Yan Jin, Wei Chen^*

International Journal of Mental Health Promotion, Vol.26, No.3, pp. 189-198, 2024, DOI:10.32604/ijmhp.2023.045331

Abstract An authoritative parenting style has been shown to promote children’s emotion regulation in European-American family studies. However, little is known about how sleep problems and the child’s sibling status in Chinese families affect this relationship. Based on family system theory, this study attempts to better understand the relationship between authoritative parenting style and emotion regulation. Mothers of preschool children in Chinese kindergartens completed questionnaires about their children’s sleep habits, their authoritative parenting styles, and children’s emotion regulation. A total of 531 children participated in this study. Results showed that authoritative parenting was positively associated with emotional regulation. Sleep problems mediated… More >

Xinqiao Liu^*, Linxin Zhang, Xinran Zhang

International Journal of Mental Health Promotion, Vol.26, No.2, pp. 105-116, 2024, DOI:10.32604/ijmhp.2023.042359

Abstract Under the effects of COVID-19 and a number of ongoing lockdown tactics, anxiety symptoms and poor sleep quality have become common mental health issues among college freshmen and are intimately related to their emotional adaptation. To explore this connection, this study gathered data from a sample of 256 freshmen enrolled in an elite university in China in September 2022. The association between sleep quality, anxiety symptoms, and emotional adaptation was clarified using correlation analysis. Additionally, the mediating function of anxiety symptoms between sleep quality and emotional adaptation was investigated using a structural equation model. The results reveal that: (1) Chinese… More >

Eun Kyoung Han, Hae Kyoung Son^*

International Journal of Mental Health Promotion, Vol.25, No.11, pp. 1197-1208, 2023, DOI:10.32604/ijmhp.2023.041560

Abstract Dementia prevalence has soared due to population aging. In Mild Cognitive Impairment (MCI) as a pre-dementia stage, sleep disturbances have raised much interest as a factor in a bidirectional relationship with cognitive decline. Thus, this study developed the Sleep and Cognition Enhancement Multimodal Intervention (SCEMI) based on Lazarus’ multimodal approach and conducted a randomized controlled experiment to investigate the effects of the novel program on sleep and cognition in MCI elderly. The participants were 55 MCI elderly with sleep disturbances at two dementia care centers located in S-city, Gyeonggi-do, South Korea (n = 25 in the experimental group and n… More >

Hafza Ayesha Siddiqa¹, Muhammad Irfan¹, Saadullah Farooq Abbasi^2,*, Wei Chen¹

CMC-Computers, Materials & Continua, Vol.77, No.2, pp. 1759-1778, 2023, DOI:10.32604/cmc.2023.041970

Abstract Automatic sleep staging of neonates is essential for monitoring their brain development and maturity of the nervous system. EEG based neonatal sleep staging provides valuable information about an infant’s growth and health, but is challenging due to the unique characteristics of EEG and lack of standardized protocols. This study aims to develop and compare 18 machine learning models using Automated Machine Learning (autoML) technique for accurate and reliable multi-channel EEG-based neonatal sleep-wake classification. The study investigates autoML feasibility without extensive manual selection of features or hyperparameter tuning. The data is obtained from neonates at post-menstrual age 37 ± 05 weeks.… More >

Fei Wang^1,2, Li Li¹, Yinxing Wan¹, Zhuorong Li¹, Lixian Luo³, Bangshun Hu¹, Jiahui Pan^1,2, Zhenfu Wen⁴, Haiyun Huang^1,2,*

CMC-Computers, Materials & Continua, Vol.76, No.2, pp. 2301-2316, 2023, DOI:10.32604/cmc.2023.037727

Abstract Sleep spindles are an electroencephalogram (EEG) biomarker of non-rapid eye movement (NREM) sleep and have important implications for clinical diagnosis and prognosis. However, it is challenging to accurately detect sleep spindles due to the complexity of the human brain and the uncertainty of neural mechanisms. To improve the reliability and objectivity of sleep spindle detection and to compensate for the limitations of manual annotation, this study proposes a new automatic detection algorithm based on Matching Pursuit (MP) and Least Squares Boosting (LSBoost), where the automatic sleep spindle detection algorithm can help reduce the visual annotation workload of sleep clinicians. Specifically,… More >

Hao Yao¹, Shuzhen Chen^2,*

International Journal of Mental Health Promotion, Vol.25, No.9, pp. 1053-1065, 2023, DOI:10.32604/ijmhp.2023.028844

