Depression in health college students: relationship factors and sleep quality

The mediating effect of social network sites addiction on the relationship between childhood psychological abuse and depression in college students and the moderating effect of psychological flexibility

BACKGROUND

Experience of child psychological abuse in college students is likely to increase their risk of depression, but the potential psychological mechanisms between the two require further exploration. This study supplemented the risk and protective factors between child psychological abuse and depression in college students by introducing social network sites addiction (SNSA) as a mediating factor and psychological flexibility as a moderating factor.

METHODS

A cross-sectional survey was conducted on 655 college students from two universities in Hunan Province, China. Self-reported measures included childhood psychological abuse, depression, SNSA, and psychological flexibility. Descriptive and correlational analyses were performed on these variables, followed by the establishment of a structural equation model.

RESULTS

Child psychological abuse was positively associated with depression (r = .507, p < .001) and SNSA (r = .208, p < .001) in college students and negatively associated with psychological flexibility (r = -.293, p < .001). SNSA played a mediating role between childhood psychological abuse and depression (β = .170, SE = 0.035, p < .001) in college students, while psychological flexibility attenuated the strength of the relationship between the latter two (β = -.095, SE = 0.031, p < .01).

CONCLUSION

The study further elucidates the psychological mechanisms underlying the relationship between childhood psychological abuse and depression in college students. SNSA may mediate the relationship between the two, while psychological flexibility may buffer the strength of the relationship between them. Future research should explore interventions enhancing college students' psychological flexibility after childhood psychological abuse to cut the risk of depression.

Utilizing machine learning techniques to identify severe sleep disturbances in Chinese adolescents: an analysis of lifestyle, physical activity, and psychological factors

Background

Adolescents often experience difficulties with sleep quality. The existing literature on predicting severe sleep disturbance is limited, primarily due to the absence of reliable tools.

Methods

This study analyzed 1966 university students. All participants were classified into a training set and a validation set at the ratio of 8:2 at random. Participants in the training set were utilized to establish models, and the logistic regression (LR) and five machine learning algorithms, including the eXtreme Gradient Boosting Machine (XGBM), Naïve Bayesian (NB), Support Vector Machine (SVM), Decision Tree (DT), CatBoosting Machine (CatBM), were utilized to develop models. Whereas, those in the validation set were used to validate the developed models.

Results

The incidence of severe sleep disturbance was 5.28% (104/1969). Among all developed models, the XGBM model performed best in AUC (0.872 [95%CI: 0.848-0.896]), followed by the CatBM model (0.853 [95% CI: 0.821-0.878]) and DT model (0.843 [95% CI: 0.801-0.870]), whereas the AUC of the logistic regression model was only 0.822 (95% CI: 0.777-0.856). Additionally, the XGBM model had the best accuracy (0.792), precision (0.780), F1 score (0.796), Brier score (0.143), and log loss (0.444).

Conclusions

The XGBM model may be a useful tool to estimate the risk of experiencing severe sleep disturbance among adolescents.

Mental health and sleep in the post-COVID-19 era among Thai undergraduate students

The purpose of this study was to examine mental health problems and sleep quality among undergraduate students in the post-COVID-19 era, as well as related factors. This cross-sectional study involved 627 undergraduate students from Chiang Mai University in northern Thailand between October and December 2022. Data were collected using a self-administered online questionnaire that included the General Health Questionnaire-12 (GHQ-12), the Center for Epidemiologic Studies-Depression Scale (CES-D), and the Pittsburgh Sleep Quality Index (PSQI). The study found that 57.9% of participants experienced mental health problems (95% CI: 54.0-61.8), 32.2% experienced depression (95% CI: 28.5-35.9), and 68.1% reported poor sleep quality (95% CI: 64.4-71.8). Multiple logistic regression analysis revealed that medical conditions, relationships with family members, relationships with friends or other people, having problems while studying at university, and self-perceived COVID-19 impact score were all associated with mental health problems and poor sleep quality (p < 0.05). Depression was associated with the field of study, relationships with family members, relationships with friends or other people, having problems while studying at university, and self-perceived COVID-19 impact score (p < 0.05). The findings highlight a significant occurrence of poor sleep and mental health issues, including depression, among undergraduate students in the post-COVID-19 era, underscoring the need for ongoing mental health monitoring and interventions to mitigate negative outcomes.

Comparison of Depressive Symptoms between International and Domestic Students in a Japanese University: Pre- and Post-COVID-19 Pandemic

BACKGROUND

The COVID-19 pandemic led to significant lifestyle changes and uncertainties, triggering a secondary wave of mental health issues in society. University students are especially susceptible to mental disorders. International students are considered more vulnerable due to limited emotional and financial support from their families and difficulties accessing community support. Hence, we conducted a longitudinal analysis to compare depressive symptoms among international students before and during the pandemic.

METHODS

Data from depression screenings conducted at the University of Tsukuba in 2019 and 2020 were utilized. We included all students enrolled in 2019 who underwent health check-ups in both 2019 and 2020. Participants completed the Patient Health Questionnaire-9 (PHQ-9), enabling a comparison of item scores between domestic and international students. Psychopathological network analysis was employed to examine relationships among the items.

RESULTS

Prior to the pandemic, international students generally exhibited relatively good mental health compared with domestic students. During the 2020 pandemic, no significant difference was observed, but international students tended to demonstrate better mental health. However, network analysis revealed intergroup variations in the relationships among PHQ-9 items, with concentration problems and suicidal thoughts being more prominent among international students.

CONCLUSION

This study's findings suggest that young people studying abroad experience mental health crises similar to their domestic counterparts. Nevertheless, the patterns of these crises may differ between the two groups.

An Artificial Intelligence Platform to Stratify the Risk of Experiencing Sleep Disturbance in University Students After Analyzing Psychological Health, Lifestyle, and Sports: A Multicenter Externally Validated Study

Background

Sleep problems are prevalent among university students, yet there is a lack of effective models to assess the risk of sleep disturbance. Artificial intelligence (AI) provides an opportunity to develop a platform for evaluating the risk. This study aims to develop and validate an AI platform to stratify the risk of experiencing sleep disturbance for university students.

Methods

A total of 2243 university students were included, with 1882 students from five universities comprising the model derivation group and 361 students from two additional universities forming the external validation group. Six machine learning techniques, including extreme gradient boosting machine (eXGBM), decision tree (DT), k-nearest neighbor (KNN), random forest (RF), neural network (NN), and support vector machine (SVM), were employed to train models using the same set of features. The models' prediction performance was assessed based on discrimination and calibration, and feature importance was determined using Shapley Additive exPlanations (SHAP) analysis.

Results

The prevalence of sleep disturbance was 44.69% in the model derivation group and 49.58% in the external validation group. Among the developed models, eXGBM exhibited superior performance, surpassing other models in metrics such as area under the curve (0.779, 95% CI: 0.728-0.830), accuracy (0.710), precision (0.737), F1 score (0.692), Brier score (0.193), and log loss (0.569). Calibration and decision curve analyses demonstrated favorable calibration ability and clinical net benefits, respectively. SHAP analysis identified five key features: stress score, severity of depression, vegetable consumption, age, and sedentary time. The AI platform was made available online at https://sleepdisturbancestudents-xakgzwectsw85cagdgkax9.streamlit.app/, enabling users to calculate individualized risk of sleep disturbance.

