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  • Open Access


    Machine Learning Based Depression, Anxiety, and Stress Predictive Model During COVID-19 Crisis

    Fahd N. Al-Wesabi1,2,*, Hadeel Alsolai3, Anwer Mustafa Hilal4, Manar Ahmed Hamza4, Mesfer Al Duhayyim5, Noha Negm6,7

    CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 5803-5820, 2022, DOI:10.32604/cmc.2022.021195

    Abstract Corona Virus Disease-2019 (COVID-19) was reported at first in Wuhan city, China by December 2019. World Health Organization (WHO) declared COVID-19 as a pandemic i.e., global health crisis on March 11, 2020. The outbreak of COVID-19 pandemic and subsequent lockdowns to curb the spread, not only affected the economic status of a number of countries, but it also resulted in increased levels of Depression, Anxiety, and Stress (DAS) among people. Therefore, there is a need exists to comprehend the relationship among psycho-social factors in a country that is hypothetically affected by high levels of stress and fear; with tremendously-limiting measures… More >

  • Open Access


    Generalized Anxiety and Major Depressive Symptoms of General Public in South Korea during the Early COVID-19 Pandemic

    Kye S. Kim1, Peter M. Kang1, He Sook N. Kim2,*

    International Journal of Mental Health Promotion, Vol.23, No.3, pp. 303-317, 2021, DOI:10.32604/IJMHP.2021.016470

    Abstract The extent of viral spread and strategies in dealing with the COVID-19 pandemic have been different in each country. There are overall increased mental health concerns in many countries but it is unclear what the general public individuals who do not have heighten vulnerability to stressors for existing mental diseases or significant physical illnesses were experiencing during the pandemic. We evaluated the stressors and mental health of general public in South Korea that has a relatively low confirmed cases and deaths. Responses on the on-line survey questions were used to assess the mental and physical symptoms in association with individuals’… More >

  • Open Access


    Development of Mental Health Literacy Scale for Depression Affecting the Help-Seeking Process in Health Professional Students

    Soshi Kodama1,*, Koichi Shido2, Nozomu Ikeda3

    International Journal of Mental Health Promotion, Vol.23, No.3, pp. 331-352, 2021, DOI:10.32604/IJMHP.2021.016337

    Abstract Despite depression being a global mental health disorder, many people with depression do not seek psychiatric help. In particular, it has been reported that only 15.7% of medical students seek treatment. A longer duration of untreated illness (DUI) leads to clinically poor results. To shorten the DUI, the mental health literacy (MHL) with regard to depression needs to be improved, although it is unclear which MHL components will improve the help-seeking process. Additionally, the existing MHL scale for depression is poorly validated for structural validity. Therefore, the purpose of this study was to develop an MHL scale for depression with… More >

  • Open Access


    Association between Active School Travel and Depressive Symptoms among 51,702 Adolescents in 26 Low- and Middle-Income Countries

    Shuan Liu1, Sitong Chen2, Xiaohong Zhu3, Brendon Stubbs4, Qian Yu5, Mark D. Griffiths6, Can Jiao7, Aiguo Chen8, Md Mahbub Hossain9, Zsolt Demetrovics10,11, Albert S. Yeung12, Jinming Li5, Xingyu Zhang5, Liye Zou5,*

    International Journal of Mental Health Promotion, Vol.23, No.2, pp. 141-153, 2021, DOI:10.32604/IJMHP.2021.016274

    Abstract Little is known about the role of active school travel (AST) on mental health among adolescents. Thus, this study aimed to explore the AST-depression association among adolescents aged 12–15 years from 26 low- and middleincome countries (LMICs). Data from the Global School-based Student Health Survey were analyzed in 51,702 adolescents [mean (SD) age 13.8 (1.0) years; 49.3% boys). Both depressive symptoms and AST were assessed by a single question self-reported measure, respectively. Participants who reported having 5 days or above were considered as AST. Multivariable logistic regression analysis (accounting for sampling weights) was performed while controlling for gender, age, physical… More >

  • Open Access


    Muscle-Strengthening Exercise Links with Lower Odds for Depression in Adolescents

    Weijun Yu1,2, Jiangang Sun3, Ying Wu1,*, Si-Tong Chen4

    International Journal of Mental Health Promotion, Vol.23, No.2, pp. 277-288, 2021, DOI:10.32604/IJMHP.2021.016153

    Abstract Purpose: Physical activity is a well-recognized protective factor against depression in adolescents. As a component of physical activity, muscle strengthening exercise (MSE) is also viewed as a correlate associated with lower risks of depression in adults. However, little is known about the association in adolescents. This study aimed to explore the association between MSE and depression in a sample of Chinese adolescents. Method: A self-reported questionnaire was used for data collection including variables of MSE, depression (assessed by Children’s Depression Inventory) and selected sociodemographic factors (e.g., sex, grade, height and weight [for body mass index]). Generalized Linear Models was utilized… More >

