Participatory Development of an Integrated, eHealth-Supported, Educational Care Pathway (Diabetes Box) for People With Type 2 Diabetes: Development and Usability Study.

BACKGROUND: Type 2 diabetes (T2D) tremendously affects patient health and health care globally. Changing lifestyle behaviors can help curb the burden of T2D. However, health behavior change is a complex interplay of medical, behavioral, and psychological factors. Personalized lifestyle advice and promotion of self-management can help patients change their health behavior and improve glucose regulation. Digital tools are effective in areas of self-management and have great potential to support patient self-management due to low costs, 24/7 availability, and the option of dynamic automated feedback. To develop successful eHealth solutions, it is important to include stakeholders throughout the development and use a structured approach to guide the development team in planning, coordinating, and executing the development process. OBJECTIVE: The aim of this study is to develop an integrated, eHealth-supported, educational care pathway for patients with T2D. METHODS: The educational care pathway was developed using the first 3 phases of the Center for eHealth and Wellbeing Research roadmap: the contextual inquiry, the value specification, and the design phase. Following this roadmap, we used a scoping review about diabetes self-management education and eHealth, past experiences of eHealth practices in our hospital, focus groups with health care professionals (HCPs), and a patient panel to develop a prototype of an educational care pathway. This care pathway is called the Diabetes Box (Leiden University Medical Center) and consists of personalized education, digital educational material, self-measurements of glucose, blood pressure, activity, and sleep, and a smartphone app to bring it all together. RESULTS: The scoping review highlights the importance of self-management education and the potential of telemonitoring and mobile apps for blood glucose regulation in patients with T2D. Focus groups with HCPs revealed the importance of including all relevant lifestyle factors, using a tailored approach, and using digital consultations. The contextual inquiry led to a set of values that stakeholders found important to include in the educational care pathway. All values were specified in biweekly meetings with key stakeholders, and a prototype was designed. This prototype was evaluated in a patient panel that revealed an overall positive impression of the care pathway but stressed that the number of apps should be restricted to one, that there should be no delay in glucose value visualization, and that insulin use should be incorporated into the app. Both patients and HCPs stressed the importance of direct automated feedback in the Diabetes Box. CONCLUSIONS: After developing the Diabetes Box prototype using the Center for eHealth and Wellbeing Research roadmap, all stakeholders believe that the concept of the Diabetes Box is useful and feasible and that direct automated feedback and education on stress and sleep are essential. A pilot study is planned to assess feasibility, acceptability, and usefulness in more detail.

Impact of a Public Health Emergency on Behavior, Stress, Anxiety and Glycemic Control in Patients With Pancreas or Islet Transplantation for Type 1 Diabetes.

A public health emergency such as the COVID-19 pandemic has behavioral, mental and physical implications in patients with type 1 diabetes (T1D). To what extent the presence of a transplant further increases this burden is not known. Therefore, we compared T1D patients with an islet or pancreas transplant (ß-cell Tx; n = 51) to control T1D patients (n = 272). Fear of coronavirus infection was higher in those with ß-cell Tx than without (Visual Analogue Scale 5.0 (3.0-7.0) vs. 3.0 (2.0-5.0), p = 0.004) and social isolation behavior was more stringent (45.8% vs. 14.0% reported not leaving the house, p < 0.001). A previous ß-cell Tx was the most important predictor of at-home isolation. Glycemic control worsened in patients with ß-cell Tx, but improved in control patients (ΔHbA1c +1.67 ± 8.74 vs. -1.72 ± 6.15 mmol/mol, p = 0.006; ΔTime-In-Range during continuous glucose monitoring -4.5% (-6.0%-1.5%) vs. +3.0% (-2.0%-6.0%), p = 0.038). Fewer patients with ß-cell Tx reported easier glycemic control during lockdown (10.4% vs. 22.6%, p = 0.015). All T1D patients, regardless of transplantation status, experienced stress (33.4%), anxiety (27.9%), decreased physical activity (42.0%), weight gain (40.5%), and increased insulin requirements (29.7%). In conclusion, T1D patients with ß-cell Tx are increasingly affected by a viral pandemic lockdown with higher fear of infection, more stringent social isolation behavior and deterioration of glycemic control. This trial has been registered in the clinicaltrials.gov registry under identifying number NCT05977205 (URL: https://clinicaltrials.gov/study/NCT05977205).

Clinical impact of an integrated e-health system for diabetes self-management support and shared decision making (POWER2DM): a randomised controlled trial.

