Explore the vast range of titles available.

The global rise in the prevalence of diabetes significantly impacts the quality of life of both patients and their families. Despite advances in diabetes care, numerous challenges remain in its management. In recent years, digital tools have been increasingly integrated into diabetes care, demonstrating some positive outcomes. However, the long-term effectiveness and associated challenges of these tools in diabetes management remain areas for future research. This study aims to assess the types and current usage of digital tools in diabetes management, analyze their benefits and limitations, and provide recommendations for optimizing their future application in diabetes care. This scoping review followed the 5-stage framework proposed by Arksey and O'Malley. A comprehensive literature search was conducted across 9 electronic databases (CNKI, Wanfang Database, VIP, Sinomed, PubMed, Embase, Web of Science, CINAHL, and Cochrane Library) from their inception to July 31, 2024. Study selection was independently performed by 2 reviewers, descriptive analysis was conducted, and findings were presented narratively, key study characteristics-including first author, publication date, country or region, study type, sample size, type of digital tools, intervention methods, intervention duration, limitations, and outcome indicators-were independently extracted and cross-checked by 2 investigators. A total of 6263 articles were initially retrieved. After deduplication and a 2-stage screening process (initial screening based on titles and abstracts followed by full-text assessment), 45 studies meeting the predefined inclusion criteria were ultimately included for analysis, originating from 7 countries. The included studies demonstrated marked heterogeneity in research designs: randomized controlled trials (RCTs; n=26, 57.8%), non-RCTs (n=15, 33.3%), quasi-RCTs (n=1, 2.2%), observational studies (n=1, 2.2%), mixed-methods studies (n=1, 2.2%), and qualitative studies (n=1, 2.2%). The digital tools primarily included mobile health apps, integrated management information platforms, Diabetes Online Community (DOC), specialized monitoring and analytics tools, blood glucose information management systems, and remote monitoring and follow-up systems, among others. These tools were applied across home, hospital, and community settings. Outcome measures were primarily focused on evaluating glycemic control efficacy (eg, fasting blood glucose, postprandial blood glucose, and glycated hemoglobin), blood lipid levels, BMI, self-management capacity, quality of life, patient satisfaction, and diabetes knowledge. This review highlights the diversity and potential value of digital tools in diabetes care, particularly in supporting patient self-management and extending care across multiple settings. From a nursing perspective, digital interventions offer opportunities for individualized care, patient engagement, and continuity of services. However, challenges such as technology acceptance remain. Future studies should address gaps related to long-term effectiveness, economic evaluation, and tool adaptation for aging populations, while incorporating interdisciplinary approaches and real-world evidence to inform sustainable digital health strategies.

The use of mobile health interventions, such as apps, are proposed to meet the challenges faced by preventive health care services due to the increasing prevalence of type 2 diabetes (T2D). Thus, we developed and conducted initial feasibility testing of the Plunde app for promoting and monitoring individual goals related to lifestyle change for people at risk of T2D. The primary aim of this study was to assess the feasibility of an app for promoting lifestyle change in people at risk of T2D. The secondary aim was to assess recruitment rate, resource requirements, and change in potential outcomes for a full scale randomized controlled trial (RCT) study . A 3-arm feasibility RCT lasting 12 weeks was designed. Participants were recruited from 9 general practitioners in Norway. Eligible participants were randomized to either (1) app follow-up; (2) app follow-up and referral to care as usual in Healthy Life Centers; or (3) referral to care as usual in a Healthy Life Center, only. The primary outcome was feasibility and was measured by app adherence (actual usage of the app), the System Usability Scale, and app motivation score gained from a questionnaire designed for this study. Criteria for success were preset based on these measures. Secondary outcomes included recruitment rate, resource requirements, and potential primary outcomes of a full-scale RCT. This included change in body weight, waist circumference, and self-evaluated functional health status, assessed with the Dartmouth Primary Care Cooperative Research Network/World Organization of Family Doctors (COOP/WONCA) functional health assessment chart. Within 8 months, 9 general practitioners recruited a total of 54 participants, of which 45 were eligble for participation in the study. Mean age was 61 (SD 13) years and 53% (n=24) were female. App adherence was 86%, the mean System Usability Scale score was 87.3 (SD 11.9), and the mean app motivation score was 74.8 (SD 30.3). Throughout the intervention period, health care professionals spent on average 3.0 (SD 1.0) minutes per participant per week providing follow-up. Statistically significant reduction in body weight and waist circumference was shown in group 1 and 3. Based on the preset criteria for success, the Plunde app is feasible in providing support for lifestyle change. The Plunde app had excellent user satisfaction. The amount of time spent on monitoring and promoting lifestyle change through the app was low; however, the recruitment was slow. Results from this study will guide the development of further research within this field.

