Search Results (133)

The COVID-19 pandemic caused immense physical disruptions, affecting young adults in the U.S. The Health Belief Model is a social psychological framework that predicts the likelihood of adopting health behavior. The purpose of this research is to investigate COVID-19-related health beliefs and dietary behaviors among undergraduate students during the pandemic. Using convenience sampling, a cross-sectional survey was completed by 304 individuals at a New Jersey state university. Survey data included the frequency of COVID-19 prevention behaviors (e.g., wearing an indoor mask, handwashing), and consumption of fruit and vegetables. The Health Belief Model constructs measured perceived susceptibility to COVID-19, severity, benefits, barriers, and self-efficacy. Frequency distributions, t-tests, and Kruskal–Wallis tests were investigated for racial subgroups (Whites, Blacks, Latinos, and Asians). The mean age of the sample was 21.7, with 27% males, and 46% self-identified as White. Whites adopted fewer COVID-19 prevention behaviors (p < 0.001) than non-Whites. Black students perceived less COVID-19 severity (p < 0.01) and stronger perceived benefits (p < 0.05) than the other subgroups. Latino students perceived greater susceptibility (p < 0.01) and greater barriers than non-Latinos. Asians practiced higher mask wearing frequency (p < 0.05) but less daily fruit intake than their counterparts (p < 0.01). This research highlights the importance of handwashing, wearing indoor masks, and consuming produce among university students. Addressing barriers to health action while promoting the benefits of enacting behaviors to mitigate the risk of COVID-19 is warranted. Full article

During the COVID-19 pandemic, the United States Centers for Disease Control and Prevention (CDC) recommended the use of well-fitting face masks or respirators as a strategy to reduce respiratory transmission; however, acceptance and utilization of face masks quickly became a contentious, politically charged matter. Given the effectiveness of masking against respiratory viruses, it is critical to understand the various normative factors and personal values associated with mask wearing. To this end, this study reports the findings of an online, cross-sectional survey (n = 1231) of college students during the COVID-19 pandemic. Findings show that ideological consistency, sharing news to create awareness, and sharing unverified news significantly predict masking behaviors, though ideological consistency most substantially explained variance in self-reported masking behaviors. Participants with more liberal political ideologies reported greater adherence to masking policies while those with more conservative ideologies reported less mask-wearing behavior. A better understanding of the predictors of masking behaviors, particularly how political ideologies continue to shape public health responses, is essential for designing more effective communication strategies to control disease spread and help inform strategies for future outbreaks. Study implications and limitations are discussed. Full article

The safety management of laboratories is of utmost importance in the construction and management of university laboratories. Abnormal behaviors such as smoking, incorrect wearing of personal protective equipment (PPE) like lab coats, hats, masks, and gloves pose significant safety hazards. In this paper, in order to improve the level of laboratory safety management and effectively provide an alert in the case of unsafe behaviors, video analysis technology is employed to achieve abnormal behavior recognition and monitoring through steps such as human key point detection, posture estimation, and behavior recognition. Firstly, the human pose estimation algorithm YOLO is used for human detection, followed by the extraction of human key points after segmentation. Finally, spatiotemporal graph convolution is used for feature detection and classification of abnormal behaviors. The experimental results show that the accuracy of abnormal behavior detection and recognition based on human key points reaches over 85%, which is of great significance for safety management and behavior warning in university laboratories, and thus, improves the efficiency and level of laboratory safety management. Full article

Training is instrumental in identifying and selecting cattle that exhibit greater cooperation with experimental conditions required in flow respirometry assays, like restraint and the use of a valved facial mask. In our study, a tailored training protocol for Nellore cattle facilitated their participation in flow respirometry assays with a valved facial mask. Over 127 days, 30 entire Nellore males, weighing 450 ± 25 kg and averaging 32 ± 2 months, underwent training from May to September 2022. The regimen involved gradually altering the animals’ environment and providing positive reinforcement, divided into three phases. Physiological and behavioral responses to containment routines and facial mask use were meticulously assessed. Principal component analyses revealed dissimilarity patterns among the animals. Animals classified as less reactive showed increased acceptance of handling, reduced reactions to weighing, and greater tolerance of the facial mask. In the final phase, the least reactive animals tolerated wearing a valved mask for extended periods without notable changes in respiratory rate. The training protocol effectively identified and selected Nellore cattle displaying enhanced cooperation with restraint and mask use during flow respirometry assays, without apparent behavioral or physiological alterations. Full article

