Digital interventions self-management education for type 1 and 2 diabetes: A systematic review and meta-analysis

Could Online Education Replace Face-to-Face Education in Diabetes? A Systematic Review

OBJECTIVE

Diabetes Self-Management Education and Support (DSMES) is a critical component of diabetes care. This study aims to examine the effect of online-based educational interventions on diabetes management compared to face-to-face interventions.

METHODS

A systematic review was conducted by searching three databases for studies in English or Spanish between December 2023 and March 2024. The inclusion criteria were studies that compared face-to-face DSMES with online interventions.

RESULTS

The follow-up duration of the trials ranged from 1 to 12 months. Multidisciplinary teams delivered online DSMES through various means, including Short Message Service (SMS), telephone calls, video calls, websites, and applications. Online DSMES was found to be comparable to face-to-face interventions in terms of glycated hemoglobin (HbA1c) levels in people with type 1 diabetes (T1D). In contrast, online interventions that focus on weight management in people with type 2 diabetes (T2D) have shown a significant reduction in HbA1c compared to face-to-face interventions. Online DSMES was found to be superior in terms of quality of life and cost-effectiveness in both T1D and T2D. None of the analyzed studies explored the differences between individual and group methodologies.

CONCLUSIONS

The current evidence indicates that online DSMES services provide at least comparable biomedical benefits to face-to-face interventions, suggesting that online interventions could be incorporated into clinical practice as a complement or reinforcement. However, further research is needed to explore the potential benefits and effectiveness of online group sessions in DSMES.

The PICOTS-ComTeC Framework for Defining Digital Health Interventions: An ISPOR Special Interest Group Report

OBJECTIVES

Digital health definitions are abundant, but often lack clarity and precision. We aimed to develop a minimum information framework to define patient-facing digital health interventions (DHIs) for outcomes research.

METHODS

Definitions of digital-health-related terms (DHTs) were systematically reviewed, followed by a content analysis using frameworks, including PICOTS (population, intervention, comparator, outcome, timing, and setting), Shannon-Weaver Model of Communication, Agency for Healthcare Research and Quality Measures, and the World Health Organization's Classification of Digital Health Interventions. Subsequently, we conducted an online Delphi study to establish a minimum information framework, which was pilot tested by 5 experts using hypothetical examples.

RESULTS

After screening 2610 records and 545 full-text articles, we identified 101 unique definitions of 67 secondary DHTs in 76 articles, resulting in 95 different patterns of concepts among the definitions. World Health Organization system (84.5%), message (75.7%), intervention (58.3%), and technology (52.4%) were the most frequently covered concepts. For the Delphi survey, we invited 47 members of the ISPOR Digital Health Special Interest Group, 18 of whom became the Delphi panel. The first, second, and third survey rounds were completed by 18, 11, and 10 respondents, respectively. After consolidating results, the PICOTS-ComTeC acronym emerged, involving 9 domains (population, intervention, comparator, outcome, timing, setting, communication, technology, and context) and 32 optional subcategories.

CONCLUSIONS

Patient-facing DHIs can be specified using PICOTS-ComTeC that facilitates identification of appropriate interventions and comparators for a given decision. PICOTS-ComTeC is a flexible and versatile tool, intended to assist authors in designing and reporting primary studies and evidence syntheses, yielding actionable results for clinicians and other decision makers.

Assessment of the impact of a personalised nutrition intervention in impaired glucose regulation over 26 weeks: a randomised controlled trial

Dietary interventions can reduce progression to type 2 diabetes mellitus (T2DM) in people with non-diabetic hyperglycaemia. In this study we aimed to determine the impact of a DNA-personalised nutrition intervention in people with non-diabetic hyperglycaemia over 26 weeks. ASPIRE-DNA was a pilot study. Participants were randomised into three arms to receive either (i) Control arm: standard care (NICE guidelines) (n = 51), (ii) Intervention arm: DNA-personalised dietary advice (n = 50), or (iii) Exploratory arm: DNA-personalised dietary advice via a self-guided app and wearable device (n = 46). The primary outcome was the difference in fasting plasma glucose (FPG) between the Control and Intervention arms after 6 weeks. 180 people were recruited, of whom 148 people were randomised, mean age of 59 years (SD = 11), 69% of whom were female. There was no significant difference in the FPG change between the Control and Intervention arms at 6 weeks (- 0.13 mmol/L (95% CI [- 0.37, 0.11]), p = 0.29), however, we found that a DNA-personalised dietary intervention led to a significant reduction of FPG at 26 weeks in the Intervention arm when compared to standard care (- 0.019 (SD = 0.008), p = 0.01), as did the Exploratory arm (- 0.021 (SD = 0.008), p = 0.006). HbA1c at 26 weeks was significantly reduced in the Intervention arm when compared to standard care (- 0.038 (SD = 0.018), p = 0.04). There was some evidence suggesting prevention of progression to T2DM across the groups that received a DNA-based intervention (p = 0.06). Personalisation of dietary advice based on DNA did not result in glucose changes within the first 6 weeks but was associated with significant reduction of FPG and HbA1c at 26 weeks when compared to standard care. The DNA-based diet was effective regardless of intervention type, though results should be interpreted with caution due to the low sample size. These findings suggest that DNA-based dietary guidance is an effective intervention compared to standard care, but there is still a minimum timeframe of adherence to the intervention before changes in clinical outcomes become apparent.Trial Registration: www.clinicaltrials.gov.uk Ref: NCT03702465.

