Cross-cultural factors influencing the adoption of virtual reality for practical learning.

Education is one area that was significantly affected by the COVID-19 pandemic with much of the education being transferred online. Many subjects that require hands-on experimental experience suffer when taught online. Education is also one area that many believe can benefit from the advances in virtual reality (VR) technology, particularly for remote, online learning. Furthermore, because the technology shows overall good results with hands-on experiential learning education, one possible way to overcome online education barriers is with the use of VR applications. Given that VR has yet to make significant inroads in education, it is essential to understand what factors will influence this technology's adoption and acceptance. In this work, we explore factors influencing the adoption of VR for hands-on practical learning around the world based on the Unified Theory of Acceptance and Use of Technology and three additional constructs. We also performed a cross-cultural analysis to examine the model fit for developed and developing countries and regions. Moreover, through open-ended questions, we gauge the overall feeling people in these countries have regarding VR for practical learning and how it compares with regular online learning.

An intelligent forecast for COVID-19 based on single and multiple features.

It is urgent to identify the development of the Corona Virus Disease 2019 (COVID-19) in countries around the world. Therefore, visualization is particularly important for monitoring the COVID-19. In this paper, we visually analyze the real-time data of COVID-19, to monitor the trend of COVID-19 in the form of charts. At present, the COVID-19 is still spreading. However, in the existing works, the visualization of COVID-19 data has not established a certain connection between the forecast of the epidemic data and the forecast of the epidemic. To better predict the development trend of the COVID-19, we establish a logistic growth model to predict the development of the epidemic by using the same data source in the visualization. However, the logistic growth model only has a single feature. To predict the epidemic situation in an all-round way, we also predict the development trend of the COVID-19 based on the Susceptible Exposed Infected Removed epidemic model with multiple features. We fit the data predicted by the model to the real COVID-19 epidemic data. The simulation results show that the predicted epidemic development trend is consistent with the actual epidemic development trend, and our model performs well in predicting the trend of COVID-19.

A novel flow cytometry procoagulant assay for diagnosis of vaccine-induced immune thrombotic thrombocytopenia.

Vaccine-induced immune thrombotic thrombocytopenia (VITT) is a severe prothrombotic complication of adenoviral vaccines, including the ChAdOx1 nCoV-19 (Vaxzevria) vaccine. The putative mechanism involves formation of pathological anti-platelet factor 4 (PF4) antibodies that activate platelets via the low-affinity immunoglobulin G receptor FcγRIIa to drive thrombosis and thrombocytopenia. Functional assays are important for VITT diagnosis, as not all detectable anti-PF4 antibodies are pathogenic, and immunoassays have varying sensitivity. Combination of ligand binding of G protein-coupled receptors (protease-activated receptor-1) and immunoreceptor tyrosine-based activation motif-linked receptors (FcγRIIa) synergistically induce procoagulant platelet formation, which supports thrombin generation. Here, we describe a flow cytometry-based procoagulant platelet assay using cell death marker GSAO and P-selectin to diagnose VITT by exposing donor whole blood to patient plasma in the presence of a protease-activated receptor-1 agonist. Consecutive patients triaged for confirmatory functional VITT testing after screening using PF4/heparin ELISA were evaluated. In a development cohort of 47 patients with suspected VITT, plasma from ELISA-positive patients (n = 23), but not healthy donors (n = 32) or individuals exposed to the ChAdOx1 nCov-19 vaccine without VITT (n = 24), significantly increased the procoagulant platelet response. In a validation cohort of 99 VITT patients identified according to clinicopathologic adjudication, procoagulant flow cytometry identified 93% of VITT cases, including ELISA-negative and serotonin release assay-negative patients. The in vitro effect of intravenous immunoglobulin (IVIg) and fondaparinux trended with the clinical response seen in patients. Induction of FcγRIIa-dependent procoagulant response by patient plasma, suppressible by heparin and IVIg, is highly indicative of VITT, resulting in a sensitive and specific assay that has been adopted as part of a national diagnostic algorithm to identify vaccinated patients with platelet-activating antibodies.

