Yun-Jung Choi^1,#,*, Jae-Won Kwak^2,#, Hae-In Namgung³

International Journal of Mental Health Promotion, Vol.26, No.6, pp. 439-447, 2024, DOI:10.32604/ijmhp.2024.050458

Abstract This study evaluated the state of anxiety, depression, post-traumatic stress disorder, general mental health, and mental well-being among citizens after a crowd-crush disaster in Korea. Individuals who experienced the crowd crush had significantly higher anxiety, depression, and post-traumatic stress disorder (PTSD) scores than those who did not (p < 0.001). Additionally, people who avoided the disaster area had significantly higher depression and PTSD scores than those who did not avoid the area (p < 0.001). Those who directly witnessed the Seoul Halloween crowd crush had a significant difference in PTSD levels in either group than those More >

Na Liu¹, Yan Zhang², Junxiu Wang^3,4,*

International Journal of Mental Health Promotion, Vol.26, No.6, pp. 449-462, 2024, DOI:10.32604/ijmhp.2024.049334

Abstract Background: In the current social environment, scarcity, as a universally present objective state, profoundly impacts individuals’ decision-making and health through the subjective feeling it induces, known as a “scarcity mindset.” Particularly, the feeling of scarcity related to money and sleep time is not only widespread but also directly linked to an individual’s mental health. Purpose: This study aims to delve into the relationship between the feeling of scarcity and mental health, with a specific focus on the relationship between the feeling of money scarcity or sleep time scarcity and mental health, as well as the… More >

Jingjing Nie^1,*, Zhenhua Chen²

CMC-Computers, Materials & Continua, Vol.79, No.3, pp. 4763-4779, 2024, DOI:10.32604/cmc.2024.051181

Abstract The Internet of Medical Things (IoMT) is an application of the Internet of Things (IoT) in the medical field. It is a cutting-edge technique that connects medical sensors and their applications to healthcare systems, which is essential in smart healthcare. However, Personal Health Records (PHRs) are normally kept in public cloud servers controlled by IoMT service providers, so privacy and security incidents may be frequent. Fortunately, Searchable Encryption (SE), which can be used to execute queries on encrypted data, can address the issue above. Nevertheless, most existing SE schemes cannot solve the vector dominance threshold… More >

YUANYUAN LIAO^1,2,3, XINSI LI^2,3, QIAN LI^2,3, YIZHONG WANG⁴, XIUJUN TAN^1,2,3, TING GONG^2,3,5,*

BIOCELL, Vol.48, No.6, pp. 873-887, 2024, DOI:10.32604/biocell.2024.050324

Abstract As we are facing an aging society, anti-aging strategies have been pursued to reduce the negative impacts of aging and increase the health span of human beings. Gut microbiota has become a key factor in the anti-aging process. Modulation of gut microbiota by fecal microbiota transplantation (FMT) to prevent frailty and unhealthy aging has been a hot topic of research. This narrative review summarizes the benefits of FMT for health span and lifespan, brains, eyes, productive systems, bones, and others. The mechanisms of FMT in improving healthy aging are discussed. The increased beneficial bacteria and More >

Yanjie Zhang^1,2, Jin Kuang³, Xun Luo^1,2, Mengxian Zhao⁴, Xiaolei Liu^5,*

International Journal of Mental Health Promotion, Vol.26, No.5, pp. 399-406, 2024, DOI:10.32604/ijmhp.2024.048925

Abstract Background: Emerging adulthood is a pivotal life stage, presenting significant psychological and social changes, such as decreased sociability, depression, and other mental health problems. Previous studies have associated these changes with an unhealthy lifestyle. The 24-h movement guidelines for healthy lifestyles have been developed to promote appropriate health behaviors and improve individual wellness. However, the relationship between adherence to the 24-h movement guidelines and different characteristics of Chinese emerging adults is yet to be explored. This cross-sectional study aimed to investigate the association between adherence to the 24-h movement guidelines and four characteristics (self-exploration, instability, possibilities,… More >