AIMS/HYPOTHESIS: There is a lack of e-health systems that integrate the complex variety of aspects relevant for diabetes self-management. We developed and field-tested an e-health system (POWER2DM) that integrates medical, psychological and behavioural aspects and connected wearables to support patients and healthcare professionals in shared decision making and diabetes self-management. METHODS: Participants with type 1 or type 2 diabetes (aged >18 years) from hospital outpatient diabetes clinics in the Netherlands and Spain were randomised using randomisation software to POWER2DM or usual care for 37 weeks. This RCT assessed the change in HbA1c between the POWER2DM and usual care groups at the end of the study (37 weeks) as a primary outcome measure. Participants and clinicians were not blinded to the intervention. Changes in quality of life (QoL) (WHO-5 Well-Being Index [WHO-5]), diabetes self-management (Diabetes Self-Management Questionnaire - Revised [DSMQ-R]), glycaemic profiles from continuous glucose monitoring devices, awareness of hypoglycaemia (Clarke hypoglycaemia unawareness instrument), incidence of hypoglycaemic episodes and technology acceptance were secondary outcome measures. Additionally, sub-analyses were performed for participants with type 1 and type 2 diabetes separately. RESULTS: A total of 226 participants participated in the trial (108 with type 1 diabetes; 118 with type 2 diabetes). In the POWER2DM group (n=111), HbA1c decreased from 60.6±14.7 mmol/mol (7.7±1.3%) to 56.7±12.1 mmol/mol (7.3±1.1%) (means ± SD, p<0.001), compared with no change in the usual care group (n=115) (baseline: 61.7±13.7 mmol/mol, 7.8±1.3%; end of study: 61.0±12.4 mmol/mol, 7.7±1.1%; p=0.19) (between-group difference 0.24%, p=0.008). In the sub-analyses in the POWER2DM group, HbA1c in participants with type 2 diabetes decreased from 62.3±17.3 mmol/mol (7.9±1.6%) to 54.3±11.1 mmol/mol (7.1±1.0%) (p<0.001) compared with no change in HbA1c in participants with type 1 diabetes (baseline: 58.8±11.2 mmol/mol [7.5±1.0%]; end of study: 59.2±12.7 mmol/mol [7.6±1.2%]; p=0.84). There was an increase in the time during which interstitial glucose levels were between 3.0 and 3.9 mmol/l in the POWER2DM group, but no increase in clinically relevant hypoglycaemia (interstitial glucose level below 3.0 mmol/l). QoL improved in participants with type 1 diabetes in the POWER2DM group compared with the usual care group (baseline: 15.7±3.8; end of study: 16.3±3.5; p=0.047 for between-group difference). Diabetes self-management improved in both participants with type 1 diabetes (from 7.3±1.2 to 7.7±1.2; p=0.002) and those with type 2 diabetes (from 6.5±1.3 to 6.7±1.3; p=0.003) within the POWER2DM group. The POWER2DM integrated e-health support was well accepted in daily life and no important adverse (or unexpected) effects or side effects were observed. CONCLUSIONS/INTERPRETATION: POWER2DM improves HbA1c levels compared with usual care in those with type 2 diabetes, improves QoL in those with type 1 diabetes, improves diabetes self-management in those with type 1 and type 2 diabetes, and is well accepted in daily life. TRIAL REGISTRATION: ClinicalTrials.gov NCT03588104. FUNDING: This study was funded by the European Union's Horizon 2020 Research and Innovation Programme (grant agreement number 689444).

Prevalence, associations and health outcomes of binge eating in adults with type 1 or type 2 diabetes: Results from Diabetes MILES - The Netherlands.

AIMS: To examine the prevalence and health risks of binge eating in people with diabetes. METHODS: Self-report data were analysed from a subsample (n = 582 type 1 diabetes/735 type 2 diabetes) of Diabetes MILES - the Netherlands, an online survey. Prevalence of binge eating was compared across diabetes type and treatment and between participants with and without binges for eating styles, diabetes treatment and outcomes, weight, BMI and psychological comorbidity. Associations between binge eating, HbA1c , BMI, diabetes distress were assessed using hierarchical linear regression analyses. RESULTS: 23% (n = 308) of participants reported eating binges, with 16% at least monthly, and 6% at least weekly. Prevalence and frequency of binges did not differ across diabetes type or treatment. People reporting binges scored higher on dietary restraint, emotional and external eating and reported higher weight and BMI than those without binges. Only people with type 1 diabetes and eating binges had a higher HbA1c . Hierarchical regression analyses demonstrated that binge eating was independently associated with higher HbA1c (ß = 0.12, p=0.001), BMI (ß = 0.13, p < 0.001) but not with diabetes distress. CONCLUSIONS: This study found binge eating to be associated with eating styles, BMI and HbA1c . However, our cross-sectional data do not allow for conclusions on causality. Future studies could further examine the directions of these associations and their clinical implications.

