Jianjun Su¹, Enxiu Wei¹, Cain Clark², Kaixin Liang³, Xiaojiao Sun^4,*

International Journal of Mental Health Promotion, Vol.24, No.5, pp. 759-769, 2022, DOI:10.32604/ijmhp.2022.020152 - 27 July 2022

Abstract Numerous studies links movement activity (e.g., physical activity, sedentary behavior [SB], and sleep) with mental health or illness indicators during the COVID-19 pandemic; however, research has typically examined time-use behaviors independently, rather than considering daily activity as a 24-hour time-use composition. This cross-sectional study aimed to use compositional isotemporal analysis to estimate the association between reallocation of time-use behaviors and depression symptoms in young adults in China. Participants (n = 1475; 68.0% of female; 20.7 [1.60] years) reported their time spent in moderate to vigorous physical activity (MVPA), light physical activity (LPA), SB, and sleep.… More >

Siti Roshaidai Mohd Arifin^1,*, Siti Mardhiah Saiful Azmi², Khadijah Hasanah Abang Abdullah³, Nurul Ain Hidayah Abas⁴, Rohayah Husain⁵, Edre M. Aidid⁶, Karimah Hanim Abd Aziz⁶, Ramli Musa⁷, Fathima Begum Syed Mohideen³, Asma Perveen⁴, Khairi Che Mat⁵, Izazol Idris⁸

International Journal of Mental Health Promotion, Vol.24, No.5, pp. 749-757, 2022, DOI:10.32604/ijmhp.2022.020972 - 27 July 2022

Abstract During the COVID-19 pandemic, medical and nursing students are faced with various challenges such as the need to attend online classes and juggling clinical postings under the new norm. This study aimed to assess the association between depression, anxiety, and behavioural changes among medical and nursing students during the COVID-19 pandemic. An online self-administered questionnaire was distributed between March 2021 and July 2021 to 292 undergraduates medical and nursing students in a higher education institute on the East Coast of Malaysia. The questionnaires consisted of four parts: sociodemographic data, the Generalised Anxiety Disorder-7, the Patient More >

Zhiyan Xiao¹, Scott Doig², Haowen Wu^3,*, Lei Wang⁴

International Journal of Mental Health Promotion, Vol.24, No.5, pp. 739-747, 2022, DOI:10.32604/ijmhp.2022.019395 - 27 July 2022

Abstract This study aimed to explore associations of sport participation with anxiety and depressive symptoms among Chinese minority adolescents. A cross-sectional study was conducted among Chinese adolescents in Tibet. A convenience sample method was used to select participants. Finally, 1452 students completed the survey and 1421 (52.10% girls, Grades 4–9, 13.46 ± 1.41 years old) adolescents met the inclusion criteria of analysis. Sociodemographic variables, sport participation, depression and anxiety were evaluated by self-reported questionnaires. Among 1421 participants, 80% of adolescents lived in rural area and more than four fifths of participants had siblings. The parent’s education… More >

Ghulam Gilanie¹, Mahmood ul Hassan², Mutyyba Asghar¹, Ali Mustafa Qamar^3,*, Hafeez Ullah⁴, Rehan Ullah Khan⁵, Nida Aslam⁶, Irfan Ullah Khan⁶

CMC-Computers, Materials & Continua, Vol.73, No.2, pp. 2513-2528, 2022, DOI:10.32604/cmc.2022.028229 - 16 June 2022

Abstract Depression is a mental psychological disorder that may cause a physical disorder or lead to death. It is highly impactful on the social-economical life of a person; therefore, its effective and timely detection is needful. Despite speech and gait, facial expressions have valuable clues to depression. This study proposes a depression detection system based on facial expression analysis. Facial features have been used for depression detection using Support Vector Machine (SVM) and Convolutional Neural Network (CNN). We extracted micro-expressions using Facial Action Coding System (FACS) as Action Units (AUs) correlated with the sad, disgust, and More >

Brigita Smolović^1,2, Marija Đurović¹, Miloš Lukić¹, Marija Abramović^2,3, Damir Muhović^1,2,*

International Journal of Mental Health Promotion, Vol.24, No.4, pp. 551-564, 2022, DOI:10.32604/ijmhp.2022.020347 - 27 May 2022

