Hubness of strategic planning and sociality influences depressive mood and anxiety in College Population

Impact of COVID-19 on Lifestyle, Personal Attitudes, and Mental Health Among Korean Medical Students: Network Analysis of Associated Patterns

The current COVID-19 pandemic have affected our daily lifestyle, pressed us with fear of infection, and thereby changed life satisfaction and mental health. The current study investigated influencing cascade of changes during the COVID-19 among the lifestyle, personal attitudes, and life (dis)satisfaction for medical students, using network-based approaches. This cross-sectional survey used self-reports of 454 medical students during June and July of 2020. Depressive mood, anxiety, and intention to drop out of school were observed in 11.9, 18.5, and 38.3% of medical students, respectively. Directed acyclic graph that estimated directional propagation of the COVID-19 in medical students' daily lives initiated from the perception of unexpected event, propagated to nervous and stressed feeling, trouble relaxing, feeling like a failure, and were followed by trouble concentrating, feeling loss of control for situation, and fear of infecting colleagues. These six features were also principal mediators within the intra-individual covariance networks comprised of changed lifestyle, personal attitude, and mental health at COVID-19 pandemic. Psychosocial supports targeting nervousness, trouble relaxing and concentrating, fear of spreading infection to colleagues, feelings of a failure or loss of situational control are required for better mental health of medical students during the COVID-19 pandemic.

The relationship between childhood emotional abuse and depressive symptoms among Chinese college students: The multiple mediating effects of emotional and behavioral problems

BACKGROUND

This study aims to explore the mediational effects of emotional and behavioral problems on the association between childhood emotional abuse and depressive symptoms among college students.

METHODS

Data were drawn from 60 universities from 10 provinces in China (n=30,374). Information about childhood maltreatment, depressive symptoms, emotional and behavioral problems were gathered through the Childhood Trauma Questionnaire-Short Form (CTQ-SF), the Center for Epidemiologic Studies Depression Scale (CES-D) and the Strengths and Difficulties Questionnaire (SDQ), respectively. Univariable and multivariable logistic regression models and mediating models were used.

RESULTS

After controlling for demographic factors, childhood emotional abuse was the strongest risk factor for depressive symptoms (adjusted odds ratio (aOR)=2.54, 95%CI=2.27-2.85). The relationship between childhood emotional abuse and depressive symptoms was partially mediated by emotional and behavioral problems with 68.7% total indirect effect. Among the 5 identified subtypes of emotional and behavioral problems, the mediating effects of emotional problems (57.3%) and hyperactivity (28.6%) were higher than peer problems (7.8%) and prosocial behavior (3.6%). Conduct problems did not show a significant mediating effect (p>0.05).

LIMITATIONS

The cross-sectional design is limited to make inferences about causality.

CONCLUSIONS

Childhood emotional abuse was strongly associated with depressive symptoms in college students. Of the five identified subtypes of emotional and behavioral problems, four subtypes mediated the relationship between childhood emotional abuse and depressive symptoms, including emotional problems, hyperactivity, peer problems and prosocial behavior.

Phenotype Network and Brain Structural Covariance Network of Major Depression

Phenotype networks enable clinicians to elucidate the patterns of coexistence and interactions among the clinical symptoms, negative cognitive styles , neurocognitive performance, and environmental factors in major depressive disorder (MDD). Results of phenotype network approach could be used in finding the target symptoms as these are tightly connected or associated with many other phenomena within the phenotype network of MDD specifically when comorbid psychiatric disorder(s) is/are present. Further, by comparing the differential patterns of phenotype networks before and after the treatment, changing or enduring patterns of associations among the clinical phenomena in MDD have been deciphered.Brain structural covariance networks describe the inter-regional co-varying patterns of brain morphologies, and overlapping findings have been reported between the brain structural covariance network and coordinated trajectories of brain development and maturation. Intra-individual brain structural covariance illustrates the degrees of similarities among the different brain regions for how much the values of brain morphological features are deviated from those of healthy controls. Inter-individual brain structural covariance reflects the degrees of concordance among the different brain regions for the inter-individual distribution of brain morphologic values. Estimation of the graph metrics for these brain structural covariance networks uncovers the organizational profile of brain morphological variations in the whole brain and the regional distribution of brain hubs.

Depressive Disorders and Sleeping Disturbances-Surveys Study of 923 Participants on the Pol'and'Rock Festival, Kostrzyn, Poland 2019

Depressive disorders are common among young people and can decrease social competences and thus the quality of life. There is a relationship between the occurrence of depressive disorders and insomnia. The aim of the study was to determine the prevalence of insomnia and depressive behavior and assess the relationship between these among participants of the Pol’and’Rock Festival, Kostrzyn, Poland 2019. The study used the Athens Insomnia Scale (AIS) and the Beck Inventory II Scale (BDI-II). The study group consisted of 923 people, with the majority of women (n = 500; 54.2%). A total of 297 persons (32.2%) reported varying severity of depressive symptoms. Insomnia was observed in 261 (28.28%) respondents. Sleeping disturbances were observed more frequently in females. Persons with insomnia had a significantly higher BDI-II score. A strong positive correlation (r = 0.65) between the number of points obtained on the Beck and AIS scales was observed. Insomnia and depressive behavior are prevalent in the Polish population. Due to long-term social and economic consequences, special attention should be paid to the prevention, early detection and treatment of both disorders.