A novel mobile health (mHealth) app \"acT1ve,\" developed using a co-design model, provides real-time support during exercise for young people with type 1 diabetes (T1D). This study aimed to demonstrate the noninferiority of acT1ve compared with \"treatment as usual\" with regard to hypoglycemic events. Thirty-nine participants living with T1D (age: 17.2, SD 3.3 years; HbA1c: 64, SD 6.0 mmol/mol) completed a 12-week single-arm, pre-post noninferiority study with a follow-up qualitative component. During the intervention, continuous glucose monitoring (CGM) and physical activity were monitored while participants used acT1ve to manage exercise. CGM data were used to assess the number of hypoglycemic events (<3.9 mmol/L for ≥15 minutes) in each phase. Using a mixed effects negative binomial regression, the difference in the rates of hypoglycemia between the preapp and app-use phases was analyzed. Participants completed both a semistructured interview and the user Mobile Application Rating Scale (uMARS) questionnaire postintervention. All interviews were audio-recorded for transcription, and a deductive content analysis approach was used to analyze the participant interviews. The uMARS Likert scores for each subscale (engagement, functionality, esthetics, and information) were calculated and reported as medians with IQRs. The rates of hypoglycemia were similar for both the preapp and app-use phases (0.79 and 0.83 hypoglycemia events per day, respectively). The upper bound of the CI of the hypoglycemia rate ratio met the prespecified criteria for noninferiority (rate ratio=1.06; 95% CI 0.91-1.22). The uMARS analysis showed a high rating (≥4 out of 5) of acT1ve by 80% of participants for both functionality and information, 72% for esthetics, and 63% for overall uMARS rating. Content analysis of the interview transcripts identified 3 main themes: \"Provision of information,\" \"Exercising with the App,\" and \"Targeted Population.\" The mHealth app \"acT1ve,\" which was developed in collaboration with young people with T1D, is functional, acceptable, and safe for diabetes management around exercise. The study supports the noninferiority of acT1ve compared with \"treatment as usual\" with regards to hypoglycemic events.

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. 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. 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. 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. 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.

Diabetic ketoacidosis represents a significant and potentially life-threatening complication of diabetes, predominantly observed in individuals with type 1 diabetes (T1D). Studies have documented suboptimal adherence to diabetes management among children and adolescents, as evidenced by deficient ketone monitoring practices. The aim of the study was to explore the potential for prediction of elevated ketone bodies from continuous glucose monitoring (CGM) and insulin data in pediatric and adult patients with T1D using a closed-loop system. Participants used the Dexcom G6 CGM system and the iLet Bionic Pancreas system for insulin administration for up to 13 weeks. We used supervised binary classification machine learning, incorporating feature engineering to identify elevated ketone bodies (>0.6 mmol/L). Features were derived from CGM, insulin delivery data, and self-monitoring of blood glucose to develop an extreme gradient boosting-based prediction model. A total of 259 participants aged 6-79 years with over 49,000 days of full-time monitoring were included in the study. Among the participants, 1768 ketone samples were eligible for modeling, including 383 event samples with elevated ketone bodies (≥0.6 mmol/L). Insulin, self-monitoring of blood glucose, and current glucose measurements provided discriminative information on elevated ketone bodies (receiver operating characteristic area under the curve [ROC-AUC] 0.64-0.69). The CGM-derived features exhibited stronger discrimination (ROC-AUC 0.75-0.76). Integration of all feature types resulted in an ROC-AUC estimate of 0.82 (SD 0.01) and a precision recall-AUC of 0.53 (SD 0.03). CGM and insulin data present a valuable avenue for early prediction of patients at risk of elevated ketone bodies. Furthermore, our findings indicate the potential application of such predictive models in both pediatric and adult populations with T1D.

