ABSTRACT
Social-Emotional Learning (SEL), the process of developing and utilizing interpersonal skills for everyday life, has become a primary vehicle for structuring students' social and emotional health in the United States and across the world. In the midst of the COVID-19 pandemic, the importance of understanding SEL practices, is increasingly at the forefront of many discussions in education today. Since "non-academic factors" like SEL were added to U.S. education law (ESSA, 2015), the state of Florida has also added two mandates concerning SEL (Florida Senate Bill 7026: The Marjorie Stoneman Douglas Act and FS 1003.42;Rule 6A-1.094121: Curriculum mandate for four hours of SEL as part of mental health education). This has led to the adoption of SEL programming in schools. In 2018, Martin County Public Schools adopted the BASE Education learning program, an SEL approach that aimed to help high school students, identified as at-risk after a discipline infraction, to "learn about and apply psycho-social concepts through supportive, therapeutic dialogue" (MCSD Code of Conduct, Chapter V, 2022, p.18). BASE Education is an online program currently being implemented in all high schools within the Martin County School District. In purchasing BASE for implementation into the disciplinary process and SEL supports, the district projected that BASE Education would increase self-awareness and increase responsible decision making, thus decreasing discipline referrals. This study examines two components of the disciplinary experience of MCSD students: (1) The SEL experience of high school students referred to BASE Education intervention programming in the Martin County School District, and (2) How students who have participated in [personalized] BASE Education modules describe the nature of their pathway within the online experience. This study represents the first time that an analysis of the student referral experience data and online SEL intervention experiential pathway program data has been undertaken in Martin County Public Schools. (PsycInfo Database Record (c) 2023 APA, all rights reserved)
ABSTRACT
The objective of this study was to determine the effect of COVID-19 on youth's social emotional competencies. Specifically, this study examined whether there was a significant difference in social emotional competency proficiency levels of self-management, social awareness, and emotion regulation as measured by the Panorama SEL Survey from October 2019 to October 2021 in fifth through twelfth grade students who attended a large, diverse suburban school district in Illinois. This study showed statistically significant differences in students' proficiency levels, which increased for self-management and decreased for social awareness and emotion regulation. Based on these results, school district leaders should consider investing funds to increase interventions and strategies for students regarding social awareness and emotion regulation. Future research should consider analyzing mindfulness interventions implemented as well as the different demographic subgroups with pre-pandemic and during-pandemic data. An extension study with additional years from the same cohort may also provide meaningful insights to school district leaders. (PsycInfo Database Record (c) 2023 APA, all rights reserved)
ABSTRACT
"Health Promotion in the Region of the Americas" is a collaboration by a team of experts from 14 countries with the objective to build capabilities for health promotion in the region. The first step of this journey was the creation of a web platform in the context of the COVID-19 global pandemic, a context that challenges the revision of development models, relationships, and training. It is a novel work because it implements the principles of an emancipatory health promotion, contributes to capacity building, promotes the construction and democratic access to high-quality information, and formalizes thoughtful spaces and the exchange of experiences. It is a living and dynamic process that is projected from a commitment to participation and co-responsibility for the construction of development models based on real proposals for health and life. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2022. All rights reserved.
ABSTRACT
Recurring outbreaks of COVID-19 have posed enduring effects on global society, which calls for a predictor of pandemic waves using various data with early availability. Existing prediction models that forecast the first outbreak wave using mobility data may not be applicable to the multiwave prediction, because the evidence in the USA and Japan has shown that mobility patterns across different waves exhibit varying relationships with fluctuations in infection cases. Therefore, to predict the multiwave pandemic, we propose a Social Awareness-Based Graph Neural Network (SAB-GNN) that considers the decay of symptom-related web search frequency to capture the changes in public awareness across multiple waves. Our model combines GNN and LSTM to model the complex relationships among urban districts, inter-district mobility patterns, web search history, and future COVID-19 infections. We train our model to predict future pandemic outbreaks in the Tokyo area using its mobility and web search data from April 2020 to May 2021 across four pandemic waves collected by Yahoo Japan Corporation under strict privacy protection rules. Results demonstrate our model outperforms state-of-the-art baselines such as ST-GNN, MPNN, and GraphLSTM. Though our model is not computationally expensive (only 3 layers and 10 hidden neurons), the proposed model enables public agencies to anticipate and prepare for future pandemic outbreaks. © 2022 Owner/Author.