Abstract Throughout its duration, the coronavirus disease 2019 (COVID-19) pandemic has been affecting lives worldwide and has had a sizeable impact on mental health, particularly for those who already suffer from a chronic illnesses. Depression, Anxiety and Stress (DAS) are common psychiatric comorbidities in inflammatory bowel disease (IBD) patients. This study aims to determine the prevalence and risk factors for moderate and severe symptoms of DAS in IBD patients have been undergoing intravenous biological therapy (IvBTh) during the COVID-19 pandemic. The study was conducted between September 1^st and November 30^th, 2020 at the Clinical Center of Montenegro-IBD… More >

Shande Liu^*

International Journal of Mental Health Promotion, Vol.24, No.4, pp. 491-501, 2022, DOI:10.32604/ijmhp.2022.018542 - 27 May 2022

Abstract Purpose: Screen-based sedentary behavior (SSB) has been identified as risk factor for mental disorders in most of adolescents. However, there is little literature pertaining to the specific kinds of SSB and its connections with depressive symptoms in most of adolescents. In the present study, we are going to find out the connections between specific types of SSB and depressive symptoms in Chinese adolescents. Methods: A cross-sectional data based on 996 study participants of middle school students in Guangdong Province. SSB was evaluated by distributing the questionnaire of Health Behavior in School-aged Children, while depressive symptoms were… More >

R. Meena^1,*, V. Thulasi Bai²

Intelligent Automation & Soft Computing, Vol.34, No.3, pp. 1643-1658, 2022, DOI:10.32604/iasc.2022.025305 - 25 May 2022

Abstract The Covid-19 outbreak has an unprecedented effects on people's daily lives throughout the world, causing immense stress amongst individuals owing to enhanced psychological disorders like depression, stress, and anxiety. Researchers have used social media data to detect behaviour changes in individuals with depression, postpartum changes and stress detection since it reveals critical aspects of mental and emotional diseases. Considerable efforts have been made to examine the psychological health of people which have limited performance in accuracy and demand increased training time. To conquer such issues, this paper proposes an efficient depression detection framework named Improved… More >

Elias Hossain¹, Abdulwahab Alazeb^2,*, Naif Al Mudawi², Sultan Almakdi², Mohammed Alshehri², M. Gazi Golam Faruque³, Wahidur Rahman³

CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 4945-4966, 2022, DOI:10.32604/cmc.2022.027058 - 21 April 2022

Abstract Depression is a crippling affliction and affects millions of individuals around the world. In general, the physicians screen patients for mental health disorders on a regular basis and treat patients in collaboration with psychologists and other mental health experts, which results in lower costs and improved patient outcomes. However, this strategy can necessitate a lot of buy-in from a large number of people, as well as additional training and logistical considerations. Thus, utilizing the machine learning algorithms, patients with depression based on information generally present in a medical file were analyzed and predicted. The methodology… More >

Maqsood Ahmad^1,2, Noorhaniza Wahid¹, Rahayu A Hamid¹, Saima Sadiq², Arif Mehmood³, Gyu Sang Choi^4,*

CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 5041-5058, 2022, DOI:10.32604/cmc.2022.026077 - 21 April 2022

Abstract Mental health signifies the emotional, social, and psychological well-being of a person. It also affects the way of thinking, feeling, and situation handling of a person. Stable mental health helps in working with full potential in all stages of life from childhood to adulthood therefore it is of significant importance to find out the onset of the mental disease in order to maintain balance in life. Mental health problems are rising globally and constituting a burden on healthcare systems. Early diagnosis can help the professionals in the treatment that may lead to complications if they… More >

Ankur Dumka¹, Parag Verma², Rajesh Singh³, Anil Kumar Bisht⁴, Divya Anand^5,6,*, Hani Moaiteq Aljahdali⁷, Irene Delgado Noya^6,8, Silvia Aparicio Obregon^6,9

CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 6029-6044, 2022, DOI:10.32604/cmc.2022.024698 - 21 April 2022

Abstract Coronavirus (COVID-19) has impacted nearly every person across the globe either in terms of losses of life or as of lockdown. The current coronavirus (COVID-19) pandemic is a rare/special situation where people can express their feelings on Internet-based social networks. Social media is emerging as the biggest platform in recent years where people spend most of their time expressing themselves and their emotions. This research is based on gathering data from Twitter and analyzing the behavior of the people during the COVID-19 lockdown. The research is based on the logic expressed by people in this… More >