Testing 3 Digital Health Platforms to Improve Mental Health Outcomes in Adults With Type 1 Diabetes: A Pilot Trial

OBJECTIVE

Our aim in this study was to examine the potential impact of a 3-pronged digital health pilot intervention (TRIFECTA) on diabetes distress and depressive symptoms among adults with type 1 diabetes (T1D) in British Columbia.

METHODS

We recruited 60 adults with T1D (mean age 38.9±15.1 years, 75% female, 77% Caucasian) who participated in the 6-month pilot intervention involving 3 digital health platforms: monthly, provider-led, group-based sessions over Zoom (virtual huddles); a WhatsApp peer texting group; and a web-based "Ask-the-expert" portal. Assessments were conducted at baseline and 6 months and measured diabetes distress (T1D Diabetes Distress Scale), depressive symptoms (9-item Personal Health Questionnaire), and TRIFECTA engagement metrics.

RESULTS

Participation in TRIFECTA was associated with significant reductions in Overall Distress (p=0.011) and 4 distress subscales: Powerlessness (p=0.006), Management Distress (p=0.001), Hypoglycemia Distress (p=0.029), and Eating Distress (p<0.001). A higher number of virtual huddles attended predicted lower Overall Distress (p=0.019) and Family/Friends Distress (p=0.023). A higher number of "Ask-the-expert" posts viewed predicted lower Overall Distress (p=0.046), whereas a higher number of WhatsApp messages posted predicted lower Management Distress (p=0.006). Furthermore, engagement in all 3 metrics was a predictor for lower Negative Social Perceptions Distress (p<0.05). No associations were seen in other distress subscales or for depressive symptoms.

CONCLUSIONS

Participation in TRIFECTA was linked to reduced diabetes distress levels, but not depressive symptoms, in a platform-dependent manner. This study provides promising pilot data for a subsequent large-scale and fully powered randomized controlled trial.

Effectiveness of Non-pharmacological Interventions for Adolescents With Type 1 Diabetes in the Last Five Years: A Systematic Review and Meta-analysis

PURPOSE

Evidence on non-pharmacological interventions for adolescents with type 1 diabetes is unclear. This review aimed to evaluate the effectiveness of non-pharmacological intervention in adolescents with type 1 diabetes.

METHODS

We conducted a search on databases from November 11 to 19, 2022, for randomized controlled trials for the effects of non-pharmacological intervention in adolescents with type 1 diabetes. To identify recent research trends, we included studies published from 2017 to November 2022. The risk of bias was assessed using the Cochrane risk-of-bias tool 2.0. To estimate the effect size, a meta-analysis was performed using RevMan 5.4 program and R Studio.

RESULTS

A total of 45 studies were included in the systematic review. Among those, 30 studies were included in the meta-analysis. Non-pharmacological interventions were significantly effective in improving Glycated hemoglobin (HbA1c) (standardized mean difference [SMD] = -0.26, 95% confidence interval [CI]: -0.42, -0.09), quality of life (SMD = 0.44, 95% CI: 0.13 to 0.76), and anxiety (SMD = -0.91, 95% CI: -1.26, -0.56). Subgroup analysis showed that duration of intervention was not a covariate related to HbA1c levels.

CONCLUSIONS

Non-pharmacological interventions have shown effectiveness in improving the HbA1c, quality of life, and anxiety in adolescents with type 1 diabetes. Future studies with more rigorous methodology are needed to confirm and strengthen the validity of these findings. Additionally, attention to changes in the lipid profile and self-care motivation among adolescents with type 1 diabetes is warranted.

TRIAL REGISTRATION NUMBER

Prospective Register of Systematic Reviews (CRD42022382190).

