control as a potential contributor to diabetes distress and whether the subjective perception of glucose control or the objective glycaemic parameters are more important for the experience. With the emergence of continuous glucose monitoring (CGM), this is a relevant question as glucose values are now visible in real-time. We employed a precision monitoring approach to analyse the independent associations of perceived and measured glucose control with diabetes distress on a daily basis. By using n-of-1 analyses, we aimed to identify individual contributors to diabetes distress per person and analyse the associations of these individual contributors with mental health at a 3 month follow-up. METHODS: In this prospective, observational study, perceived (hypoglycaemia/hyperglycaemia/glucose variability burden) and measured glucose control (time in hypoglycaemia and hyperglycaemia, CV) were assessed daily for 17 days using an ecological momentary assessment (EMA) approach with a special EMA app and CGM, respectively. Mixed-effect regression analysis was performed, with daily diabetes distress as the dependent variable and daily perceived and CGM-measured metrics of glucose control as random factors. Individual regression coefficients of daily distress with perceived and CGM-measured metrics were correlated with levels of psychosocial well-being at a 3 month follow-up. RESULTS: Data from 379 participants were analysed (50.9% type 1 diabetes; 49.6% female). Perceived glucose variability (t=14.360; p<0.0001) and perceived hyperglycaemia (t=13.637; p<0.0001) were the strongest predictors of daily diabetes distress, while CGM-based glucose variability was not significantly associated (t=1.070; p=0.285). There was great heterogeneity between individuals in the associations of perceived and measured glucose parameters with diabetes distress. Individuals with a stronger association between perceived glucose control and daily distress had more depressive symptoms (ß=0.32), diabetes distress (ß=0.39) and hypoglycaemia fear (ß=0.34) at follow-up (all p<0.001). Individuals with a stronger association between CGM-measured glucose control and daily distress had higher levels of psychosocial well-being at follow-up (depressive symptoms: ß=-0.31; diabetes distress: ß=-0.33; hypoglycaemia fear: ß=-0.27; all p<0.001) but also higher HbA1c (ß=0.12; p<0.05). CONCLUSIONS/INTERPRETATION: Overall, subjective perceptions of glucose seem to be more influential on diabetes distress than objective CGM parameters of glycaemic control. N-of-1 analyses showed that CGM-measured and perceived glucose control had differential associations with diabetes distress and psychosocial well-being 3 months later. The results highlight the need to understand the individual drivers of diabetes distress to develop personalised interventions within a precision mental health approach.

Effectiveness of the MyDiaMate application in reducing diabetes distress in adults with type 1 diabetes: Study protocol of the multi-national, randomised-controlled MyREMEDY trial.

AIMS: Diabetes distress is common among people with type 1 diabetes (T1D), negatively affecting quality of life, self management, and diabetes outcomes. E-health-based interventions could be an effective and low-cost way to improve the psychological care for people with T1D experiencing diabetes distress. The MyREMEDY study aims to test the effectiveness of the online unguided self-help intervention MyDiaMate in decreasing diabetes distress in adults with T1D. MyDiaMate is based on Cognitive Behavioural Therapy and consists of eight modules, each focusing on a different aspect of living with T1D that is often experienced as burdensome (e.g. hypoglycaemia, fatigue). METHODS: The effectiveness of MyDiaMate will be tested through a randomised-controlled trial across four European countries (the Netherlands, Germany, Spain and the United Kingdom). Six hundred and sixty adults (N = 165 per country) with T1D will be recruited and randomised with a balance of 2:1 into the intervention and care as usual groups. Intervention group members receive access to MyDiaMate for 6 months, care as usual group members receive access after 3 months for 3 months. Participants fill in questionnaires at 0 (baseline), 3 (effectiveness) and 6 months (follow-up). Primary outcome is diabetes distress at 3 months. Secondary outcomes are emotional well-being, psychological self-efficacy in relation to diabetes, social engagement, fatigue, and glycaemic outcomes. Moreover, logdata of MyDiaMate use is passively collected. Linear mixed model analyses will be used to test the effectiveness of MyDiaMate along with identifying which user subgroup benefits most from MyDiaMate use. TRIAL REGISTRATION: Clinicaltrials.gov NCT06308549.

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.

