BACKGROUND: Type 1 diabetes is a constraining disease due to the burden of its management, and diabetes outcome largely depends on the effectiveness of diabetes self-care. Digital health technology (DHT), which includes continuous glucose monitoring, insulin delivery devices, and related mobile health apps, can support diabetes self-care and thereby improve diabetes outcomes. In literature, experiences with the use of DHT vary widely among people with diabetes and are a less studied area among adults with type 1 diabetes.

OBJECTIVE: The study aimed to explore experiences of using DHT for diabetes self-care among adults with type 1 diabetes.

METHODS: A qualitative design with an inductive approach was used. Adults with type 1 diabetes who are users of DHT and could understand Swedish were included in the study. Participants were recruited primarily via digital advertisements through social media. A convenient sampling method was used. Data were collected through open-ended questions in a web-based survey (autumn 2022) and 2 digital group interviews (autumn 2024). The survey questionnaire and interview guide attempted to capture positive and negative experiences of using DHTs for diabetes self-care through personally relevant incidents and behavioral details. Data from a total of 161 participants (n=156 survey participants and n=5 interview participants), using 1 or more forms of DHTs, were included in the study. Data were analyzed using qualitative content analysis with an inductive approach as per Graneheim and Lundman. The data in this study generated 324 meaning units relevant to the aim.

RESULTS: The participants experienced using DHTs in diabetes self-care as a balancing act between feeling empowered and feeling exasperated. This is described under 5 categories: promoting autonomy in daily life, self-awareness through collaborative learning, feeling secure, tackling technical challenges and the need for support, and navigating the burden of psychosocial challenges. DHTs were experienced as empowering when they supported autonomy in daily life, enhanced self-awareness through collaborative learning, and fostered a sense of security. However, having to tackle technical challenges and the need for support, and navigating the burden of psychosocial challenges, led to feelings of exasperation. The exasperating experiences hindered participants from experiencing a full sense of empowerment with DHT use.

CONCLUSIONS: This study sheds light on both positive and negative experiences of using DHTs for diabetes self-care in a real-life setting. The exasperating experiences may widen the digital health inequities and therefore are important to address. Improving technological literacy and ongoing support from health care or device manufacturers may help users to address exasperating experiences. Further studies are needed to validate our findings.

BACKGROUND: Regular physical activity is essential for preventing and managing type 2 diabetes. This study evaluates self-reported outcomes including depression, anxiety, stress, diabetes distress, and health-related quality of life during a 2-year pedometer-based intervention, with or without physical activity counseling, in people with prediabetes or type 2 diabetes.

METHODS: This study was a 3-armed parallel randomized controlled trial conducted in primary healthcare, involving people with prediabetes or type 2 diabetes. The 3 arms were: a multi-component intervention (self-monitoring of steps with counseling support), a single-component intervention (self-monitoring of steps without counseling support), and a control group (standard care). Secondary outcomes were measured using questionnaires for self-reported depression and anxiety (the Hospital Anxiety and Depression Scale [HADS]), stress (Perceived Stress Scale [PSS]), health-related quality of life (EuroQol, [EQ-5D 3L, and EQ-VAS] ), and diabetes distress (The Problem Areas in Diabetes questionnaire, [Swe-PAID-20]), at baseline and at months 3, 6, 12, 18, and 24. Intervention effects were evaluated by a robust linear mixed model.

RESULTS: In total, 188 patients (n = 64, 59, 65 in the respective group) were included. The mean (SD) age was 64.1 (7.7) years, 21% had prediabetes, 40% were female, and HbA1c was 49.9 (11.4) mmol/mol. The retention rate was approximately 91% of participants in the first year and 81% at the end of the second year. There were no significant within-group changes in self-reported outcomes from baseline up to 24 months. Moreover, there were no significant differences in outcomes between the interventions and control group at any time in any outcome.

CONCLUSION: This 2-year, pedometer-based physical activity intervention, despite its effectiveness for other outcomes in previous studies, is likely insufficient on its own to improve psychological well-being or reduce diabetes distress in a primary care population with prediabetes or type 2 diabetes with generally well-managed mental health at baseline. The study offers methodological insights that can guide future research. It highlights the complexity of assessing mental health outcomes within practical, low-intensity physical activity interventions.

BACKGROUND: Digital interventions offering behaviour change support are warranted to prevent and treat non-communicable diseases, and have been evaluated rigorously in controlled settings. Effectivenss, factors influencing the uptake of scaled-up interventions-such as reach, received dose, usability and acceptability- and predictors and mediators of efficiency are rarely explored in research. The study described herein aims to evaluate the effectiveness of a personally tailored digital intervention (the app EviBody®), intended to support healthy and sustained lifestyle behaviours among the adult population, on well-being and behaviour change. Further aims are to explore context and uptake factors, predictors and mediators for behaviour change over 24 months.