Conclusion

Sleep disturbance is prevalent among university students. This study presents an AI model capable of identifying students at high risk for sleep disturbance. The AI platform offers a valuable resource to guide interventions and improve sleep outcomes for university students.

Identity Fusion and Aggressive Behavior Among Chinese Freshmen: The Chain Mediating Role of Depressive Mood and Sleep Quality

Aggressive behavior is considered one of the indicators of maladjustment and increases during the transition to college. Previous studies have demonstrated that having identity fusion with particular social groups significantly predicts college adjustment among freshmen. However, the relationship between identity fusion and aggressive behavior in college freshmen has rarely been studied. Thus, guided by the frustration-aggression theory, this study aimed to explore the association between identity fusion with class and aggressive behavior among Chinese college freshmen and examine the potential mediating roles of depressive mood and sleep quality. A cross-sectional survey study was carried out among 1,037 Chinese college freshmen (Mage = 19.56, SD = 1.068, 29.12% males). Class identity fusion, depressive mood, sleep quality, and aggressive behavior were measured via four self-reported questionnaires. Structural equation modeling was used to test the mediation model. Analyses showed that identity fusion was negatively related to depressive mood and aggressive behavior and positively correlated with sleep quality. The results also revealed that the direct effect of identity fusion on aggressive behavior was significant, and identity fusion can indirectly affect aggressive behavior not only through the mediation effect of depressive mood but also through the chain mediation effect of depressive mood and sleep quality. Moreover, the mediating effect of depressive mood varied by gender. These findings suggest that strategies that help freshmen promote identity fusion and those that alleviate depressive mood and sleep problem may help reduce aggressive behavior.

Mind Matters: Exploring the Intersection of Psychological Factors and Cognitive Abilities of University Students by Using ANN Model

Purpose

While previous studies have suggested close association of psychological variables of students withtheir higher-order cognitive abilities, such studies have largely been lacking for third world countries like India, with their unique socio-economic-cultural set of challenges. We aimed to investigate the relationship between psychological variables (depression, anxiety and stress) and cognitive functions among Indian students, and to predict cognitive performance as a function of these variables.

Patients and Methods

Four hundred and thirteen university students were systematically selected using purposive sampling. Widely used and validated offline questionnaires were used to assess their psychological and cognitive statuses. Correlational analyses were conducted to examine the associations between these variables. An Artificial Neural Network (ANN) model was applied to predict cognitive levels based on the scores of psychological variables.

Results

Correlational analyses revealed negative correlations between emotional distress and cognitive functioning. Principal Component Analysis (PCA) reduced the dimensionality of the input data, effectively capturing the variance with fewer features. The feature weight analysis indicated a balanced contribution of each mental health symptom, with particular emphasis on one of the symptoms. The ANN model demonstrated moderate predictive performance, explaining a portion of the variance in cognitive levels based on the psychological variables.

Conclusion

The study confirms significant associations between emotional statuses of university students with their cognitive abilities. Specifically, we provide evidence for the first time that in Indian students, self-reported higher levels of stress, anxiety, and depression are linked to lower performance in cognitive tests. The application of PCA and feature weight analysis provided deeper insights into the structure of the predictive model. Notably, use of the ANN model provided insights into predicting these cognitive domains as a function of the emotional attributes. Our results emphasize the importance of addressing mental health concerns and implementing interventions for the enhancement of cognitive functions in university students.

Depression and Anxiety of Portuguese University Students: A Cross-Sectional Study about Prevalence and Associated Factors

Background

The mental health of university students has worsened over time, and it is young people who have suffered the most from the COVID-19 pandemic in terms of mental health. Anxiety and depression are the most common symptoms reported by university students and are often the cause of disabilities, either in academic performance or in other spheres of life.

Aim

The aim of this study was to both assess the prevalence of depressive and anxiety symptoms in Portuguese university students and analyze the factors associated with these symptoms.

Methods

A quantitative cross-sectional study with a sample of 3,399 university students from seven Portuguese higher education institutions was conducted. The following questionnaires were used: the generalized anxiety disorder assessment scale (GAD-7), the patient health questionnaire (PHQ-9), and a study-created sociodemographic questionnaire. The Kendall correlation coefficient, chi-square test of independence, Spearman correlation coefficient, Shapiro-Wilk test, Mann-Whitney-Wilcoxon test, and Kruskall-Wallis test were used to analyze the association between variables. The statistical analysis was done using the software R Statistics (Version 4.0.4), using a significance level of 0.05.

Results

Mild to severe anxiety symptoms were reported by 75% of the participants, and 61.2% described mild to severe depressive symptoms. Of the sample, 19.5% reported a previous diagnosis of a mental disorder, with 38.7% diagnosed after the pandemic began. Additionally, 23% reported taking medication for mental health issues, and 26.7% had considered self-harm or harbored thoughts of being "better off dead." The study found lower anxiety and depressive symptoms (p < 0.05) among men, students with higher socioeconomic status, those who frequently traveled home, individuals without prior mental health diagnoses, those with better academic performance, and those who avoided substances like coffee, tobacco, cannabis, and other illegal psychoactive substances. Interestingly, students in romantic relationships exhibited more anxiety symptoms (p < 0.05). Moreover, participants who believed they had experienced moral or sexual harassment displayed higher levels of anxiety and depressive symptoms (p < 0.001).

Conclusions

There was a decrease in the mental health of university students after the pandemic compared to prepandemic studies, and the proportion of students with anxiety and depressive symptoms was alarming. There is an urgent need to implement programs in universities to promote students' mental health.

The relationship between academic stress and depression among college students during the COVID-19 pandemic: a cross-sectional study from China

BACKGROUND

The COVID-19 pandemic is a global public health crisis. During the COVID-19 pandemic, mental health has attracted great attention. However, there is a lack of research on the relationship between academic stress and depression in Chinese college students and its mechanisms. Therefore, this study investigated the mechanisms of coping style, sleep quality, and interpersonal relationship in academic stress and depression among college students.

METHODS

The cross-sectional study was conducted from May to June 2022 through face-to-face questionnaires with college students in Anhui Province, China. The questionnaires included sociodemographic information, the Simplified Coping Style Questionnaire, and the Self-Rating Depression Scale. Ordered logistic regression model was used to study the relationship between academic stress and depression of college students during the COVID-19 pandemic through the mechanism analysis of coping style, sleep quality and interpersonal relationship.

RESULTS

Two thousand thirty-three Chinese college students participated in the study, including 1,285 female and 748 male college students, with an average age 19.81 years old (SD = 1.22 years old). The results showed that (1) Academic stress had a significant impact on depression in college students under the background of COVID-19 (p < 0.01); (2) The influence of academic stress on depression had a difference in work experience as student cadres, which showed that college students who had served as student cadres were less affected by academic stress (p < 0.10), college students who had not served as student cadres were greatly affected by the academic stress (p < 0.05); (3) College students' attitudes toward COVID-19 significantly affected depression (p < 0.01); (4) Counselors' concern had a significant impact on college students' depression (p < 0.01); (5) Positive coping style, high quality sleep and good interpersonal relationship were the important mechanisms of the impact of academic stress on college students' depression.

CONCLUSIONS

This study provides new findings for in-depth understanding of the relationship between academic stress and depression among college students in China during the COVID-19 pandemic, which is conducive to the provision of targeted intervention measures for the mental health of college students.