Virtual Reality for Supporting the Treatment of Depression and Anxiety: Scoping Review.

BACKGROUND: Mental health conditions pose a major challenge to health care providers and society at large. The World Health Organization predicts that by 2030, mental health conditions will be the leading cause of disease burden worldwide. The current need for mental health care is overwhelming. In New Zealand, 1 in 6 adults has been diagnosed with common mental disorders, such as depression and anxiety disorders, according to a national survey. Cognitive behavioral therapy (CBT) has been shown to effectively help patients overcome a wide variety of mental health conditions. Virtual reality exposure therapy (VRET) might be one of the most exciting technologies emerging in the clinical setting for the treatment of anxiety and depression. OBJECTIVE: This study aims to investigate the virtual reality (VR) technologies currently being used to help support the treatment of depression and anxiety. We also aim to investigate whether and how CBT is included as part of VRET and look at the VR technologies and interventions that have been used in recent studies on depression and anxiety. METHODS: We performed a scoping review. To identify significant studies, we decided to use already aggregated sources from the Google Scholar database. Overall, the goal of our search strategy was to limit the number of initial results related to VR in mental health to only a relevant minimum. RESULTS: Using our defined keywords, Google Scholar identified >17,300 articles. After applying all the inclusion and exclusion criteria, we identified a total of 369 articles for further processing. After manual evaluation, 34 articles were shortlisted; of the 34 articles, 9 (26%) reported the use of CBT with VR. All of the articles were published between 2017 and 2021. Out of the 9 studies, CBT was conducted within a VR environment in 5 (56%) studies, whereas in the remaining 4 (44%) studies, CBT was used as an addition to VRET. All 9 studies reported the use of CBT either in vivo or in a virtual environment to be effective in supporting the treatment of anxiety or depression. CONCLUSIONS: Most studies demonstrated the use of VR to be effective for supporting the treatment of anxiety or depression in a range of settings and recommended its potential as a tool for use in a clinical environment. Even though standalone headsets are much easier to work with and more suitable for home use, the shift from tethered VR headsets to standalone headsets in the mental health environment was not observed. All studies that looked at the use of CBT either in vivo or in a virtual environment found it to be effective in supporting the treatment of anxiety or depression.

In-Situ exploration of emotion regulation via smart clothing: an empirical study of healthcare workers in their work environment

Healthcare personnel suffer from an increased risk of stress, burnout, and depression due to the challenges of the COVID-19 pandemic. Studies show that interactive smart textiles help people alleviate their emotions. In this research, we investigate how to utilise interactive textiles to help healthcare workers mitigate their negative feelings. We have designed a smart t-shirt that encourages its wearers to perform body movements to enhance their positive emotions, stimulated by vibrotactile and audio feedback mechanisms. We demonstrate our smart t-shirt’s utility by asking healthcare workers (including physicians and nurses) to use it for five consecutive days. Our prototype design supports using it anywhere, including work, home, and other places. We evaluated our smart t-shirt prototype for emotion regulations at work for healthcare workers through an in-situ user study conducted at three hospitals. Results show that using the smart t-shirt positively impacts the healthcare workers’ immediate emotion regulation when they experienced emotion fluctuation and provided a more positive attitude towards their work. We conclude by analysing the potential factors that influence emotions and outline the design space of e-textiles for emotion regulation in real-life use. [ABSTRACT FROM AUTHOR] Copyright of Behaviour & Information Technology is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Limited Early Warnings and Public Attention to Coronavirus Disease 2019 in China, January-February, 2020: A Longitudinal Cohort of Randomly Sampled Weibo Users.