METHODS: This is a real-world study, employing a quasi-experimental design and a process evaluation. EviBody® will be marketed and managed by its owner. A four-armed design will allow for comparison between three levels of intervention (basic, standard and premium) and a control group. Adults who sign up for the app will be invited to the research study including sharing app data and answering questionnaires at 0, 1, 3, 6, 12, 18, and 24 months. Study start is Autumn 2025. Controls (n = 200 to evaluate the primary endpoint well-being at 6 months) will be recruited through advertisements on social media and asked to answer the same questionnaires at 0 and 6 months provided by email. For predicting and mediating analyses the intention is to recruit 1500 app users. Well-being (measured with the WHO-5 Well-Being Index), goal achievement, physical activity, eating habits, mental health, mediators (motivation, self-efficacy, and perceived barriers), and demographics will be self-reported. Uptake will be collected using analytics and ratings of usability and acceptability, and described by demographics. Mixed models for repeated measures and structural equation modelling will be employed for data analysis.

DISCUSSION: Besides evaluating the effectivenss of a digital intervention, this study also applies a theory-based evaluation to understand which mediators are effective, for whom they are effective, and the specific conditions under which they are most beneficial.

TRIAL REGISTRATION: ClinicalTrials.gov, ID: NCT05973383 on 8 July 2023.

BACKGROUND: The use of digital health technology in diabetes self-care is increasing, making eHealth literacy an important factor to consider among people with type 1 diabetes. There are very few studies investigating eHealth literacy among adults with type 1 diabetes, highlighting the need to explore this area further.

OBJECTIVE: The aim of this study was to explore associations between eHealth literacy and demographic factors, disease-specific factors, and well-being among adults with type 1 diabetes.

METHODS: The study used data from a larger cross-sectional survey conducted among adults with type 1 diabetes in Sweden (N=301). Participants were recruited using a convenience sampling method primarily through advertisements on social media. Data were collected between September and November 2022 primarily through a web-based survey, although participants could opt to answer a paper-based survey. Screening questions at the beginning of the survey determined eligibility to participate. In this study, eHealth literacy was assessed using the Swedish version of the eHealth Literacy Scale (Sw-eHEALS). The predictor variables, well-being was assessed using the World Health Organization-5 Well-Being Index and psychosocial self-efficacy using the Swedish version of the Diabetes Empowerment Scale. The survey also included research group-developed questions on demographic and disease-specific variables as well as digital health technology use. Data were analyzed using multiple linear regression presented as nested models. A sample size of 270 participants was required in order to detect an association between the dependent and predictor variables using a regression model based on an F test. The final sample size included in the nested regression model was 285.

RESULTS: The mean Sw-eHEALS score was 33.42 (SD 5.32; range 8-40). The model involving both demographic and disease-specific variables explained 31.5% of the total variation in eHealth literacy and was deemed the best-fitting model. Younger age (P=.01; B=-0.07, SE=0.03;95% CI -0.12 to -0.02), lower self-reported glycated hemoglobin levels (P=.04; B=-0.06, SE=0.03; 95% CI -0.12 to 0.00), and higher psychosocial self-efficacy (P<.001; B=3.72, SE=0.53; 95% CI 2.68-4.75) were found associated with higher Sw-eHEALS scores when adjusted for demographic and disease-specific variables in this model. Well-being was not associated with eHealth literacy in this study.

CONCLUSIONS: The demographic and disease-specific factors explained the variation in eHealth literacy in this sample. Further studies in this area using newer eHealth literacy tools are important to validate our findings. The study highlights the importance of development and testing of interventions to improve eHealth literacy in this population for better glucose control. These eHealth literacy interventions should be tailored to meet the needs of people in varying age groups and with differing levels of psychosocial self-efficacy.

AIM: To evaluate the quality of care from the patients' perspective after receiving either person-centred, nurse-led follow-up or standard care after surgical treatment of intermittent claudication.

DESIGN: Secondary analysis of a randomised controlled trial.

METHODS: Patients at two centres for vascular surgery in Stockholm, Sweden were randomised to either a person-centred, nurse-led follow-up programme (intervention group) or a standard follow-up programme with surgeons. During their visits at 4 to 8 weeks and 1 year after surgery, they received the questionnaire Quality from patients' perspective with 28 items. The patients responded to each item from two aspects: (1) how they perceived the quality of received care and (2) subjective importance (how important the care was for them).

RESULTS: A total of 104 of 138 patients at 4-8 weeks and 159 of 193 patients at 1 year after surgery completed the questionnaire. At 4-8 weeks, the intervention group scored significantly higher perceived quality of care regarding five items: receiving useful information about "How I should take care of myself" and "Which nurse were responsible for my care", "Nurses were respectful towards me", "Nurses showed commitment/cared about me" and "Easy to get in contact with the clinic through telephone". At 1 year, the intervention group scored higher regarding two items: "Which nurses were responsible for my care" and "Next of kin treated well".