Abstract In the context of the COVID-19 pandemic and under the pressure of high competitiveness for higher education in China, junior high school students’ mental health is facing greater challenges. Understanding the time allocation of study and sleep is necessary for developing effective prevention and treatment programs. Based on a survey of 31,057 junior high school students in 47 junior high schools in Gansu Province, mainland China, the study analyzed the associations of time spent on study and sleep with anxiety and depressive symptoms among junior high school students through chi-square test, ANOVA, logistic regression model and threshold regression model. It… More >

D. Boinon, C. Charles, L. Fasse, J. Journiac, G. Pallubicki, E. Guerdoux-Ninot, G. Ninot, A. Couillet, J.-B. Le Provost, J. Savard, S. Dauchy

Psycho-Oncologie, Vol.16, No.1, pp. 173-181, 2022, DOI:10.3166/pson-2022-0179

Abstract La thérapie cognitivocomportementale de l’insomnie (TCC-I) demeure difficile d’accès pour les patients atteints de cancer. Sa digitalisation semble une solution prometteuse pour bénéficier au plus grand nombre. La faisabilité d’un programme TCC-I québécois a été démontrée en France, tout en révélant les limites d’un dispositif suivi en autonomie et à distance. L’enjeu reste de mieux comprendre le rôle des professionnels de santé dans l’accompagnement des patients dans ce type de programme. C’est l’objectif de l’étude Sleep-4-All-2.0 dont nous présenterons ici le protocole. More >

W. M. Faizal^1,*, C. Y. Khor¹, Muhammad Nooramin Che Yaakob¹, N. N. N. Ghazali², M. Z. Zainon², Norliza Binti Ibrahim³, Roziana Mohd Razi⁴

CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.1, pp. 43-61, 2023, DOI:10.32604/cmes.2023.022716

Abstract This paper aims to investigate and present the numerical investigation of airflow characteristics using Turbulent Kinetic Energy (TKE) to characterize the upper airway with obstructive sleep apnea (OSA) under inhale and exhale breathing conditions. The importance of TKE under both breathing conditions is that it show an accurate method in expressing the severity of flow in sleep disorder. Computational fluid dynamics simulate the upper airway’s airflow via steady-state Reynolds-averaged Navier-Stokes (RANS) with k–ω shear stress transport (SST) turbulence model. The three-dimensional (3D) airway model is created based on the CT scan images of an actual patient, meshed with 1.29 million… More > Graphic Abstract

Anwer Mustafa Hilal^1,*, Amal Al-Rasheed², Jaber S. Alzahrani³, Majdy M. Eltahir⁴, Mesfer Al Duhayyim⁵, Nermin M. Salem⁶, Ishfaq Yaseen¹, Abdelwahed Motwakel¹

Computer Systems Science and Engineering, Vol.45, No.2, pp. 1249-1263, 2023, DOI:10.32604/csse.2023.030603

Abstract Sleep plays a vital role in optimum working of the brain and the body. Numerous people suffer from sleep-oriented illnesses like apnea, insomnia, etc. Sleep stage classification is a primary process in the quantitative examination of polysomnographic recording. Sleep stage scoring is mainly based on experts’ knowledge which is laborious and time consuming. Hence, it can be essential to design automated sleep stage classification model using machine learning (ML) and deep learning (DL) approaches. In this view, this study focuses on the design of Competitive Multi-verse Optimization with Deep Learning Based Sleep Stage Classification (CMVODL-SSC) model using Electroencephalogram (EEG) signals.… More >

Mei Chen, Haoran Dong, Yang Luo, Hui Meng^*

International Journal of Mental Health Promotion, Vol.24, No.6, pp. 901-916, 2022, DOI:10.32604/ijmhp.2022.020006

Abstract This study aimed to investigate the relationship between sleep and workplace interpersonal conflict and the role of ego depletion as the mediating mechanism. A survey was conducted daily for two weeks using an experience sampling method. A sample of 79 employees from the East Coast of China was collected. A multilevel regression analysis was conducted to test the proposed hypotheses. Results indicated that higher sleep quantity was associated with lower daily ego depletion at noon and lower workplace interpersonal conflict. Moreover, ego depletion mediated the effects of sleep quantity on workplace interpersonal conflict. The findings identified the adverse effects of… More >