Decision-Making under Uncertainty: How Easterners and Westerners Think Differently.

It has long been known that Easterners exhibit more conservative attitudes, cautiousness behaviors, and self-control ability than Westerners; people in Eastern countries show stronger defensive reactions to societal threats than Western people. Are East Asians really risk averters or do some richer underlying preferences drive their behaviors in their decision-making under uncertainty? To answer this question, we examined the risk and ambiguity attitudes of East Asian populations in both gain and loss domains using classical behavioral economic experimental methods. Based on our sample of university students, we found that Easterners are more risk intolerant but more willing to accept ambiguous conditions than their Westerner counterparts in the gain domain. Perhaps surprisingly, Eastern people and Western people have a similar attitude toward risk and ambiguity in the loss domain. The higher level of risk aversion observed among East Asians may be due to the cultural difference between Western countries and Eastern countries. Historically, such risk aversion may make sense, because it would minimize the influence of numerous ecological and historical threats and socio-political practices. Our findings suggest that models that were designed to analyze and predict aggregate behaviors and markets may be ineffective for Eastern populations, and, in the future, it is of significance to develop appropriate representative agent models from the eastern perspective.

Sintilimab versus placebo in combination with chemotherapy as first line treatment for locally advanced or metastatic oesophageal squamous cell carcinoma (ORIENT-15): multicentre, randomised, double blind, phase 3 trial.

OBJECTIVE: To evaluate sintilimab versus placebo in combination with chemotherapy (cisplatin plus paclitaxel or cisplatin plus 5-fluorouracil) as first line treatment of unresectable locally advanced, recurrent, or metastatic oesophageal squamous cell carcinoma. DESIGN: Multicentre, randomised, double blind, phase 3 trial. SETTING: 66 sites in China and 13 sites outside of China between 14 December 2018 and 9 April 2021. PARTICIPANTS: 659 adults (aged ≥18 years) with advanced or metastatic oesophageal squamous cell carcinoma who had not received systemic treatment. INTERVENTION: Participants were randomised 1:1 to receive sintilimab or placebo (3 mg/kg in patients weighing <60 kg or 200 mg in patients weighing ≥60 kg) in combination with cisplatin 75 mg/m2 plus paclitaxel 175 mg/m2 every three weeks. The trial was amended to allow investigators to choose the chemotherapy regimen: cisplatin plus paclitaxel or cisplatin plus 5-fluorouracil (800 mg/m2 continuous infusion on days 1-5). MAIN OUTCOME MEASURES: Overall survival in all patients and in patients with combined positive scores of ≥10 for expression of programmed cell death ligand 1. RESULTS: 659 patients were randomly assigned to sintilimab (n=327) or placebo (n=332) with chemotherapy. 616 of 659 patients (93%) received sintilimab or placebo in combination with cisplatin plus paclitaxel and 43 of 659 patients (7%) received sintilimab or placebo in combination with cisplatin plus 5-fluorouracil. At the interim analysis, sintilimab with chemotherapy showed better overall survival compared with placebo and chemotherapy in all patients (median 16.7 v 12.5 months, hazard ratio 0.63, 95% confidence interval 0.51 to 0.78, P<0.001) and in patients with combined positive scores of ≥10 (17.2 v 13.6 months, 0.64, 0.48 to 0.85, P=0.002). Sintilimab and chemotherapy significantly improved progression free survival compared with placebo and chemotherapy in all patients (7.2 v 5.7 months, 0.56, 0.46 to 0.68, P<0.001) and in patients with combined positive scores of ≥10 (8.3 v 6.4 months, 0.58, 0.45 to 0.75, P<0.001). Adverse events related to treatment occurred in 321 of 327 patients (98%) in the sintilimab-chemotherapy group versus 326 of 332 (98%) patients in the placebo-chemotherapy group. Rates of adverse events related to treatment, grade ≥3, were 60% (196/327) and 55% (181/332) in the sintilimab-chemotherapy and placebo-chemotherapy groups, respectively. CONCLUSIONS: Compared with placebo, sintilimab in combination with cisplatin plus paclitaxel showed significant benefits in overall survival and progression free survival as first line treatment in patients with advanced or metastatic oesophageal squamous cell carcinoma. Similar benefits of sintilimab with cisplatin plus 5-fluorouracil seem promising. TRIAL REGISTRATION: ClinicalTrials.gov NCT03748134.

Prevalence of Self-Reported Symptoms of Computer Vision Syndrome and Associated Risk Factors among School Students in China during the COVID-19 Pandemic.