CONCLUSION: Person-centred, nurse-led follow-up as implemented in this study has been shown to lead to a higher perception of quality of care regarding information about self-care, the experience of being respected, and knowing the care provider responsible for their care. Thus, it could contribute towards improved patient satisfaction without compromising the perception of quality of care regarding other factors such as receiving the best medical care or timeliness.

IMPLICATIONS FOR THE PROFESSION AND/OR PATIENT CARE: This study addresses how patients with intermittent claudication, who underwent revascularisation, perceive a follow-up care that is person-centred and nurse-led compared to standard care delivered by surgeons. The results indicate that patients find the person-centred and nurse-led follow-up programme satisfactory, with equal or higher quality of care and that follow-up can be delivered by nurses with retained patient safety. Thus, vascular units may consider transitioning follow-up care from surgeons to nurses while maintaining positive patient's perception of quality of care, patient satisfaction and safety.

REPORTING METHOD: Reporting of the work was made using the Consolidated Standards of Reporting Trials (CONSORT) statement.

PATIENT OR PUBLIC CONTRIBUTION: No patient or public contribution.

TRIAL REGISTRATION: Study Details | Person-centred Follow-up and Health Promotion Programme After Revascularization for Intermittent Claudication | ClinicalTrials.gov: NCT03283358.

BACKGROUND: There is a limited amount of evidence concerning the association between seasonal variation and the level of physical activity in individuals with chronic disease. This longitudinal observational study aimed to explore seasonal, monthly, and holiday variations in self-monitored step counts over two years among adults with prediabetes and type 2 diabetes in Sweden.

METHODS: Participants were recruited at primary care centers from 2013 to 2018 to take part in a physical activity intervention. Inclusion criteria included the following: an age of 40-80 years, having prediabetes or type 2 diabetes (≥1 year), and the ability to communicate in Swedish. Individuals with recent myocardial infarction, impaired renal function, diabetic ulcers, a limited capacity for physical activity, insulin onset (<6 months), recurrent or severe hypoglycemia, a high baseline for physical activity, or no internet access were excluded. In total, 120 participants wore step counters and recorded daily steps for two years. Linear mixed models adjusted for sex, age, and body mass index were applied.

RESULTS: Mean (95% CI) step counts were statistically significantly higher in summer (7825 [7762, 7889]) and spring (7805 [7757, 7853]) compared to winter (7098 [7052, 7145]) and fall (7422 [7349, 7490]). Highest step counts were registered in May (7993 [7904, 8071]), followed by June (7968 [7895, 8063]), and the lowest in January (6944 [6856, 7034]) and November (7208 [7113, 7289]). Step counts during holiday periods were statistically significantly lower than non-holiday periods across all seasons.

CONCLUSION: Self-monitored daily steps varied over the seasons in this sample of individuals with prediabetes and type 2 diabetes. Declined physical activity levels in months with unfavorable weather conditions require attention in consultations and research.

BACKGROUND: Many studies have identified key factors affecting the rates of engagement in physical activity in older adults with chronic disease. Environmental conditions, such as weather variations, can present challenges for individuals with chronic diseases, such as type 2 diabetes when engaging in physical activity. However, few studies have investigated the influence of weather on daily steps in people with chronic diseases, especially those with prediabetes and type 2 diabetes.

OBJECTIVE: This study investigated the association between weather variations and daily self-monitored step counts over two years among individuals with prediabetes and type 2 diabetes in Sweden.

METHODS: The study is a secondary analysis using data from the Sophia Step Study, aimed at promoting physical activity among people with prediabetes and type 2 diabetes, which recruited participants from two urban primary care centers in Stockholm and one rural primary care center in southern Sweden over eight rounds. This study measured physical activity using step counters (Yamax Digiwalker SW200) and collected self-reported daily steps. Environmental factors such as daily average temperature, precipitation, and hours of sunshine were obtained from the Swedish Meteorological and Hydrological Institute. A robust linear mixed-effects model was applied as the analysis method.

RESULTS: There was no association found between weather variations and the number of steps taken on a daily basis. The analysis indicated that only 10% of the variation in daily steps could be explained by the average temperature, precipitation, and sunshine hours after controlling for age, gender, and BMI. Conversely, individual factors explained approximately 38% of the variation in the observations.

CONCLUSION: This study revealed that there was no association between weather conditions and the number of daily steps reported by individuals with prediabetes and type 2 diabetes taking part in a physical activity intervention over two years. Despite the weather conditions, women and younger people reported more steps than their male and older counterparts.