Somatic and mental symptoms associated with dysglycaemia, diabetes-related complications and mental conditions in people with diabetes: Assessments in daily life using continuous glucose monitoring and ecological momentary assessment.

AIM: To analyse the potential drivers (glucose level, complications, diabetes type, gender, age and mental health) of diabetes symptoms using continuous glucose monitoring (CGM) and ecological momentary assessment. MATERIALS AND METHODS: Participants used a smartphone application to rate 25 diabetes symptoms in their daily lives over 8 days. These symptoms were grouped into four blocks so that each symptom was rated six times on 2 days (noon, afternoon and evening). The symptom ratings were associated with the glucose levels for the previous 2 hours, measured with CGM. Linear mixed-effects models were used, allowing for nested random effects and the conduct of N = 1 analysis of individual associations. RESULTS: In total, 192 individuals with type 1 diabetes and 179 with type 2 diabetes completed 6380 app check-ins. Four symptoms showed a significant negative association with glucose values, indicating higher ratings at lower glucose (speech difficulties, P = .003; coordination problems, P = .00005; confusion, P = .049; and food cravings, P = .0003). Four symptoms showed a significant positive association with glucose values, indicating higher scores at higher glucose (thirst, P = .0001; urination, P = .0003; taste disturbances, P = .021; and itching, P = .0120). There were also significant positive associations between microangiopathy and eight symptoms. Elevated depression and diabetes distress were associated with higher symptom scores. N = 1 analysis showed highly idiosyncratic associations between symptom reports and glucose levels. CONCLUSIONS: The N = 1 analysis facilitated the creation of personalized symptom profiles related to glucose levels with consideration of factors such as complications, gender, body mass index, depression and diabetes distress. This approach can enhance precision monitoring for diabetes symptoms in precision medicine.

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.

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.

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.

Real-time continuous glucose monitoring in adults with type 1 diabetes and impaired hypoglycaemia awareness or severe hypoglycaemia treated with multiple daily insulin injections (HypoDE): a multicentre, randomised controlled trial.

BACKGROUND: The effectiveness of real-time continuous glucose monitoring (rtCGM) in avoidance of hypoglycaemia among high-risk individuals with type 1 diabetes treated with multiple daily insulin injections (MDI) is unknown. We aimed to ascertain whether the incidence and severity of hypoglycaemia can be reduced through use of rtCGM in these individuals. METHODS: The HypoDE study was a 6-month, multicentre, open-label, parallel, randomised controlled trial done at 12 diabetes practices in Germany. Eligible participants had type 1 diabetes and a history of impaired hypoglycaemia awareness or severe hypoglycaemia during the previous year. All participants wore a masked rtCGM system for 28 days and were then randomly assigned to 26 weeks of unmasked rtCGM (Dexcom G5 Mobile system) or to the control group (continuing with self-monitoring of blood glucose). Block randomisation with 1:1 allocation was done centrally, with the study site as the stratifying variable. Masking of participants and study sites was not possible. Control participants wore a masked rtCGM system during the follow-up phase (weeks 22-26). The primary outcome was the baseline-adjusted number of hypoglycaemic events (defined as glucose ≤3·0 mmol/L for ≥20 min) during the follow-up phase. The full dataset analysis comprised participants who wore the rtCGM system during the baseline and follow-up phases. The intention-to-treat analysis comprised all randomised participants. This trial is registered with ClinicalTrials.gov, number NCT02671968. FINDINGS: Between March 4, 2016, and Jan 12, 2017, 149 participants were randomly assigned (n=74 to the control group; n=75 to the rtCGM group) and 141 completed the follow-up phase (n=66 in the control group, n=75 in the rtCGM group). The mean number of hypoglycaemic events per 28 days among participants in the rtCGM group was reduced from 10·8 (SD 10·0) to 3·5 (4·7); reductions among control participants were negligible (from 14·4 [12·4] to 13·7 [11·6]). Incidence of hypoglycaemic events decreased by 72% for participants in the rtCGM group (incidence rate ratio 0·28 [95% CI 0·20-0·39], p<0·0001). 18 serious adverse events were reported: seven in the control group, ten in the rtCGM group, and one before randomisation. No event was considered to be related to the investigational device. INTERPRETATION: Usage of rtCGM reduced the number of hypoglycaemic events in individuals with type 1 diabetes treated by MDI and with impaired hypoglycaemia awareness or severe hypoglycaemia. FUNDING: Dexcom Inc.

