Early mobilization has been proven to be an effective and safe intervention for preventing complications in mechanically ventilated patients; however, there is currently no unified definition of the optimal mobilization initiation time, hindering widespread clinical implementation. As clinicians are increasingly aware of the benefits of early mobilization, the definition of early mobilization is important. The purpose of this study was to evaluate the effects of different early mobilization initiation times on mechanically ventilated patients and rank these times for practical consideration. The Chinese Biomedical Literature Database, the Chinese Knowledge Infrastructure, Wanfang Data, PubMed, Cochrane Library, Web of Science, and Embase databases, along with grey literature and reference lists, were searched for randomized control trials (RCTs) that evaluated the effects of early mobilization for improving patient outcomes; databases were searched from inception to October 2018. Two authors extracted data independently, using a predesigned Excel form, and assessed the quality of included RCTs according to the Cochrane Handbook (v5.1.0). Data were analyzed using Stata (v13.0) and Review Manager (v5.3.0). A total of 15 RCTs involving 1726 patients and seven mobilization initiation times (which were all compared to usual care) were included in our analysis. Network meta-analysis showed that mechanical ventilation for 48–72 h may be optimal to improve intensive care unit acquired weakness (ICU-AW) and reduce the duration of mechanical ventilation; however, there were no significant differences in length of ICU stay according to mobilization initiation time. The results of this study indicate that initiation of mobilization within 48–72 h of mechanical ventilation may be optimal for improving clinical outcomes for mechanically ventilated patients.

Aim To compare the safety and effects of unrestricted visiting policies (UVPs) and restricted visiting policies (RVPs) in intensive care units (ICUs) with respect to outcomes related to delirium, infection, and mortality. Methods MEDLINE, Cochrane Library, Embase, Web of Science, CINAHL, CBMdisc, CNKI, Wanfang, and VIP database records generated from their inception to 22 January 2022 were searched. Randomized controlled trials and quasi-experimental studies were included. The main outcomes investigated were delirium, ICU-acquired infection, ICU mortality, and length of ICU stay. Two reviewers independently screened studies, extracted data, and assessed risks of bias. Random‑effects and fixed-effects meta‑analyses were conducted to obtain pooled estimates, due to heterogeneity. Meta-analyses were performed using RevMan 5.3 software. The results were analyzed using odds ratios (ORs), 95% confidence intervals (CIs), and standardized mean differences (SMDs). Results Eleven studies including a total of 3741 patients that compared UVPs and RVPs in ICUs were included in the analyses. Random effects modeling indicated that UVPs were associated with a reduced incidence of delirium (OR = 0.4, 95% CI 0.25–0.63, I2 = 71%, p = 0.0005). Fixed-effects modeling indicated that UVPs did not increase the incidences of ICU-acquired infections, including ventilator-associated pneumonia (OR = 0.96, 95% CI 0.71–1.30, I2 = 0%, p = 0.49), catheter-associated urinary tract infection (OR 0.97, 95% CI 0.52–1.80, I2 = 0%, p = 0.55), and catheter-related blood stream infection (OR = 1.15, 95% CI 0.72–1.84, I2 = 0%, p = 0.66), or ICU mortality (OR = 1.03, 95% CI 0.83–1.28, I2 = 49%, p = 0.12). Forest plotting indicated that UVPs could reduce the lengths of ICU stays (SMD =  − 0.97, 95% CI − 1.61 to 0.32, p = 0.003). Conclusion The current meta-analysis indicates that adopting a UVP may significantly reduce the incidence of delirium in ICU patients, without increasing the risks of ICU-acquired infection or mortality. Further large-scale, multicenter studies are needed to confirm these indications.

The treatment of depressive symptoms of bipolar disorder (BD) has received increasing attention. Recently, some studies have shown that bright light therapy (BLT) seems to be useful for BD depression. This meta-analysis is intended to further elucidate the role of BLT in depressive symptoms in patients with BD. Register of Systematic Reviews PROSPERO: CRD 420191 33642.Randomized controlled trials and cohort studies were retrieved in PubMed, Cochrane Library, EMbase, Web of Science, CINHAL, CBM, CNKI, VIP, and Wanfang from their foundation to March 2020, and other sources as supplement was also retrieved. Data were extracted after strict evaluation of literature quality by two researchers, and Meta-analysis was conducted on literatures that met the inclusion criteria. Meta-analysis was performed using Revman 5.3 software. In total, 12 studies including 847 patients with BD depression were included in our meta-analysis. A meta-analysis found significant differences between BLT and placebo for the following outcomes: (1) depression severity before and after BLT [SMD =-0.43, 95% CI (-0.73,-0.13), P<0.05] in RCT and [SMD =-2.12, 95% CI (-2.3,-1.94), P<0.05] in cohort studies.; (2) the efficacy of duration/timing of light therapy for depressive symptoms in BD [I 2 = 85%, SMD =-1.88, 95% CI (-2.04,-1.71), P<0.05] and [I 2 = 71%, SMD =-2.1,95% CI(-2.24,-1.96), P<0.05]; (3) the efficacy of different color/color temperatures for depressive symptoms in BD [I 2 = 0%, SMD =-0.56, 95% CI (-0.92,-0.19), P<0.05] and [I 2 = 97%, SMD =-1.74, 95% CI (-1.99,-1.49), P<0.05].We performed a subgroup meta-analysis of studies that used different light intensities. The results showed that light intensity�5000 lux significantly reduced the severity of depression. And patients without psychotropic drugs revealed significantly decreased disease severity [I 2 = 0%, SMD =-0.6, 95% CI (-1.06,-0.13), P<0.05]. Limitations of the study include studies only assessed short-term effects, and insufficient duration may underestimate adverse reactions and efficacy. Our results highlight the significant efficiency of BLT in the treatment of bipolar depression. Prospective studies with more rigorous design and consistent follow-up.

Abstract-Psychologists have demonstrated that pets have a positive impact on owners' happiness. For example, lonely people are often advised to have a dog or cat to quell their social isolation. Conventional psychological research methods of analyzing this phenomenon are mostly based on surveys or self-reported questionnaires, which are time-consuming and lack of scalability. Utilizing social media as an alternative and complimentary resource could potentially address both issues and provide different perspectives on this psychological investigation. In this paper, we propose a novel and effective approach that exploits social media to study the effect of pets on owners' happiness. The proposed framework includes three major components: 1) collecting user-level data from Instagram consisting of about 300,000 images from 2905 users; 2) constructing a convolutional neural network (CNN) for pets classification, and combined with timeline information, further identifying pet owners and the control group; 3) measuring the confidence score of happiness by detecting and analyzing selfie images. Furthermore, various factors of demographics are employed to analyze the fine-grained effects of pets on happiness. Our experimental results demonstrate the effectiveness of the proposed approach and we believe that this approach can be applied to other related domains as a large-scale, high-confidence methodology of user activity analysis through social media.

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