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  • Open Access

    ARTICLE

    The COVID-19 Pandemic: A Double Threat to Chinese Americans’ Mental Health

    Aoli Li1,#, Yan You1,2,#, Kunli Wu3, Huibin Shan4, Younglee Kim5, Qilian He1,*

    International Journal of Mental Health Promotion, Vol.25, No.6, pp. 783-797, 2023, DOI:10.32604/ijmhp.2023.026956

    Abstract Objective: To explore the double psychosocial threats of the COVID-19 pandemic, targeted behavior toward Chinese Americans, and the correlates to their mental health. Methods: A quantitative, cross-sectional, and descriptive design was utilized by using a purposive convenience sample of 301 Chinese Americans over the age of 18 residing in the United States. Online data collection was conducted through the social media platform WeChat from April 8–21, 2021. Descriptive statistical analysis was used for the participants’ demographic characteristics, Multidimensional Scale of Perceived Social Support (MSPSS), Double Threat Situations, COVID-19 Racial Discrimination, and General Anxiety Disorder-7 (GAD-7). Stepwise logistic… More > Graphic Abstract

    The COVID-19 Pandemic: A Double Threat to Chinese Americans’ Mental Health

  • Open Access

    ARTICLE

    Ensemble Deep Learning Framework for Situational Aspects-Based Annotation and Classification of International Student’s Tweets during COVID-19

    Shabir Hussain1, Muhammad Ayoub2, Yang Yu1, Junaid Abdul Wahid1, Akmal Khan3, Dietmar P. F. Moller4, Hou Weiyan1,*

    CMC-Computers, Materials & Continua, Vol.75, No.3, pp. 5355-5377, 2023, DOI:10.32604/cmc.2023.036779

    Abstract As the COVID-19 pandemic swept the globe, social media platforms became an essential source of information and communication for many. International students, particularly, turned to Twitter to express their struggles and hardships during this difficult time. To better understand the sentiments and experiences of these international students, we developed the Situational Aspect-Based Annotation and Classification (SABAC) text mining framework. This framework uses a three-layer approach, combining baseline Deep Learning (DL) models with Machine Learning (ML) models as meta-classifiers to accurately predict the sentiments and aspects expressed in tweets from our collected Student-COVID-19 dataset. Using the… More >

  • Open Access

    ARTICLE

    Sine Cosine Optimization with Deep Learning-Based Applied Linguistics for Sentiment Analysis on COVID-19 Tweets

    Abdelwahed Motwakel1,*, Hala J. Alshahrani2, Abdulkhaleq Q. A. Hassan3, Khaled Tarmissi4, Amal S. Mehanna5, Ishfaq Yaseen1, Amgad Atta Abdelmageed1, Mohammad Mahzari6

    CMC-Computers, Materials & Continua, Vol.75, No.3, pp. 4767-4783, 2023, DOI:10.32604/cmc.2023.034840

    Abstract Applied linguistics is an interdisciplinary domain which identifies, investigates, and offers solutions to language-related real-life problems. The new coronavirus disease, otherwise known as Coronavirus disease (COVID-19), has severely affected the everyday life of people all over the world. Specifically, since there is insufficient access to vaccines and no straight or reliable treatment for coronavirus infection, the country has initiated the appropriate preventive measures (like lockdown, physical separation, and masking) for combating this extremely transmittable disease. So, individuals spent more time on online social media platforms (i.e., Twitter, Facebook, Instagram, LinkedIn, and Reddit) and expressed their… More >

  • Open Access

    ARTICLE

    Extension of Goal-Directed Behavior Model for Post-Pandemic Korean Travel Intentions to Alternative Local Destinations: Perceived Risk and Knowledge

    Heesup Han1, Hong Ngoc Nguyen2, Hyerin Lee3, Sanghyeop Lee4,*

    International Journal of Mental Health Promotion, Vol.25, No.4, pp. 449-469, 2023, DOI:10.32604/ijmhp.2023.025379

    Abstract Since the outbreak of COVID-19, tourists have been increasingly concerned over various risks of international travel, while knowledge of the pandemic appears to vary significantly. In addition, as travel restrictions continue to impact adversely on international tourism, tourism efforts should be placed more on the domestic markets. Via structural equation modeling, this study unearthed different risk factors impacting Korean travelers’ choices of alternative local destinations in the post-pandemic era. In addition, this study extended the goal-directed behavior framework with the acquisition of perceived risk and knowledge of COVID-19, which was proven to hold a significantly More >

  • Open Access

    ARTICLE

    Short-Term Mindfulness Intervention on Adolescents’ Negative Emotion under Global Pandemic

    Yue Yuan1,*, Aibao Zhou1,*, Tinghao Tang1, Manying Kang2, Haiyan Zhao1, Zhi Wang3

    International Journal of Mental Health Promotion, Vol.25, No.4, pp. 563-577, 2023, DOI:10.32604/ijmhp.2023.022161

    Abstract Objective: In this research, we tried to explore how short-term mindfulness (STM) intervention affects adolescents’ anxiety, depression, and negative and positive emotion during the COVID-19 pandemic. Design: 10 classes were divided into experiment groups (5 classes; n = 238) and control (5 classes; n = 244) randomly. Hospital Anxiety and Depression Scale (HADS) and Positive and Negative Affect Schedule (PANAS) were used to measure participants’ dependent variables. In the experiment group, we conducted STM practice interventions every morning in their first class from March to November 2020. No interventions were conducted in the control group. Methods: Paired-sample t-tests were used to identify… More >