Change is possible: How increased patient activation is associated with favorable changes in well-being, self-management and health outcomes among people with type 2 diabetes mellitus: A prospective longitudinal study.

OBJECTIVE: To examine the relationship between risk factors for low patient activation and change in patient activation, well-being, and health outcomes in people with type 2 diabetes mellitus (T2DM). METHOD: A longitudinal prospective study was conducted with measurements at baseline and 20-week follow-up among 603 people with T2DM participating in a group-based walking intervention. Patient activation and risk factors were assessed using online questionnaires. Health outcomes were assessed in participants' general practices. RESULTS: No association was found between risk factors for activation and change in patient activation. Patient activation significantly increased (t(602) = 2.53, p = 0.012) and was associated with an increase in emotional well-being (ß = 0.22), exercise behavior (ß = 0.17), general diet behavior (ß = 0.20), and a reduction in BMI (ß = -0.28), weight (ß = -0.29), and HbA1c (ß = -0.27). CONCLUSION: Favorable changes in patient activation, self-management, well-being, and health outcomes occurred during a walking intervention, despite highly prevalent risk factors for low activation and less engagement in self-management. PRACTICE IMPLICATIONS: Group-based walking interventions might empower people with T2DM to begin taking a larger role in their self-care and improve (mental) health outcomes. Vulnerable groups of patients (with multiple risk factors for low activation) can change and presumably need this kind of interventions to be able to change.

Psychological factors associated with changes in physical activity in Dutch people with type 2 diabetes under societal lockdown: A cross-sectional study.

Aims: To investigate changes in physical activity (PA) and psychological factors during societal lockdown in people with type 2 diabetes. Methods: A cross-sectional study among Dutch adults with type 2 diabetes. Data were collected using online questionnaires. A multivariate multinomial logistic regression was performed with change in PA during societal lockdown as outcome and perceived change in stress, anxiety, perceived risk for COVID-19 infection, emotional well-being and former PA status as determinants. Results: Five hundred and sixty seven respondents filled out the questionnaire, 536 were included in the final analysis: mean age of 65.9 ± 7.9 years; mean diabetes duration 13.3 ± 8 years; 54% men; 47% reported no change in PA, 27% became less active and 26% became more active during societal lockdown. Participants who were more likely to become less active were participants who experienced more stress (OR: 2.27; 95% CI 1.25-4.13) or less stress (OR: 2.20; 95% CI 1.03-4.71). Participants who were more likely to become more active were participants who experienced more stress (OR: 2.31; 95% CI 1.25, 4.26). Participants with higher emotional well-being (OR: 0.98; 95% CI 0.97, 0.99) were less likely to become less active than to report no change in PA. Conclusions: Changes in PA in people with type 2 diabetes during societal lockdown are associated with changes in psychological factors such as perceived stress and emotional well-being. People with diabetes and their caregivers should be aware of these possible changes.

Increased stress, weight gain and less exercise in relation to glycemic control in people with type 1 and type 2 diabetes during the COVID-19 pandemic.

INTRODUCTION: Lockdown measures have a profound effect on many aspects of daily life relevant for diabetes self-management. We assessed whether lockdown measures, in the context of the COVID-19 pandemic, differentially affect perceived stress, body weight, exercise and related this to glycemic control in people with type 1 and type 2 diabetes. RESEARCH DESIGN AND METHODS: We performed a short-term observational cohort study at the Leiden University Medical Center. People with type 1 and type 2 diabetes ≥18 years were eligible to participate. Participants filled out online questionnaires, sent in blood for hemoglobin A1c (HbA1c) analysis and shared data of their flash or continuous glucose sensors. HbA1c during the lockdown was compared with the last known HbA1c before the lockdown. RESULTS: In total, 435 people were included (type 1 diabetes n=280, type 2 diabetes n=155). An increase in perceived stress and anxiety, weight gain and less exercise was observed in both groups. There was improvement in glycemic control in the group with the highest HbA1c tertile (type 1 diabetes: -0.39% (-4.3 mmol/mol) (p<0.0001 and type 2 diabetes: -0.62% (-6.8 mmol/mol) (p=0.0036). Perceived stress was associated with difficulty with glycemic control (p<0.0001). CONCLUSIONS: An increase in perceived stress and anxiety, weight gain and less exercise but no deterioration of glycemic control occurs in both people with relatively well-controlled type 1 and type 2 diabetes during short-term lockdown measures. As perceived stress showed to be associated with glycemic control, this provides opportunities for healthcare professionals to put more emphasis on psychological aspects during diabetes care consultations.