ABSTRACT
Purpose>Training is one of the key dimensions of internal marketing. Virtual reality (VR), a computer technology that replicates an environment (real or imagined) and simulates a user’s physical presence in that environment to allow for user interaction, offers unique opportunities from a training perspective, such as allowing users to improve their skills without the consequence of failing real customers or the need to be in the real environment physically. This study aims to focus on comparing the effectiveness of VR hospitality training with that of real-world hospitality training.Design/methodology/approach>This study adopts situated cognition theory to empirically test the effect of the awareness of contextual variables (social interaction, location and task) on learning and compare learning outcomes between tourism training in VR and real-world experimental settings.Findings>Results indicate that location and task awareness enhance cognitive absorption, but social awareness does not influence cognitive absorption. There is no significant difference between training in real-world and VR environments. Finally, cognitive absorption has a positive effect on mental model change (the learning outcome).Originality/value>This result advances the theoretical understanding on the significance of learning context by applying situated cognition theory in hospitality training and has significant implications for training that aims for rigor and efficiency within cost, location and time constraints.
ABSTRACT
The rapid social, economic and technological changes taking place in the world today, have led to the rise of social and emotional processes as an essential requirement in positive human development and meaningful education. Children and young people need to grow and develop as autonomous, productive and healthy citizens in a fast-changing world. The term 'social and emotional learning' (SEL) captures both the intra and interpersonal core competences, namely self-awareness, self-management and regulation, social awareness and empathy, relationships and responsible decision making. There is consistent evidence that SEL has a positive impact on both cognitive and social and emotional outcomes in children and young people. The worldwide anxiety created by the recent COVID-19 pandemic, both amongst children and adults alike, underlined the need for such 'life competences' to help overcome our fears, manage our anxiety, maintain a sense of control and build our resilience to cope effectively with the psychological impact of the crisis. This introductory chapter describes the concept of SEL and provides a brief overview of the following chapters. (PsycInfo Database Record (c) 2022 APA, all rights reserved)
ABSTRACT
In this article, we propose and analyze a mathematical model of COVID-19 transmission among a closed population, with social awareness and rapid test intervention as the control variables. For this, we have constructed the model using a compartmental system of the ordinary differential equations. Dynamical analysis regarding the existence and local stability of equilibrium points is conducted rigorously. Our analysis shows that COVID-19 will disappear from the population if the basic reproduction number is less than one, and persist if the basic reproduction number is greater than one. In addition, we have shown a trans-critical bifurcation phenomenon based on our proposed model when the basic reproduction number equals one. From the elasticity analysis, we have observed that rapid testing is more promising in reducing the basic reproduction number as compared to a media campaign to improve social awareness on COVID-19. Using the Pontryagin Maximum Principle (PMP), the characterization of our optimal control problem is derived analytically and solved numerically using the forward-backward iterative algorithm. Our cost-effectiveness analysis shows that using rapid test and media campaigns partially are the best intervention strategy to reduce the number of infected humans with the minimum cost of intervention. If the intervention is to be implemented as a single intervention, then using solely the rapid test is a more promising and low-cost option in reducing the number of infected individuals vis-a-vis a media campaign to increase social awareness as a single intervention. © 2021 Published by Indonesian Biomathematical Society,.