Association between depressive symptoms and employment type of Korean workers: the Fifth Korean Working Conditions Survey

BACKGROUND

This study analyzed the association between depressive symptoms and employment type, by considering both socioeconomic status and job stress factors.

METHODS

We analyzed 27,369 participants (13,134 men and 14,235 women) using data from the fifth Korean Working Conditions Survey. The participants were divided into regular and precarious workers. Depressive symptoms were defined using the World Health Organization-5 Well-Being Index. A multivariate logistic regression analysis was performed to assess the association between depressive symptoms and employment type.

RESULTS

Of the participants, 71.53% (N = 19578) were regular workers and 28.47% (N = 7791) were precarious workers. The weighted frequencies of participants with depressive symptoms (42.50%) were significantly higher than those of precarious workers (32.54%, p < 0.001). In the univariate and multivariate analyses, precarious workers had a significantly higher risk of depressive symptoms than regular workers (odds ratio [OR] 1.53, 95% confidence interval [CI] 1.42-1.64; OR 1.16, 95% CI 1.07-1.26, respectively). The significant association between depressive symptoms and precarious workers has also been reflected in propensity score matched participants through crude and multivariate analysis (OR 1.54 [95% CI 1.43-1.66] and OR 1.15 [95% CI 1.04-1.26], respectively).

CONCLUSIONS

The findings suggest that precarious workers may have a higher risk of depressive symptoms than regular workers. However, this is only a cross-sectional study. Therefore, further study is required to investigate the relevance association between depressive symptoms and employment types.

Impact of the COVID-19 pandemic on the sleep quality of students: A meta-analysis and meta-regression

OBJECTIVE

The present systematic review aims to assess the impact of the COVID19 pandemic on the sleep quality of students.

METHODS

An electronic search was performed in the databases and in gray literature for articles published up to January 2022. The results included observational studies that assessed sleep quality through validated questionnaires, comparing moments pre and postCOVID19 pandemic. The risk of bias was assessed using the Joanna Briggs Institute Critical Assessment Checklist. The Grading of Assessment, Development and Evaluation (GRADE) was used to assess the certainty of scientific evidence. Estimates of interest were calculated using random effects meta-analyses and possible confounding factors were meta-regressed.

RESULTS

Eighteen studies were considered for qualitative synthesis and thirteen were considered for meta-analysis. Considering the comparison of means obtained by the Pittsburgh Sleep Quality Index, there was an increase in the scores obtained during the pandemic period [MD = -0.39; 95% CI = -0.72 - -0.07; I2 = 88.31%], thus evidencing a slight worsening in the sleep quality of these individuals. Risk of bias was considered low in nine studies, moderate in eight studies, and high in one study. The unemployment rate (%) in the country of origin of each included study partially explained the heterogeneity of analysis. GRADE analysis showed a very low certainty of scientific evidence.

CONCLUSION

The COVID-19 pandemic may have a slight negative impact on the sleep quality of high school and college students, but the evidence is still uncertain. The socioeconomic reality must be considered when evaluating this outcome.

Depression and Anxiety among Undergraduate Health Science Students: A Scoping Review of the Literature

Background: Health science students in post-secondary institutions experience high levels of depression and anxiety due to increased stress levels, workload, low socioeconomic status, and history of family mental illness, among other factors. Given the significant negative impact that depression and anxiety can have on undergraduate health science students, it is essential to understand the prevalence and correlation of these conditions in this population. In light of this, this scoping review aims to identify, document, and analyze the literature on the prevalence and determinants of anxiety and depression among undergraduate health sciences students and identify gaps in knowledge for future research. Methods: This scoping review was planned and executed using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for the Scoping Reviews statement. A comprehensive and systematic search was carried out for five databases, namely MEDLINE, Scopus, EMBASE, CINAHL, and PubMed. Results: From the literature identified by our search strategy, the lowest prevalence for anxiety was 5.8%, and the highest was 82.6%, with a median of 44.25%. The prevalence of depression ranged from a high of 88.8% to a low of 2.1%, with a median value of 34.8%. Our analysis revealed that correlates of anxiety and depression among health science students include sociodemographic factors such as age, sex, gender, relationships, ethnicity, and family history, personal health conditions, and academic and socioeconomic issues. Conclusions: With the high incidence of anxiety and depression among health science students, there is an increasing need to find practical remedies to support these students. It is also essential for policymakers and university authorities to implement interventions such as supportive text messages and other strategies geared toward providing support and improving the psychological well-being of health science students.

Magnitude, relationship and determinants of attention deficit hyperactivity disorder and depression among University of Gondar undergraduate students, Northwest Ethiopia, 2022: Non-recursive structural equation modeling

BACKGROUND

Up to 80% of adults with attention deficit hyperactivity disorder (ADHD) may have a concomitant psychiatric disorder. ADHD and depression, combined with the demands of University life, can pose serious challenges for students. However, there are limited studies conducted on this topic in our country. Therefore, the current study assessed the magnitude, relationship, and determinants of ADHD and depressive symptoms among students at the University of Gondar.

METHOD

An institution-based cross-sectional study was employed among 1514 undergraduate students at the University of Gondar from June 1-20, 2022. A stratified, simple random sampling technique was applied. Structural equation modeling was employed. The degree of relationship was interpreted based on the adjusted regression coefficient with 95% confidence interval (CI) and p-value (<0.05).

RESULT

In our study, 37.6% [CI: 35.2-40.1%] and 20.01% [CI: 18.1-22.1%] of the participants had depressive and ADHD symptoms, respectively. Chronic illness [β = 0.19, CI; 0.09, 0.30], alcohol use [β = 0.10, CI; 0.03, 0.17], social support [β = -0.23, CI; -0.29, -0.17], problematic internet use (PIU) [β = 0.23, CI; 0.18, 0.27], and insomnia [β = 0.24, CI; 0.17, 0.30] had a direct relationship with depressive symptoms. Mother education level [β = -0.09, CI; -0.13, -0.06], birth order [β = -0.09, CI; -0.11, -0.07], chat chewing [β = 0.18, CI; 0.06, 0.30], and depressive symptoms [β = 0.73, CI; 0.62, 0.86] had a direct relationship with ADHD. Chronic illness [β = 0.14, CI; 0.06, 0.22], PIU [β = 0.16, CI; 0.13, 0.21], social support [β = -0.16, CI; -0.22, -0.12], and insomnia [β = 0.17, CI; 0.13, 0.23] had an indirect effect on ADHD.

CONCLUSION AND RECOMMENDATION

The prevalence of ADHD and depressive symptoms was high. Chronic disease, alcohol use, social support, PIU, and insomnia had a direct effect on depressive symptoms and an indirect effect on ADHD. Mother education, birth order, chat chewing, and depressive symptoms had a direct effect on ADHD. Our study provided useful clues for clinical treatment and school-based interventions that aim to improve college students' mental well-being. It is better to design school-based intervention and prevention programs to achieve timely diagnosis and treatment of these disorders among university students.

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

BACKGROUND

Growing competition in tight job market and academic excellence as a social norm in Asian culture have made Chinese college students burdened with immense academic stress.

OBJECTIVES

This study aimed to explore the associations between academic stress and depression, and the mediating roles of negative affect and sleep quality, as well as the moderating role of social support in the relationship between negative affect and sleep quality.

METHODOLOGY

A convenience sample of 221 male and 479 female college students aged between 17 and 25 completed questionnaires on academic stress, depression, negative affect, sleep quality and social support.