Psychological Symptoms and Quality of Life After Simultaneous Kidney and Pancreas Transplantation.

Patients that have undergone successful simultaneous pancreas/kidney (SPK) transplantation attain normoglycemia and are free from dialysis. However, only a minor improvement in quality of life (QOL) has been demonstrated. Here, we evaluated the role of psychological symptoms in QOL after SPK transplantation. METHODS: We assessed patients with type 1 diabetes and end-stage renal disease waitlisted for SPK transplantation (pre-SPK, n = 47), and recipients of an SPK transplant (post-SPK, n = 72). Matched patients with type 1 diabetes without end-stage renal disease were included as reference group (type 1 diabetes [T1D] reference group, n = 42). The brief symptom inventory (BSI) was used to measure psychological symptoms. The Short Form-36 (SF-36) was used to determine QOL. RESULTS: Post-SPK patients scored slightly better on the SF-36 than pre-SPK patients ("General health" 47.2 ± 23.1 versus 37.5 ± 18.1 [P = 0.017]). In the T1D reference group, this score was 60.6 ± 22.3. Post- and pre-SPK patients had similar BSI scores (0.54 ± 0.55 and 0.45 ± 0.42, respectively [P = 0.34]). This score was better in the T1D reference group (BSI score 0.32 ± 0.33). The BSI score inversely correlated with the SF-36 (r = -0.61, P < 0.001). CONCLUSIONS: Psychological symptoms are prevalent in both pre-SPK and post-SPK patients and could play an important role in the reduced QOL observed in these groups.

Empowering Diabetes Patients with Interventions Based on Behaviour Change Techniques.

The number of people with diabetes is increasing in every European country and like all chronic diseases it cannot be cured. However, patient empowerment is an acknowledged strategy for improving the patients' health situation. This paper describes the Action Plan Engine developed as a tool for diabetes patients in the POWER2DM project. The Action Plan Engine offers a guided workflow based on treatment goals and activities. A periodic review evaluates how successful a patient has fulfilled these goals and activities. Part of the evaluation is detailed feedback, in particular about 170 interventions based on Behaviour Change Techniques in order to change a patient's lifestyle behaviour towards a healthier, diabetes-appropriate lifestyle. Additionally, the Action Plan Engine offers decision trees for coping with barriers regarding glucose monitoring, exercise, carbohydrate, insulin and stress.

An expandable approach for design and personalization of digital, just-in-time adaptive interventions.

Objective: We aim to deliver a framework with 2 main objectives: 1) facilitating the design of theory-driven, adaptive, digital interventions addressing chronic illnesses or health problems and 2) producing personalized intervention delivery strategies to support self-management by optimizing various intervention components tailored to people's individual needs, momentary contexts, and psychosocial variables. Materials and Methods: We propose a template-based digital intervention design mechanism enabling the configuration of evidence-based, just-in-time, adaptive intervention components. The design mechanism incorporates a rule definition language enabling experts to specify triggering conditions for interventions based on momentary and historical contextual/personal data. The framework continuously monitors and processes personal data space and evaluates intervention-triggering conditions. We benefit from reinforcement learning methods to develop personalized intervention delivery strategies with respect to timing, frequency, and type (content) of interventions. To validate the personalization algorithm, we lay out a simulation testbed with 2 personas, differing in their various simulated real-life conditions. Results: We evaluate the design mechanism by presenting example intervention definitions based on behavior change taxonomies and clinical guidelines. Furthermore, we provide intervention definitions for a real-world care program targeting diabetes patients. Finally, we validate the personalized delivery mechanism through a set of hypotheses, asserting certain ways of adaptation in the delivery strategy, according to the differences in simulation related to personal preferences, traits, and lifestyle patterns. Conclusion: While the design mechanism is sufficiently expandable to meet the theoretical and clinical intervention design requirements, the personalization algorithm is capable of adapting intervention delivery strategies for simulated real-life conditions.

The effect of family-based multidisciplinary cognitive behavioral treatment on health-related quality of life in childhood obesity.