Abdullah A. Alharbi¹, Ahmad Y. Alqassim^1,*, Mohammed A. Muaddi¹, Najat H. Aldubayyan¹, Rana I. Abuhadi¹, Futon A. Akoor¹, Sarah J. Mobarki¹, Imtenan A. Oberi¹, Ghaidaa H. Alharbi¹, Yara Ajeebi¹, Adnan M. Alkhayat², Hafiz Malhan³, Mohammed Bakkar⁴, Anwar M. Makeen¹

International Journal of Mental Health Promotion, Vol.26, No.5, pp. 351-359, 2024, DOI:10.32604/ijmhp.2024.047219

Abstract Sickle Cell Anemia (SCA) is a prevalent genetic condition in Saudi Arabia, particularly in the Jazan region. The study’s purpose was to assess the prevalence of de-pression among individuals with SCA in this area and to identify the factors associated with this condition. The study involved 391 adult participants, all patients in the hematology center of Prince Mohammed bin Nasser Hospital (PMNH). Data was collected through an anonymous interview questionnaire–the Arabic version of the Patient Health Questionnaire-9 (PHQ-9)–between March–May 2022. The questionnaire covered socio-demographic information and variables related to the participant’s SCA history, such as… More >

Pakorn Santakij¹, Samai Srisuay^2,*, Pongporn Punpeng¹

Computer Systems Science and Engineering, Vol.48, No.3, pp. 665-689, 2024, DOI:10.32604/csse.2024.045066

Abstract Social media has revolutionized the dissemination of real-life information, serving as a robust platform for sharing life events. Twitter, characterized by its brevity and continuous flow of posts, has emerged as a crucial source for public health surveillance, offering valuable insights into public reactions during the COVID-19 pandemic. This study aims to leverage a range of machine learning techniques to extract pivotal themes and facilitate text classification on a dataset of COVID-19 outbreak-related tweets. Diverse topic modeling approaches have been employed to extract pertinent themes and subsequently form a dataset for training text classification models.… More >

Dominique Vervoort^1,2,3,*, Amy Verstappen³, Sreehari Madhavankutty Nair⁴, Chong Chin Eu⁵, Bistra Zheleva^3,6

Congenital Heart Disease, Vol.19, No.2, pp. 131-138, 2024, DOI:10.32604/chd.2024.049814

Abstract This article has no abstract. More >

Moshe Dayan Sirapangi¹, S. Gopikrishnan^1,*

CMC-Computers, Materials & Continua, Vol.79, No.2, pp. 2229-2251, 2024, DOI:10.32604/cmc.2024.047438

Abstract Medical Internet of Things (IoT) devices are becoming more and more common in healthcare. This has created a huge need for advanced predictive health modeling strategies that can make good use of the growing amount of multimodal data to find potential health risks early and help individuals in a personalized way. Existing methods, while useful, have limitations in predictive accuracy, delay, personalization, and user interpretability, requiring a more comprehensive and efficient approach to harness modern medical IoT devices. MAIPFE is a multimodal approach integrating pre-emptive analysis, personalized feature selection, and explainable AI for real-time health… More >

Umi Salma Basha¹, Shashi Kant Gupta², Wedad Alawad³, SeongKi Kim^4,*, Salil Bharany^5,*

CMC-Computers, Materials & Continua, Vol.79, No.2, pp. 3397-3416, 2024, DOI:10.32604/cmc.2024.046265

Abstract A new era of data access and management has begun with the use of cloud computing in the healthcare industry. Despite the efficiency and scalability that the cloud provides, the security of private patient data is still a major concern. Encryption, network security, and adherence to data protection laws are key to ensuring the confidentiality and integrity of healthcare data in the cloud. The computational overhead of encryption technologies could lead to delays in data access and processing rates. To address these challenges, we introduced the Enhanced Parallel Multi-Key Encryption Algorithm (EPM-KEA), aiming to bolster… More >