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  • Open Access

    ARTICLE

    Do Public Health Events Promote the Prevalence of Adjustment Disorder in College Students? An Example from the COVID-19 Pandemic

    Rong Fu*, Luze Xie

    International Journal of Mental Health Promotion, Vol.26, No.1, pp. 21-30, 2024, DOI:10.32604/ijmhp.2023.041730

    Abstract COVID-19, as one of the most serious sudden public health problems in this century, is a serious threat to people’s mental health. College students, as a vulnerable group, are more likely to develop mental health problems. When the body is unable to adapt to new changes in the environment, the main mental health problem that arises is adjustment disorder. The aim of this study was to assess the prevalence and influencing factors of adjustment disorder among college students during the COVID-19 outbreak in China. Cross-sectional data collected by web-based questionnaires were obtained through convenience sampling and snowball sampling between March… More >

  • Open Access

    ARTICLE

    Effect of Online Social Networking on Emotional Status and Its Interaction with Offline Reality during the Early Stage of the COVID-19 Pandemic in China

    Xiaolin Lu1,*, Xiaolei Miao2

    International Journal of Mental Health Promotion, Vol.25, No.9, pp. 1041-1052, 2023, DOI:10.32604/ijmhp.2023.030232

    Abstract Background: During the early stages of the COVID-19 pandemic in China, social interactions shifted to online spaces due to lock-downs and social distancing measures. As a result, the impact of online social networking on users’ emotional status has become stronger than ever. This study examines the association between online social networking and Internet users’ emotional status and how offline reality affects this relationship. Methods: The study utilizes cross-sectional online survey data (n = 3004) and Baidu Migration big data from the first 3 months of the pandemic. Two dimensions of online networking are measured: social support and information sources. Results:More > Graphic Abstract

    Effect of Online Social Networking on Emotional Status and Its Interaction with Offline Reality during the Early Stage of the COVID-19 Pandemic in China

  • Open Access

    ARTICLE

    Impact of COVID-19 Pandemic on Mental Health of Healthcare Workers–A Perception of Indian Hospital Administrators

    Anahita Ali*, Santosh Kumar

    International Journal of Mental Health Promotion, Vol.25, No.7, pp. 833-845, 2023, DOI:10.32604/ijmhp.2023.028799

    Abstract Since the coronavirus pandemic, many factors led to the change in the mental well-being of hospital administrators and their staff. The pandemic negatively impacted the availability and capability of health professionals to deliver essential services and meet rising demand. Therefore, this study aimed to understand the perspective of hospital administrators about issues and challenges that negatively impacted their staff’s mental health and hospital administrators’ coping response to mitigate those challenges and issues. An exploratory qualitative study was conducted with 17 hospital administrators (superintendents, deputy superintendents, nursing in charge and hospital in charge) working in a government district hospital of Rajasthan… More > Graphic Abstract

    Impact of COVID-19 Pandemic on Mental Health of Healthcare Workers–A Perception of Indian Hospital Administrators

  • 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 regression was conducted… 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 proposed aspect2class annotation algorithm, we… 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 thoughts and feelings about coronavirus… 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 to Problems Experienced Inventory (Brief… 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 Gathering (DLFMD-RMG) technique during the… 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 Self-Regulation Scale, and the Center… More >

  • Open Access

    ARTICLE

    The Early Emotional Responses and Central Issues of People in the Epicenter of the COVID-19 Pandemic: An Analysis from Twitter Text Mining

    Eun-Joo Choi1, Yun-Jung Choi2,*

    International Journal of Mental Health Promotion, Vol.25, No.1, pp. 21-29, 2023, DOI:10.32604/ijmhp.2022.022641

    Abstract This study aimed to explore citizens’ emotional responses and issues of interest in the context of the coronavirus disease 2019 (COVID-19) pandemic. The dataset comprised 65,313 tweets with the location marked as New York State. The data collection period was four days of tweets when New York City imposed a lockdown order due to an increase in confirmed cases. Data analysis was performed using R Studio. The emotional responses in tweets were analyzed using the Bing and NRC (National Research Council Canada) dictionaries. The tweets’ central issue was identified by Text Network Analysis. When tweets were classified as either positive… More > Graphic Abstract

    The Early Emotional Responses and Central Issues of People in the Epicenter of the COVID-19 Pandemic: An Analysis from Twitter Text Mining

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