Majority world successes and European and American failure to contain COVID‐19: Cultural collectivism and global leadership

United Nations and World Health Organization data show a positive correlation, r = .53, p < .0001, N = 189, between COVID‐19 infection rates and the human development index (HDI). Less wealthy, less educated countries with lower life spans were also more successful in maintaining lower fatality rates, r = .46, p < .0001, N = 189 whereas 9 of the top‐10 countries in the world in per capita fatalities due to COVID‐19 were Western societies high in HDI. Similar positive correlations were found between COVID‐19 infection and fatality rates and a smaller sample of 76 countries measured on Schwartz intellectual autonomy (or individualism), and negative correlations of similar magnitude were found for embeddedness (or collectivism). East Asia was a global leader in preventing the spread of COVID‐19 because of a vigilant public concerned for public safety and compliant with public safety measures. African Union leaders coordinated their responses, and bought into a continent‐wide African Medical Supplies Platform that prevented panicked competition for scare supplies. Western global media and scholars have not paid attention to the successes of East Asia, Africa, and the South Pacific in fighting the pandemic. It is worth asking why this should be the case; understand the weaknesses of extreme individualism in fighting a pandemic requiring coordinated and unified public response, and consider the lessons for global scholars from the pandemic for doing research in the future.     

Effects of containment and closure policies on controlling the COVID‐19 pandemic in East Asia

Growing efforts have been made to pool coronavirus data and control measures from countries and regions to compare the effectiveness of government policies. We examine whether these strategies can explain East Asia’s effective control of the COVID‐19 pandemic based on time‐series data with cross‐correlations between the Stringency Index and number of confirmed cases during the early period of outbreaks. We suggest that multidisciplinary empirical research in healthcare and social sciences, personality, and social psychology is needed for a clear understanding of how cultural values, social norms, and individual predispositions interact with policy to affect life‐saving behavioural changes in different societies.     

Selfish power and unselfish status in Chinese work situations

The present research explored the selfishness of power and status as well as the mechanism in Chinese work situations. By using experimental and survey methods, two studies were designed to investigate the relationships among power, status, and self‐interested behaviour (SIB) as well as the mediating effect of perspective‐taking (PT). Results of the two studies consistently indicated that power increases whereas status reduces SIB. These opposing behavioural effects are partially attributed to the fact that power reduces whereas status increases PT. In addition, our results showed an interaction between power and status on SIB in Study 1 (interaction as a mental function), and a positive correlation between perceived power and status in Study 2 (correlation as a mental perception). Through the discussion from the perspective of the self/other‐orientation trait, as well as the stable effects of power and status on SIB in the two studies, we conclude that power is selfish and status is unselfish in Chinese work situations.     

Safety of micro-mobility: Riders’ psychological factors and risky behaviors of cargo TTWs in China

Cargo two- or three-wheeled vehicles (TTWs), as a new form of micro-mobility, have become a popular mode of urban cargo transportation in China. Cargo TTW riders’ psychological factors and risky behaviors lead to a number of accidents. A questionnaire is designed by comprehensively considering these factors and behaviors of cargo TTW riders that includes eleven risk factors to quantitatively analyze the risky behaviors based on structural equation modeling (SEM). One thousand three hundred nineteen participants reported using cargo TTWs on a questionnaire distributed across the country. The characteristics of riding behavior data are analyzed to verify the three-layer risk theoretical framework of “Psychological factors (Personality traits/specific factors) - Psychological acceptability of risks (confidence/perception/attitude) - Risky behaviors”. The results show that anger has a strong direct effect on riding violations, while normlessness and altruism have a direct effect on riding errors. Workload has a weak but direct effect on risky behaviors, and riding feedback has a weak and mixed effect. In addition, high-risk groups are identified by analysis of variance (ANOVA) with rider population attributes. These quantitative analyses can help guide safety countermeasures to mitigate accidents involving cargo TTWs.     

Correlations of multiple rider behaviors with self-reported attitudes,perspectives on traffic rule strictness and social desirability

Powered Two-Wheeler (PTW) riders constitute a very vulnerable group of road users, while riding a PTW is considerably more dangerous than using any other motor vehicle. Behavioral issues have been identified major moderating factors to PTW crashes, as riders display great variability in their attitudes towards road safety. Τhe aim of this paper is to present a thorough, overarching structure of relationships correlating various unsafe stated PTW rider behaviors (riding after alcohol consumption, speeding, helmet use and texting) with several self-reported attitude parameters and factors regarding rider perspectives on traffic rule strictness and social desirability. A structural equation model (SEM) was developed using data from the ESRA2 survey, which provided a broad sample encompassing 5,958 respondent riders from 32 countries. Numerous statistical relationships were discovered and quantified correlating the four examined unsafe rider behaviors with eight latent unobserved variables. All covariances between unsafe behaviors were found to be positive and statistically significant, indicating that a rider who will engage more frequently in every single one of the four examined unsafe riding behaviors is more likely to also engage in all the others as well.     