The COVID-19 pandemic officially started in March 2020 and ended in May 2023. Preventive behaviors have been proven to be one of the most effective strategies for preventing COVID-19 transmission. Common preventive behaviors against COVID-19 include but are not limited to wearing a face mask, washing and sanitizing one’s hands frequently, avoiding crowds, and avoiding traveling. Underserved communities and racial/ethnic minorities across the U.S. have been disproportionately affected by the COVID-19 pandemic. Using a three-wave longitudinal survey conducted from early 2021 to late 2022, the present study investigated changes in the adoption of COVID-19-preventive behaviors among residents living in Delaware’s most underserved communities. We also examined whether changes in COVID-19-preventive behaviors differed by race. Our results indicated that fewer people adopted preventive behaviors as the pandemic progressed, and this finding is applicable to both Black people and White people. However, Black people had a consistently greater likelihood of adopting preventive behaviors compared to White people from early 2021 to late 2022. Scientific and policy implications are discussed. Full article

Deep learning technology can automatically learn features from large amounts of data, with powerful feature extraction and pattern recognition capabilities, thereby improving the accuracy and efficiency of object detection. [The objective of this study]: In order to improve the accuracy and speed of mask wearing deep learning detection models in the post pandemic era, the [Problem this study aimed to resolve] was based on the fact that no research work has been reported on standardized detection models for mask wearing with detecting nose targets specially. [The topic and method of this study]: A mask wearing normalization detection model (towards the wearing style exposing the nose to outside, which is the most obvious characteristic of non-normalized style) based on improved YOLOv5s (You Only Look Once v5s is an object detection network model) was proposed. [The improved method of the proposed model]: The improvement design work of the detection model mainly includes (1) the BottleneckCSP (abbreviation of Bottleneck Cross Stage Partial) module was improved to a BottleneckCSP-MASK (abbreviation of Bottleneck Cross Stage Partial-MASK) module, which was utilized to replace the BottleneckCSP module in the backbone architecture of the original YOLOv5s model, which reduced the weight parameters’ number of the YOLOv5s model while ensuring the feature extraction effect of the bonding fusion module. (2) An SE module was inserted into the proposed improved model, and the bonding fusion layer in the original YOLOv5s model was improved for better extraction of the features of mask and nose targets. [Results and validation]: The experimental results indicated that, towards different people and complex backgrounds, the proposed mask wearing normalization detection model can effectively detect whether people are wearing masks and whether they are wearing masks in a normalized manner. The overall detection accuracy was 99.3% and the average detection speed was 0.014 s/pic. Contrasted with original YOLOv5s, v5m, and v5l models, the detection results for two types of target objects on the test set indicated that the mAP of the improved model increased by 0.5%, 0.49%, and 0.52%, respectively, and the size of the proposed model compressed by 10% compared to original v5s model. The designed model can achieve precise identification for mask wearing behaviors of people, including not wearing a mask, normalized wearing, and wearing a mask non-normalized. Full article

Background: Now that the spread of COVID-19 has been controlled, it is important to investigate changes in young people’s perceptions of the vaccine and their behavior toward infection. The objectives of this study were as follows: (1) to investigate the association between Omicron strain vaccination rates among college students, their perceptions of the vaccine, and past adverse reactions to the vaccine; (2) to compare 2021 (when COVID-19 was spreading) and 2023 (when COVID-19 was strained) to identify changes in attitudes toward vaccination and motivations for vaccination and changes in infection prevention behavior. Methods: This cross-sectional survey was conducted via e-mail from 5 January to 30 January 2023. All students at Hiroshima University were sent an e-mail, which provided them access to the survey form and requested their cooperation. The questionnaire consisted of 33 items related to attributes, vaccination status, adverse reactions after vaccination, motivation for vaccination, perception of the vaccine, presence of coronavirus infection, sequelae, and infection prevention measures. Results: A total of 1083 students responded to the survey. Over 50% of the students were vaccinated with the Omicron booster. Regarding trust in vaccines, the majority of both male and female respondents said they had some trust in vaccines, although this was less than that observed in the 2021 survey. As for infection control measures, only 2% of males and 0.3% of females answered that they did not take any infection control measures. The most common response was “wear a mask”, as in the 2021 survey, with 476 men (96.6%) and 575 women (99.5%). Conclusions: The survey showed a high Omicron-responsive vaccination rate of more than 50%. In addition, more than 99% of the students were found to be taking measures to prevent infection, such as wearing masks. Full article