PURPOSE: To evaluate the effect of multidisciplinary treatment on obesity and health-related quality of life (HRQOL). METHODS: Obese children were randomized to a multidisciplinary lifestyle treatment, including medical, nutritional, physical, and psychological counseling during 3 months, (n = 40, BMI-SDS; 4.2 ± 0.7, age; 13.3 ± 2.0) or standard care, including an initial advice on nutrition and physical activity by the pediatrician (n = 39, BMI-SDS; 4.3 ± 0.7, age; 13.1 ± 1.9). At baseline, after 3 months of treatment and at 12 months follow-up, data were collected for BMI-SDS and a European validated questionnaire for assessing HRQOL (DISABKIDS). RESULTS: A significantly reduced BMI-SDS was found for the intervention group after 3 months treatment (4.0 ± 0.9 vs. 4.2 ± 0.7, P = 0.02) and at 12 months follow-up (3.8 ± 1.1 vs. 4.2 ± 0.7, P = 0.03). HRQOL in the intervention group was significantly improved at 12 months follow-up and unchanged in the obese control group. Agreement between child and parent report was moderate (67-85%), with parents reporting a lower HRQOL for their obese children than children themselves in both groups. CONCLUSION: Multidisciplinary treatment is effective in reducing BMI-SDS and improving HRQOL after 12 months follow-up.

Low goal ownership predicts drop-out from a weight intervention study in overweight patients with type 2 diabetes.

BACKGROUND: Drop-out is a major problem in weight loss studies. Although previous attrition research has examined some predictors of drop-out, theoretically grounded research on psychological predictors of drop-out from weight interventions has been lacking. PURPOSE: To examine psychological predictors of drop-out from a weight reduction study in diabetes type 2 patients. METHOD: A clinical trial was conducted with 101 overweight/obese (body mass index >27) diabetes type 2 patients. Patients were randomly assigned to a self-regulation intervention, an active control group, and a passive control group. Psychological, somatic, socio-demographic, and lifestyle variables were examined as predictors of drop-out from baseline to 6 months follow-up. RESULTS: Multiple logistic regression analysis indicated that low autonomous regulation or low 'goal ownership' was the best predictor of drop-out. CONCLUSION: It is suggested that the assessment of 'goal ownership' prior to a weight reduction intervention could identify patients who are sufficiently motivated to participate. Patients who score low on 'goal ownership' may be offered pretreatment interventions to increase their motivation.

The effect of weight reduction interventions for persons with type 2 diabetes: a meta-analysis from a self-regulation perspective.

PURPOSE: The main purpose of this article was to investigate the value of a self-regulation approach for weight reduction interventions in patients with type 2 diabetes. In addition, the potentially moderating effect of other intervention characteristics was explored. METHODS: In a meta-analysis of 34 studies, overall effect sizes were calculated for weight and A1C. The focus of the analysis was, however, on the moderating effect of intervention characteristics, especially whether interventions that score high on self-regulation produce stronger effects. RESULTS: The overall effect sizes (d) for weight loss in the short term (<6 months) were low and even lower in the longer term (>6 months). The overall effect sizes for A1C outcomes were higher and remained stable in the longer term. Interventions that scored high on self-regulation characteristics produced significantly better effects on both weight and A1C outcomes. Furthermore, "goal reformulation" increased the effect on weight outcomes whereas "emotion regulation" increased the effect on A1C. With respect to the other intervention characteristics, only the "inclusion of a patient's partner or relative" increased the effect on weight loss. CONCLUSIONS: This meta-analysis underlines the importance of a self-regulation approach for weight reduction interventions in diabetes patients, in particular, for A1C outcomes. However, more research is needed to fully understand the relationship among self-regulation, weight, and A1C.

Self-regulation and weight reduction in patients with type 2 diabetes: a pilot intervention study.

OBJECTIVE: To evaluate the efficacy of a self-regulation (SR) weight reduction intervention on weight, body mass index (BMI), glycosylated hemoglobin (HbA1c) (primary outcomes), exercise, nutrition and quality of life (secondary outcomes). METHODS: A pilot intervention (n=53) based on SR-principles consisted of a motivational interview, group sessions and a workbook and was evaluated against standard care with (n=38) and without a self-help manual (n=38). Subjects were overweight (BMI>27) patients with type 2 diabetes (52% female) from a Dutch hospital (mean age 58.14, S.D.=8.86). RESULTS: No differences in the outcomes were found between the intervention and control groups at 3 (T2) or 6 (T3) months. However, results at T2 and T3 revealed that patients with higher SR-skills scores had lower HbA1c levels than patients with lower scores. CONCLUSION: The SR-intervention did not significantly influence the outcomes. This apparent lack of effect might, however, partly be due to high attrition rates in all treatment groups. SR-skills were positively related to changes in HbA1c-levels. PRACTICE IMPLICATIONS: Improving SR-skills of overweight diabetes type 2 patients may improve their glycemic control. Patients who are 'external regulators' may however profit more from directive than from SR-interventions.