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Introduction: Since the coronavirus disease outbreak in 2019, there have been several preventive measures and restrictions applied to minimize the transmission of the virus. While lockdown has affected our everyday lives, it has negatively impacted sport and athletes as well. Methods: 1,387 Slovenian dual-career (DC) athletes (47.4% females, 52.6% males) participated in the 22-item questionnaire to gather information on their sports and academic engagement before and during COVID-19 lockdown period. Half of the athletes were enrolled in education at the secondary level (n = 819, aged 15-18 years), while the others were enrolled in primary (n = 301, 8-14 years) and tertiary (n = 267, 19-36 years) education. All participants in the current study have a valid athlete categorization by the Slovenian Olympic Committee and are competing at either junior (31.7%), national (26.9%), prospective (29.5%), international (8.5%), world (2.3%) or Olympic (1.2%) level. Results: DC athletes spent less time on training (-4.7 h; p < 0.001), learning (-1.0 h; p < 0.001), exams (-0.9 h; p < 0.001), laboratory work (-0.6 h; p < 0.001), and other educational activities (-0.3 h; p < 0.001) during COVID-19 lockdown compared to period before the lockdown. Their training environment was changed so they trained either at home or outdoors. Results showed that indoor (-3.7 h; p < 0.001) and team sport athletes (-1.3 h; p < 0.001) trained less than outdoor and individual sports. Male athletes spent more time on training both before (1.3 h; p < 0.001) and during lockdown (1.3 h; p < 0.001) and other sport-related activities (1.3 h; p < 0.001). On the other hand, female athletes spent more time on studying both before (1.5 h; p < 0.001) and during lockdown (2.6 h; p < 0.001). Both sport and educational activities were influenced by athletes' age (p ≤ 0.017). Conclusion: Indoor and team sport athletes were more affected by the governmental measures than outdoor and individual sport athletes. Male athletes experienced a greater decline in learning time compared to female athletes. DC is shown to be beneficial for athletes even in times of COVID-19 lockdown, as DC athletes report smaller decline in motivation, shifting attention from sport to study and having fewer mental problems due to uncertain sports future. The feedback of the preventive measures could serve to assist policy makers and athlete's support staff to form and apply preventive measures that are more effective for DC athletes' training and education.
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As the use of COVID-19 vaccines gains more prevalence, rare and uncommon side effects are reported in the medical literature. This is a case report of a 75-year-old male patient who presented on the second day after receiving the Moderna Bivalent mRNA COVID-19 booster vaccine with abrupt onset behavioral changes and global aphasia with no focal deficits. Stroke and infectious meningitis/encephalitis were ruled out. Signs of aseptic inflammation were seen on cerebrospinal fluid (CSF) analysis. Workup for autoimmune and paraneoplastic encephalitis was unyielding. The observation of rapid clinical improvement prompted watchful waiting that concluded in the resolution of clinical manifestations within less than a week of onset. This case is reported to support the currently limited knowledge of rare neurological sequelae of mRNA vaccine and is in line with recently published few cases that suggest vaccine-related encephalitis.
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Aim of the present study was to assess physical activity, nutrition and psychological status of the population during lockdown due to covid-19. Online survey was conductedamong 534 participants within the age range of 16-78 years using convenient sampling. Participantsfrom varied regions within India and abroad were enrolled for the present study. Volunteered participants were solicited to take part in a survey that has to be carried out by filling an online questionnaire form available to them as a URL link in the invitation through WhatsApp/Messenger. The gathered data has been compiled, coded and cleaned using Microsoft Excel. Analysis has been carried out employing descriptive and inferential statistics in SPSS 17.0.Majority of participants in the studied population showed significant change in their nutrition and physical activity status due to lockdown. Covid-19 lockdown did limit their daily activities. It also had impacted their psychological status.The current investigation accentuates the need to pursue suitable life style for the maintenance of optimum metabolism and physiology. Sticking to more regular timetable of meals, effective management of stress levels and continued physical activity during the quarantine and in all the following phases of living is desirable.
