Background: Virtual reality (VR) training is a promising intervention strategy that has been utilized in health care fields like stroke rehabilitation and psychotherapy. Current studies suggest that VR training is effective in improving the locomotor ability of stroke patients. Objective: This is the first meta-meta-analysis of the effects of VR on motor function in stroke patients. This study aimed to systematically summarize and quantify the present meta-analyses results of VR training and produce high-quality meta-meta-analysis results to obtain a more accurate prediction. Methods: We searched 4 online databases (Web of Science, Scopus, PubMed, and Chinese National Knowledge Infrastructure) for meta-analysis studies. After accounting for overlap, 10 studies (accounting for almost 550 stroke patients) were obtained. Based on the meta-meta-analysis of these patients, this study quantified the impact of VR training on stroke patients’ motor performance, mainly including upper limb function, balance, and walking ability. We combined the effects under the random effect model and pooled the estimates as standardized mean differences (SMD). Results: The results of the meta-meta-analysis showed that VR training effectively improves upper limb function (SMD 4.606, 95% CI 2.733-6.479, P<.05) and balance (SMD 2.101, 95% CI 0.202-4.000, P<.05) of stroke patients. However, the results showed considerable heterogeneity and thus, may need to be treated with caution. Due to the limited research, a meta-meta-analysis of walking ability was not performed. Conclusions: These findings represent a comprehensive body of high-quality evidence that VR training is more effective at improving upper limb function and balance of stroke patients.

The prevalence of diabetes has been increasing in recent years, and previous research has found that machine-learning models are good diabetes prediction tools. The purpose of this study was to compare the efficacy of five different machine-learning models for diabetes prediction using lifestyle data from the National Health and Nutrition Examination Survey (NHANES) database. The 1999–2020 NHANES database yielded data on 17,833 individuals data based on demographic characteristics and lifestyle-related variables. To screen training data for machine models, the Akaike Information Criterion (AIC) forward propagation algorithm was utilized. For predicting diabetes, five machine-learning models (CATBoost, XGBoost, Random Forest (RF), Logistic Regression (LR), and Support Vector Machine (SVM)) were developed. Model performance was evaluated using accuracy, sensitivity, specificity, precision, F1 score, and receiver operating characteristic (ROC) curve. Among the five machine-learning models, the dietary intake levels of energy, carbohydrate, and fat, contributed the most to the prediction of diabetes patients. In terms of model performance, CATBoost ranks higher than RF, LG, XGBoost, and SVM. The best-performing machine-learning model among the five is CATBoost, which achieves an accuracy of 82.1% and an AUC of 0.83. Machine-learning models based on NHANES data can assist medical institutions in identifying diabetes patients.

Background: Virtual reality (VR) technology has shown significant potential in improving the social skills of children and adolescents with autism spectrum disorder (ASD). Objective: This study aimed to systematically review the evidence supporting the effectiveness of VR technology in improving the social skills of children and adolescents with ASD. Methods: The search for eligible studies encompassed 4 databases: PubMed, Web of Science, IEEE, and Scopus. Two (XY and JW) researchers independently assessed the extracted studies according to predefined criteria for inclusion and exclusion. These researchers also independently extracted information regarding gathered data on the sources, samples, measurement methods, primary results, and data related to the main results of the studies that met the inclusion criteria. The quality of the studies was further evaluated using the Physiotherapy Evidence Database scale. Results: This review analyzed 14 studies on using VR technology interventions to improve social skills in children and adolescents with ASD. Our findings indicate that VR interventions have a positive effect on improving social skills in children and adolescents with ASD. Compared with individuals with low-functioning autism (LFA), those with high-functioning autism (HFA) benefited more from the intervention. The duration and frequency of the intervention may also influence its effectiveness. In addition, immersive VR is more suitable for training complex skills in individuals with HFA. At the same time, nonimmersive VR stands out in terms of lower cost and flexibility, making it more appropriate for basic skill interventions for people with LFA. Finally, while VR technology positively enhances social skills, some studies have reported potential adverse side effects. According to the quality assessment using the Physiotherapy Evidence Database scale, of the 14 studies, 6 (43%) were classified as high quality, 4 (29%) as moderate quality, and 4 (29%) as low quality. Conclusions: This systematic review found that VR technology interventions positively impact social skills in children and adolescents with ASD, with particularly significant effects on the enhancement of complex social skills in individuals with HFA. For children and adolescents with LFA, progress was mainly observed in basic skills. Immersive VR interventions are more suitable for the development of complex skills. At the same time, nonimmersive VR, due to its lower cost and greater flexibility, also holds potential for application in specific contexts. However, the use of VR technology may lead to side effects such as dizziness, eye fatigue, and sensory overload, particularly in immersive settings. These potential issues should be carefully addressed in intervention designs to ensure user comfort and safety. Future research should focus on optimizing individualized interventions and further exploring the long-term effects of VR interventions. Trial Registration: International Platform of Registered Systematic Review and Meta-analysis Protocols INPLASY202420079U1; https://inplasy.com/inplasy-2024-2-0079/

