The effect of a lifestyle intervention program using a mobile application versus the effect of a program using a booklet for adults with metabolic syndrome: A three-arm randomized controlled trial

Smartphone application-based intervention to lower blood pressure: a systematic review and meta-analysis

Nowadays, the mHealth market is flooded with smartphone applications (apps) lacking validation for blood pressure (BP)-lowering effects and BP measurement accuracy. This systematic review for Guidelines for BP control using digital technologies of the Japanese Society of Hypertension aimed to assess the validation studies of apps. We searched eligible studies in Ovid MEDLINE, Cochrane Library, and Ichushi, focusing on randomized controlled trials and observational studies comparing the effects of smartphone app-based interventions with non-digital healthcare. Random effects models of meta-analysis were employed to estimate the pooled effects of mean BP change and 95% confidence intervals (CIs). Out of 7385 studies screened, 76 studies with 46,459 participants were included. The interventions were significantly associated with a reduction in office systolic and diastolic BP at six months (systolic BP, -2.76 mmHg, 95% CI: -3.94 to -1.58; diastolic BP, -1.23 mmHg, -1.80 to -0.67). Normotensives saw a significant reduction in office systolic BP at three-month (-4.44 mmHg, -6.96 to -1.92), diminishing afterward (six-month, 0.86 mmHg, -2.81 to 4.52; twelve-month, 0.86 mmHg, -2.81 to 4.52). Conversely, hypertensive participants experienced a significant reduction in office systolic BP at both three- and six-month (three-month, -7.71 mmHg, -10.63 to -4.79; six-month, -1.88 mmHg, -3.41 to -0.35), albeit with limited evidence thereafter. A larger BP reduction was observed among participants using apps with wireless transmission of BP measurements (P = 0.047 for interaction), while there was no clear difference in BP reduction according to the presence of other functions. Smartphone app-based interventions may hold the potential to improve BP levels.

An internet-based platform with a low-calorie dietary intervention improves cardiometabolic risk factors in overweight and obese people in China: Half-year follow-up results of a randomized controlled trial

AIM

To explore the effectiveness of the Metawell programme on cardiometabolic risk factors in China, which combines meal replacement biscuits, a wireless scale, and a mobile phone application.

METHODS

In this two-arm, parallel-design randomized study, 220 participants were randomly assigned to an intervention (n = 110) and a control (n = 110) group. Participants in the intervention group were instructed to use meal replacement products and scales for weight loss and monitoring, whereas participants in the control group received printed materials containing a sample diet and face-to-face weight loss education at enrolment. The trial lasted 6 months, including a weight loss period in Months 1-3 and a weight maintenance period in Months 3-6. Generalized estimating equations were used to compare differences between the two groups.

RESULTS

The median (interquartile range) ages of the intervention and control groups were 32.00 (28.00, 39.00) years and 33.00 (28.25, 41.00) years, with body mass indices of 28.20 (26.30, 30.95) kg/m2 and 27.70 (26.02, 29.70) kg/m2, respectively. Participants in the intervention group experienced significantly greater decreases in waist circumference, hip circumference, triglycerides, total cholesterol: high-density lipoprotein cholesterol ratio, fasting blood glucose, fasting insulin, and homeostatic model assessment of insulin resistance index compared to the control group (p < 0.01). Among participants who did not regain weight during the maintenance period after weight loss, the reductions in systolic and diastolic blood pressure were significantly greater in the intervention group than in the control group (p < 0.05).

CONCLUSIONS

The Metawell programme of caloric restriction and remote monitoring can be adapted to overweight and obese people in China to reduce their cardiometabolic risk factors. Furthermore, there was a better improvement in blood pressure in participants who maintained the effects of weight loss.

How do we make progress in phenotyping patients with LUT such as OAB and underactive detrusor, including using urine markers and microbiome data, in order to personalize therapy? ICI-RS 2023: Part 1

INTRODUCTION

Overactive bladder (OAB) and Underactive bladder (UAB) could be associated with metabolic syndrome, affective disorders, sex hormone deficiency, changes in urinary microbiota, functional gastrointestinal disorders, or autonomic nervous system dysfunction.

OBJECTIVES

The aim of this Think Tank was to provide a guide on how to investigate OAB and/or detrusor underactivity (DU) patients to better clarify the underlying pathophysiology and possibly personalize the treatment.

METHODS

A compendium of discussion based on the current evidence related to phenotyping patients with OAB or DU investigating metabolic, neurogical, psychological and gastrointestinal aspects with the aim to personalize the treatment.

RESULTS AND CONCLUSIONS

The article emphasizes the critical significance of adopting a comprehensive yet tailored approach to phenotyping patients with lower urinary tract symptoms, such as OAB and UAB. The intricate interplay between the lower urinary tract and various factors, metabolic, neurological, psychological, and gastrointestinal can define unique LUT profiles, enabling personalized therapies to replace the one-size-fits-all approach.