PURPOSE: To determine the prevalence and risk factors of self-reported symptoms of Computer Vision Syndrome (CVS) in school students during COVID-19 pandemic. METHODS: In this cross-sectional study in Nanjing, China, students (grades 1-12) from six randomly selected schools self-administered the online survey questionnaire about hours on electronic devices, outdoor activities, frequency and intensity of 17 CVS symptoms during virtual learning period of COVID-19 pandemic. RESULTS: Among 2363 invited students, 2005 (84.8%) completed the survey. Mean (SD) age was 12 (3.0) years, 51% were male, 53% wore glasses, 56% did not know the 20-20-20 rule (take a 20 second break every 20 min of close work and gaze at objects at least 20 feet away) and 6.5% knew but never followed the 20-20-20 rule. Mean (SD) hours/day was 4.6 (3.4) for screen time and 1.2 (1.0) for outdoor activities. Total of 1543 (77.0%) students reported at least one CVS symptom (median = 4) with eye dryness and itching the most common (48%). In multivariable analysis, CVS score 4 or more was independently associated with older age (adjusted odds ratio (aOR) = 1.05 for per-year increase, p = 0.02), children with myopia not wearing glasses (aOR = 2.12, p = 0.0003), astigmatism (aOR = 1.37, p = 0.04), other ocular diseases (aOR = 1.59, p = 0.005), not complying 20-20-20 rule (aOR = 2.13, p = 0.04), more screen time (aOR = 1.53 for >6 vs. ≤2 hours, p = 0.0001) and less outdoor activities (aOR = 1.37 for ≤0.6 vs. ≥1.9 hours, p = 0.005). CONCLUSIONS: During COVID-19 pandemic, self-reported CVS symptoms occurred in more than three-quarters of students. Besides pre-existing ocular diseases, children with myopia not wearing glasses, excessive time on screens, non-compliance of the 20-20-20 rule and reduced outdoor activities were associated with higher risk of CVS.

An integrated multi-criteria decision making approach with linguistic hesitant fuzzy sets for E-learning website evaluation and selection.

Network teaching has been widely developed under the influence of COVID-19 pandemic to guarantee the implementation of teaching plans and protect the learning rights of students. Selecting a particular website for network teaching can directly affects end users' performance and promote network teaching quality. Normally, e-learning website selection can be considered as a complex multi-criteria decision making (MCDM) problem, and experts' evaluations over the performance of e-learning websites are often imprecise and fuzzy due to the subjective nature of human thinking. In this article, we propose a new integrated MCDM approach on the basis of linguistic hesitant fuzzy sets (LHFSs) and the TODIM (an acronym in Portuguese of interactive and multi-criteria decision making) method to evaluate and select the best e-learning website for network teaching. This introduced method deals with the linguistic assessments of experts based on the LHFSs, determines the weights of evaluation criteria with the best-worst method (BWM), and acquires the ranking of e-learning websites utilizing an extended TODIM method. The applicability and superiority of the presented linguistic hesitant fuzzy TODIM (LHF-TODIM) approach are demonstrated through a realistic e-learning website selection example. Results show that the LHF-TODIM model being proposed is more practical and effective for solving the e-learning website selection problem under vague and uncertain linguistic environment.

Construction of a Medical Resource Sharing Mechanism Based on Blockchain Technology: Evidence from the Medical Resource Imbalance of China.

Health equity is a very important part of social equity. The outbreak of the novel coronavirus pneumonia (COVID-19) in a short period of time exposed the problems existing in the allocation of medical resources and the response to major public health emergencies in China. By using Kernel density estimation and Data envelopment analysis (DEA), it is found that the allocation and imbalance of medical resources in China are greatly different among regions, and the polarization phenomenon is obvious. As an important part of the information technology system, blockchain technology is characterized by decentralization and non-tampering. It can realize sharing of medical resources through a mechanism of resource storage, circulation, supervision, and protection. The construction of a medical resource sharing mechanism under the condition of blockchain technology will greatly improve the degree of medical resource sharing, will narrow the differences in resource allocation between regions, and can effectively respond to an outbreak of major public health emergencies.

Does Internet Use Affect Individuals' Medical Service Satisfaction? Evidence from China.

Empirical evidence that combines traditional factors and information technology factors to predict public attitudes toward to medical services is inadequate. To fill this gap, this study investigates the impact of Internet use on people's satisfaction with medical services by employing the Chinese Social Survey for 2013, 2015 and 2017 (including 28,239 samples in total). Estimation results under the ordered probit reveal that Internet use is negatively correlated with individuals' medical services satisfaction. The results support the negativity bias theory, namely, compared with positive information, netizens pay more attention to negative medical-related information on the Internet. The results are still reliable by adopting substitution variable methods, subdividing the samples, employing other estimation methods and carrying out placebo tests to conduct robustness checks. This study further enriches the literature on public attitudes toward medical services and provides additional policy implications for medical risk management in the digital era.

Multiplexed Nanomaterial-Based Sensor Array for Detection of COVID-19 in Exhaled Breath.

This article reports on a noninvasive approach in detecting and following-up individuals who are at-risk or have an existing COVID-19 infection, with a potential ability to serve as an epidemic control tool. The proposed method uses a developed breath device composed of a nanomaterial-based hybrid sensor array with multiplexed detection capabilities that can detect disease-specific biomarkers from exhaled breath, thus enabling rapid and accurate diagnosis. An exploratory clinical study with this approach was examined in Wuhan, China, during March 2020. The study cohort included 49 confirmed COVID-19 patients, 58 healthy controls, and 33 non-COVID lung infection controls. When applicable, positive COVID-19 patients were sampled twice: during the active disease and after recovery. Discriminant analysis of the obtained signals from the nanomaterial-based sensors achieved very good test discriminations between the different groups. The training and test set data exhibited respectively 94% and 76% accuracy in differentiating patients from controls as well as 90% and 95% accuracy in differentiating between patients with COVID-19 and patients with other lung infections. While further validation studies are needed, the results may serve as a base for technology that would lead to a reduction in the number of unneeded confirmatory tests and lower the burden on hospitals, while allowing individuals a screening solution that can be performed in PoC facilities. The proposed method can be considered as a platform that could be applied for any other disease infection with proper modifications to the artificial intelligence and would therefore be available to serve as a diagnostic tool in case of a new disease outbreak.