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.

Effect of automated insulin delivery systems on person-reported outcomes in people with diabetes: a systematic review and meta-analysis.

Background: Conclusive evidence on the benefits of automated insulin delivery (AID) systems on person-reported outcomes (PROs) is missing. Methods: In this systematic review and meta-analysis, four databases (PubMed, PsycINFO, Cochrane, and GoogleScholar) were searched from inception up to August 7th, 2024. All types of studies were included if studies reported on PROs in people with diabetes using an AID system. All types of control groups in randomised controlled trials (RCT) were included. Summary data were extracted by three reviewers. Main outcomes focused on diabetes distress, fear of hypoglycaemia and quality of life. Meta-analyses were conducted for RCTs and observational studies separately. When five or more studies could be pooled, random-effects meta-analysis was used, otherwise common-effects meta-analysis was used. Risk of bias was evaluated with Cochrane tools. This study was registered with PROSPERO, CRD42022352502. Findings: A total of 62 studies (n = 9253) were included reporting on 45 different questionnaires. Twenty-seven studies were RCTs and 25 were observational studies. RCT meta-analyses showed reduced diabetes distress (standardised mean difference [95% CI]: -0.159 [-0.309, -0.010], I2 = 23.0%), reduced fear of hypoglycaemia (-0.339 [-0.566, -0.111], I2 = 42.6%), and improved hypoglycaemia unawareness (-0.231 [-0.424, -0.037], I2 = 0.0%), quality of life in adults (0.347 [0.134, 0.560], I2 = 0.0%) and children/adolescents (0.249 [0.050, 0.448], I2 = 0.0%). Observational meta-analyses corroborated improvements in diabetes distress (-0.217 [-0.403, -0.031], I2 = 68.5%), fear of hypoglycaemia (-0.445 [-0.540, -0.349], I2 = 0.0%), hypoglycaemia unawareness (-0.212 [-0.419, -0.004], I2 = 0.0%), and showed improved sleep quality (-0.158 [-0.255, -0.061], I2 = 0.0%). Interpretation: We found low to moderate effect sizes indicating that AID therapy is associated with reduced burden and improved well-being in people with diabetes. Evidence comes from both RCTs and observational studies. However, for some PROs only a limited number of studies could be pooled with a large heterogeneity in questionnaires used. More research is needed with a more uniformed assessment of PROs to demonstrate the added value of AID therapy on psychosocial outcomes. Funding: None.

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.

Clinical Usage and Potential Benefits of a Continuous Glucose Monitoring Predict App.

Continuous glucose monitoring (CGM) has become an increasingly important tool for self-management in people with diabetes mellitus (DM). In this paper, we discuss recommendations on how to implement predictive features provided by the Accu-Chek SmartGuide Predict app in clinical practice. The Predict app's features are aimed at ultimately reducing diabetes stress and fear of hypoglycemia in people with DM. Furthermore, we explore the use cases and potential benefits of continuous glucose prediction, predictions of low glucose, and nocturnal hypoglycemia.

How to Use Continuous Glucose Monitoring Efficiently in Diabetes Management: Opinions and Recommendations by German Experts on the Status and Open Questions.

Today, continuous glucose monitoring (CGM) is a standard diagnostic option for patients with diabetes, at least for those with type 1 diabetes and those with type 2 diabetes on insulin therapy, according to international guidelines. The switch from spot capillary blood glucose measurement to CGM was driven by the extensive and immediate support and facilitation of diabetes management CGM offers. In patients not using insulin, the benefits of CGM are not so well studied/obvious. In such patients, factors like well-being and biofeedback are driving CGM uptake and outcome. Apps can combine CGM data with data about physical activity and meal consumption for therapy adjustments. Personalized data management and coaching is also more feasible with CGM data. The same holds true for digitalization and telemedicine intervention ("virtual diabetes clinic"). Combining CGM data with Smart Pens ("patient decision support") helps to avoid missing insulin boluses or insulin miscalculation. Continuous glucose monitoring is a major pillar of all automated insulin delivery systems, which helps substantially to avoid acute complications and achieve more time in the glycemic target range. These options were discussed by a group of German experts to identify concrete gaps in the care structure, with a view to the necessary structural adjustments of the health care system.

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.

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).

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.

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.