Subject(s)
Male , Female , Adolescent , Adult , Middle Aged , Aged , Exercise/psychology , Quarantine/psychology , Mental Health , Feeding Behavior/psychology , COVID-19/epidemiology , Sleep , Social Behavior , Pandemics/prevention & control , Diet, Healthy/psychology , Interpersonal Relations , Life StyleABSTRACT
This article aimed to observe the efforts of Indonesia and the problems faced in fighting the COVID-19 pandemic regarding the indecisive public policy and the reluctance of people from all walks of life to comply with the Health Protocols (HP) from the perspective of sociological institutionalism (Nee 2003; Nee and Opper 2015). A two-step variant of SSM-based multi method by Muhammaditya et al. (2021) was applied by inserting (1) Textual Network Analysis by Segev (2020) at stage 1 of SSM to obtain an insightful understanding of the problem situation and to enrich the rich picture, and (2) Social Network Analysis at stage 5 of SSM to expand a skillful discussion on the reality. The research novelty was elaborated in four main empirical facts: First, government policies had initially faltered in dealing with the pandemic, reflected by the dissonance in the statements made by high-ranking state officials. Second, there was a great number of people disregarding HP and pandemic mitigation policies, particularly during annual rites, the end of year celebration, and Eid Al-Fitr. Third, the government encountered a dilemma in issuing policies, whether to remain encouraging economic growth, guarantee the continuity of economic activities, or end the spread of COVID-19. Fourth, the direct involvement of the president in handling COVID-19 had a significant impact in reducing active cases that no province was declared as alert areas in October 2021. Meanwhile, the methodological novelty reflected in broader data and analysis through SNA and TNA methods had enriched the practice of SSM in finding sharper conclusions.
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This data article analyzes the changes in travel habits and destination preferences among Thai domestic travelers before and after the COVID-19 pandemic. The data was collected through an online survey conducted on Facebook, Line, and Instagram, with a sample size of 460 valid respondents. The article provides descriptive statistics and frequency data on travel behavior and attitudes related to various tourist attractions before and after the onset of the pandemic. These insights can be valuable for transportation and tourist destination management in Thailand, as they can be used to compare with other studies using similar methods and outcomes and help to develop specialized and targeted solutions for addressing changes in travel trends and demand after the pandemic. For more information, see the full article titled "Using factor analyses to understand the post-pandemic travel behavior in domestic tourism through a questionnaire survey."
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The commonly applied strategies for promoting compliance with public health and safety policies can be inefficient and coercive, posing a need to examine novel motivational strategies to aid in this endeavor. Gamification, which aims to foster engagement and intrinsic motivation towards mundane activities and behaviors, is one of the vanguard design approaches among behavioral change support systems. Despite the increasing interest in gamification, the corpus lacks studies on its effects on policy compliance. Therefore, this study examines the relationships between gamification design types, gameful experience, and policy compliance in the social distancing context (during COVID-19) using a vignette-based online experiment (n=937). Based on the results, gameful experience mediates the positive relationships between achievement and progression-based, competitive, and immersive gamification and policy compliance, while social gamification is not associated with gameful experience. The results provide evidence of gamification's potential as a non-coercive method of helping people follow policies. © 2023 IEEE Computer Society. All rights reserved.
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The present study aims at understanding and analyzing the COVID-19-induced behavioral change spurting artificial intelligence (AI) adoption in Indian banking industry. The study has further identified and analyzed the usage pattern of Indian customers for mobile banking/online banking services in the pre-pandemic phase and progression of Indian customers for mobile banking/online banking services during the pandemic. Secondary data has been used for deep understanding of the AI adoption in Indian banking industry, with reports from McKinsey, PWC, RBI, NPCI, BIS, etc., to form the base. The period of study was taken from 2016 to 20, and this was taken keeping in mind the timing of another unprecedented event of demonetization. Behavioral change of Indian banking industry customer was assessed on three broad parameters change in value and volume of mobile banking transactions on year on year basis. COVID-19-induced behavioral change translating in massive jump of 178% in volume of mobile transactions between March 2019 and 2021. The increase in number of smart phone users and access to connectivity and desired technology has helped the cause. With 2020–21 punctuated by several nationwide as well as localized lockdowns adoption of AI for customer engagement has been crucial for Indian banking industry, which has further translated in to designing and customizing products and risk profiling of customers further resulting in increased operational efficiency and intuitive decision making. The behavioral change induced by COVID-19 in the Indian baking industry achieves competitive advantage by truly responding to huge customer data base which has been utilized by other financial industries as now it can have systems which understand and are responsive to behavior of varied customers. From responses feeded chatbots to intuitively responsive AI bots, the customer engagement is going to be a whole new experience which will help in customer acquisition and retention. Further, with falling data storage costs, increasing processing speeds and capabilities and improved connectivity and access for all has helped the rapid automation and AI adoption. Enterprise level adoption of AI has led to revenue generation and optimization of functional resources this reducing the cost at functional level. The AI adoption has been continuous from the banks over the years though banks have started to harness its potential in the recent years with customers adoption of smart hand-held devices. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023.