RESULTS

Results indicated that academic stress could not only directly affect depression (b = 0.31, p < 001), but also affect depression through the mediation role of negative affect and sleep quality. The chain mediating effects includes three paths, namely, the mediating role of negative affect (indirect effect = 0.21, percentage of total effect = 69.58 %), the mediating role of sleep quality (indirect effect = 0.06, percentage of total effect = 21.03 %), and the chain mediating role of negative affect and sleep quality (indirect effect = 0.06, percentage of total effect = 19.86 %). Social support moderated the adverse influence of negative affect on sleep quality. Social support decreases the impact of negative affect on sleep quality. Specifically, the association between negative affect and sleep quality was stronger for college students with low (bsimple = 0.44, p < 0.001) social support than those with high (bsimple = 0.32, p < 0.001) social support.

IMPLICATIONS

The results advanced our understanding of how academic stress affects college students' depression. These findings provide implications on the cultivation of stress coping strategies, promotion of emotion regulation skills, exaltation of sleep quality, and improvement of the social support level aiming for future depression preventions and interventions. Specific measures include setting up psychological health courses, teaching emotion management strategies, and establishing web-based programme steming from acceptance and commitment therapy. It should be noted that the cross-sectional design means the causal associations among the variables could not be determined.

The relationship between depression, healthy lifestyle behaviors and internet addiction: a cross-sectional study of the athlete university students in Turkey

Introduction

Mental health research exists for university students in the areas of prevalence and association of depression, internet addiction and healthy lifestyle behaviors. However, the studies examining prevalence rates and these relationships in athlete university students are needed. This study aimed to evaluate the relationship between depression, healthy lifestyle behaviors and internet addiction among athlete university students in Turkey.

Methods

A cross-sectional design was conducted, measuring depression using the Center for Epidemiologic Studies Depression Scale, healthy lifestyle behaviors (HPLP-II), and internet addiction (YIAT-SF). Predictive factors associated with depressive symptoms were estimated using binary logistic regression.

Results

Of the 501 participants, 61.3% were male, with a mean age of 21.45 years (SD: 3.19). Student-athletes were at risk of depressive symptoms (76.4%), internet addiction (34.4%) and had moderate healthy lifestyle behaviors (130.41 ± 22.93). No significant differences were found for age, smoking, time spent on social network, number of sports days, number of social networks use for depressive symptoms (p > 0.05), however significant differences were found for depressive symptoms by sex and living with family status (p < 0.05). Pathological internet addiction (OR: 12.74, 95% CI: 2.91-55.77) and low spiritual growth (OR: 0.854, 95% CI: 0.79-0.92) were found to be predictors of depressive symptoms within the athlete university students (p < 0.001).

Conclusion

The athlete university students are at increased risk for depressive symptoms and internet addiction and decreased healthy lifestyle behaviors. It is essential to establish programs to improve the mental health of students in universities and to strengthen the psychological counseling services offered to students. These findings can assist universities in establishing effective measures to improve mental health outcomes.

Do anxiety sensitivity cognitive concerns and/or depression symptoms independently explain sleep disturbances in a high anxiety sensitive treatment-seeking sample?

Cognitive models of insomnia posit a role for anxiety sensitivity (AS) in sleep difficulties. While sleep disturbances have been linked to AS, particularly AS cognitive concerns, prior studies have rarely accounted for the correlated construct of depression. We used pre-treatment intervention trial data from 128 high AS, treatment-seeking adults with a DSM-5 diagnosis of an anxiety, depressive, or posttraumatic stress disorder to determine whether AS cognitive concerns and/or depression are independently associated with sleep impairment domains (e.g., sleep quality, latency, daytime dysfunction). Participants provided data on AS, depressive symptoms, and sleep impairments. AS cognitive concerns (but not other AS dimensions) were correlated with four of five sleep impairment domains; depression was correlated with all five. Multiple regressions revealed four of five sleep impairment domains were predicted by depression with no independent contribution of AS cognitive concerns. In contrast, AS cognitive concerns and depression were independently associated with daytime dysfunction. Results suggest previous findings linking AS cognitive concerns to sleep impairments may have been largely secondary to the overlap of cognitive concerns with depression. Findings demonstrate the importance of incorporating depression into the cognitive model of insomnia. Both AS cognitive concerns and depression may be useful targets for reducing daytime dysfunction.

Psychological Health and Drugs: Data-Driven Discovery of Causes, Treatments, Effects, and Abuses

Mental health issues can have significant impacts on individuals and communities and hence on social sustainability. There are several challenges facing mental health treatment; however, more important is to remove the root causes of mental illnesses because doing so can help prevent mental health problems from occurring or recurring. This requires a holistic approach to understanding mental health issues that are missing from the existing research. Mental health should be understood in the context of social and environmental factors. More research and awareness are needed, as well as interventions to address root causes. The effectiveness and risks of medications should also be studied. This paper proposes a big data and machine learning-based approach for the automatic discovery of parameters related to mental health from Twitter data. The parameters are discovered from three different perspectives: Drugs and Treatments, Causes and Effects, and Drug Abuse. We used Twitter to gather 1,048,575 tweets in Arabic about psychological health in Saudi Arabia. We built a big data machine learning software tool for this work. A total of 52 parameters were discovered for all three perspectives. We defined six macro-parameters (Diseases and Disorders, Individual Factors, Social and Economic Factors, Treatment Options, Treatment Limitations, and Drug Abuse) to aggregate related parameters. We provide a comprehensive account of mental health, causes, medicines and treatments, mental health and drug effects, and drug abuse, as seen on Twitter, discussed by the public and health professionals. Moreover, we identify their associations with different drugs. The work will open new directions for a social media-based identification of drug use and abuse for mental health, as well as other micro and macro factors related to mental health. The methodology can be extended to other diseases and provides a potential for discovering evidence for forensics toxicology from social and digital media.

Sleep Hygiene Practices and Its Impact on Mental Health and Functional Performance Among Adults in Tabuk City: A Cross-Sectional Study

Background Poor or imperfect sleep hygiene practices include all factors that promote arousal or disrupt the normal balance of the sleep-wake cycle. It is necessary to clarify the relationship between sleep hygiene behaviors and a person's mental health. This may allow a better understanding of this problem and might help design effective awareness programs about good sleep hygiene practices for reducing the serious outcomes of this problem. Therefore, the current study was conducted to evaluate sleep hygiene practices and assess the impact of sleep hygiene on sleep quality and the mental health of the adult population of Tabuk city, Saudi Arabia. Methodology This cross-sectional, survey-based study was conducted in Tabuk city, Saudi Arabia in 2022. All adult residents of Tabuk city, Saudi Arabia were invited to participate. Participants with incomplete data were excluded from the study. A self-administered questionnaire was developed by the researchers to assess sleep hygiene practices and their impact on the sleep quality and mental health of the study participants. Results The study included 384 adults. There was a significant association between the frequency of sleep problems and poor sleep hygiene practices (p < 0.001). The percentage of subjects who had problems sleeping during the past three months was significantly higher among those having poor sleep hygiene practices (76.5%) than their counterparts (56.1%). The rates of excessive or severe daytime sleepiness were significantly higher among individuals with poor hygiene practices (22.5% versus 11.7% and 5.2% versus 1.2%, p = 0.001). Participants with depression were found to be significantly higher among the poor hygiene group (75.8%) in comparison to those having good hygiene practices (59.6%) (p = 0.001). Conclusions The findings of the present study indicate significant associations between poor sleep hygiene practices and sleep problems, daytime sleepiness, and depression among adult residents of Tabuk city, Saudi Arabia.