  • Open Access

    ARTICLE

    The Impact of COVID-19 on the Mental-Emotional Wellbeing of Primary Healthcare Professionals: A Descriptive Correlational Study

    Regina Lai-Tong Lee1,2,*, Anson Chiu-Yan Tang3, Ho-Yu Cheng1, Connie Yuen-Yu Chong1, Wilson Wai-San Tam4, Wai-Tong Chien1, Sally Wai-Chi Chan5

    International Journal of Mental Health Promotion, Vol.25, No.3, pp. 327-342, 2023, DOI:10.32604/ijmhp.2022.026388

    Abstract The present study aimed to examine work environment related factors and frontline primary healthcare professionals’ mental-emotional wellbeing during the COVID-19 pandemic in school communities of Hong Kong. A total of 61 (20%) school health nurses (frontline primary healthcare professionals) participated in a cross-sectional online survey from March to June 2020. Outcomes of mental-emotional health were measured using the Mental Health Continuum-Short Form (14-item scale with three subscales related to emotional, social and psychological wellbeing); the Perceived Stress Scale (10-item scale with two subscales related to perceived helplessness and lack of self-efficacy; and the Coping Orientation… More >

  • Open Access

    ARTICLE

    Deep Learning Based Face Mask Detection in Religious Mass Gathering During COVID-19 Pandemic

    Abdullah S. AL-Malaise AL-Ghamdi1,2,3, Sultanah M. Alshammari3,4, Mahmoud Ragab3,5,6,*

    Computer Systems Science and Engineering, Vol.46, No.2, pp. 1863-1877, 2023, DOI:10.32604/csse.2023.035869

    Abstract Notwithstanding the religious intention of billions of devotees, the religious mass gathering increased major public health concerns since it likely became a huge super spreading event for the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Most attendees ignored preventive measures, namely maintaining physical distance, practising hand hygiene, and wearing facemasks. Wearing a face mask in public areas protects people from spreading COVID-19. Artificial intelligence (AI) based on deep learning (DL) and machine learning (ML) could assist in fighting covid-19 in several ways. This study introduces a new deep learning-based Face Mask Detection in Religious Mass… More >

  • Open Access

    ARTICLE

    Effect of Family Cohesion on Depression of Chinese College Students in the COVID-19 Pandemic: Chain Mediation Effect of Perceived Social Support and Intentional Self-Regulation

    Jingjing Wang1, Xiangli Guan1,*, Yue Zhang2, Yang Li1, Md Zahir Ahmed3, Mary C. Jobe4, Oli Ahmed5

    International Journal of Mental Health Promotion, Vol.25, No.2, pp. 223-235, 2023, DOI:10.32604/ijmhp.2022.025570

    Abstract Individuals’ perceptions, attitudes, and patterns of getting along with family members are important factors influencing Chinese people’s self-evaluation. The aim of this study was to investigate the effect of family cohesion on depression and the role of perceived social support and intentional self-regulation in this association. A hypothesized model of the association of family cohesion, perceived social support, intentional self-regulation, and depression was examined. A convenience sampling method was used to survey 1,180 college students in Yunnan Province using self-report. Data were collected using the Family Cohesion Scale, the Perceived Social Support Scale, the Intentional More >

  • Open Access

    ARTICLE

    Development of Pandemic Monitoring System Based on Constellation of Nanosatellites

    Omar Ben Bahri*, Abdullah Alhumaidi Alotaibi

    Computer Systems Science and Engineering, Vol.46, No.1, pp. 1249-1263, 2023, DOI:10.32604/csse.2023.032677

    Abstract Covid-19 is a global crisis and the greatest challenge we have faced. It affects people in different ways. Most infected people develop a mild to moderate form of the disease and recover without hospitalization. This presents a problem in spreading the pandemic with unintentionally manner. Thus, this paper provides a new technique for COVID-19 monitoring remotely and in wide range. The system is based on satellite technology that provides a pivotal solution for wireless monitoring. This mission requires a data collection technique which can be based on drones’ technology. Therefore, the main objective of our More >

  • Open Access

    ARTICLE

    Optimization of Coronavirus Pandemic Model Through Artificial Intelligence

    Manal. M. Alqarni1, Arooj Nasir2,3, Dumitru Baleanu4,5,6, Ali Raza7, Tahir Nawaz Cheema8,*, Nauman Ahmed9, Muhammad Rafiq10, Umbreen Fatima11, Emad E. Mahmoud12

    CMC-Computers, Materials & Continua, Vol.74, No.3, pp. 6807-6822, 2023, DOI:10.32604/cmc.2023.033283

    Abstract Artificial intelligence is demonstrated by machines, unlike the natural intelligence displayed by animals, including humans. Artificial intelligence research has been defined as the field of study of intelligent agents, which refers to any system that perceives its environment and takes actions that maximize its chance of achieving its goals. The techniques of intelligent computing solve many applications of mathematical modeling. The research work was designed via a particular method of artificial neural networks to solve the mathematical model of coronavirus. The representation of the mathematical model is made via systems of nonlinear ordinary differential equations.… More >

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