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Many studies conducted previously have reported that due to lockdowns or stay-at-home orders associated with the COVID-19 pandemic in April 2020 residential power consumption has increased in countries, particularly in cities worldwide. This study compared the power consumption of 1,339 detached houses in Japan over the past three years as well as a year after the pandemic and analyzed living behavioral changes in the 12 months after the pandemic using a questionnaire survey of occupants. As of March 2021, which is after 12 months of the beginning of the pandemic, it was confirmed that the way of life had returned to almost normal, and as a factor in increasing consumption, working from home would remain the only behavioral change that may take root in Japanese society.
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Social distancing as a health-related behavior during epidemics and pandemics, can significantly influence their control. In this regard, the identification of the factors influencing behavior change can play a remarkable role in assessing for how behaviors form. This paper is an attempt to show that the extended theory of planned behavior can provide a useful theoretical framework for explaining social distancing in the face of a contagion disease. The results showed that the constructs of attitude, descriptive norms, perceived behavioral control, and self-efficacy significantly influenced the students' intention to adhere to social distancing in the form of university closure. Among these constructs, self-efficacy was found to be the main predictor of the students' intention. Interestingly, the research revealed that injunctive norms were not a significant predictor of the students' intention. Practically, this study is a justification for the use of attitude, descriptive norms, perceived behavioral control, and self-efficacy in planning and decision-making for encouraging students to adhere to social distancing during epidemics and pandemics, like the COVID-19 pandemic. The extended theory of planned behavior is useful in understanding Iranian College Students' Intention toward Social Distancing in COVID-19 Pandemic.
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The COVID-19 pandemic has led communities, including Kinshasa peri-urban schools, to reinforce WASH-related practices as a key com-ponent in preventing the spread of COVID-19. This study aimed to determine the institutional and behavioural changes in adolescent girl students' handwashing practices before and during the COVID-19 pandemic. A cross-sectional study was performed, observing the hand hygiene of adolescent girl students, and assessing WASH facilities at schools, chosen from a sample previously selected in the study area. The results indicate significant increases in the prevalence of water points in schools from 10.9 to 22.5%, of handwashing facilities from 43 to 60.1% of schools with an average number of handwashing facilities from one to two, and the prevalence of school WASH brigades from 4.8 to 11.8% of schools. There was also a significant increase in schools receiving funds, and other support for WASH, respectively, from 24.9 to 70.3%, and from 17 to 45.9%, while the proportion of adolescent girl students washing their hands after using the toilet and before eating significantly increased from 6 to 28.4%. However, to improve the current WASH picture, and succeed in curtailing the spread of COVID-19 and related impacts, additional efforts to enhance handwashing practice and WASH items' coverage are expected. © 2023 The Authors.
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The COVID-19 pandemic outbreak, declared in March 2020, has led to several behavioral changes in the general population, such as social distancing and mask usage among others. Furthermore, the sanitary emergency has stressed health system weaknesses in terms of disease prevention, diagnosis, and cure. Thus, smart technologies allowing for early and quick detection of diseases are called for. In this framework, the development of point-of-care devices can provide new solutions for sanitary emergencies management. This work focuses on the development of useful tools for early disease diagnosis based on nanomaterials on cotton substrates, to obtain a low-cost and easy-to-use detector of breath volatiles as disease markers. Specifically, we report encouraging experimental results concerning acetone detection through impedance measurements. Such findings can pave the way to the implementation of VOCs (Volatile Organic Compounds) sensors into smart and user friendly diagnostic devices. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.
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Health professionals are increasingly using digital technology as a strategy to maximize community engagement and effectively implement health interventions, a phenomenon evidenced by the COVID-19 pandemic. While technology has improved health information dissemination, communication, and data management, it cannot replace the human-based interactions offered by traditional grassroots outreach that can influence long-term health behavior change, particularly for underserved communities. Digital community engagement can be part of the digital divide, often widening disparities by excluding those without access or limited access to technology. It may hinder the accurate collection of contextual and comprehensive data needed to analyze social determinants of health, thereby widening the equity gap. This commentary explores the challenges of using digital technology and justifies leveraging it to complement traditional community engagement rather than as a replacement.