Objectives: This study aimed to tailor and pilot a health education program using the PRECEDE-PROCEED model to promote vaccination and enhance self-protective behaviors against COVID-19 in Hong Kong populations. Study design: Quasi-experimental study. Methods: Phases 1–4 of the PRECEDE-PROCEED model were used to identify the needs for COVID-19 prevention. Strategies to address predisposing, reinforcing, and enabling factors in the PRECEDE-PROCEED model were developed, and an intervention package was generated thereafter. A pre–post experimental study was conducted among 50 participants to preliminarily assess the effects of the intervention based on Phases 5 and 8 of the PRECEDE-PROCEED model. Results: The 3-month intervention package contained 16 health education videos, 36 health tips, individual consultations, regular reminders of vaccination, incentive of anti-epidemic packages, and vaccine booking services. By the third month, 33 participants took a new dose of COVID-19 vaccine, and 5 participants withdrew. The vaccination rate for new dose achieved 73.3% (95% CI: 58.06–85.40%). Compared with the Hong Kong population in the same period, our study demonstrated higher increase in vaccination rate (9.97 vs. 1.36 doses per 1000 person-days). The percentage of early testing in personal and family level increased to 86.7% and 84.4%, respectively (both p < 0.05). For correct mask wearing and hand washing, the scores increased from a baseline score of 9.1 ± 1.6 and 4.9 ± 1.3 to 9.5 ± 1.0 and 5.3 ± 1.2, respectively (both p < 0.05). Conclusions: The application of the PRECEDE-PROCEED model effectively facilitated the stepwise development, implementation, and evaluation of a health education program for improving vaccination rates and fostering self-protective behaviors against infections. Full article

Drowsiness impairs drivers’ concentration and reaction time, doubling the risk of car accidents. Various methods for detecting drowsy driving have been proposed that rely on facial changes. However, they have poor detection for drivers wearing a mask or sunglasses, and they do not reflect the driver’s drowsiness habits. Therefore, this paper proposes a novel method to detect drowsy driving even with facial detection obstructions, such as masks or sunglasses, and regardless of the driver’s different drowsiness habits, by recognizing behavioral patterns. We achieve this by constructing both normal driving and drowsy driving datasets and developing a 3D-CNN (3D Convolutional Neural Network) model reflecting the Inception structure of GoogleNet. This binary classification model classifies normal driving and drowsy driving videos. Using actual videos captured inside real vehicles, this model achieved a classification accuracy of 85% for detecting drowsy driving without facial obstructions and 75% for detecting drowsy driving when masks and sunglasses are worn. Our results demonstrate that the behavioral pattern recognition method is effective in detecting drowsy driving. Full article

The widespread adoption of face masks has been a crucial strategy in mitigating the spread of infectious diseases, particularly in communal settings. However, ensuring compliance with mask-wearing directives remains a significant challenge due to inconsistencies in usage and the difficulty in monitoring adherence in real time. This paper addresses these challenges by leveraging advanced deep learning techniques within computer vision to develop a real-time mask detection system. We have designed a sophisticated convolutional neural network (CNN) model, trained on a diverse and comprehensive dataset that includes various environmental conditions and mask-wearing behaviors. Our model demonstrates a high degree of accuracy in detecting proper mask usage, thereby significantly enhancing the ability of organizations and public health authorities to enforce mask-wearing rules effectively. The key contributions of this research include the development of a robust real-time monitoring system that can be integrated into existing surveillance infrastructures to improve public health safety measures during ongoing and future health crises. Furthermore, this study lays the groundwork for future advancements in automated compliance monitoring systems, extending their applicability to other areas of public health and safety. Full article

During the COVID-19 pandemic, people exhibited various forms of adjustments. This study examines how situational factors (i.e., the severity of COVID-19) and individual differences (i.e., the HEXACO traits) affect one’s COVID-19-related responses regarding behaviors (i.e., mask-wearing and hoarding), worries (i.e., worrying about infecting and spreading COVID-19), and attitudes (i.e., discrimination and empathy toward people infecting COVID-19) in China. With a sample of 927 participants, our results show that the severity of COVID-19 was predictive of all the responses, and its predictive value was more pronounced relative to personality traits. Concerning the association between personality traits and responses, Honesty-Humility and Conscientiousness were predictive of one’s behaviors, Emotionality was predictive of one’s worries, and almost all the HEXACO traits were associated with one’s attitudes toward people infected with COVID-19. This study sheds some light on understanding how situations and individual differences shape one’s responses in a time of emergency. Full article

