Smartphone-Based mHealth and Internet of Things for Diabetes Control and Self-Management

A mobile health application use among diabetes mellitus patients: a systematic review and meta-analysis

Background

Mobile health technologies are increasingly acknowledged as a cost-effective and convenient means of delivering top-notch healthcare services to patients in low- and middle-income countries. This research explores the utilization of mobile health applications in managing, monitoring, and self-care for adult diabetes mellitus (DM) patients. The objective is to gain insight into how diabetic patients currently utilize Mobile health applications for self-management and their inclination to use them in the future.

Methods

The authors conducted a systematic review and meta-analysis using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. They included articles that reported on the use of mobile/smartphone applications for diabetic mellitus disorders, focusing on ownership, application use, future interest in use, and use patterns. The search was conducted in the PubMed, Web of Science, Embase, and SCOPUS electronic databases, with various published articles from January 2016 up to February 2024. The methodological quality was evaluated using the Joanna Briggs Institute critical appraisal tool. Statistical techniques were applied, including the heterogeneity test, publication bias assessment, Egger's test, and funnel plots. The pooled prevalence was calculated using meta-analysis proportion with a random-effects model.

Results

Thirteen studies were included, out of 4568 recognized articles. The pooled prevalence of mobile health application use for current diabetic management self-management, future interest in using the application for diabetic disorder self-management, and lack of belief in mobile health application users for self-management was 35%, 57%, and 39%, respectively. We observed significant heterogeneity (I2 = 97.7, p=<0.001), but no significant publication bias was detected on Egger's test.

Conclusions

Our meta-analysis results show that over one-third of individuals use mobile health applications for diabetic self-management, and more than half of individuals would like to manage their diabetes mellitus in the future by using mobile health applications. These mobile health apps may be promising in future diabetes mellitus self-management. However, we still need to study the effectiveness of these apps. In addition, adopting mobile health apps based on the cultural context makes this self-management more achievable, practical, and impactful for individuals with diabetes.

Systematic review registration

https://www.crd.york.ac.uk/prospero/, identifier 42024537917.

Benchmarking mobile applications for the health of people with Diabetes Mellitus

OBJECTIVE

to map the content and features of mobile applications on the management of Diabetes Mellitus and their usability on the main operating systems.

METHOD

benchmarking research. The mapping of apps, content, and resources on the Play Store and App Store platforms was based on an adaptation of the Joanna Briggs Institute's scoping review framework. For the usability analysis, the apps were tested for two weeks and the System Usability Scale instrument was used, with scores between 50-67 points being considered borderline, between 68-84, products with acceptable usability and above 85, excellent user acceptance and, for the analysis, descriptive statistics.

RESULTS

the most prevalent contents were capillary blood glucose management, diet, oral drug therapy, and insulin therapy. As for resources, diaries and graphs were the most common. With regard to usability, two apps were considered to have excellent usability; 34, products with acceptable usability; 29, the resource may have some flaws but still has acceptable usability standards and 6, with flaws and no usability conditions.

CONCLUSION

the content and resources of mobile applications address the fundamental points for managing Diabetes Mellitus with user-friendly resources, with usability acceptable to users and have the potential to assist in the management of Diabetes Mellitus in patients' daily lives.

Stratified support pattern-based internet-assisted self-management therapy for diabetes mellitus -mild cognitive impairment: a randomized controlled trial protocol

BACKGROUND

Mild cognitive impairment (MCI) associated with diabetes mellitus (DM) is common among older adults, and self-management is critical to controlling disease progression. However, both MCI and DM are heterogeneous diseases, and existing integrated self-management interventions do not consider patient differences. Grouping patients by disease characteristics could help to individualize disease management and improve the use of available resources. The current study sought to explore the feasibility and effectiveness of a stratified support model for DM-MCI patients.