Technology can be an effective tool for providing health services and disease self-management, especially in diabetes care. Technology tools for disease self-management include health-related applications for computers and smartphones as well as the use of robots. To provide a more effective continuity of care and to better understand and facilitate disease management in middle-aged and older adult patients with diabetes, robots can be used to improve the quality of care and supplement community health resources, such as community pharmacies. The aim of this study was to develop a health care robot prototype that can be integrated into current community pharmacies. Three user-centered approaches were used: (1) review of the literature on technology use among older adults, 2) reference to the seven key diabetes self-care behaviors by the American Association of Diabetes Educators (AADE), and (3) meeting with health care providers in the community. Field investigations and interviews were conducted at community pharmacies and diabetes health education centers to determine the appearance, interface, content, and function of the robot. The results show that diabetes health care prototype robots can be established through user-centered design. The following important features were revealed: (1) perceived ease of use is considered a friendly operating interface; therefore, we used less than 3 buttons in an interface; (2) minimization of the interface between blue and yellow, which is unfriendly to older adults; (3) the health education mode was the most preferred mode with sound, image, and video presentation; (4) the most predilected functions are health education resources and health records, and that patient data can be easily collected through health education games and dialogue with robots; and (5) touching the screen is the most preferred operation mode. An evidence-based health care robot can be developed through user-centered design, an approach in which a model that connects medical needs to people with health conditions can be built, thereby facilitating the sustainable development of technology in the diabetes care field.

Continuous glucose monitoring (CGM) and continuous subcutaneous insulin infusions (CSIIs) are the current standard treatment devices for type 1 diabetes (T1D) management. With a high prevalence of T1D beginning in pediatrics and carrying into adulthood, insufficient glycemic control leads to poor patient outcomes. Dermatologic complications such as contact dermatitis, lipodystrophies, and inflammatory lesions are among those associated with CGM and CSII, which reduce glycemic control and patient compliance. This systematic review aims to explore the current literature surrounding dermatologic complications of CGM and CSII as well as the impact on patient outcomes. A systematic review of the literature was carried out using PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) 2020 guidelines using 5 online databases. Included articles were those containing primary data relevant to human participants and adverse reactions to CGM and CSII devices in pediatric populations, of which greater than 50% of the sample size were aged 0-21 years. Qualitative analysis was chosen due to the heterogeneity of outcomes. Following the application of exclusion criteria, 25 studies were analyzed and discussed. An additional 5 studies were identified after the initial search and inclusion. The most common complication covered is contact dermatitis, with 13 identified studies. Further, 7 studies concerned lipodystrophies, 5 covered nonspecific cutaneous changes, 3 covered unique cutaneous findings such as granulomatous reactions and panniculitis, and 2 discussed user acceptability. The dermatologic complications of CGM and CSII pose a potential risk to long-term glycemic control in T1D, especially in young patients where skin lesions can lead to discontinuation. Increased manufacturer transparency is critical and further studies are needed to expand upon the current preventative measures such as device site rotation and steroid creams, which lack consistent effectiveness.

Background Mobile phone applications (apps) have been shown to successfully facilitate the self-management of chronic disease. This study aims to evaluate firstly the experiences, barriers and facilitators to app usage among people with Type 2 Diabetes Mellitus (T2DM) and secondly determine recommendations to improve usage of diabetes apps. Methods Participants were aged ≥ 18 years with a diagnosis of T2DM for ≥ 6 months. Semi-structured phone-interviews were conducted with 16 app and 14 non-app users. Interviews were based on the Technology Acceptance Model, Health Information Technology Acceptance Model (HITAM) and the Mobile Application Rating Scale. Data were analysed using deductive content analysis. Results Most app-users found apps improved their T2DM self-management and health. The recommendation of apps by health professionals, as well as positive interactions with them, improved satisfaction; however, only a minority of patients had practitioners involved in their app use. All non-app users had never had the concept discussed with them by a health professional. Facilitators to app use included the visual representation of trends, intuitive navigation and convenience (for example, discretion and portability). Barriers to app use were participant’s lack of knowledge and awareness of apps as healthcare tools, perceptions of disease severity, technological and health literacy or practical limitations such as rural connectivity. Factors contributing to app use were classified into a framework based on the Health Belief Model and HITAM. Recommendations for future app design centred on educational features, which were currently lacking (e.g. diabetes complications, including organ damage and hypoglycaemic episodes), monitoring and tracking features (e.g. blood glucose level monitoring with trends and dynamic tips and comorbidities) and nutritional features (e.g. carbohydrate counters). Medication reminders were not used by participants. Lastly, participants felt that receiving weekly text-messaging relating to their self-management would be appropriate. Conclusions The incorporation of user-centred features, which engage T2DM consumers in self-management tasks, can improve health outcomes. The findings may guide app developers and entrepreneurs in improving app design and usability. Given self-management is a significant factor in glycaemic control, these findings are significant for GPs, nurse practitioners and allied health professionals who may integrate apps into a holistic management plan which considers strategies outside the clinical environment.