Analysing the influence of attitude and habit on bicycle commuting

New transport trends have emerged in developing countries to promote bicycling due to its individual and societal benefits. Although bicycle infrastructure provision has been one of the most utilised strategies to encourage bicycling, it has had a limited immediate impact on the bicycling modal share. Published research indicates the need to incorporate the psychosocial dimension to understand commuters' transport behaviour and explain why bicycling infrastructure usage is lower than expected. This study highlights the processes behind bicycle mode choice decisions, explicitly incorporating pro-bicycle attitudes and habits, while also considering the influence of socioeconomic, bicycle facilities and bicycling experience variables on shaping that attitude. For this purpose, an online survey was designed and sent to students, faculty members and staff of two Chilean universities to collect ad-hoc data. The modelling used an approach based on an integrated choice and latent variable model. The main findings are: attitude in itself is a relevant construct to explain behaviour; bicycling infrastructure contribute to explain bicycle choice but only indirectly through attitude; socioeconomic characteristics, bicycling familiarity and practical issues have both a direct effect on bicycle choice decision and an indirect one by fostering pro-bicycling attitudes. Additionally, results show that the explicit inclusion of habit reduces the contribution of pro-bicycle attitude in explaining bicycle choice. This might be due to interaction and reinforcement between habit and attitude.     

An adaptive network model covering metacognition to control adaptation for multiple mental models

Learning processes can be described by adaptive mental (or neural) network models. If metacognition is used to regulate learning, the adaptation of the mental network becomes itself adaptive as well: second-order adaptation. In this paper, a second-order adaptive mental network model is introduced for metacognitive regulation of learning processes. The focus is on the role of multiple internal mental models, in particular, the case of visualisation to support learning of numerical or symbolic skills. The second-order adaptive network model is illustrated by a case scenario for the role of visualisation to support learning multiplication at the primary school.     

Decision-making bioinspired model for target definition and “satisfactor” selection for physiological needs

Every person, from an early age, has to make decisions to resolve situations that arise in life. In general, different people make different decisions in the same situation, since decision-making takes into account different factors such as age, emotional state, experience, among others. We can make decisions about situations that we classify as: more important than others, routine, unexpected, or trivial. However, making the correct decision(s) in a timely manner for these situations is one of the most complex and delicate challenges that human beings face. This is due to the arduous mental process required to be carried out. Providing such behavior to a virtual entity is possible through the use of Cognitive Architectures (CAs). CAs are an approach for modeling human intelligence and behavior. This paper presents an functional bioinspired computational decision-making model to satisfy the physiological needs of hunger and thirst. Our proposal considers as black boxes other cognitive functions that are part of a general CA (named Cuäyöllötl or brain in Nahuatl). In the proposed case study, it is proved that the decision-making process plays an essential role in determining the objective and selecting the object that satisfies the established need.     

Declarative working memory: A bio-inspired cognitive architecture proposal

Memory is considered one of the most important functions since it allows us to code, store and retrieve knowledge. These qualities make it an indispensable function for a virtual creature. In general, memory can be classified based on the durability of the stored data in working memory and long-term memory. Working memory refers to the capacity to maintain temporarily a limited amount of information in mind, which can then be used to support various abilities, including learning, reasoning, planning and decision-making. Unlike short-term memory, working memory is not only a storage site, but it is also a framework of interacting processes that involve the temporary storage and manipulation of information in the service of performing complex cognitive activities. Declarative memory is a type of long-term memory related with the storage of facts and events. This research focuses on the development of a cognitive architecture for the type of working memory that maintains and manipulates declarative information. The construction of the model was grounded in theoretical evidence taken from cognitive sciences such as neuroscience and psychology, which gave us the components and their processes. The model was evaluated through a case study that covers the encoding, storing, and retrieval stages. Our hypothesis is that a virtual creature endowed with our working memory model will provide faster access to the information needed for the ongoing task. Therefore, it improves the planning and decision-making processes.