The associations between academic stress and depression among college students: A moderated chain mediation model of negative affect, sleep quality, and social support

Machine learning identifies different related factors associated with depression and suicidal ideation in Chinese children and adolescents

BACKGROUND

Depression and suicidal ideation often co-occur in children and adolescents, yet they possess distinct characteristics. This study sought to identify the different related factors associated with depression and suicidal ideation.

METHODS

A nationwide cross-sectional survey collected data from Chinese children and adolescents aged 8 to 18 (N = 160,962; 48.91 % girls). The survey included inquiries about demographics, depression, suicidal ideation, anxiety, perceived stress, academic burnout, internet addiction, non-suicidal self-injury, bullying, and being bullied. Fifteen machine learning algorithms were conducted to identify the different related factors associated with depression and suicidal ideation. Additionally, we conducted external validation on an independent sample of 1,812,889 children and adolescents.

RESULTS

Our findings revealed seven related factors linked to depression and six associated with suicidal ideation, with average accuracy rates of 86.86 % and 85.82 %, respectively. For depression, the most influential factors were anxiety, perceived stress, academic burnout, internet addiction, non-suicidal self-injury, experience of bullying, and age. Similarly, anxiety, non-suicidal self-injury, perceived stress, internet addiction, academic burnout, and age emerged as paramount factors for suicidal ideation. Moreover, these related factors showed notable variations in their predictive capacities for depression and suicidal ideation across different subgroups.

CONCLUSION

Anxiety emerged as the predominant shared factor for both depression and suicidal ideation, whereas the other related factors displayed distinct predictive patterns for each condition. These findings highlight the critical need for tailored strategies from public mental health service providers and policymakers to address the pressing concerns of depression and suicidal ideation.

Enhancing psychological well-being in college students: the mediating role of perceived social support and resilience in coping styles

BACKGROUND

The prevalence of depression among college students is higher than that of the general population. Although a growing body of research suggests that depression in college students and their potential risk factors, few studies have focused on the correlation between depression and risk factors. This study aims to explore the mediating role of perceived social support and resilience in the relationship between trait coping styles and depression among college students.

METHODS

A total of 1262 college students completed questionnaires including the Trait Coping Styles Questionnaire (TCSQ), the Patient Health Questionnaire-9 (PHQ-9), the Perceived Social Support Scale (PSSS), and the Resilience Scale-14 (RS-14). Common method bias tests and spearman were conducted, then regressions and bootstrap tests were used to examine the mediating effects.

RESULTS

In college students, there was a negative correlation between perceived control PC and depression, with a significant direct predictive effect on depression (β = -0.067, P < 0.01); in contrast, negative control NC showed the opposite relationship (β = 0.057, P < 0.01). PC significantly positively predicted perceived social support (β = 0.575, P < 0.01) and psychological resilience (β = 1.363, P < 0.01); conversely, NC exerted a significant negative impact. Perceived social support could positively predict psychological resilience (β = 0.303, P < 0.01), and both factors had a significant negative predictive effect on depression. Additionally, Perceived social support and resilience played a significant mediating role in the relationship between trait coping styles and depression among college students, with three mediating paths: PC/NC → perceived social support → depression among college students (-0.049/0.033), PC/NC→ resilience → depression among college students (-0.122/-0.021), and PC/NC → perceived social support → resilience → depression among college students (-0.016/0.026).

CONCLUSION

The results indicate that trait coping styles among college students not only directly predict lower depression but also indirectly influence them through perceived social support and resilience. This suggests that guiding students to confront and solve problems can alleviate their depression.

Prevalence and correlates of sleep disturbance among adolescents in the eastern seaboard of China

BACKGROUND

Sleep disturbances are serious public health issues that warrant increased attention, especially in adolescents. The aim of this study was to investigate the prevalence and factors associated with sleep disorders among urban adolescents in China.

METHODS

This study utilized an online survey to assess the demographic characteristics and mental health status of secondary school students in Lianyungang City. The Patient Health Questionnaire-9 (PHQ-9) was used to evaluate sleep disturbances in adolescents. The seven-item Generalized Anxiety Disorder (GAD-7) assessed anxiety symptoms, and the Perceived Social Support Scale (PSSS) was used to measure perceived social support.