Moderating effects of PER3 gene DNA methylation on the association of sleep quality with mental health in Chinese young adults

BACKGROUND

Poor sleepers have a higher prevalence of mental health problems, and vice versa. However, the mechanisms underlying this association remain unknown. We aimed to examine the bidirectional association between sleep quality and mental health, and further explore the moderating effects of PER3 gene DNA methylation on the association.

METHODS

This prospective longitudinal study was conducted from April 2019 to May 2021, integrated questionnaire and blood sample data from 2 universities in Anhui and Jiangxi Provinces. The current study recruited 1179 young adults at baseline and conducted the follow-up survey among 1135 half a year later. The sleep quality and depressive symptoms, anxiety symptoms, and stress symptoms were assessed using a questionnaire at baseline and follow-up. Blood samples were collected at baseline, and MethyTarget™ was used to detect the PER3 gene DNA methylation level. A cross-lag model was used to examine the bidirectional association between sleep quality and mental health. The PROCESS plug-in of SPSS software was used to analyse the moderating effects of PER3 gene DNA methylation.

RESULTS

Cross-lagged analyses suggested a significant bidirectional relationship between poor sleep quality and depressive symptoms, anxiety symptoms, and stress symptoms. Sleep quality at baseline was a significant predictor of depressive symptoms (β = 0.344, P < 0.001), anxiety symptoms (β = 0.348, P < 0.001), and stress symptoms (β = 0.324, P < 0.001) half a year later. Depressive symptoms (β = 0.049, P < 0.001), anxiety symptoms (β = 0.055, P < 0.001), and stress symptoms (β = 0.063, P < 0.001) at baseline were also significant predictors of poor sleep quality half a year later. Furthermore, PER3 gene DNA methylation has negative moderating effects between sleep quality at baseline and depressive symptoms (β = -11.706, P = 0.012), anxiety symptoms (β = -10.289, P = 0.019), and stress symptoms (β = -10.799, P = 0.024) half a year later and a sex difference. Among boys, PER3 gene DNA methylation has positive moderating effects between anxiety symptoms at baseline and sleep quality (β = 3.337, P = 0.018) half a year later. However, there was no association between mental health at baseline and sleep quality half a year later among girls.

CONCLUSION

Bidirectional relationships were identified between sleep quality and mental health among Chinese young adults during the study period. DNA methylation evidence supports a negative moderating effect of PER3 gene DNA methylation on the relationship between sleep quality at baseline and mental health half a year later and had sex differences. Among boys, PER3 gene DNA methylation had positive moderating effects between anxiety symptoms at baseline and sleep quality half a year later. These findings point to the importance of circadian clock gene DNA methylation in the relationship between sleep quality and mental health.

Hypertension, sleep quality, depression, and cognitive function in elderly: A cross-sectional study

Background

Hypertension, sleep disorders, and depression are highly prevalent in the elderly population and are all associated with cognitive impairment, but the role that sleep quality and depression play in the association between hypertension and cognitive impairment is unclear. The aim of this study was to investigate whether sleep quality and depression have a mediating role in the association between hypertension and cognitive impairment.

Methods

A cross-sectional study was conducted to collect data from the Tongji Hospital Comprehensive Geriatric Assessment Database. Sleep quality, depression and cognitive function were measured by the Pittsburgh Sleep Quality Index (PSQI), the Geriatric Depression Scale (GDS-15) and the Mini-Mental State Examination (MMSE), respectively. Correlation analysis, regression analysis and Bootstrap analysis were used to examine correlations between key variables and mediating effects of sleep quality and depression. Adjustments for multiple comparisons were performed using Benjamini-Hochberg adjustment for multiple testing.

Results

A total of 827 participants were included, hypertension was present in 68.3% of the sample. After correcting for covariates, hypertensive patients aged 65 years or older had worse cognitive function, poorer-sleep quality and higher levels of depression. Sleep quality was significantly negatively associated with depression and cognitive function, while depression was negatively associated with cognitive function. Mediation analysis revealed that hypertension can affect cognitive function in older adults through a single mediating effect of sleep quality and depression and a chain mediating effect of sleep quality and depression.

Conclusion

This study found that sleep quality and depression can mediate the relationship between hypertension and cognitive function in elderly. Enhanced supervision of sleep quality and depression in elderly patients with hypertension may be beneficial in maintaining cognitive function.

Different Effects of Perceived Social Support on the Relationship between Perceived Stress and Depression among University Students with Borderline Personality Disorder Symptoms: A Multigroup Mediation Analysis

Background: While perceived social support can mediate the relationship between perceived stress and depression, little is known about the differences between individuals with high and low borderline personality disorder symptoms (BPDS). This study aimed to investigate the associations among perceived stress, perceived social support, and depression, and compare low and high levels of BPDS. Methods. This cross-sectional analysis was a secondary analysis of data from the SI-Bord study. University students across Thailand completed a screening instrument for borderline personality disorder, the Perceived Stress Scale (PSS), the Revised Thai Multi-dimensional Scales of Perceived Social Support (MSPSS), and the Patient-Health Questionnaire (PHQ)-9. Mediation analysis using PROCESS was applied to test the direct and indirect effects of perceived stress on depression. Multigroup mediational analysis was adopted to compare low and high levels of BPDS. Results. The mean age of the 330 participants was 20.27 (SD, 1.4) and 80% were female. Significant correlations were observed between the PSS, MSPSS, and PHQ scores, with greater magnitude among the high-level BPDS group (p < 0.001). A significant direct effect on perceived stress and a significant indirect effect on depression through perceived social support were noted. Of all the sources of social support, only the significant others variable significantly differed between the two groups (p < 0.05). Conclusion. Perception of social support had a significant mediating role in perceived stress and depression. The magnitude of associations was remarkably high for individuals with high BPDS compared to those with low BPDS. Unlike those with low BPDS, all sources of social support were significant mediators between the two groups.

The Relationship between University Students' Depression, Anxiety, and Stress with Positivity Attitudes and the COVID-19 Pandemic

Background:

The physical activity of university students is restricted during the pandemic, changes in education and training, and uncertainties during the pandemic caused their social lives to change completely.

Aim:

This study aims to determine the relationship between the depression, anxiety, and stress, and positivity attitudes of university students during the Covid-19 (coronavirus disease-2019) outbreak and their attitudes and behaviors toward the pandemic.

Subjects and Methods:

This cross-sectional study was conducted online among university students, n = 2153 from April 30, 2020 to May 10, 2020. Data were collected with the Positivity Scale and the Depression Anxiety Stress Scale.

Results:

The proportion of those with moderate and above depression, anxiety, and stress symptoms in the study group, respectively, were 40.6%, 24.6%, and 22.5%. The risk ratio of these symptoms is higher among those with lower positive attitudes (OR [odds ratio] = 0.804, 0.897, 0.895, respectively), being women (OR = 1.446, 1.666, 1.471), who are concerned with the transmission of the Covid-19 (OR = 1.144, 1.374, 1.201), who believe their intra-family relations (OR = 1.886, 1.728, 2.083) and education (OR = 1.680, 1.682, 2.132) are negatively affected, and those who are more worried about life after the pandemic.

