Background Low back pain is one of the most common health problems and a main cause of disability, which imposes a great burden on patients. Mobile health (mHealth) affects many aspects of people’s lives, and it has progressed rapidly, showing promise as an effective intervention for patients with low back pain. However, the efficacy of mHealth interventions for patients with low back pain remains unclear; thus, further exploration is necessary. Objective The purpose of this study was to evaluate the efficacy of mHealth interventions in patients with low back pain compared to usual care. Methods This was a systematic review and meta-analysis of randomized controlled trials designed according to the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-analysis) statement standard. We searched for studies published in English before October 2020 in the PubMed, EMBASE, Web of Science, and Cochrane Library databases. Two researchers independently scanned the literature, extracted data, and assessed the methodological quality of the included studies. Bias risks were assessed using the Cochrane Collaboration tool. We used RevMan 5.4 software to perform the meta-analysis. Results A total of 9 studies with 792 participants met the inclusion criteria. The simultaneous use of mHealth and usual care showed a better reduction in pain intensity than usual care alone, as measured by the numeric rating scale (mean difference [MD] –0.85, 95% CI –1.29 to –0.40; P<.001), and larger efficacy in reducing disability, as measured by the Rolland-Morris Disability Questionnaire (MD –1.54, 95% CI –2.35 to –0.73; P<.001). Subgroup analyses showed that compared with usual care, mHealth using telephone calls significantly reduced pain intensity (MD –1.12, 95% CI –1.71 to –0.53; P<.001) and disability score (MD –1.68, 95% CI –2.74 to –0.63; P<.001). However, without the use of telephone calls, mHealth had no obvious advantage over usual care in improving pain intensity (MD –0.48, 95% CI –1.16 to 0.20; P=.16) and the disability score (MD –0.41, 95% CI –1.88 to 1.05; P=.58). The group that received a more sensitive feedback intervention showed a significantly reduced disability score (MD –4.30, 95% CI –6.95 to –1.69; P=.001). Conclusions The use of simultaneous mHealth and usual care interventions has better efficacy than usual care alone in reducing pain intensity and disability in patients with low back pain. Moreover, the results of subgroup analysis revealed that mHealth using telephone calls might play a positive role in improving pain intensity and disability in patients with low back pain.

Background Breastfeeding is essential for maintaining the health of mothers and babies. Breastfeeding can reduce the infection rate and mortality in newborns, and can reduce the chances of overweight and obesity in children and adolescents. For mothers, a longer duration of breastfeeding can reduce the risk of breast cancer, ovarian cancer, and type 2 diabetes. Although breastfeeding has many benefits, the global breastfeeding rate is low. With the progress of time, the popularity of mobile devices has increased rapidly, and interventions based on mobile health (mHealth) may have the potential to facilitate the improvement of the breastfeeding status. Objective The main objective of this study was to analyze the existing evidence to determine whether mHealth-based interventions can improve the status of breastfeeding. Methods We systematically searched multiple electronic databases (PubMed, Web of Science, The Cochrane Library, Embase, CNKI, WanFang, and Vip ) to identify eligible studies published from 1966 to October 29, 2020. Included studies were randomized controlled trials (RCTs) studying the influence of mHealth on breastfeeding. The Cochrane Collaboration Risk of Bias tool was used to examine the risk of publication bias. RevMan 5.3 was used to analyze the data. Results A total of 15 RCTs with a total sample size of 4366 participates met the inclusion criteria. Compared with usual care, interventions based on mHealth significantly increased the postpartum exclusive breastfeeding rate (odds ratio [OR] 3.18, 95% CI 2.20-4.59; P<.001), enhanced breastfeeding self-efficacy (mean difference [MD] 8.15, 95% CI 3.79-12.51; P=.002; I2=88%), reduced health problems in infants (OR 0.62, 95% CI 0.43-0.90; P=.01; I2=0%), and improved participants’ attitudes toward breastfeeding compared with usual care (MD 3.94, 95% CI 1.95-5.92; P<.001; I2=0%). There was no significant difference in the initiation of breastfeeding within an hour of birth between the intervention group and the usual care group (OR 1.26, 95% CI 0.55-2.90; P=.59). In addition, subgroup analysis was carried out according to different subjects and publication times. The results showed that the breastfeeding rate was not limited by the types of subjects. The breastfeeding rate based on mHealth at 1 month and 2 months after delivery did not change over the time of publication (2009 to 2020), and the breastfeeding rate based on mHealth at 3 months and 6 months after delivery gradually increased with time (2009 to 2020). Conclusions Interventions based on mHealth can significantly improve the rate of postpartum exclusive breastfeeding, breastfeeding efficacy, and participants’ attitudes toward breastfeeding, and reduce health problems in infants. Therefore, encouraging women to join the mHealth team is feasible, and breastfeeding-related information can be provided through simple measures, such as text messages, phone calls, and the internet, to improve the health of postpartum women and their babies.

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Objective: Virtual reality technology has begun to be gradually applied to clinical stroke rehabilitation. The study aimed to evaluate the effect of traditional plus virtual reality rehabilitation on motor function recovery, balance, and activities of daily living in stroke patients. Method: Studies published in English before October 2020 were retrieved from PubMed, Embase, Web of Science, and the Cochrane Library. This study used RevMan 5.3 software for meta-analysis. Result: A total of 21 randomized controlled trials were included, which enrolled 619 patients. Traditional plus virtual reality rehabilitation is better than traditional rehabilitation in upper limb motor function recovery measured by Fugl-Meyer Assessment-Upper Extremity (mean difference = 3.49, 95% confidence interval = 1.24 to 5.73, P = 0.002) and manual dexterity assessed by Box and Block Test (mean difference = 6.59, 95% confidence interval = 3.45 to 9.74, P < 0.0001). However, there is no significant difference from traditional rehabilitation in activities of daily living assessed by Functional Independence Measure (mean difference = 0.38, 95% confidence interval = −0.26 to 1.02, P = 0.25) and balance assessed by Berg Balance Scale (mean difference = 2.18, 95% confidence interval = −0.35 to 4.71, P = 0.09). Conclusions: Traditional plus virtual reality rehabilitation therapy is an effective method to improve the upper limb motor function and manual dexterity of patients with limb disorders after stroke, and immersive virtual reality rehabilitation treatment may become a new option for rehabilitation after stroke.