5. Facilitating Positive Health Behaviors and Well-being to Improve Health Outcomes: Standards of Care in Diabetes-2024

The American Diabetes Association (ADA) "Standards of Care in Diabetes" includes the ADA's current clinical practice recommendations and is intended to provide the components of diabetes care, general treatment goals and guidelines, and tools to evaluate quality of care. Members of the ADA Professional Practice Committee, an interprofessional expert committee, are responsible for updating the Standards of Care annually, or more frequently as warranted. For a detailed description of ADA standards, statements, and reports, as well as the evidence-grading system for ADA's clinical practice recommendations and a full list of Professional Practice Committee members, please refer to Introduction and Methodology. Readers who wish to comment on the Standards of Care are invited to do so at professional.diabetes.org/SOC.

Health Outcomes Following Engagement With a Digital Health Tool Among People With Prediabetes and Type 2 Diabetes: Prospective Evaluation Study

BACKGROUND

Diabetes is a worldwide chronic condition causing morbidity and mortality, with a growing economic burden on health care systems. Complications from poorly controlled diabetes are associated with increased socioeconomic costs and reduced quality of life. Smartphones have become an influential platform, providing feasible tools such as health apps to deliver tailored support to enhance the ability of patients with diabetes for self-management. Gro Health is a National Health Service division X-certified digital health tool used to deliver educational and monitoring support to facilitate the development of skills and practices for maintaining good health.

OBJECTIVE

This study aims to assess self-reported outcomes of the Gro Health app among users with diabetes and prediabetes and identify the factors that determine engagement with the digital health tool.

METHODS

This was a service evaluation of self-reported data collected prospectively by the developers of the Gro Health app. The EQ-5D questionnaire is a standardized tool used to measure health status for clinical and economic appraisal. Gro Health users completed the EQ-5D at baseline and 6 months after using the app. Users provided informed consent for the use of their anonymized data for research purposes. EQ-5D index scores and visual analogue scale (VAS) scores were calculated at baseline and 6 months for individuals with prediabetes and type 2 diabetes. Descriptive statistics and multiple-regression models were used to assess changes in the outcome measures and determine factors that affected engagement with the digital tool.

RESULTS

A total of 84% (1767/2114) of Gro Health participants completed EQ-5D at baseline and 6 months. EQ-5D index scores are average values that reflect people's preferences about their health state (1=full health and 0=moribund). There was a significant and clinically meaningful increase in mean EQ-5D index scores among app users between baseline (0.746, SD 0.23) and follow-up (0.792, SD 0.22; P<.001). The greatest change was observed in the mean VAS score, with a percentage change of 18.3% improvement (61.7, SD 18.1 at baseline; 73.0, SD 18.8 at follow-up; P<.001). Baseline EQ-5D index scores, age, and completion of educational modules were associated with significant changes in the follow-up EQ-5D index scores, with baseline EQ-5D index scores, race and ethnicity, and completion of educational modules being significantly associated with app engagement (P<.001).

CONCLUSIONS

This study provides evidence of a significant positive effect on self-reported quality of life among people living with type 2 diabetes engaging with a digital health intervention. The improvements, as demonstrated by the EQ-5D questionnaire, are facilitated through access to education and monitoring support tools within the app. This provides an opportunity for health care professionals to incorporate National Health Service-certified digital tools, such as Gro Health, as part of the holistic management of people living with diabetes.

Evaluation of the DigiBete App, a Self-Management App for Type 1 Diabetes: Experiences of Young People, Families, and Healthcare Professionals

Type 1 diabetes (T1DM) is a public health issue for children, young people, and families (CYPF) and requires innovative interventions. The DigiBete app is a self-management and educational app to help CYPF and healthcare professionals (HCPs) manage T1DM, featuring educational advice and resources such as guidance, quizzes, and educational and instructional videos on how to manage T1DM. To assess the impact and implementation of the app, the service-level evaluation deployed a mixed-methods design. App data were captured via the DigiBete platform and an online survey with a non-probability sample of HCPs (N = 178) and CYPF (N = 1165) = 1343. Overall, 55.7% (n = 512/919) of app users were female, and 4855 videos were viewed across the participating areas, with an average of 1213 videos per site (range 776-1679) and 4.4 videos per app user. The most popular videos were how to give a glucagon injection and "My Sick Day Rules", which showed what to do when CYPF were unwell due to T1DM. Interviews (n = 63) were undertaken with 38 CYPF and 25 HCPs. The findings indicate that CYPF and HCPs found the app an essential tool in the management of T1DM. CYPF and HCPs felt the app provided a valuable educational resource in a central location that was invaluable in an emergency or unknown situation. The app was a trusted and bona-fide source of information that could be accessed at any time. HCPs validated DigiBete in helping CYPF to manage their T1DM. At the same time, the app saved HCPs' service time and money and helped CYPF take back some of the control in managing their diabetes.