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Sexual well-being is a fundamental facet of the overall well-being of most individuals and implies the ability to have safe and pleasurable sexual experiences, beyond the absence of disease or disturbance. The extent to which people can achieve sexual well-being depends, among other aspects, on whether they live in an environment that promotes and support it. The present study focuses on the unexplored impacts of the perceived acoustic environment (i.e., the soundscape) on human sexual activity carried out in domestic settings. Verbal descriptions have been gathered from open-ended questions included in a survey administered to 848 respondents living in the UK (London area) and in Italy in January 2021 during the COVID-19 lockdown. Thematic analysis was used to extract a framework detailing the positive and negative impacts of the acoustic environment on sexual activity. The results show the mechanisms by which the acoustic features of the environment can impact on the sexual experience in terms of privacy, distraction, disruption or support, up to trigger coping strategies (e.g., controlling windows, playing music) and behavioural changes (e.g., lowering the volume of the voice) that can in turn limit or enhance the freedom of sexual behaviour, affect or foster sexual well-being. © 2022 Internoise 2022 - 51st International Congress and Exposition on Noise Control Engineering. All rights reserved.
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This study aims at identifying the tools necessary for COVID-19 health emergency management, with particular reference to the period following the first lockdown, a crucial phase in which it was important to favor the maintenance of protective behaviors. It also aims at identifying the messages and sources that were most effective in managing communication correctly in such a crucial phase that is likely characterized by a fall in perceived health risk (due to the flattening of the epidemic curve) and a simultaneous rise in perceived economic and social risks (due to the enduring calamity). Knowing what source will be most effective to convey a specific message is fundamental in enabling individuals to focus on and comply with the rules. At the same time, it is necessary to understand how the message should be presented, and the relationships between messages, sources and targets. To meet these goals, data were collected through a self-administered online questionnaire submitted to a sample of undergraduate students from a University in Lombardy-the region most affected by the pandemic in the first wave- (Study 1), and to a national sample composed of Italian citizens (Study 2). Through our first manipulation which explored the effectiveness of social norms in relation to different sources, we found that, in the national sample, the injunctive norm conveyed by the government was the most effective in promoting behavioral intentions. By contrast, among the students, results showed that for the critical group with a lower risk perception (less inclined to adopt prevention behavior) descriptive norms, which implicitly convey the risk perception of peers, were as effective as the government injunctive norm. Our second manipulation, identical in Study 1 and 2, compared four types of communication (emotional, exponential growth, both of them, or neutral). The neutral condition was the most memorable, but no condition was more effective than the others. Across all message types there was a high intention to adopt protective behaviors. The results indicate possible applicative implications of the adopted communicative tools.
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In today's world, it is very common among children to use a smartphone or a handheld digital device such as a tablet to entertain themselves and as a medium of socializing with people easily. The COVID-19 pandemic forced many people to stay in their homes and rely on these digital devices to do their day-to-day work and communication. The latter caused the increase in reliance on digital devices to acquire information about the outside world and as a source of entertainment. This new tendency increased the likelihood of children being exposed to pornography, cyberbullying, cyberstalking, excessive gaming, sexting, and behavioral traits related to narcissism. These habits caused many children to develop psychological and physiological illnesses, which affected them in the short term and, for some, which affected them and their families in the long run, such as suicide. Our research proposes to constantly monitor behavioral patterns such as this, notify the relevant individuals, and prevent the children from being prone to such ill fates. According to the findings, using machine learning and natural language processing, sexting, phonographic words, and cyberbullying can all be recognized with pinpoint accuracy. Also, by using two machine learning models, depression and anxiety are detected with an accuracy of 0.84 and 0.86. To prevent and analyze computer vision syndrome caused by improper face-screen distance. An image processing-based algorithm is used to measure the distance from face to screen, and results are narrowed down to an accuracy of 1 inch. © 2022 IEEE.
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Music listening choices are considered to be a factor capable of measuring people's emotions. Thanks to the explosion of streaming music applications in recent years, it is possible to describe listening trends of the global population based on emotional features. In this paper we have analysed the most popular songs from 52 countries on Spotify through their features of danceability, positivity and intensity. This analysis allows exploring how these song features reflect mood trends along with other contextual factors that may affect the population's listening behaviour, such as the weather or the influence of the COVID-19 pandemic. Finally, we have proposed a multivariate time series model to predict the preferred type of music in those countries based on their previous music listening patterns and the contextual factors. The results show some relevant behavioural changes in these patterns due to the effect of the pandemic. Furthermore, the resulting prediction model enables forecasting the type of music listened to in three different groups of countries in the next 4 months with an error around 1%. These results may help to better understand streaming music consumption in businesses related to the music and marketing industry. © 2022 Elsevier B.V.