Conclusion:

Compared with the pre-pandemic period, the frequency of university students showing symptoms of depression increased, and there was no significant change in anxiety and stress levels.

Influencing factors, prediction and prevention of depression in college students: A literature review

The high prevalence of depression among college students has a strong negative impact on individual physical and mental health, academic development, and interpersonal communication. This paper reviewed the extant literature by identifying nonpathological factors related to college students' depression, investigating the methods of predicting depression, and exploring nonpharmaceutical interventions for college students' depression. The influencing factors of college students' depression mainly fell into four categories: biological factors, personality and psychological state, college experience, and lifestyle. The outbreak of coronavirus disease 2019 has exacerbated the severity of depression among college students worldwide and poses grave challenges to the prevention and treatment of depression, given that the coronavirus has spread quickly with high infection rates, and the pandemic has changed the daily routines of college life. To predict and measure mental health, more advanced methods, such as machine algorithms and artificial intelligence, have emerged in recent years apart from the traditional commonly used psychological scales. Regarding nonpharmaceutical prevention measures, both general measures and professional measures for the prevention and treatment of college students' depression were examined in this study. Students who experience depressive disorders need family support and personalized interventions at college, which should also be supplemented by professional interventions such as cognitive behavioral therapy and online therapy. Through this literature review, we insist that the technology of identification, prediction, and prevention of depression among college students based on big data platforms will be extensively used in the future. Higher education institutions should understand the potential risk factors related to college students' depression and make more accurate screening and prevention available with the help of advanced technologies.

Relationship between premenstrual syndrome and sleep quality among nursing and medical students

PURPOSE

This study was performed to determine relationship between premenstrual syndrome (PMS) and sleep quality among nursing and medical students.

DESIGN AND METHODS

This descriptive, cross-sectional and correlational study was completed with 313 students attending the nursing department and medical faculty. Data were collected using the premenstrual syndrome scale (PMSS) and Pittsburgh sleep quality index (PSQI).

FINDINGS

The PSQI was positively correlated with PMSS and its subscales scores. Sleep changes were the strongest predictor, followed by depressive thoughts (p < .01), depressive mood, bloating and total PMSS (p < .05) for sleep quality.

PRACTICE IMPLICATIONS

Training should be organized about PMS for university students to provide information and skills about managing symptoms, and to increase the awareness about this syndrome. Interventional studies should be planned to increase sleep quality in PMS.

The association of sleep patterns and depressive symptoms in medical students: a cross-sectional study

Objective

Mental health is a fundamental aspect in ensuring the stable and successful professional life of future physicians. Depressive symptoms can negatively affect the work-life-balance and efficiency at work of medical students.

To date, there have been very few studies involving medical students that examine the association between single sleep characteristics and the outcome of the Beck Depression Inventory-II score. Therefore, the aim of the present study is to investigate this possible association. A classroom survey using socio-demographic characteristics, the Beck Depression Inventory-II, and the Pittsburgh Sleep Quality Index was conducted amongst students at a German medical school from December 2017 to September 2018. Data analysis was performed with descriptive statistics and binary logistic regression.

Results

Of the students surveyed, 19% showed depressive symptoms with a Beck Depression Inventory-II score over 13 and 42% of these cases were moderate or severe. The occurrence of relevant depressive symptoms was associated with lower sleep quality, higher sleep latency, and the consumption of sleeping pills. In general, female students and students from abroad had a higher risk of depressive symptoms. Addressing these relevant findings in medical school can increase awareness of mental health.

Prevalence and Associated Factors of Depression in Medical Students in a Northern Thailand University: A Cross-Sectional Study

This study was conducted to investigate the prevalence and associated factors of depression in medical students. This cross-sectional study investigated the prevalence and associated factors of depression in medical students from May 2018 to April 2019. Depression was diagnosed using the nine-item Patient Health Questionnaire. We evaluated the following potential predictors: demographic data, stressors, psychiatric comorbidities, emotional intelligence (EI), and perceived social support. The association between potential factors and depression was analyzed using multiple logistic regression analysis. The prevalence of depression was 149 of 706 students with 12.5% suicidality. Second- and fourth-year medical students were high-risk groups. Risk factors identified were insufficient income, physical illness, and previous psychiatric illness. Depression in medical students likely coincides with anxiety, internet addiction, sleep problems, and loneliness. Highly associated stressors were personal relationships, physical health, mental health, difficulties in social relationships, satisfaction with grades, and boredom with medical education. Protective EI factors included emotional self-control, problem-solving abilities, inner peace, and life satisfaction. Up to 21.1% of medical students had depression. In this study, among multiple known risk factors of depression, we found that EI is the novel protective factor against depression among medical students. EI training might be protective intervention for medical students in the future.

Perceived Academic Stress and Depression: The Mediation Role of Mobile Phone Addiction and Sleep Quality

BACKGROUND

Although academic stress is a well-known risk factor for students' depression, little is known about the possible psychological mechanisms underlying this association. In this study, we investigated the prevalence of depression and sleep disturbance among Chinese students, examined the relationship between perceived academic stress and depression, considered if mobile phone addiction and sleep quality is a mediator of this relationship, and tested if mobile phone addiction and sleep quality together play a serial mediating role in the influence of perceived academic stress on depression.

METHOD

A cross-sectional survey was conducted among students from September to December 2018 in Heilongjiang Province, China. The final analysis included 5,109 students. Mobile phone addiction, sleep quality, and depressive symptoms were assessed using the Mobile Phone Addiction Index, Pittsburgh Sleep Quality Index, and Center for Epidemiologic Studies-Depression scales, respectively. The serial mediation model was used to analyse the relationship between perceived academic stress, mobile phone addiction, sleep quality, and depression.

RESULTS

Among all participants, the prevalence of depressive symptoms and sleep disturbance was 28.69 and 27.95%, respectively. High school students showed the highest scores of perceived academic stress (2.68 ± 1.06), and the highest prevalence of depressive symptoms (33.14%) and sleep disturbance (36.47%). The serial mediation model indicated that perceived academic stress was a significant predictor of depression (B = 0.10, SE = 0.02, 95% CI = 0.06 - 0.13). Additionally, mobile phone addiction (B = 0.08, 95% boot CI = 0.06-0.11) and sleep quality (B = 0.27, 95% boot CI = 0.22-0.33) played a mediating role between perceived academic stress and depression. Mobile phone addiction and sleep quality together played a serial mediating role in the influence of perceived academic stress on depression (B = 0.11, 95% boot CI = 0.08-0.14). Furthermore, the indirect effect (i.e., the mediating effect of mobile phone addiction and sleep quality) was significant and accounted for 64.01% of the total effect.

CONCLUSIONS

Our research results underscore the need for stakeholders-including family members, educators, and policy makers-to take preventative intervention measures to address depression among Chinese students, especially high school students.