METHODS

Eighty-four DM-MCI patients will be randomly divided into an intervention group and a control group in a 1:1 ratio. The intervention group will receive a self-management intervention using the stratified support pattern-based internet-assisted therapy (SISMT), while the control group will receive the health manual intervention (HMI). The study recruiter will be blinded to the group allocation and unable to foresee which group the next participant will be assigned to. At the same time, the allocation will be also hidden from the research evaluators and participants. After 12 weeks and 24 weeks, cognitive function, blood glucose, self-management ability, psychological status, health literacy, and self-management behavior of patients in both groups will be measured and compared.

DISCUSSION

This study developed a stratified support pattern-based internet-assisted to provide self-management intervention for patients with DM-MCI. The impact of different models and forms of self-management intervention on cognitive function, blood glucose management, and psychological status health literacy and self-management behavior of patients will be assessed. The results of this study will inform related intervention research on the stratified support pattern-based internet-assisted self-management therapy, and help to slow the decline of cognitive function in patients with DM-MCI.

TRIAL REGISTRATION

ChiCTR2200061991. Registered 16 July 2022.

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.

Retracted: Smartphone-Based mHealth and Internet of Things for Diabetes Control and Self-Management

[This retracts the article DOI: 10.1155/2021/2116647.].

Device-supported automated basal insulin titration in adults with type 2 diabetes: a systematic review and meta-analysis of randomized controlled trials

Background

Technological advances make it possible to use device-supported, automated algorithms to aid basal insulin (BI) dosing titration in patients with type 2 diabetes.

Methods

A systematic review and meta-analysis of randomized controlled trials were performed to evaluate the efficacy, safety, and quality of life of automated BI titration versus conventional care. The literature in Medline, Embase, Web of Science, and the Cochrane databases from January 2000 to February 2022 were searched to identify relevant studies. Risk ratios (RRs), mean differences (MDs), and their 95% confidence intervals (CIs) were calculated using random-effect meta-analyses. Certainty of evidence was assessed using the Grading of Recommendations, Assessment, Development and Evaluations (GRADE) approach.

Findings

Six of the 7 eligible studies (889 patients) were included in meta-analyses. Low- to moderate-quality evidence suggests that patients who use automated BI titration versus conventional care may have a higher probability of reaching a target of HbA_1c <7.0% (RR, 1.82 [95% CI, 1.16-2.86]); and a lower level of HbA_1c (MD, -0.25% [95% CI, -0.43 to -0.06%]). No statistically significant differences were detected between the two groups in fasting glucose results, incidences of hypoglycemia, severe or nocturnal hypoglycemia, and quality of life, with low to very low certainty for all the evidence.

Interpretation

Automated BI titration is associated with small benefits in reducing HbA_1c without increasing the risk of hypoglycemia. Future studies should explore patient attitudes and the cost-effectiveness of this approach.

Funding

Sponsored by the Chinese Geriatric Endocrine Society.

Influence of Information-Based Continuous Care on Disease Control and Treatment Compliance of Elderly Diabetic Patients

Background

The incidence of diabetes is increasing year by year. For elderly diabetic patients, poor blood glucose control and worsening immune function greatly increase the risk of complications, which will seriously affect their quality of life.

Purpose

This paper primarily clarifies the influence of information-based continuous care on disease control and treatment compliance of elderly diabetic patients.

Methods

From December 2018 to December 2021, 106 elderly diabetic patients were selected, and their clinical data were retrospectively studied. Patients were grouped according to the type of care they received: an observation group (OG) comprising 56 cases receiving information-based continuous care and a control group (CG) including 50 cases treated with routine nursing. The two cohorts of patients were compared regarding disease control, treatment compliance, glucose and lipid metabolism (GLM), and self-management.

Results

After analysis, it was found that the disease control and treatment compliance were statistically higher in OG compared with CG. OG also showed significantly reduced fasting blood glucose (FBG), 2-hour postprandial blood glucose (2hPG), total cholesterol (TC), and triglyceride (TG) after nursing that were all lower compared with CG. In terms of self-management, OG outperformed CG in diet, exercise, blood glucose monitoring, and adherence to medical regimens.

Conclusions

Information-based continuous care has beneficial effects on disease control and treatment compliance of elderly diabetic patients and can help control blood sugar and optimize patients' self-management level, with high clinical promotion value.