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Air transport challenges the world's net-zero carbon ambitions. The sector has consistently grown and causes warming as a result of both CO2 and other, short-lived emissions. Two principal solutions have been proposed to reduce the contribution of aviation to climate change: innovations of technology and the development of interventions to trigger behavioral change. Technological innovations include new propulsion technologies and the use of sustainable aviation fuels. Behavioral change includes flight avoidance, substitution with other means of transport, the choice of efficient flight options, and carbon offsetting. This article focuses on behavior;it offers an overview of factors that lead to consumers traveling by air and discusses demand distribution complexities. The importance of price for air travel decisions is assessed, and evidence of travel "wants” are contrasted with "needs,” the latter investigated in light of the COVID-19 pandemic. The review of relevant scholarly work culminates in an action list enabling air travelers, policy makers, the aviation industry, researchers and society to meaningfully advance low-carbon air transport trajectories. This article is categorized under: Perceptions, Behavior, and Communication of Climate Change > Behavior Change and Responses The Carbon Economy and Climate Mitigation > Policies, Instruments, Lifestyles, Behavior. © 2022 The Authors. WIREs Climate Change published by Wiley Periodicals LLC.
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Vaccines have proved to be effective in reducing mortality of the COVID-19 pandemic. However, a part of the population is still reluctant to be vaccinated. Thus, the aim of this work was to apply a framework to create Personas, fictional representations of real people, to assess the characteristics of the population willing to be vaccinated in order to develop personalized eHealth-based interventions to increase compliance to vaccinations. Data was collected through an online survey at the beginning of 2021. Multiple dimensionality reduction methods were used as input for K-Medoids clustering with PAM algorithm to create Personas. The optimal number of Personas and dimensionality reduction method to be used were evaluated through the average silhouette graph and the percentage of statistically different attributes between Personas. From 1070 respondents, three Personas were identified. Persona 3 showed statistically significant lower trust in institutions, lower education and lower willingness of being vaccinated when compared to the other two Personas. The developed approach to create Personas was deemed able to identify the main characteristics of those more prone not willing to be vaccinated, suggesting that behavioral change techniques should focus on taking advantage of the closer social circle of those reluctant to vaccines. © 2022 IEEE.
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This study aims to assess and evaluate the knowledge, beliefs, behaviors, and practices about COVID-19 among different categories of Jordanian people including pregnant and breastfeeding mothers. A cross-sectional study is designed using an online survey questionnaire and a five-section questionnaire was devised to address perceptions and attitudes of the participants towards COVID-19. This study was found that more than 80% of the participants had a belief that COVID-19 can be transmitted through direct contact or spreading of air droplets from infected people to healthy ones. Around 15% of pregnant and breastfeeding women realized that the COVID-19 virus could transmit the virus to their babies. Third-fourth of the participants agreed that the elderly, pregnant, and immunocompromised people have a higher risk of being infected with COVID-19. In addition, 80% of the participants believed that using paracetamol is a good way of treating COVID-19 or reducing symptoms, while the remaining believed that they should use antibiotics as well as some vitamins to combat COVID-19. Around 70% of the participants have got their information about COVID-19 through social media while others got the information through the Jordanian Ministry of Health official website, other websites, television news, friends, relatives, and colleagues. Participants' practices to avoid transmission of COVID-19 were adequate in more than 80% of the participants who reported that they should protect themselves as well as their families as a priority. we believe that this study allow other governments worldwide to understand the views of public people in Jordan during pandemic disease outbreaks. Copyright © RJPT All right reserved.
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Advanced Driver Assistance Systems (ADAS) are enabling technologies in Intelligent Transportation Systems. Modern ADAS include algorithms to classify drivers' actions and distractions, aiming at identifying situations in which the driver is inattentive. Such systems typically include components for Driver Action Recognition (DAR) and Visual Distraction Classification (VDC), which prevent risky situations during semi-autonomous driving. DAR and VDC often rely on cameras that track the driver and classify actions based on image recognition algorithms. The COVID-19 pandemic has changed several common social behaviours, including the widespread use of face mask even during driving. In some cases (taxi, bus) face covering policies are compulsory in many legislations. We here show that these behavioural changes challenge state-of-the-art DAR and VDC systems, with the average F1-score in some scenarios dropping by around 30% when exposed to images of drivers wearing masks. Noting a lack of public datasets to update the ML classifiers performing such tasks, we contribute Maskdar, a dataset for Action Recognition of Drivers wearing face Masks. Finally, using Maskdarwe show the importance of including subjects with face masks in datasets for DAR. © 2022 IEEE.