The relationship between teacher-student relationships and academic grades among Chinese rural high school students: the moderating role of mental health symptoms and the conditional moderating effect of academic resilience.

Objective: This study examines the relationship between Teacher-Student Relationships and academic grades among Chinese rural high school students, focusing on the moderating role of mental health symptoms and the conditional moderating effect of academic resilience.

Method: A moderated moderation analysis was conducted via Mplus on data collected from a sample of rural Chinese high school students. SEM was used to test the direct and interactive effects of these variables on academic outcomes.

Emotional intelligence impact on academic achievement and psychological well-being among university students: the mediating role of positive psychological characteristics.

The main objective of this study is to examine the relationship of emotional intelligence with psychological well-being and academic achievement through positive psychological characteristics among university students in China. The study was conducted with postgraduate and undergraduate students. The integration of emotional intelligence theory and positive psychological theory was used in this study.

Assessing the impact of physical activity on reducing depressive symptoms: a rapid review.

Context: The prevalence of depression among teenagers is a significant issue worldwide, which calls for a thorough investigation of non-drug treatments. This expedited evaluation examines 24 specifically chosen studies to clarify the correlation between physical activity depression symptoms in teenagers, undertaken following PRISMA principles.

Methods: A wide range of research methods, including longitudinal studies, surveys, and cross-sectional analyses, were used in different nations to understand the intricate relationship between physical activity, sedentary behaviours, and depression symptoms.

Application of Bayesian structural equation modeling in construction and demolition waste management studies: Development of an extended theory of planned behavior.

Sustainable construction and demolition waste management relies heavily on the attitudes and actions of its constituents; nevertheless, deep analysis for introducing the best estimator is rarely attained. The main objective of this study is to perform a comparison analysis among different approaches of Structural Equation Modeling (SEM) in Construction and Demolition Waste Management (C&DWM) modeling based on an Extended Theory of Planned Behaviour (Extended TPB). The introduced research model includes twelve latent variables, six independent variables, one mediator, three control variables, and one dependent variable.

Evaluation of depression and obesity indices based on applications of ANOVA, regression, structural equation modeling and Taguchi algorithm process.

Introduction: Depression and obesity are the main threat among women which have been considered by many research scholars in psychology studies. In their analysis for measuring and estimating obesity and depression they were involving statistical functions.

Methods: Regression, Analysis of Variance (ANOVA), and in the last two decades Structural Equation Modeling are the most familiar statistical methods among research scholars.

Postpartum depression symptoms in survey-based research: a structural equation analysis.

Background: Since the last decade, postpartum depression (PPD) has been recognized as a significant public health problem, and several factors have been linked to PPD. Mothers at risk are rarely undetected and underdiagnosed. Our study aims to determine the factors leading to symptoms of depression using Structural Equation Modeling (SEM) analysis.

Associations of Body Mass Index with Demographics, Lifestyle, Food Intake, and Mental Health among Postpartum Women: A Structural Equation Approach.

As postpartum obesity is becoming a global public health challenge, there is a need to apply postpartum obesity modeling to determine the indicators of postpartum obesity using an appropriate statistical technique. This research comprised two phases, namely: (i) development of a previously created postpartum obesity modeling; (ii) construction of a statistical comparison model and introduction of a better estimator for the research framework. The research model displayed the associations and interactions between the variables that were analyzed using the Structural Equation Modeling (SEM) method to determine the body mass index (BMI) levels related to postpartum obesity.

mHealth Apps Assessment among Postpartum Women with Obesity and Depression.

Background: Pregnancy has become the main constituent for women to become overweight or obese during the postpartum phase. This could lead women to suffer from postpartum depression as well. Information technology (IT) has become more prevalent in the healthcare industry.