ABSTRACT
Decreased air quality is connected to an increase in daily mortality rates. Thus, people's behavioural response to sometimes elevated air pollution levels is vital. We aimed to analyse spatial and seasonal changes in air pollution-related information-seeking behaviour in response to nationwide reported air quality in Poland. Google Trends Search Volume Index data was used to investigate Poles' interest in air pollution-related keywords. PM10 and PM2.5 concentrations measured across Poland between 2016 and 2019 as well as locations of monitoring stations were collected from the Chief Inspectorate of Environmental Protection databases. Pearson Product-Moment Correlation Coefficients were used to measure the strength of spatial and seasonal relationships between reported air pollution levels and the popularity of search queries. The highest PM10 and PM2.5 concentrations were observed in southern voivodeships and during the winter season. Similar trends were observed for Poles' interest in air pollution-related keywords. Greater interest in air quality data in Poland strongly correlates with both higher regional and higher seasonal air pollution levels. It appears that Poles are socially aware of this issue and that their intensification of the information-seeking behaviour seems to indicate a relevant ad hoc response to variable threat severity levels.
Subject(s)
Air Pollutants , Air Pollution , Air Pollutants/analysis , Air Pollution/analysis , Environmental Monitoring , Humans , Particulate Matter/analysis , Poland , Search Engine , SeasonsABSTRACT
The COVID-19 pandemic took the world by surprise and surpassed the expectations of epidemiologists, governments, medical experts, and the scientific community as a whole. The majority of epidemiological models failed to capture the non-linear trend of the susceptible compartment and were unable to model this pandemic accurately. This study presents a variant of the well-known SEIRD model to account for social awareness measures, variable death rate, and the presence of asymptomatic infected individuals. The proposed SEAIRDQ model accounts for the transition of individuals between the susceptible and social awareness compartments. We tested our model against the reported cumulative infection and death data for different states in the US and observed over 98.8% accuracy. Results of this study give new insights into the prevailing reproduction number and herd immunity across the US.
Subject(s)
COVID-19 , Pandemics , Humans , Models, Statistical , SARS-CoV-2ABSTRACT
The COVID-19 pandemic has affected daily lives of people around the world. People have already started to live wearing masks, keeping a safe distance from others, and maintaining a high level of hygiene. This paper deals with an in-depth analysis of riskness associated with COVID-19 infections in Kolkata Municipal Corporation (KMC) at the subcity (ward) level. Attempts have been made to identify the areas with high or low risk of infections using GIS-based geostatistical approach. Cosine Similarity Index has been used to rank different wards of KMC according to the degree of riskness. Four indices were computed to address intervention objectives and to determine "Optimized Prevention Rank" of wards for future policy decisions. The highest risk areas were located in the eastern and western part of the city, to a great extent overlapped with wards containing larger share of population living in slums and/or below poverty level. On the other hand, highly infected areas lie in central Kolkata and in several wards at the eastern and northeastern periphery of the KMC. The "Optimized Prevention Rank" have indicated that the lack of social awareness along with lack of social distancing have contributed to the increasing number of containments of COVID-19 cases. The rankings of the wards would no doubt provide the policy makers a basis to control further spread of the disease. Since effective antiviral drugs are already in the market, the best application of our research would be in the ensuing vaccination drive against further COVID-19 infections.
ABSTRACT
Since the initial identification of a COVID-19 case in Wuhan, China, the novel disease quickly becomes a global pandemic emergency. In this paper, we propose a dynamic model that incorporates individuals' behavior change in social interactions at different stages of the epidemics. We fit our model to the data in Ontario, Canada and calculate the effective reproduction number $\mathcal{R}_t$ within each stage. Results show that $\mathcal{R}_t$ > 1 if the public's awareness to practice physical distancing is rela-tively low and $\mathcal{R}_t$ < 1 otherwise. Simulations show that a reduced contact rate between the susceptible and asymptomatic/unreported symptomatic individuals is effective in mitigating the disease spread. Moreover, sensitivity analysis indicates that an increasing contact rate may lead to a second wave of disease outbreak. We also investigate the effectiveness of disease intervention strategies. Simulations demonstrate that enlarging the testing capacity and motivating infected individuals to test for an early diagnosis may facilitate mitigating the disease spread in a relatively short time. Results also indicate a significantly faster decline of confirmed positive cases if individuals practice strict physical distancing even if restricted measures are lifted.