Introduction The prevalence of both type 2 diabetes mellitus (T2DM) and obesity is increasing among people living with HIV (PLHIV) in sub-Saharan Africa. We examined the perceptions and management of these two conditions among PLHIV and healthcare workers in Côte D’Ivoire. Method From June to August 2022, we conducted semi-structured face-to-face interviews with PLHIV diagnosed with T2DM and/or obesity, as well as healthcare workers, in one of the major HIV clinics in Abidjan, Cote d’Ivoire. We explored topics such as experiences, perceptions and acceptability of the diagnosis and management of T2DM and obesity among PLHIV. Among healthcare workers, professional experience, professional relationships with patients diagnosed with T2DM/obesity, involvement in patient management and care provision were explored. Interviews were audio recorded and transcribed manually. Data were analysed using thematic analysis. Results A total of 15 PLHIV and 5 healthcare workers participated in semi-structured in-depth interviews. Perceptions towards T2DM and obesity were largely influenced by cultural factors, PLHIV reported negative perceptions of T2DM and positive perceptions of obesity. Both patients and healthcare providers considered the management of these conditions as sub-optimal. Patient-reported barriers to care for these metabolic disorders were mainly socio-economic and environmental, while healthcare workers emphasized patients' denial of their illness and the limited range of treatment options available at the clinic. Conclusion These results highlight the complexity surrounding the perceptions and management of T2DM and obesity among PLHIV in Abidjan, Côte d’Ivoire. In order to implement innovative and efficient intervention strategies to prevent and treat these metabolic conditions, cultural beliefs as well as socio-economic barriers must be addressed.

PurposeThe Swedish National Diabetes Register (NDR) has developed a diabetes-specific questionnaire to collect information on individuals' management of their diabetes, collaboration with healthcare providers and the disease’s impact on daily life. Our main objective was to develop measures of well-being, abilities to manage diabetes and judgements of diabetes care, and to detect and quantify differences using the NDR questionnaire.Design, setting and participantsThe questionnaire was analysed with using responses from 3689 participants with type 1 and 2 diabetes, randomly sampled from the NDR population, combined with register data on patient characteristics and cardiovascular and diabetes complication risk factors.MethodsWe used item response theory to develop scales for measuring well-being, abilities to manage diabetes and judgements of diabetes care (scores). Test–retest reliability on the scale level was analysed with intraclass correlation. Associations between scores and risk factor levels were investigated with subgroup analyses and correlations.ResultsWe obtained scales with satisfactory measurement properties, covering patient reported outcome measures such as general well-being and being free of worries, and patient reported experience measure, for example, access and continuity in diabetes care. All scales had acceptable test–retest reliability and could detect differences between diabetes types, age, gender and treatment subgroups. In several aspects, for example, freedom of worries, type 1 patients report lower than type 2, and younger patients lower than older. Associations were found between some scores and glycated haemoglobin, but none with systolic blood pressure or low-density lipoprotein cholesterol. Clinicians report positive experience of using scores, visually presented, in the patient dialogue.ConclusionsThe questionnaire measures and detects differences in patient well-being, abilities and judgements of diabetes care, and identifies areas for improvement. To further improve diabetes care, we conclude that patient-reported measures are important supplements to cardiovascular and diabetes complication risk factors, reflecting patient experiences of living with diabetes and diabetes care.