The purpose of this meta-analytic review was to quantitatively examine the effects of myofascial release technique (MFR) on pain intensity, back disability, lumbar range of motion, and quality of life in patients with low back pain (LBP). Potential articles were retrieved using five electronic databases (Web of Science, PubMed, Scopus, China National Knowledge Infrastructure, and Wanfang). The search period was from inception to January 27, 2021. Two researchers independently completed record retrieval and selection, data extraction, and methodological quality assessment. Randomized controlled trials (RCTs) assessing the effect of MFR on pain intensity, back disability, lumbar range of motion, and quality of life in LBP patients were included. Pooled effect sizes were calculated using random effects models and 95 % confidence interval (95 % CI). Data from eight RCTs (386 patients with back pain) meeting the inclusion criteria were extracted for meta-analysis with methodological quality assessment scores ranging from 6 to 10. Compared to the control intervention, MFR induced significant decrease in back disability (SMD = -0.35, 95 % confidence interval [CI] = -0.68, -0.02, P = 0.04, I² = 46 %, n = 284). MFR induced non-significant decrease in the pain intensity (SMD = -0.12, 95 % confidence interval[CI] = -0.35, 0.11, P = 0.32, I² = 0%, n = 294), non-significant improvement in quality of life (SMD = -0.09, 95 % confidence interval [CI] = -0.46, 0.28, P = 0.62, I² = 0%, n = 114), and non-significant improvement in lumbar range of motion (Flexion SMD = 0.57,95 % confidence interval [CI] = -0.09, 1.24, P = 0.09, I² = 54 %, n = 80) (Extension SMD = 0.68, 95 % confidence interval[CI] = -0.72, 2.08, P = 0.34, I² = 89 %, n = 80) (Right flexion SMD = 0.05, 95 % confidence interval[CI] = -0.90, 0.99, P = 0.92, I² = 78 %, n = 80) (Left flexion SMD = 0.14, 95 % confidence interval[CI] = -0.59, 0.88, P = 0.70, I² = 64 %, n = 80). The findings suggest that MFR can improve the effect of physical therapy alone and exercise therapy alone, and that MFR can be an effective adjuvant therapy. Meta-analysis showed that MFR has a significant effect on reducing back disability in patients with low back pain, but no significant effect on reducing pain intensity, improving quality of life, and improving lumbar range of motion.

Background: Previous studies have reported a potential negative correlation between physical activity (PA) and mobile phone addiction (MPA) among adolescents and young adults. To date, the strength of this correlation has not been well characterized. Objective: This review and meta-analysis aimed to synthesize available empirical studies to examine the correlations between PA and MPA among adolescents and young adults. We also explored several potential moderators, including time of data collection, country or region, and type of population, associated with the relationship between PA and MPA. Methods: Four electronic databases (PubMed, Scopus, PsycINFO, and Web of Science) were searched from database inception to March 2022 to identify relevant studies. The pooled Pearson correlation coefficients and their corresponding 95% CIs for the relationship between PA and MPA were calculated using the inverse variance method. The methodological quality of the included cross-sectional studies was determined based on the Joanna Briggs Institute appraisal checklist. The study conformed to the PRISMA (Preferred Reporting Items for Systematic Review and Meta-analyses) guidelines. Results: In total, 892 relevant articles were identified, of which 22 were selected based on the inclusion and exclusion criteria. The final meta-analysis included 17 of the 22 studies. Results of random effects modeling revealed a moderate correlation between PA and MPA among adolescents and young adults (summary r=–0.243, P<.001). Sensitivity and publication bias analyses further demonstrated the robustness of our results. All the included studies were scored as high quality with a low risk of bias. Subgroup analysis further indicated that none of the hypothesized moderators (time of data collection, country or region, and type of population) significantly affected the relationship between PA and MPA, as confirmed by the mixed effects analysis. In addition, in the data collection subgroups, medium effect sizes were obtained for data collected before COVID-19 (r=–0.333, P<.001) and data collected during COVID-19 (r=–0.207, P<.001). In subgroup analyses for country or region, the correlation coefficient for China and other developing regions showed a similarly moderate effect size (r=–0.201, P<.001 and r= –0.217, P<.001, respectively). However, the effect sizes for developed regions were not significant (r=–0.446, P=.39). In a subgroup analysis based on the type of population, we found that the effect size for young adults was moderate (r=–0.250, P<.001). However, that of adolescents was not significant (r=–0.129, P=.24). Conclusions: Our results demonstrate a moderately negative relationship between PA and MPA among young adults. The strength of this relationship was not influenced by the time of data collection, country or region, or type of population.

This research aims to evaluate the effect of virtual reality (VR) games on balance recovery of children with cerebral palsy (CP) by quantitatively synthesizing the existing literature, and to further determine the impact of VR game intervention (the duration of each intervention, intervention frequency, intervention cycle, and total intervention time) on the balance recovery of children with CP. To this end, relevant literature up until 3 August 2019 was retrieved from Chinese databases (CNKI and Wanfang Data) and the databases in other languages (Web of Science, Pubmed, EBSCOhost, Informit, Scopus, Science Direct, and ProQuest), and bias analysis was conducted with the PEDro scale in this research. Randomized controlled trials (RCTs) were selected and underwent meta-analysis, and combined effect size was calculated with a random effects model. The results showed that VR games may improve the balance of children with CP (Hedge’s g = 0.29; 95% CI 0.10–0.48), and no significant influence of the intervention on balance of children with CP was shown in the subgroup analysis. In conclusion, VR games played a positive role in the improvement of balance of children with CP, but these results should be viewed with caution owing to current methodological defects (difference in measurement, heterogeneity of control groups, intervention combined with other treatments, etc.).