OBJECTIVE: Awareness and attentiveness have implications for the acceptance and adoption of disease prevention and control measures. Social media posts provide a record of the public's attention to an outbreak. To measure the attention of Chinese netizens to coronavirus disease 2019 (COVID-19), a pre-established nationally representative cohort of Weibo users was searched for COVID-19-related key words in their posts. METHODS: COVID-19-related posts (N = 1101) were retrieved from a longitudinal cohort of 52 268 randomly sampled Weibo accounts (December 31, 2019-February 12, 2020). RESULTS: Attention to COVID-19 was limited prior to China openly acknowledging human-to-human transmission on January 20. Following this date, attention quickly increased and has remained high over time. Particularly high levels of social media traffic appeared around when Wuhan was first placed in quarantine (January 23-24, 8-9% of the overall posts), when a scandal associated with the Red Cross Society of China occurred (February 1, 8%), and, following the death of Dr Li Wenliang (February 6-7, 11%), one of the whistleblowers who was reprimanded by the Chinese police in early January for discussing this outbreak online. CONCLUSION: Limited early warnings represent missed opportunities to engage citizens earlier in the outbreak. Governments should more proactively communicate early warnings to the public in a transparent manner.

Impact of Shenfu injection on a composite of organ dysfunction development in critically ill patients with coronavirus disease 2019 (COVID-19): A structured summary of a study protocol for a randomized controlled trial.

OBJECTIVES: This study aims to determine the protection provided by Shenfu injection (a traditional Chinese medicine) against development of organ dysfunction in critically ill patients with coronavirus disease 2019 (COVID-19). TRIAL DESIGN: This study is a multicenter, randomized, controlled, open-label, two-arm ratio 1:1, parallel group clinical trial. PARTICIPANTS: The patients, who are aged from 18 to 75 years old, with a confirmed or suspected diagnosis of severe or critical COVID-19, will be consecutively recruited in the study, according to the guideline on diagnosis and treatment of COVID-19 (the 7th version) issued by National Health Commission of the People's Republic of China. Exclusion criteria include pregnant and breastfeeding women, atopy or allergies to Shenfu Injection (SFI), severe underlying disease (malignant tumor with multiple metastases, uncontrolled hemopathy, cachexia, severe malnutrition, HIV), active bleeding, obstructive pneumonia caused by lung tumor, severe pulmonary interstitial fibrosis, alveolar proteinosis and allergic alveolitis, continuous use of immunosuppressive drugs in last 6 months, organ transplantation, expected death within 48 hours, the patients considered unsuitable for this study by researchers. The study is conducted in 11 ICUs of designated hospitals for COVID-19, located in 5 cities of China. INTERVENTION AND COMPARATOR: The enrolled patients will randomly receive 100 ml SFI (study group) or identical volume of saline (control group) twice a day for seven consecutive days. Patients in the both groups will be given usual care and the necessary supportive therapies as recommended by the latest edition of the management guidelines for COVID-19 (the 7th version so far). MAIN OUTCOMES: The primary endpoint is a composite of newly developed or exacerbated organ dysfunction. This is defined as an increase in the sequential organ failure assessment (SOFA) score of two or more, indicating sepsis and involvement of at least one organ. The SOFA score will be measured for the 14 days after enrolment from the baseline (the score at randomization). The secondary endpoints are shown below: • SOFA score in total • Pneumonia severity index score • Dosage of vasoactive drugs • Ventilation free days within 28 days • Length of stay in intensive care unit • Total hospital costs to treat the patient • 28-day mortality • The incidence of adverse drug events related to SFI RANDOMISATION: The block randomization codes were generated by SAS V.9.1 for allocation of participants in this study. The ratio of random distribution is 1:1. The sealed envelope method is used for allocation concealment. BLINDING (MASKING): The patients and statistical personnel analyzing study data are both blinded. The blinding of group assignment is not adopted for the medical staff. NUMBERS TO BE RANDOMISED (SAMPLE SIZE): This study is expected to recruit 300 patients with COVID-19, (150 in each group). TRIAL STATUS: Protocol version 2.0, February 15, 2020. Patient recruitment started on February 25, and will end on August 31, 2020. TRIAL REGISTRATION: Chinese Clinical Trial Registry: ChiCTR2000030043. Registered February 21, 2020, http://www.chictr.org.cn/showprojen.aspx?proj=49866 FULL PROTOCOL: The full protocol is attached as an additional file, accessible from the Trials website (Additional file 1). In the interest in expediting dissemination of this material, the familiar formatting has been eliminated; this letter serves as a summary of the key elements of the full protocol.