RESUMO
BACKGROUND: The aim of this study was to determine the effect of a Self-Monitoring Blood Glucose (SMBG) intervention package through a subscription model in improving HbA1c and health parameters among type-2 diabetes mellitus (T2DM) individuals in Malaysia. METHODS: This is a quasi-experimental study involving a total number of 111 individuals with T2DM (mean age 57.0 ± 11.7 years, 61% men) who were assigned to intervention (n = 51) and control (n = 60) groups. The intervention group participants were the subscribers of SugO365 program which provided a personalized care service based on self-recorded blood glucose values. Subscribers received a Contour® Plus One glucometer which can connect to Health2Sync mobile app to capture all blood glucose readings as well as physical and virtual follow up with dietitians, nutritionists, and pharmacists for 6 months. Outcome measures were body weight, body mass index (BMI), random blood glucose (RBG), glycated haemoglobin (HbA1c) and health-related quality of life (HRQoL, assessed by SF-36 questionnaire). Data were measured at baseline, third and sixth months. RESULTS: Repeated-measure analysis of covariance showed significant improvement in HbA1c level (Æp2 = 0.045, p = 0.008) in the intervention (baseline mean 7.7% ± 1.1%; end mean 7.3% ± 1.3%) as compared to control (baseline mean 7.7% ± 0.9%; end mean 8.1% ± 1.6%) group. Similar trend was observed for Role Emotional domain of the quality of life (Æp2 = 0.047, p = 0.023) in the intervention (baseline mean 62.8 ± 35.1, end mean 86.3 ± 21.3) compared to control (baseline mean group 70.5 ± 33.8; end mean 78.4 ± 27.3) group. Negative association was found in HbA1c changes using Z-score and Physical Function domain (r = - 0.217, p = 0.022). CONCLUSION: A 6 months SMBG intervention package through a subscription model improved blood glucose control as measured by HbA1c and health-related quality of life, particularly the Role Emotional domain. Elevated HbA1c levels are correlated with decreased physical function.There is a need to further examine the efficacy of SMBG intervention package using a larger sample and a longer period of intervention and to determine its cost efficacy.
RESUMO
Background: The success of mobile apps in improving the lifestyle of patients with noncommunicable diseases through self-management interventions is contingent upon the emerging growth in this field. While users of mobile health (mHealth) apps continue to grow in number, little is known about the quality of available apps that provide self-management for common noncommunicable diseases such as diabetes, hypertension, and obesity. Objective: We aimed to investigate the availability, characteristics, and quality of mHealth apps for common noncommunicable disease health management that included dietary aspects (based on the developer's description), as well as their features for promoting health outcomes and self-monitoring. Methods: A systematic search of English-language apps on the Google Play Store (Google LLC) and Apple App Store (Apple Inc) was conducted between August 7, 2022, and September 13, 2022. The search terms used included weight management, obesity, diabetes, hypertension, cardiovascular diseases, stroke, and diet. The selected mHealth apps' titles and content were screened based on the description that was provided. Apps that were not designed with self-management features were excluded. We analyzed the mHealth apps by category and whether they involved health care professionals, were based on scientific testing, and had self-monitoring features. A validated and multidimensional tool, the Mobile App Rating Scale (MARS), was used to evaluate each mHealth app's quality based on a 5-point Likert scale from 1 (inadequate) to 5 (excellent). Results: Overall, 42 apps were identified. Diabetes-specific mHealth apps accounted for 7% (n=3) of the market, hypertension apps for 12% (n=5), and general noncommunicable disease management apps for 21% (n=9). About 38% (n=16) of the apps were for managing chronic diseases, while 74% (n=31) were for weight management. Self-management features such as weight tracking, BMI calculators, diet tracking, and fluid intake tracking were seen in 86% (n=36) of the apps. Most mHealth apps (n=37, 88%) did not indicate whether there was involvement of health professionals in app development. Additionally, none of the apps reported scientific evidence demonstrating their efficacy in managing health. The overall mean MARS score was 3.2 of 5, with a range of 2.0 to 4.1. Functionality was the best-rated category (mean score 3.9, SD 0.5), followed by aesthetics (mean score 3.2, SD 0.9), information (mean score 3.1, SD 0.7), and engagement (mean score 2.9, SD 0.6). Conclusions: The quality of mHealth apps for managing chronic diseases was heterogeneous, with roughly half of them falling short of acceptable standards for both quality and content. The majority of apps contained scant information about scientific evidence and the developer's history. To increase user confidence and accomplish desired health outcomes, mHealth apps should be optimized with the help of health care professionals. Future studies on mHealth content analysis should focus on other diseases as well.