Social Media-Delivered Lifestyle Interventions Among Individuals Living with Diabetes and Prediabetes: A Scoping Review

PURPOSE OF REVIEW

There is a lack of synthesized evidence on social media-delivered lifestyle interventions for managing and preventing diabetes. This scoping review aims to evaluate recently reported lifestyle interventions delivered on social media for individuals with diabetes and prediabetes.

RECENT FINDINGS

Twelve studies were included in this review. A team of multidisciplinary healthcare professionals coordinated most interventions, half of which lasted for 6 months, and used a combination of videos, texts, images or audio to deliver the educational materials. The glycosylated hemoglobin (HbA1c) level improved in most of the studies, followed by diabetes self-care and fasting plasma glucose. The dietary intakes were only assessed in two interventions among the individuals with prediabetes and showed promising improvements. This scoping review provides a holistic overview of the recent designs of lifestyle interventions for diabetes management and prevention on social media. This is essential for various healthcare professionals and stakeholders to formulate and implement population-based, cost-effective interventions in combating diabetes using social media.

Comparative efficacy of digitally assisted interventions for glycated haemoglobin levels among patients with type 2 diabetes: A systematic review and component network Meta-Analysis

AIMS

To compare the efficacy of digitally assisted interventions on the glycated haemoglobin (HbA1c) levels of patients with type 2 diabetes by performing a systematic review, network meta-analysis and component network meta-analysis.

METHODS

Six databases were searched to identify eligible articles from the inception of each database until 17 March 2023. We included randomized controlled trials evaluating HbA1c levels. Data were pooled with a random-effects model under a frequentist framework. The evidence certainty was assessed using Confidence in Network MetaAnalysis (CINeMA). The PROSPERO registration number was CRD42021283815.

RESULTS

In total, 75 trials involving 9764 participants were included. Results from standard network meta-analyses of 17 interventions revealed that compared with standard care, a mobile application (MA) combined with a professional education programme and peer support education (PSE; -1.98, 95% confidence interval = -2.90 to -1.06, CINeMA score: moderate to high) significantly reduced HbA1c levels. The component analysis found that PSE (-1.50, -2.36 to -0.64), SMS (-0.33, -0.56 to -0.11), MA (-0.30, -0.56 to -0.04) and telephone calls (-0.30, -0.53 to -0.06) most effectively reduced HbA1c levels among patients with type 2 diabetes.

CONCLUSIONS

SMS and MA are the optimal digitally assisted interventions for reducing HbA1c levels. Educators can integrate digitally assisted interventions complemented by educational programmes, particularly MA combined with professional education programme and PSE, into daily care to control HbA1c. The limitations of included trials include a lack of information on allocation concealment and blinding and the fact that long-term follow-up effects were not investigated.

Digital Phenotyping in Adults with Schizophrenia: A Narrative Review

PURPOSE OF REVIEW

As care for older adult patients with schizophrenia lacks innovation, technology can help advance the field. Specifically, digital phenotyping, the real-time monitoring of patients' behaviors through smartphone sensors and symptoms through surveys, holds promise as the method can capture the dynamicity and environmental correlates of disease.

RECENT FINDINGS

Few studies have used digital phenotyping to elucidate adult patients' experiences with schizophrenia. In this narrative review, we summarized the literature using digital phenotyping on adults with schizophrenia. No study focused solely on older adult patients. Studies including all adult patients were heterogeneous in measures used, duration, and outcomes. Despite limited research, digital phenotyping shows potential for monitoring outcomes such as negative, positive, and functional symptoms, as well as predicting relapse. Future research should work to target the symptomology persistent in chronic schizophrenia and ensure all patients have the digital literacy required to benefit from digital interventions and homogenize datasets to allow for more robust conclusions.

Association between eHealth literacy, diabetic behavior rating, and burden among caregivers of children with type 1 diabetes: Cross-sectional survey study

OBJECTIVE

The purpose of this study was to clarify the relationship between eHealth literacy, diabetic behavior rating, and caregiving burden among caregivers of children with type 1 diabetes mellitus (T1DM).