Phenotype Network and Brain Structural Covariance Network of Anxiety

Network-based approach for psychological phenotypes assumes the dynamical interactions among the psychiatric symptoms, psychological characteristics, and neurocognitive performances arise, as they coexist, propagate, and inhibit other components within the network of mental phenomena. For differential types of dataset from which the phenotype network is to be estimated, a Gaussian graphical model, an Ising model, a directed acyclic graph, or an intraindividual covariance network could be used. Accordingly, these network-based approaches for anxiety-related psychological phenomena have been helpful in quantitative and pictorial understanding of qualitative dynamics among the diverse psychological phenomena as well as mind-environment interactions. Brain structural covariance refers to the correlative patterns of diverse brain morphological features among differential brain regions comprising the brain, as calculated per participant or across the participants. These covarying patterns of brain morphology partly overlap with longitudinal patterns of brain cortical maturation and also with propagating pattern of brain morphological changes such as cortical thinning and brain volume reduction in patients diagnosed with neurologic or psychiatric disorders along the trajectory of disease progression. Previous studies that used the brain structural covariance network could show neural correlates of specific anxiety disorder such as panic disorder and also elucidate the neural underpinning of anxiety symptom severity in diverse psychiatric and neurologic disorder patients.

Sex-Specific Differences in Severity of Depressive Symptoms, Heart Rate Variability, and Neurocognitive Profiles of Depressed Young Adults: Exploring Characteristics for Mild Depression

Mild depressive symptoms (MDS) reflect vulnerability to major depression that does not meet the criteria for a major depressive disorder (MDD). Previous research indicates that it is difficult to identify MDS in young adults, and they exhibit diverse aspects of depressive symptoms caused by clinical depression, which can lead to poor academic performance, relationship difficulties, and even suicide. Additionally, many young adults remain unaware of their depressive symptoms during the early stages of MDD. Thus, the present study investigated clinical, neurocognitive, and physiological characteristics of young adults with various symptoms of depression and explored sex-specific differences. A total of 113 students aged 18-35 (MDD: n = 32; MDS: n =37; control [CON]: n = 44) participated in the study. Self-report clinical measures, short-term cardiac activity measured by finger sensors, and neurocognitive data were collected. Pearson's correlations, two-way analysis of variance (ANOVA), principal component analysis, and exploratory structural equation modeling were conducted for the statistical analyses. Furthermore, the measurement invariance of the latent factor model was tested, and fit indices were compared according to sex. The results revealed that male students showed greater sympatho-vagal activity than female students. Additionally, male MDS students tended to exhibit decreased performance levels in neurocognitive function tasks compared with MDD and CON males, whereas female MDS students showed distinct characteristics compared to MDD and CON females on self-report measures of anxiety. Correlation analyses identified a positive association between the level of anger perception and latency in the executive function test among both males and females. Additionally, the use of a structured model revealed significant sex-specific differences in factor estimates. The present results suggest that recognizing the early signs of MDS that account for sex-specific differences in both subjective and objective measures may improve the diagnosis and monitoring of young adults with MDS.

The relationship between levels of self-esteem and the development of depression in young adults with mild depressive symptoms

Little is known about the relationship between levels of self-esteem and the development of depression in young adults. The present study investigated the relationship between self-esteem and depression to determine whether self-esteem levels are a risk factor for the development of depression in young adults. This study was conducted with 113 college students aged 19 to 35 (major depressive disorder (MDD) n = 44, Mild Depressive Symptoms (MDS) n = 37, Healthy Control n = 32). The levels of clinical symptoms, self-esteem, resilience, social support, and quality of life, as well as personality traits, were assessed (by Patient Health Questionnaire-9, generalized anxiety disease-7, State-Trait Anxiety Inventory-S, Resilience Appraisal Scale, Rosenberg Self-Esteem Scale, Quality of Life, and NEO-personality inventory (NEO-PI)). The MDS group with high self-esteem reported having the lowest levels of social support, resilience, agreeableness, and extraversion compared to those of the MDD group and control group with high self-esteem. In contrast, the MDS group with low self-esteem showed no differences in social support, resilience, agreeableness and openness according to the NEO-PI scale. Sex and age had no significant impact on the results. Levels of self-esteem are strongly associated with the development of depression. Results suggest that early intervention for depression in young adults needs to focus on improving their levels of social support, resilience, and positive domains of personality. Further studies on the effects of high self-esteem in the development of depression are warranted.

Verbal Abuse Related to Self-Esteem Damage and Unjust Blame Harms Mental Health and Social Interaction in College Population

Verbal abuse is an emotional abuse intended to inflict intense humiliation-denigration-fear as perceived by exposed person. Network-based approaches have been applied to explore the integrative-segregated patterns of associations among the psychological features and external stimuli for diverse populations; few studies reported for verbal abuse effects in college population. Self-reporting measurements acquired form 5,616 college students were used for network analyses. Escalating cascades of verbal abuse from differential sources (parents, peers, or supervisors; network 1) and directed associations among verbal abuse severity-psychopathology-social interaction (network 2) were estimated using the directed acyclic graphs. Principal connectors of verbal abuse–psychopathology–social interaction were shown using the graph theory metrics calculated from the intra-individual covariance networks (network 3). Directed propagating patterns of verbal abuse phenomena differed by source (network 1). Severe peer-related verbal abuse affected psychomotor changes and influenced irritability (network 2). Verbal abuse of self-esteem damage and unjust blame served as connectors in the verbal abuse-psychopathology-social interaction; influence of smartphone overuse-related distress was stronger in cases with more severe verbal abuse (network 3). Verbal abuse that damages self-esteem and conveys unjust blame harms mental health and social interaction for college population.