Sleep quality and its correlates among undergraduate medical students in Nepal: A cross-sectional study

Poor sleep quality has been found to affect students' learning abilities, academic performance, and interpersonal relationships. However, little is known about this issue in Nepal. This study aimed to identify the factors associated with poor sleep quality among undergraduate medical students in Nepal. A web-based survey was conducted in March 2021 among 212 undergraduate medical students at the Institute of Medicine, Kathmandu, Nepal. Sleep quality was measured using a 19-item Pittsburgh Sleep Quality Index (PSQI). Multivariable logistic regression analysis was done to assess the factors associated with sleep quality. In the study participants, 38.2% of the students were identified as poor sleepers. Factors like being depressed (AOR = 4.5, 95% CI; 1.2-5.4), current alcohol use (AOR = 2.5, 95% CI; 1.8-10.8), poor academic achievement (AOR = 3.4, 95% CI; 1.1-10.9), and being a fourth-year student (AOR = 3.6, 95% CI; 1.1-11.8) were significantly associated with poor sleep quality. Poor sleep quality was common among undergraduate medical students. Routine screening of sleep quality and depressive symptoms is necessary to mitigate their impact among medical students. Medical students of the fourth year, current alcohol users, and those who did not have good academic achievement had poor sleep quality. Special attention on these population subgroups is thus needed to enhance sleep quality.

Prediction of sleep quality among university students after analyzing lifestyles, sports habits, and mental health

The aim of this study was to develop and validate a prediction model to evaluate the risk of poor sleep quality. We performed a cross-sectional study and enrolled 1,928 college students from five universities between September and November 2021. The quality of sleep was evaluated using the Chinese version of the Pittsburgh Sleep Quality Index (PSQI). Participants were divided into a training (n = 1,555) group and a validation (n = 373) group. The training group was used to establish the model, and the validation group was used to validate the predictive effectiveness of the model. The risk classification of all participants was performed based on the optimal threshold of the model. Of all enrolled participants, 45.07% (869/1,928) had poor sleep quality (PSQI score ≧ 6 points). Multivariate analysis showed that factors such as older age, a higher grade, previous smoking, drinking, midday rest, chronic disease, anxiety, and stress were significantly associated with a higher rate of poor sleep quality, while preference for vegetables was significantly associated with better sleep quality, and all these variables were included to develop the prediction model. The area under the curve (AUC) was 0.765 [95% confidence interval (CI): 0.742-0.789] in the training group and 0.715 (95% CI: 0.664-0.766) in the validation group. Corresponding discrimination slopes were 0.207 and 0.167, respectively, and Brier scores were 0.195 and 0.221, respectively. Calibration curves showed favorable matched consistency between the predicted and actual probability of poor sleep quality in both groups. Based on the optimal threshold, the actual probability of poor sleep quality was 29.03% (317/1,092) in the low-risk group and 66.03% (552/836) in the high-risk group (P < 0.001). A nomogram was presented to calculate the probability of poor sleep quality to promote the applicationof the model. The prediction model can be a helpful tool to stratify sleep quality, especially among university students. Some intervention measures or preventive strategies to quit smoking and drinking, eat more vegetables, avoid midday rest, treat chronic disease, and alleviate anxiety and stress may be considerably beneficial in improving sleep quality.

Within- and across-day patterns of interplay between depressive symptoms and related psychopathological processes: a dynamic network approach during the COVID-19 pandemic

BACKGROUND

In order to understand the intricate patterns of interplay connected to the formation and maintenance of depressive symptomatology, repeated measures investigations focusing on within-person relationships between psychopathological mechanisms and depressive components are required.

METHODS

This large-scale preregistered intensive longitudinal study conducted 68,240 observations of 1706 individuals in the general adult population across a 40-day period during the COVID-19 pandemic to identify the detrimental processes involved in depressive states. Daily responses were modeled using multi-level dynamic network analysis to investigate the temporal associations across days, in addition to contemporaneous relationships between depressive components within a daily window.

RESULTS

Among the investigated psychopathological mechanisms, helplessness predicted the strongest across-day influence on depressive symptoms, while emotion regulation difficulties displayed more proximal interactions with symptomatology. Helplessness was further involved in the amplification of other theorized psychopathological mechanisms including rumination, the latter of which to a greater extent was susceptible toward being influenced rather than temporally influencing other components of depressive states. Distinctive symptoms of depression behaved differently, with depressed mood and anhedonia most prone to being impacted, while lethargy and worthlessness were more strongly associated with outgoing activity in the network.

CONCLUSIONS

The main mechanism predicting the amplifications of detrimental symptomatology was helplessness. Lethargy and worthlessness revealed greater within-person carry-over effects across days, providing preliminary indications that these symptoms may be more strongly associated with pushing individuals toward prolonged depressive state experiences. The psychopathological processes of rumination, helplessness, and emotion regulation only exhibited interactions with the depressed mood and worthlessness component of depression, being unrelated to lethargy and anhedonia. The findings have implications for the impediment of depressive symptomatology during and beyond the pandemic period. They further outline the gaps in the literature concerning the identification of psychopathological processes intertwined with lethargy and anhedonia on the within-person level.

The impact of COVID-19 pandemic on medical students’ mental health and sleep quality in Jordan: a nationwide cross-sectional study

Background

COVID-19 pandemic is expected to affect the mental health, especially among medical students. Data from the literature in Jordan are scarce, especially during the second wave of the pandemic. We aimed to assess medical students’ level of fear, prevalence of depressive and anxiety symptoms—represented in psychological distress (PD)—and sleep quality (SQ) amid the current pandemic of COVID-19. A total of 2104 students were included through convenient sampling from the six schools of Medicine in Jordan. Online-based questionnaire using Patient Health Questionnaire-4 (PHQ-4) scale, Fear of COVID-19 scale (FCV-19S), and Sleep Quality Scale (SQS) was used to collect the data. Chi-square, t-tests, and ANOVA were used to establish the associations.

Results

88.4% and 47.4% of the students were found to have PD and poor or just fair sleep quality on SQS, respectively, with PD ranging from mild (18.6%) to severe (42.1%). Calculated FCV-19S score was 14.62 (SD=5.38), indicating high level of fear. Students with excellent SQ had significantly lower rates of depression, anxiety, and PD as compared to those with good, fair, and poor SQ (P < 0.001 for all).

Conclusion

Jordanian medical students appear to be especially susceptible to COVID-19 pandemic impact on mental health and reported high rates of PD. While rates of COVID-19 fear are still considered high, they are remarkably lower than that reported in early studies. We strongly recommend providing resources and access to professional mental health care to students reporting poor SQ and/or symptoms of anxiety and depression.

Limitations

Using a cross-sectional design, online-based survey, convenient sampling, and scarcity of local literature are among the inevitable limitations caused by the pandemic that have prevented us from drawing cause-effect associations.

Heart and Head: Profiles and Predictors of Self-Assessed Cognitive and Affective Empathy in a Sample of Medical and Health Professional Students

For medical and health professions, students learning to respond to others' distress with well-regulated empathy is an important developmental skill linked to positive health outcomes and professionalism. Our study aimed to investigate the sociodemographic, psychological, and psychosocial differences between medical (MS) and health professional (HPS) students and their empathic abilities, since both populations share common stressors, namely, dealing with suffering people. Additionally, we were interested in assessing the psychological and psychosocial predictors of empathy of MS compared to HPS. One hundred thirty MS and 86 HPS were administered the Patient Health Questionnaire-9, Interpersonal Reactivity Index, Integrative Hope Scale, and UCLA Loneliness Scale. The two groups showed differences in their contextual characteristics, with the HPS group having larger families, lower parents' education levels, and lower family income compared to the MS group. In both groups, ~15% of students reported previous contact for psychological problems. A higher proportion of HPS (23.3%) reported depressive symptoms than MS (10%), and female HPS reported more intense feelings of loneliness than other subgroups of students. No differences were found between the two groups in self-assessed cognitive and affective empathy. In both groups, women showed greater affective scores than men and, at the same time, seemed to be particularly prone to personal distress. The cognitive empathic dimension of “perspective taking” was predicted by young age (OR, 612; 95% CI, 1.395–15.242) and the overall socioeconomic status (OR, 3.175; 95% CI, 1.154–8.734) of the HPS. Self-assessed affective competence was predicted by female gender (OR, 3.112; 95% CI, 1.328–7.288), depressive symptomatology (OR, 2.777; 95% CI, 1.004–7.681), higher mother's level of education (OR, 2.764; 95% CI, 1.147–6.659), and feeling of hope related to social relationships (OR, 1.367; 95% CI, 1.152–1.622). Risk factors for poor self-assessed affective emphatic skills were previous contact for psychological problems (OR, 3.263; 95% CI, 1.238–8.601) and feelings of loneliness (OR, 1.18; 95% CI, 1.09–1.276). Our findings emphasize the need to test psychosocial models to better understand empathic skills.