METHODS

A questionnaire-based cross-sectional study of 143 primary caregivers of T1DM was conducted. Electronic health literacy was quantified using the Chinese version of the eHealth Literacy Scale (eHEALS). Their diabetic management behavior rating and caregiving burden were measured by Diabetes Behavior Rating Scale-Parent Version (DBRS-P) and Zarit Burden Interview (ZBI), respectively. Pearson correlation analysis was used to estimate the relationship between the above variables.

RESULTS

Only 54 (37.76%) caregivers qualified by eHEALS scale, with a total score of 30.07 ± 4.54 out of 40. A positive correlation between DRBS-P scores and the scores of eHEALS (Pearson correlation coefficient r = 0.226, P = 0.007) and a negative correlation between ZBI and eHEALS scores (r = -0.166, P = 0.047) were observed.

CONCLUSIONS

The eHealth literacy level of caregivers of children with T1DM in China remains to be improved. Caregivers with higher eHealth literacy had better diabetic management behaviors and less caregiving burden.

IMPLICATIONS TO PRACTICE

This study suggests that hierarchical electronic health-based interventions should be designed according to the different levels of eHealth literacy of individuals, to enhance the ability of caregivers with different eHealth literacy levels to fully utilize eHealth resources to improve their daily disease management skills and reduce their burden when caring for T1DM children. In addition, improving eHealth literacy of caregivers for children with T1DM can be one of the important ways to enhance the effectiveness of electronic health-based programs designed for them.

Factors affecting the willingness of patients with type 2 diabetes to use digital disease management applications: a cross-sectional study

Background

The global burden of type 2 diabetes has significantly increased, leading to a considerable impact on healthcare systems worldwide. While the advent of mobile healthcare has provided some relief by addressing the shortage of certain medical resources, its adoption among the Chinese population remains relatively low. To extend the benefits of mHealth to a greater number of Chinese diabetic patients, it is essential to investigate the factors that influence their willingness to utilize it and implement targeted interventions based on these influencing factors. The Technology Acceptance Model (TAM) is widely employed to examine users' ultimate usage behaviors, and previous studies have indicated the potential relevance of the Perceived Risk (PR) theory and the eHealth Literacy Theory to users' usage behaviors.

Objective

Our objective was to investigate the determinants that affect the willingness of Chinese patients diagnosed with type 2 diabetes patients to utilize digital disease management applications (DDMAs).

Methods

We conducted a cross-sectional study of patients with type 2 diabetes in three tertiary general hospitals in Chengdu using questionnaires designed by the investigators. Participants were sampled using a convenience sampling method. The questionnaire comprised three sections: socio-demographic profile and medical history; current awareness and willingness to use digital disease management applications; and the current level of e-health literacy. Structural equation modeling was employed to assess the impact of patient awareness of DDMAs and e-health literacy on the willingness to use such DDMAs.

Results

(1) Patients' attitudes toward using DDMAs were significantly influenced by perceived ease of use (β = 0.380, P < 0.001) and perceived usefulness (β = 0.546, P < 0.001); (2) Electronic health literacy exerted a significant impact on patients' perceived usefulness (β = 0.115, P = 0.018) and perceived ease of use (β = 0.659, P < 0.001); (3) Patients' willingness to use was significantly influenced by perceived usefulness (β = 0.137, P < 0.001) and use attitude (β = 0.825, P < 0.001).

Conclusions

The present research findings hold both theoretical and practical significance, and can serve as a guide for healthcare practitioners and researchers to gain a deeper comprehension of the acceptance of digital disease management applications (DDMAs) among type 2 diabetes patients.

Evaluation of negative binomial and zero-inflated negative binomial models for the analysis of zero-inflated count data: application to the telemedicine for children with medical complexity trial

BACKGROUND

Two characteristics of commonly used outcomes in medical research are zero inflation and non-negative integers; examples include the number of hospital admissions or emergency department visits, where the majority of patients will have zero counts. Zero-inflated regression models were devised to analyze this type of data. However, the performance of zero-inflated regression models or the properties of data best suited for these analyses have not been thoroughly investigated.

METHODS

We conducted a simulation study to evaluate the performance of two generalized linear models, negative binomial and zero-inflated negative binomial, for analyzing zero-inflated count data. Simulation scenarios assumed a randomized controlled trial design and varied the true underlying distribution, sample size, and rate of zero inflation. We compared the models in terms of bias, mean squared error, and coverage. Additionally, we used logistic regression to determine which data properties are most important for predicting the best-fitting model.

RESULTS

We first found that, regardless of the rate of zero inflation, there was little difference between the conventional negative binomial and its zero-inflated counterpart in terms of bias of the marginal treatment group coefficient. Second, even when the outcome was simulated from a zero-inflated distribution, a negative binomial model was favored above its ZI counterpart in terms of the Akaike Information Criterion. Third, the mean and skewness of the non-zero part of the data were stronger predictors of model preference than the percentage of zero counts. These results were not affected by the sample size, which ranged from 60 to 800.