Background and Objectives: Before COVID-19 vaccinations became available, adhering to non-pharmaceutical interventions (NPIs), like social distancing (SD), wearing masks, and hand hygiene, were crucial to mitigating viral spread. Many studies reported that younger individuals were more reluctant to follow these measures compared with older ones. We hypothesized that it would be worthwhile to find factors that influenced SD compliance among young people during the pre-vaccination phase of a pandemic. Materials and Methods: We analyzed data of adults aged 19–44 from the 2020 South Korean Community Health Survey and compared socio-demographic, health-related behavioral, and psychological factors between compliant and non-compliant cohorts. Results: A total of 59,943 participants were enrolled and we found that older age groups (30–39 and 40–44) and safety concerns (such as viral infection, virus-related death, economic damage, and transmitting virus to vulnerable people) were significantly associated with adherence to SD. Conversely, participants who were not living with a spouse, were unable to stay at home despite symptoms, smoked, drank, and had a negative attitude toward government policy statistically correlated with non-compliance. Conclusions: In times when NPIs were the primary defense against the pandemic, it is essential to identify factors that positively or negatively affect individual compliance with them, especially among young people. Using a large-scale, well-designed national survey, we could gain insights into the early recognition of risk factors for non-compliance and appropriate follow-up interventions (i.e., education campaigns, clear communication of public guidelines, and implementation of guidelines), which will help people to avoid suffering from other waves of future infectious diseases. Full article

Alexithymia is a clinically relevant personality construct characterized by difficulties identifying and communicating one’s emotions and externally oriented thinking. Alexithymia has been found to be related to poor emotion decoding and diminished attention to the eyes. The present eye tracking study investigated whether high levels of alexithymia are related to impairments in recognizing emotions in masked faces and reduced attentional preference for the eyes. An emotion recognition task with happy, fearful, disgusted, and neutral faces with face masks was administered to high-alexithymic and non-alexithymic individuals. Hit rates, latencies of correct responses, and fixation duration on eyes and face mask were analyzed as a function of group and sex. Alexithymia had no effects on accuracy and speed of emotion recognition. However, alexithymic men showed less attentional preference for the eyes relative to the mask than non-alexithymic men, which was due to their increased attention to face masks. No fixation duration differences were observed between alexithymic and non-alexithymic women. Our data indicate that high levels of alexithymia might not have adverse effects on the efficiency of emotion recognition from faces wearing masks. Future research on gaze behavior during facial emotion recognition in high alexithymia should consider sex as a moderating variable. Full article

Since the outbreak of COVID-19, mask-wearing has become a widespread phenomenon. Even after the pandemic, people continue to maintain the habit of wearing masks in their daily lives. While existing research has explored how mask-wearing can influence wearers’ behavior in everyday life, its effects in the workplace have received less attention. Drawing on self-perception theory, this study examined the positive effect of mask-wearing in the workplace on wearers’ voice behavior via psychological safety. An online experiment (N = 291) using a within-subject manipulation of wearing masks supported our hypotheses. This study uncovered the positive psychological and behavioral consequences of mask-wearing beyond its benefits in people’s health conditions and everyday life. Full article

Although the Japanese government removed mask-wearing requirements in 2023, relatively high rates of mask wearing have continued in Japan. We aimed to assess psychological reasons and the strength of habitual mask wearing in Japan. An Internet-based cross-sectional survey was conducted with non-random participant recruitment. We explored the frequency of mask usage, investigating psychological reasons for wearing masks. A regression analysis examined the association between psychological reasons and the frequency of mask wearing. The habitual use of masks was assessed in the participant’s most frequently visited indoor space and public transport using the self-report habit index. The principal component analysis with varimax rotation revealed distinct habitual characteristics. Among the 2640 participants surveyed from 6 to 9 February 2023, only 4.9% reported not wearing masks at all. Conformity to social norms was the most important reason for masks. Participants exhibited a slightly higher degree of habituation towards mask wearing on public transport compared to indoor spaces. The mask-wearing rate was higher in females than in males, and no significant difference was identified by age group. Daily mask wearing in indoor spaces was characterized by two traits (automaticity and behavioral frequency). A high mask-wearing frequency has been maintained in Japan during the social reopening transition period. Mask wearing has become a part of daily habit, especially on public transport, largely driven by automatic and frequent practice. Full article