  • Open Access


    Unpacking the Associations between Traumatic Events and Depression among Chinese Elderly: Two Dimensions of Aging Attitudes as Mediators and Moderators

    Chaoxin Jiang*

    International Journal of Mental Health Promotion, Vol.23, No.2, pp. 231-242, 2021, DOI:10.32604/IJMHP.2021.015253

    Abstract Traumatic events have been considered significant risk factors for older adults’ mental health, but the mediating mechanism and moderating effect of aging attitudes that underlie this relationship have yet been completely investigated. The attitudes of the elderly toward aging can be divided into two closely related but conceptually different dimensions, including positive and negative. Positive aging attitudes refer to optimistic feelings and experiences about aging, whereas negative attitudes toward aging are related to detrimental thoughts and sensations experienced about the increasing age. The purpose of this study is to explore the mediating and moderating roles of these two dimensions of… More >

  • Open Access


    Effects of Stress, Depression, and Problem Drinking on Suicidal Ideation among Korean Workers

    Yun-Jung Choi1,#, Mi-ra Won2,#,*, Youn-Joo Um3,*

    International Journal of Mental Health Promotion, Vol.23, No.2, pp. 189-199, 2021, DOI:10.32604/IJMHP.2021.015095

    Abstract The mental health of workers is an important issue that affects not only individuals and their families but also workplaces and communities. Therefore, it is necessary to regularly evaluate and analyze workers’ mental health status, including levels of stress, depression, and addictive behaviors to apply these findings in creating mental health promotion programs. This study aims to provide basic data that would facilitate early intervention for workers’ mental health problems by analyzing factors such as stress, depression, and problem drinking that can affect suicidal ideation. From April 15 to October 25, 2019, a survey was conducted with 165 workers across… More >

  • Open Access


    Acceptability and Feasibility of YouthCHAT to Detect Psychosocial Problems in Young People with Congenital Heart Disease

    Hiran Thabrew1,*, Harshali Kumar1, Vanessa Garcia-Hoyos2, Felicity Goodyear-Smith3

    International Journal of Mental Health Promotion, Vol.23, No.2, pp. 221-230, 2021, DOI:10.32604/IJMHP.2021.015033

    Abstract Objective: Young people with congenital heart disease (CHD) are at increased risk of psychosocial issues, including anxiety and depression that can affect their medical care and quality of life. This open trial investigated the acceptability, feasibility and preliminary effectiveness of YouthCHAT, a tablet-based screener, designed to identify similar issues to a face to face psychosocial assessment, with young people who have CHD. Methods: YouthCHAT was administered to 44 such young people aged 15–25 years attending a specialist outpatient clinic at a New Zealand tertiary hospital. Key outcomes were (i) acceptability and (ii) feasibility of YouthCHAT, assessed via feedback from young… More >

  • Open Access


    Mental Health Impacts of Information and Communication Technology Usage in South Africa

    Akinboade Oludele Akinloye1,*, Obareng Baldwin Manoko2, Mmafani Serote2, Trevor Taft3

    International Journal of Mental Health Promotion, Vol.23, No.2, pp. 255-276, 2021, DOI:10.32604/IJMHP.2021.011111

    Abstract This study examined mental health issues affecting the group of individuals who are in the social media contact list of the researchers. This was done by administering a closed structured questionnaire, covering information from participants’ demographic characteristics, duration of time spent on ICT usage, to their perceived health effects thereof. Male respondents, largely unemployed are active ICT users, addicted to the Internet, and also suffer from unspecified ailments. Aged 31–35 and above, half of men and all women participants spend more than 5 h per day. High-intensive ICT use is associated, in general, with concurrent symptoms of information overload, depression… More >

  • Open Access


    Automatic Sleep Staging Based on EEG-EOG Signals for Depression Detection

    Jiahui Pan1,6,*, Jianhao Zhang1, Fei Wang1,6, Wuhan Liu2, Haiyun Huang3,6, Weishun Tang3, Huijian Liao4, Man Li5, Jianhui Wu1, Xueli Li2, Dongming Quan2, Yuanqing Li3,6

    Intelligent Automation & Soft Computing, Vol.28, No.1, pp. 53-71, 2021, DOI:10.32604/iasc.2021.015970

    Abstract In this paper, an automatic sleep scoring system based on electroencephalogram (EEG) and electrooculogram (EOG) signals was proposed for sleep stage classification and depression detection. Our automatic sleep stage classification method contained preprocessing based on independent component analysis, feature extraction including spectral features, spectral edge frequency features, absolute spectral power, statistical features, Hjorth features, maximum-minimum distance and energy features, and a modified ReliefF feature selection. Finally, a support vector machine was employed to classify four states (awake, light sleep [LS], slow-wave sleep [SWS] and rapid eye movement [REM]). The overall accuracy of the Sleep-EDF database reached 90.10 ± 2.68% with… More >

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