CONCLUSIONS

We recommend that the rate of zero inflation and overdispersion in the outcome should not be the sole and main justification for choosing zero-inflated regression models. Investigators should also consider other data characteristics when choosing a model for count data. In addition, if the performance of the NB and ZINB regression models is reasonably comparable even with ZI outcomes, we advocate the use of the NB regression model due to its clear and straightforward interpretation of the results.

Impact of digital health interventions for adolescents with type 1 diabetes mellitus on health literacy: a systematic review

BACKGROUND

Evidence shows that living with diabetes mellitus type 1 (T1DM) in adolescent age is particularly challenging and difficult to manage. A high level of health literacy is important to prevent and avoid debilitating complications. Despite the increasing prevalence and incidence of T1DM by adolescent and the large use of digital health interventions, little is known about the association between this use and health literacy. This systematic review provides an overview on the impact of digital health interventions for adolescents with type 1 diabetes on health literacy and derive recommendations for further research.

METHODS

Electronic searches were performed in five databases in Medline (Medline, PubMed + via PubMed), The Cochrane Library, EMBASE (via Ovid), Web of Science and PsycINFO from 2011 to 2021. In addition, grey literature searches were conducted in Google Scholar, OAlster and Trip. Relevant studies that have been missed by electronic and hand-searching strategies were searched in the reference lists of all included studies. The review followed PRISMA guidelines. Two researchers independently screened abstracts for initial eligibility and applied the inclusion and exclusion criteria to the relevant full-text articles. Quality was assessed using the tools RoB2 Cochrane, ROBINS I, NOS (Newcastle-Ottawa Scale), CASP (Critical Appraisal Skills Programme) for primary studies and Amstar-2 for secondary studies.

RESULTS

Out of 981 studies, 22 were included in the final review. Most primary studies included in this review were judged as moderate overall risk of bias or with some concerns and most of the secondary studies as critically low quality reviews. Our findings suggest that the interplay of health care providers (HCP) and patients through social media helps the management of the disease. This corroborates Bröder et al.' (2017) dimension of 'communication and interactions' in their concept of health literacy.

CONCLUSIONS

For adolescents with T1DM, social media may be a specific and beneficial intervention for an improved communication and interaction with their HCP. Further research should investigate what specific form of social media suits best for which adolescents.

TRIAL REGISTRATION

The study protocol was registered on the 15th of November 2021 on Prospero (reg. NR: CRD42021282199).

How general practitioners and patients discuss type 2 diabetes mellitus and cardiovascular diseases concerns during consultations: Implications for digital health

Objective

To analyse general practitioner-patient consultations about type 2 diabetes mellitus or cardiovascular diseases and describe (i) the nature of self-management discussions; (ii) actions required from patients during and after consultation regarding self-management; and (iii) implications for digital health to support patients during (and after) consultation.

Method

This study screened 281 general practitioner consultations conducted in 2017 within the UK general practice setting from an existing dataset containing videos and transcripts of consultations between GPs and patients. Secondary analysis was conducted using a multi-method approach, including descriptive, content, and visualisation analysis, to inform the nature of self-management discussions, what actions are required from patients, and whether digital technology was mentioned during the consultation to support self-management.

Results

Analysis of eligible 19 consultations revealed a discord between what self-management actions are required of patients during and after consultations. Lifestyle discussions are often discussed in depth, but these discussions rely heavily on subjective inquiry and recall. Some patients in these cohorts are overwhelmed by self-management, to the detriment of their personal health. Digital support for self-management was not a major topic of discussion, however, we identified a number of emergent gaps where digital technology can support self-management concerns.

Conclusion

There is potential for digital technology to reconcile what actions are required of patients during and after consultations. Furthermore, a number of emergent themes around self-management have implications for digitalisation.

The efficacy of interventions provided by nurses to improve glycemic control of children with type 1 diabetes: A systematic review

PURPOSE

Nurses have a very important role in diabetes education of children and adolescents, however, no systematic review has been performed that evaluates the effectiveness of the independent interventions of the nurses. This systematic review aims to identify and assess randomized controlled trials (RCT) that included interventions implemented by nurses to improve glycemic control for children and adolescents with type 1 diabetes.

ELIGIBILITY CRITERIA

PubMed, the Cochrane Central Register of Controlled Trials, Scopus, Web of Science, Science Direct databases were systematically searched up to 2022. Interventions provided by nurses for any child ≤18 years diagnosed with type 1 diabetes mellitus were included.

