Effectiveness of mobile applications in diabetic patients' healthy lifestyles: A review of systematic reviews

Improving the management of type 2 diabetes in China using a multifaceted digital health intervention in primary health care: the SMARTDiabetes cluster randomised controlled trial

Background

There is limited evidence, mainly from high-income countries, that digital health interventions improve type 2 diabetes (T2DM) care. Large-scale implementation studies are lacking.

Methods

A multifaceted digital health intervention comprising: (1) a self-management application ('app') for patients and lay 'family health promotors' (FHPs); and (2) clinical decision support for primary care doctors was evaluated in an open-label, parallel, cluster randomized controlled trial in 80 communities (serviced by a primary care facility for >1000 residents) in Hebei Province, China. People >40 years with T2DM and a glycated haemoglobin (HbA1c) ≥7% were recruited (∼25/community). After baseline assessment, community clusters were randomly assigned to intervention or control groups (1:1) via a web-based system, stratified by locality (rural/urban). Control arm clusters received usual care without access to the digital health application or family health promoters. The primary outcome was at the participant level defined as the proportion with ≥2 "ABC" risk factor targets achieved (HbA1c < 7.0%, blood pressure < 140/80 mmHg and LDL-cholesterol < 2.6 mmol/L) at 24 months.

Findings

A total of 2072 people were recruited from the 80 community clusters (40 urban and 40 rural), with 1872 (90.3%) assessed at 24 months. In the intervention arm, patients used FHPs for support more in rural than urban communities (252 (48.6%) rural vs 92 (21.5%) urban, p < 0.0001). The mean monthly proportion of active app users was 46.4% (SD 7.8%) with no significant difference between urban and rural usage rates. The intervention was associated with improved ABC control rates (339 [35.9%] intervention vs 276 [29.9%] usual care; RR 1.20, 95% CI 1.02-1.40; p = 0.025), with significant heterogeneity by geography (rural 220 [42.6%] vs 158 [31.0%]; urban 119 [27.9%] vs 118 [28.6%]; p = 0.022 for interaction). Risk factor reductions were mainly driven by improved glycaemic control (mean HbA1C difference -0.33%, 95% CI -0.48 to -0.17; p = 0.00025 and mean fasting plasma glucose difference -0.58 mmol, 95% CI -0.89 to -0.27; p = 0.00013). There were no changes in blood pressure and LDL-cholesterol levels.

Interpretation

A multifaceted digital health intervention improved T2DM risk factor control rates, particularly in rural communities where there may be stronger relationships between patients and doctors and greater family member support.

Funding

National Health and Medical Research CouncilGlobal Alliance for Chronic Diseases (ID 1094712).

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.

The effect of personalized intelligent digital systems for self-care training on type II diabetes: a systematic review and meta-analysis of clinical trials

AIMS

Type 2 diabetes (T2D) is rising worldwide. Self-care prevents diabetic complications. Lack of knowledge is one reason patients fail at self-care. Intelligent digital health (IDH) solutions have a promising role in training self-care behaviors based on patients' needs. This study reviews the effects of RCTs offering individualized self-care training systems for T2D patients.

METHODS

PubMed, Web of Science, Scopus, Cochrane Library, and Science Direct databases were searched. The included RCTs provided data-driven, individualized self-care training advice for T2D patients. Due to the repeated studies measurements, an all-time-points meta-analysis was conducted to analyze the trends over time. The revised Cochrane risk-of-bias tool (RoB 2.0) was used for quality assessment.

RESULTS

In total, 22 trials met the inclusion criteria, and 19 studies with 3071 participants were included in the meta-analysis. IDH interventions led to a significant reduction of HbA1c level in the intervention group at short-term (in the third month: SMD = - 0.224 with 95% CI - 0.319 to - 0.129, p value < 0.0; in the sixth month: SMD = - 0.548 with 95% CI - 0.860 to - 0.237, p value < 0.05). The difference in HbA1c reduction between groups varied based on patients' age and technological forms of IDH services delivery. The descriptive results confirmed the impact of M-Health technologies in improving HbA1c levels.

