1.
Effects of the e-Motivate4Change Program on Metabolic Syndrome in Young Adults Using Health Apps and Wearable Devices: Quasi-Experimental Study.
Lee, JS, Kang, MA, Lee, SK
Journal of medical Internet research. 2020;(7):e17031
Abstract
BACKGROUND The health behaviors of young adults lag behind those of other age groups, and active health management is needed to improve health behaviors and prevent chronic diseases. In addition, developing good lifestyle habits earlier in life could reduce the risk of metabolic syndrome (MetS) later on. OBJECTIVE The aim of this study is to investigate the effects of the e-Motivate4Change program, for which health apps and wearable devices were selected based on user needs. The program was developed for the prevention and management of MetS in young adults. METHODS This experimental study used a nonequivalent control group. In total, 59 students from 2 universities in Daegu, Korea participated in the study (experimental group n=30; control group n=29). Data were collected over 4 months, from June 1 to September 30, 2018. The experimental group received a 12-week e-Motivate4Change program intervention, and the control group received MetS education and booklets without the e-Motivate4Change program intervention. RESULTS After the program, the experimental group had significantly higher scores for health-related lifestyle (t=3.86; P<.001) and self-efficacy (t=6.00; P<.001) than did the control group. Concerning BMI, there were significant effects by group (F=1.01; P<.001) and for the group × time interaction (F=4.71; P=.034). Concerning cholesterol, there were significant main effects for group (F=4.32; P=.042) and time (F=9.73; P<.001). CONCLUSIONS The e-Motivate4Change program effectively improved participants' health-related lifestyle scores and self-efficacy, and significantly reduced their BMI and cholesterol levels. The program can be used to identify and prevent MetS among young adults.
2.
The effects of mobile health interventions on lipid profiles among patients with metabolic syndrome and related disorders: A systematic review and meta-analysis of randomized controlled trials.
Akbari, M, Lankarani, KB, Naghibzadeh-Tahami, A, Tabrizi, R, Honarvar, B, Kolahdooz, F, Borhaninejad, V, Asemi, Z
Diabetes & metabolic syndrome. 2019;(3):1949-1955
Abstract
OBJECTIVE The current systematic review and meta-analysis of randomized controlled trials (RCTs) was conducted to summarize the effect of mobile health (m-health) interventions on lipid profiles among patients with metabolic syndrome and related disorders. METHODS Cochrane Library, EMBASE, PubMed, and Web of Science databases were searched to indentify the relevant randomized clinical trials published up April 30th, 2018. Two reviewers examined study eligibility, extracted data, and assessed risk of bias of included clinical trials, individually. Heterogeneity was measured using I-square (I2) statistic and Cochran's Q test. Data were pooled the standardized mean difference (SMD) effect size by the random-effect model. RESULTS 18 trials of 1681 citations were identified to be appropriate for the current meta-analysis. Findings random-effects model indicated that m-health interventions significantly decreased total- (SMD -0.54; 95% CI, -1.05, -0.03) and LDL-cholesterol levels (SMD -0.66; 95% CI, -1.18, -0.15). M-health interventions had no significant effect on triglycerides (SMD -0.14; 95% CI, -0.56, 0.28) and HDL-cholesterol levels (SMD -0.35; 95% CI, -0.81, 0.11). CONCLUSION Overall, the current meta-analysis demonstrated that m-health interventions resulted in an improvement in total- and LDL-cholesterol, but did not affect triglycerides and HDL-cholesterol levels.
3.
Mobile health applications for chronic diseases: A systematic review of features for lifestyle improvement.
Debon, R, Coleone, JD, Bellei, EA, De Marchi, ACB
Diabetes & metabolic syndrome. 2019;(4):2507-2512
Abstract
AIMS: To identify mobile health applications with features for improving the lifestyle of patients with chronic diseases. METHODS We performed a systematic literature review between November 2017 and May 2018 on the Virtual Health Library's interface. A total of 816 records were identified. In the selection process, 24 studies met inclusion criteria for analysis. Study characteristics were extracted and synthesized. RESULTS We identified applications with similar functionalities, such as the use of reminders and medical monitoring. Most of them addressed the treatment of conditions related to an already diagnosed chronic disease, including Diabetes Mellitus, Hypertension, Cardiovascular Diseases, Asthma, Neoplasms, and chronic conditions in general. The main lifestyle changes were the reduction of body weight, promotion of healthy eating, and adherence to the regular practice of physical exercises. CONCLUSIONS Technology can facilitate health care with simple messages and alerts that aid in adherence to treatment. Changes in lifestyle with the use of applications are remarkable. Benefits may be even greater if more applications address the importance of prevention and not just treatment.