SAMPLE

Seven RCT articles met our review criteria.

RESULTS

All included studies were published between 2005 and 2021. Studies varied in terms of intervention type; telephone case management, coping skills training, motivational interview as well as home visit education programs. Interventions were found to significantly decrease the HbA1c level in three of seven studies.

CONCLUSIONS

Our systematic review suggests that nurses can improve the glycemic control of children with type 1 diabetes by conducting care interventions. According to current evidence, this study suggests that telephone contact by nurses and motivational interviewing can be beneficial in improving glycemic control in this population.

IMPLICATIONS

Nurses may encourage children and adolescents with diabetes to engage in self-management of their glucose levels. There is a need for more randomized controlled studies assessing the efficacy of nursing interventions for children with type 1 diabetes.

Digital health experiences reported in chronic disease management: An umbrella review of qualitative studies

Introduction

Digital health interventions can be useful for the management of chronic disease. The aim of this study was to draw out universal themes to understand how people with chronic conditions experience digital health services, programmes, and interventions, and consequently, better inform future digital health delivery.

Methods

An umbrella review was conducted to identify qualitative systematic reviews reporting digital health experiences in chronic disease. Themes for each included review were independently extracted and appraised by two review authors. Data analysis was conducted using the Constant Comparative method.

Results

Twenty-two systematic reviews containing 240 individual studies were selected for inclusion. Mental health was the most common condition ( n = 5, 23%), followed by cancer ( n = 4, 18%) or a combination of chronic diseases ( n = 4, 18%). Common themes across the conditions were categorised under nine headings, including: (i) participation and engagement (strong usability and engagement vs reluctance to use digital health when these concepts are ignored), (ii) trust, confidence, and competence (users felt reassured, however technology illiteracy led to a perceived lack of control), (iii) perceived value, perceived effectiveness, transaction cost (gained from efficient aspects of digital health, but also lost through the burden of keeping up with data entry), (iv) perceived care quality (requiring tailoring and fostering motivation), (v) barriers and threats (related to technology risks and challenges), (vi) health outcomes (improved self-management capability), (vii) relationships (improved participant-health professional interaction, but interpersonal aspects such as face-to-face contact were lacking), (viii) unplanned benefit (where digital health often led to users feeling more empowered in their health journey), and (ix) diversity of experiences (reflecting ambivalence of experiences and discipline-specific experiences).

Conclusion

People with chronic conditions perceive digital health provides feelings of reassurance and the ability to self-manage their condition. While there is ambivalence across the participant experiences reported within the major themes, this umbrella review has outlined a need for future interventions that are user-friendly, flexible, and tailored to individual users. This will be best achieved through a co-design model, with the consumer actively involved in the planning and design of digital health products and services.

The effectiveness of digital health technologies for patients with diabetes mellitus: A systematic review

Introduction

Diabetes mellitus (DM) is a leading cause of morbidity and mortality worldwide. At the same time, digital health technologies (DHTs), which include mobile health apps (mHealth) have been rapidly gaining popularity in the self-management of chronic diseases, particularly following the COVID-19 pandemic. However, while a great variety of DM-specific mHealth apps exist on the market, the evidence supporting their clinical effectiveness is still limited.

Methods

A systematic review was performed. A systematic search was conducted in a major electronic database to identify randomized controlled trials (RCTs) of mHealth interventions in DM published between June 2010 and June 2020. The studies were categorized by the type of DM and impact of DM-specific mHealth apps on the management of glycated haemoglobin (HbA1c) was analysed.

Results

In total, 25 studies comprising 3,360 patients were included. The methodological quality of included trials was mixed. Overall, participants diagnosed with T1DM, T2DM and Prediabetes all demonstrated greater improvements in HbA1c as a result of using a DHT compared with those who experienced usual care. The analysis revealed an overall improvement in HbA1c compared with usual care, with a mean difference of –0.56% for T1DM, –0.90% for T2DM and –0.26% for Prediabetes.

Conclusion

DM-specific mHealth apps may reduce HbA1c levels in patients with T1DM, T2DM and Prediabetes. The review highlights a need for further research on the wider clinical effectiveness of diabetes-specific mHealth specifically within T1DM and Prediabetes. These should include measures which go beyond HbA1c, capturing outcomes including short-term glycemic variability or hypoglycemic events.