Effectiveness of digital health interventions for telemedicine/telehealth for managing blood pressure in adults: a systematic review and meta-analysis

This systematic review and meta-analysis included randomized controlled trials or observational studies that compare digital health interventions (DHIs) for telemedicine/telehealth versus usual care for managing blood pressure (BP) in adults. We searched PubMed, Cochrane CENTRAL, and IchuShi-Web, and used a random-effects meta-analysis of the weighted mean difference (MD) between the comparison groups to pool data from the included studies. The outcome included the pooled MD of office BP from baseline to each follow-up period. This meta-analysis considered 117 studies with 68677 participants as eligible. The 3-month intervention period reduced office systolic BP (SBP) compared with usual care in 38 studies (MD: -3.21 mmHg [95% confidence interval: -4.51 to -1.90]), with evidence of heterogeneity. Office SBP across intervention periods demonstrated comparable effects (3-, 6- [54 studies], 12- [43 studies], and >12-month periods [9 studies]). The benefits for office diastolic BP were similar to those for office SBP. Additionally, the interventions significantly reduced the office SBP compared with the control, regardless of the mode of intervention delivery (smartphone apps [38 studies], text messages [35 studies], and websites [34 studies]) or type of facility (medical [74 studies] vs. non-medical [33 studies]). The interventions were more effective in 41 hypertension cohorts compared with 66 non-hypertension cohorts (-4.81 mmHg [-6.33, -3.29] vs. -2.17 mmHg [-3.15, -1.19], P = 0.006 for heterogeneity). In conclusion, DHIs for telemedicine/telehealth improved BP management compared with usual care. The effectiveness with heterogeneity should be considered, as prudent for implementing evidence-based medicine. This meta-analysis considered 117 studies with 68677 participants eligible. The DHIs for telemedicine/telehealth reduced office BP compared with usual care, regardless of intervention duration, intervention delivery mode, facility type, and cohort type. Additionally, the DHIs reduced the risk of uncontrolled BP compared with usual care, regardless of intervention duration, intervention delivery mode, and facility type. BP blood pressure, DHI digital health intervention, MD mean difference, RR risk ratio, SBP systolic blood pressure.

Effects of an Individualized mHealth-Based Intervention on Health Behavior Change and Cardiovascular Risk Among People With Metabolic Syndrome Based on the Behavior Change Wheel: Quasi-Experimental Study

BACKGROUND

Metabolic syndrome (MetS) is a common public health challenge. Health-promoting behaviors such as diet and physical activity are central to preventing and controlling MetS. However, the adoption of diet and physical activity behaviors has always been challenging. An individualized mobile health (mHealth)-based intervention using the Behavior Change Wheel is promising in promoting health behavior change and reducing atherosclerotic cardiovascular disease (ASCVD) risk. However, the effects of this intervention are not well understood among people with MetS in mainland China.

OBJECTIVE

We aimed to evaluate the effects of the individualized mHealth-based intervention using the Behavior Change Wheel on behavior change and ASCVD risk in people with MetS.

METHODS

We conducted a quasi-experimental, nonrandomized study. Individuals with MetS were recruited from the health promotion center of a tertiary hospital in Zhejiang province, China. The study involved 138 adults with MetS, comprising a control group of 69 participants and an intervention group of 69 participants. All participants received health education regarding diet and physical activity. The intervention group additionally received a 12-week individualized intervention through a WeChat mini program and a telephone follow-up in the sixth week of the intervention. Primary outcomes included diet, physical activity behaviors, and ASCVD risk. Secondary outcomes included diet self-efficacy, physical activity self-efficacy, knowledge of MetS, quality of life, and the quality and efficiency of health management services. The Mann-Whitney U test and Wilcoxon signed rank test were primarily used for data analysis. Data analysis was conducted based on the intention-to-treat principle using SPSS (version 25.0; IBM Corp).

RESULTS

Baseline characteristics did not differ between the 2 groups. Compared with the control group, participants in the intervention group showed statistically significant improvements in diet behavior, physical activity behavior, diet self-efficacy, physical activity self-efficacy, knowledge of MetS, physical health, and mental health after a 12-week intervention (P=.04, P=.001, P=.04, P=.04, P=.001, P=.04, P=.04, and P<.05). The intervention group demonstrated a statistically significant improvement in outcomes from pre- to postintervention evaluations (P<.001, P=.03, P<.001, P=.04, P<.001, P<.001, and P<.001). The intervention also led to enhanced health management services and quality.

CONCLUSIONS

The individualized mHealth-based intervention using the Behavior Change Wheel was effective in promoting diet and physical activity behaviors in patients with MetS. Nurses and other health care professionals may incorporate the intervention into their health promotion programs.