CONCLUSIONS

IDH systems had significant and small effects on HbA1c reduction in T2D patients. IDH interventions' impact needs long-term RCTs. This review will help diabetic clinicians, self-care training system developers, and researchers interested in using IDH solutions to empower T2D patients.

What are the roles of eHealth literacy and empowerment in self-management in an eHealth care context? A cross-sectional study

AIMS

To examine the relationship among eHealth literacy, empowerment and self-management and the mediating effects of empowerment in diabetic kidney disease (DKD) patients in the eHealthcare context.

BACKGROUND

Self-management is an essential aspect of healthcare in delaying disease progression for DKD. In the eHealthcare era, health services providing self-management are transforming. The ability and confidence of patients to use eHealth services is a critical issue that impacts the effectiveness of self-management, but little is known about the role of eHealth literacy and empowerment in self-management.

DESIGN

A cross-sectional study guided by the STROBE.

METHODS

Overall, 127 Taiwanese patients were enrolled using convenience sampling. Data collection used structured questionnaires and chart reviews. Multiple regression was used to infer self-management predictors, and SPSS PROCESS macro and bootstrapping verified the mediating effects.

RESULTS

Empowerment and eHealth literacy both showed significant positive correlations with self-management. Empowerment was the main predictor of self-management and had a complete mediating effect between eHealth literacy and self-management.

CONCLUSION

Increasing patients' eHealth literacy can improve empowerment and prevent health inequality issues. Healthcare providers should consider improving patients' eHealth literacy to enhance their self-management.

RELEVANCE TO CLINICAL PRACTICE

Healthcare service systems need to create user-friendly eHealthcare environments, and healthcare professionals can provide multifaceted instructions that fit patients' eHealth literacy levels to enhance their motivation and confidence in disease care, thus cultivating positive self-management behaviours.

IMPACT

The popularity of eHealthcare services aimed at promoting self-management behaviours is increasing. However, the level of eHealth literacy is an essential factor that affects the effectiveness of self-management in the healthcare environment. In addition, empowerment is a major critical influence factor of self-management and a completely mediating variable between self-management and eHealth literacy. Consequently, healthcare providers should consider promoting patients' eHealth literacy to empower people using eHealthcare services for implementing self-management.

REPORTING METHOD

The Strengthening the Reporting of Observational Studies in cross-sectional studies (STROBE) checklist was used to ensure comprehensive reporting.

PATIENT OR PUBLIC CONTRIBUTION

Patients were diagnosed with DKD in the study hospital. Physicians and case managers transferred patients to research assistants who screened them for the inclusion criteria and invited them to participate in this study if they met the requirements. After participants signed informed consent, the research nurse encouraged participants to respond to the research questionnaire face to face.

Machine Learning and Smart Devices for Diabetes Management: Systematic Review

(1) Background: The use of smart devices to better manage diabetes has increased significantly in recent years. These technologies have been introduced in order to make life easier for patients with diabetes by allowing better control of the stability of blood sugar levels and anticipating the occurrence of dangerous events (hypo/hyperglycemia), etc. That being said, the main objectives of the self-management of diabetes is to improve the lifestyle and life quality of patients with diabetes; (2) Methods: We performed a systematic review based on articles that focus on the use of smart devices for the monitoring and better management of diabetes. The search was focused on keywords related to the topic, such as “Diabetes”, “Technology”, “Self-management”, “Artificial Intelligence”, etc. This was performed using databases, such as Scopus, Google Scholar, and PubMed; (3) Results: A total of 89 studies, published between 2011 and 2021, were included. The majority of the selected research aims to solve a diabetes management problem (e.g., blood glucose prediction, early detection of risk events, and the automatic adjustment of insulin doses, etc.). In these studies, wearable devices were used in combination with artificial intelligence (AI) techniques; (4) Conclusions: Wearable devices have attracted a great deal of scientific interest in the field of healthcare for people with chronic conditions, such as diabetes. They are capable of assisting in the management of diabetes, as well as preventing complications associated with this condition. Furthermore, the usage of these devices has improved illness management and quality of life.