Effectiveness of Therapeutic Patient Education Interventions in Obesity and Diabetes: A Systematic Review and Meta-Analysis of Randomized Controlled Trials

Diabetes mellitus (DM) and obesity account for the highest burden of non-communicable diseases. There is increasing evidence showing therapeutic patient education (TPE) as a clinically and cost-effective solution to improve biomedical and psychosocial outcomes among people with DM and obesity. The present systematic review and meta-analysis present a critical synthesis of the development of TPE interventions for DM and obesity and the efficacy of these interventions across a range of biomedical, psychosocial and psychological outcomes. A total of 54 of these RCTs were identified among patients with obesity and diabetes and were thus qualitatively synthesized. Out of these, 47 were included in the quantitative synthesis. There was substantial heterogeneity in the reporting of these outcomes (I2 = 88.35%, Q = 317.64), with a significant improvement noted in serum HbA1c levels (standardized mean difference (SMD) = 0.272, 95% CI: 0.118 to 0.525, n = 7360) and body weight (SMD = 0.526, 95% CI: 0.205 to 0.846, n = 1082) in the intervention group. The effect sizes were comparable across interventions delivered by different modes and delivery agents. These interventions can be delivered by allied health staff, doctors or electronically as self-help programs, with similar effectiveness (p < 0.001). These interventions should be implemented in healthcare and community settings to improve the health outcomes in patients suffering from obesity and DM.

An automated process for supporting decisions in clustering-based data analysis

BACKGROUND AND OBJECTIVE

Metrics are commonly used by biomedical researchers and practitioners to measure and evaluate properties of individuals, instruments, models, methods, or datasets. Due to the lack of a standardized validation procedure for a metric, it is assumed that if a metric is appropriate for analyzing a dataset in a certain domain, then it will be appropriate for other datasets in the same domain. However, such generalizability cannot be taken for granted, since the behavior of a metric can vary in different scenarios. The study of such behavior of a metric is the objective of this paper, since it would allow for assessing its reliability before drawing any conclusion about biomedical datasets.

METHODS

We present a method to support in evaluating the behavior of quantitative metrics on datasets. Our approach assesses a metric by using clustering-based data analysis, and enhancing the decision-making process in the optimal classification. Our method assesses the metrics by applying two important criteria of the unsupervised classification validation that are calculated on the clusterings generated by the metric, namely stability and goodness of the clusters. The application of our method is facilitated to biomedical researchers by our evaluomeR tool.

RESULTS

The analytical power of our methods is shown in the results of the application of our method to analyze (1) the behavior of the impact factor metric for a series of journal categories; (2) which structural metrics provide a better partitioning of the content of a repository of biomedical ontologies, and (3) the heterogeneity sources in effect size metrics of biomedical primary studies.

CONCLUSIONS

The use of statistical properties such as stability and goodness of classifications allows for a useful analysis of the behavior of quantitative metrics, which can be used for supporting decisions about which metrics to apply on a certain dataset.

Accessibility and Openness to Diabetes Management Support via Mobile Phones: A Survey of People with Type 1 Diabetes Using Advanced Diabetes Technologies (Preprint)

Background

Little is known about the feasibility of mobile health (mHealth) support among people with type 1 diabetes (T1D) using advanced diabetes technologies including continuous glucose monitoring (CGM) systems and hybrid closed-loop insulin pumps (HCLs).

Objective

This study aims to evaluate patient access and openness to receiving mHealth diabetes support in people with T1D using CGM systems or HCLs.

Methods

We conducted a cross-sectional survey among patients with T1D using CGM systems or HCLs managed in an academic medical center. Participants reported information regarding their mobile device use; cellular call, SMS text message, or internet connectivity; and openness to various channels of mHealth communication (smartphone apps, SMS text messages, and interactive voice response [IVR] calls). Participants’ demographic characteristics and CGM data were collected from medical records. The analyses focused on differences in openness to mHealth and mHealth communication channels across groups defined by demographic variables and measures of glycemic control.

Results

Among all participants (N=310; female: n=198, 63.9%; mean age 45, SD 16 years), 98.1% (n=304) reported active cellphone use and 80% (n=248) were receptive to receiving mHealth support to improve glucose control. Among participants receptive to mHealth support, 98% (243/248) were willing to share CGM glucose data for mHealth diabetes self-care assistance. Most (176/248, 71%) were open to receiving messages via apps, 56% (139/248) were open to SMS text messages, and 12.1% (30/248) were open to IVR calls. Older participants were more likely to prefer SMS text messages (P=.009) and IVR calls (P=.03) than younger participants.

Conclusions

Most people with T1D who use advanced diabetes technologies have access to cell phones and are receptive to receiving mHealth support to improve diabetes control.