Prevalence and correlates of lifestyle behavior, anxiety and depression in Chinese college freshman: A cross-sectional survey

Objectives

First-year college students had exposure to unhealthy lifestyle behaviors that correlate with a high prevalence of anxiety and depression. Regarding to the modifiable lifestyle behaviors factors, this study investigated the prevalence and correlation of multiple lifestyle behaviors, anxiety and depression in a sample of Chinese first-year college students.

Methods

Cross-sectional data were extracted from Residents eHealth app of health lifestyle behaviors survey from September to October 2019. Anxiety, depression, eating regular meals, consumption of snacks in-between meals, consumption of fruit, dessert and sugar-sweetened beverages, smoking and secondhand smoke exposure, consuming alcohol, physical activity, sedentary time were assessed by self-report. Socio-demographic including age, gender, education, family income, religion, and health condition were captured. Logistic regression was used to explore the association of multiple lifestyle behaviors, anxiety and depression.

Results

Totally 1,017 participants were included in the study. The prevalence of anxiety and depression (from mild to severe) were 40.3% and 45.3%, respectively. In multivariable analyses, religion (believe in Buddhism, OR = 2.438, 95%CI: 1.097-5.421; believe in Christian, OR = 5.886, 95%CI: 1.604-21.597), gender (Female, OR = 1.405, 95%CI: 1.001-1.971), secondhand smoke exposure (OR = 1.089, 95%CI: 1.001-1.184), and eating regular meals (OR = 0.513, 95%CI: 0.346-0.759) were associated with anxiety. Family income (OR = 0.732, 95%CI: 0.596-0.898), eating regular meals (OR = 0.641, 95%CI: 0.415-0.990), frequency of breakfast (OR = 0.813, 95%CI: 0.690-0.959), with a chronic disease (OR = 1.902, 95%CI: 1.335-2.712), and consumption of nocturnal snack (OR = 1.337, 95%CI: 1.108-1.612) were associated with depression.

Conclusions

These results highlighted the need for early lifestyle behavior intervention, especially modifying diet patterns considering the background of religion, health condition, and social-economic status in first-year college students to improve their mental health.

Effect of COVID-19 Quarantine on the Sleep Quality and the Depressive Symptom Levels of University Students in Jordan During the Spring of 2020

Objectives: This study was designed to assess the effect of COVID-19 home quarantine and its lifestyle challenges on the sleep quality and mental health of a large sample of undergraduate University students in Jordan. It is the first study applied to the Jordanian population. The aim was to investigate how quarantine for several weeks changed the students' habits and affected their mental health. Methods: A cross-sectional study was conducted using a random representative sample of 6,157 undergraduate students (mean age 19.79 ± 1.67 years, males 28.7%) from the University of Jordan through voluntarily filling an online questionnaire. The Pittsburgh Sleep Quality Index (PSQI) and the Center for Epidemiologic Studies-Depression Scale (CES-D) were used to assess sleep quality and depressive symptoms, respectively. Results: The PSQI mean score for the study participants was 8.1 ± 3.6. The sleep quality of three-quarters of the participants was negatively affected by the extended quarantine. Nearly half of the participants reported poor sleep quality. The prevalence of poor sleep quality among participants was 76% (males: 71.5% and females: 77.8%). Similarly, the prevalence of the depressive symptoms was 71% (34% for moderate and 37% for high depressive symptoms), with females showing higher prevalence than males. The overall mean CES-D score for the group with low depressive symptoms is 9.3, for the moderate group is 19.8, while it is 34.3 for the high depressive symptoms group. More than half of the students (62.5%) reported that the quarantine had a negative effect on their mental health. Finally, females, smokers, and students with decreased income levels during the extended quarantine were the common exposures that are significantly associated with a higher risk of developing sleep disturbances and depressive symptoms. Conclusions: Mass and extended quarantine succeeded in controlling the spread of the COVID-19 virus; however, it comes with a high cost of potential psychological impacts. Most of the students reported that they suffer from sleeping disorders and had a degree of depressive symptoms. Officials should provide psychological support and clear guidance to help the general public to reduce these potential effects and overcome the quarantine period with minimum negative impacts.

The relationship between bullying victimization and depression in adolescents: multiple mediating effects of internet addiction and sleep quality

Various studies have found that bullying victimization is an important factor affecting depression. However, few studies have explored the underlying mechanism of this effect.  The purpose of this study was to examine the effects of bullying victimization on depression, as well as the mediating roles of internet addiction and sleep quality. The participants were 2022 Chinese junior high school students who completed questionnaires regarding bullying victimization, internet addiction, sleep quality and depression. Correlation analysis indicated that bullying victimization, poor sleep quality, internet addiction, and depression have significant, positive correlations with each other. Hayes' PROCESS macro revealed that internet addiction and sleep quality played multiple mediation roles in the relationship between bullying victimization and depression. These results suggested that effective strategies focusing on improving problematic internet use along with sleep quality may contribute to reducing the negative effect of bullying victimization on depressive symptoms.

The Fate of Emotional Memories Over a Week: Does Sleep Play Any Role?

Although there is a wide consensus on how sleep processes declarative memories, how sleep affects emotional memories remains elusive. Moreover, studies assessing the long-term effect of sleep on emotional memory consolidation are scarce. Studies testing subclinical populations characterized by REM abnormalities are also lacking. Here we aimed to (i) investigate the fate of emotional memories and the potential unbinding (or preservation) between content and affective tone over time (i.e., 1 week), (ii) explore the role of seven nights of sleep (recorded via actigraphy) in emotional memory consolidation, and (iii) assess whether participants with self-reported mild-moderate depressive symptoms forget less emotional information compared to participants with low depression symptoms. We found that, although at the immediate recognition session emotional information was forgotten more than neutral information, a week later it was forgotten less than neutral information. This effect was observed both in participants with low and mild-moderate depressive symptoms. We also observed an increase in valence rating over time for negative pictures, whereas perceived arousal diminished a week later for both types of stimuli (unpleasant and neutral); an initial decrease was already observable at the immediate recognition session. Interestingly, we observed a negative association between sleep efficiency across the week and change in memory discrimination for unpleasant pictures over time, i.e., participants who slept worse were the ones who forgot less emotional information. Our results suggest that emotional memories are resistant to forgetting, particularly when sleep is disrupted, and they are not affected by non-clinical depression symptomatology.