RESULTS

Among 3443 adolescents, the prevalence of sleep disorders were 10.8%, with significantly higher proportions of sleep disorders (13.7% VS 8.3%, P < 0.001) among female adolescents when compared to males. Binary regression analysis revealed that anxiety symptoms (OR = 1.305, 95% CI: 1.269-1.342, P < 0.001) was risk factor for sleep disturbances, and significant other support (OR = 0.944, 95% CI: 0.896-0.994, P = 0.028) and good annual household income (OR = 0.616, 95% CI: 0.394-0.963, P = 0.034) were protective factors. Furthermore, multinomial logistic regression analysis showed that age, sex, and anxiety symptoms were associated with an elevated risk of experiencing more frequent sleep disturbances (all P < 0.05).

CONCLUSIONS

We have found that 10.8% of adolescents experience sleep disorders, and it is evident that various factors can influence healthy sleeping. These results underscore the significance of addressing these factors to enhance sleep health among this population.

Is sleep quality a moderated mediator between perceived stress and depression among stroke patients?

Background

Sleep quality can offer new insights into addressing depression among stroke patients. However, the current understanding of the mechanism by which sleep quality reduces depression is not clear in existing research.

Objectives

This study aimed to identify the relationships and mechanisms among perceived stress, sleep quality, social support, and depression in stroke patients.

Methods

A multicenter cross-sectional study was conducted from January to May 2023. Cluster random sampling was used to recruit 500 stroke patients from five hospitals in Henan Province, China. The Chinese Perceived Stress Scale (CPSS), Pittsburgh Sleep Quality Index (PSQI), Social Support Rating Scale (SSRS), and Hamilton Depression Scale (HAMD-24) were employed to assess perceived stress, sleep quality, social support, and depression, respectively. Data were analyzed using descriptive analysis, Pearson's correlation analysis, and moderated mediation analysis. The study adhered to the STROBE checklist for reporting.

Results

Out of 500 participants, 471 completed the survey (94.2%). After controlling for sex and age, mediation analysis revealed that poor sleep quality partially mediated the relationship between perceived stress and depression (β = 0.184, 95% CI: 0.110, 0.359). Additionally, social support played a moderating role in the mediation model.

Conclusion

This study explained the moderated mediation of sleep quality and social support between perceived stress and depression. It provided a theoretical basis for the development of a sleep quality intervention program for reducing depression among stroke patients.

The 24-h activity cycle and cardiovascular outcomes: establishing biological plausibility using arterial stiffness as an intermediate outcome

This review proposes a biologically plausible working model for the relationship between the 24-h activity cycle (24-HAC) and cardiovascular disease. The 24-HAC encompasses moderate-to-vigorous physical activity (MVPA), light physical activity, sedentary behavior (SB), and sleep. MVPA confers the greatest relative cardioprotective effect, when considering MVPA represents just 2% of the day if physical activity guidelines (30 min/day) are met. While we have well-established guidelines for MVPA, those for the remaining activity behaviors are vague. The vague guidelines are attributable to our limited mechanistic understanding of the independent and additive effects of these behaviors on the cardiovascular system. Our proposed biological model places arterial stiffness, a measure of vascular aging, as the key intermediate outcome. Starting with prolonged exposure to SB or static standing, we propose that the reported transient increases in arterial stiffness are driven by a cascade of negative hemodynamic effects following venous pooling. The subsequent autonomic, metabolic, and hormonal changes further impair vascular function. Vascular dysfunction can be offset by using mechanistic-informed interruption strategies and by engaging in protective behaviors throughout the day. Physical activity, especially MVPA, can confer protection by chronically improving endothelial function and associated protective mechanisms. Conversely, poor sleep, especially in duration and quality, negatively affects hormonal, metabolic, autonomic, and hemodynamic variables that can confound the physiological responses to next-day activity behaviors. Our hope is that the proposed biologically plausible working model will assist in furthering our understanding of the effects of these complex, interrelated activity behaviors on the cardiovascular system.