The Critical Relationship Between Anxiety and Depression

Prospective prediction of anxiety onset in the Canadian longitudinal study on aging (CLSA): A machine learning study

BACKGROUND

Anxiety disorders are among the most common mental health disorders in the middle aged and older population. Because older individuals are more likely to have multiple comorbidities or increased frailty, the impact of anxiety disorders on their overall well-being is exacerbated. Early identification of anxiety disorders using machine learning (ML) can potentially mitigate the adverse consequences associated with these disorders.

METHODS

We applied ML to the data from the Canadian Longitudinal Study on Aging (CLSA) to predict the onset of anxiety disorders approximately three years in the future. We used Shapley value-based methods to determine the top factor for prediction. We also investigated whether anxiety onset can be predicted by baseline depression-related predictors alone.

RESULTS

Our model was able to predict anxiety onset accurately (Area under the Receiver Operating Characteristic Curve or AUC = 0.814 ± 0.016 (mean ± standard deviation), balanced accuracy = 0.741 ± 0.016, sensitivity = 0.743 ± 0.033, and specificity = 0.738 ± 0.010). The top predictive factors included prior depression or mood disorder diagnosis, high frailty, anxious personality, and low emotional stability. Depression and mood disorders are well known comorbidity of anxiety; however a prior depression or mood disorder diagnosis could not predict anxiety onset without other factors.

LIMITATION

While our findings underscore the importance of a prior depression diagnosis in predicting anxiety, they also highlight that it alone is inadequate, signifying the necessity to incorporate additional predictors for improved prediction accuracy.

CONCLUSION

Our study showcases promising prospects for using machine learning to develop personalized prediction models for anxiety onset in middle-aged and older adults using easy-to-access survey data.

Machine learning models predict the emergence of depression in Argentinean college students during periods of COVID-19 quarantine

Introduction

The COVID-19 pandemic has exacerbated mental health challenges, particularly depression among college students. Detecting at-risk students early is crucial but remains challenging, particularly in developing countries. Utilizing data-driven predictive models presents a viable solution to address this pressing need.

Aims

1) To develop and compare machine learning (ML) models for predicting depression in Argentinean students during the pandemic. 2) To assess the performance of classification and regression models using appropriate metrics. 3) To identify key features driving depression prediction.

Methods

A longitudinal dataset (N = 1492 college students) captured T1 and T2 measurements during the Argentinean COVID-19 quarantine. ML models, including linear logistic regression classifiers/ridge regression (LogReg/RR), random forest classifiers/regressors, and support vector machines/regressors (SVM/SVR), are employed. Assessed features encompass depression and anxiety scores (at T1), mental disorder/suicidal behavior history, quarantine sub-period information, sex, and age. For classification, models' performance on test data is evaluated using Area Under the Precision-Recall Curve (AUPRC), Area Under the Receiver Operating Characteristic curve, Balanced Accuracy, F1 score, and Brier loss. For regression, R-squared (R2), Mean Absolute Error, and Mean Squared Error are assessed. Univariate analyses are conducted to assess the predictive strength of each individual feature with respect to the target variable. The performance of multi- vs univariate models is compared using the mean AUPRC score for classifiers and the R2 score for regressors.

Results

The highest performance is achieved by SVM and LogReg (e.g., AUPRC: 0.76, 95% CI: 0.69, 0.81) and SVR and RR models (e.g., R2 for SVR and RR: 0.56, 95% CI: 0.45, 0.64 and 0.45, 0.63, respectively). Univariate models, particularly LogReg and SVM using depression (AUPRC: 0.72, 95% CI: 0.64, 0.79) or anxiety scores (AUPRC: 0.71, 95% CI: 0.64, 0.78) and RR using depression scores (R2: 0.48, 95% CI: 0.39, 0.57) exhibit performance levels close to those of the multivariate models, which include all features.

Discussion

These findings highlight the relevance of pre-existing depression and anxiety conditions in predicting depression during quarantine, underscoring their comorbidity. ML models, particularly SVM/SVR and LogReg/RR, demonstrate potential in the timely detection of at-risk students. However, further studies are needed before clinical implementation.

Positive psychotherapy and cognitive behavioral therapy in anxiety patients - A study protocol for a randomized control trial in an online group setting

BACKGROUND

Anxiety disorders are common and debilitating which is why treatment is so important. According to the guidelines, Cognitive Behavioral Therapy (CBT) has the highest level of effectiveness among psychotherapeutic treatments and is the recommended procedure. However, not everyone responds well or at all to CBT which makes a wider range of therapy options valuable. Positive Psychotherapy (PPT) comes to mind as an alternative with its strength-based approach focusing on enhancing well-being and life satisfaction. Additionally, it has not yet been extensively studied how the processes that occur during treatment sessions and between treatment sessions effect treatment outcome. Thus, to lessen the lack of evidence regarding the efficacy of PPT as an anxiety treatment the planned study examines and compares the effectiveness of CBT and PPT as well as the effect of intrasession and intersession processes of the two therapy approaches.

METHOD

The study is in the planning stage and consists of an efficacy and a process study. The efficacy study is a randomized controlled comparative study of patients with anxiety disorders (generalized anxiety disorder and/or panic disorder with or without agoraphobia) with two active treatment conditions (PPT and CBT) and a control group (CG; positive psychotherapy with minimal therapeutic supervision) in an online group setting. There are three measurement time points: before treatment begins (T0), at the end of the ten-week treatment (T1), and a follow-up after three months (T2). The aim of the study is to evaluate the efficacy of PPT and CBT in the treatment of anxiety disorders, and to compare the efficacy of online-based PPT with minimal therapeutic supervision and online-based PPT with intensive therapeutic supervision in the treatment of anxiety disorders. The process study will be used to evaluate both the intrasession processes and the intersession processes of the therapy in the two intervention groups. In addition, the process variables that predict the success of the therapy and the extent to which PPT and CBT differ in the therapy processes will be tested. The study is registered at the German Clinical Trial Register (№ DRKS00027521).

DISCUSSION

To our knowledge, this is the first randomized controlled comparative study to examine the effectiveness of CBT and PPT for anxiety disorders in an online group setting.

Symptom patterns in the co-occurrence of depressive and generalized anxiety symptoms: A network analysis of a Canadian nationally representative sample

BACKGROUND

This study aimed to investigate the symptom patterns of major depressive disorder (MDD) and generalized anxiety disorder (GAD) in a matched nationally representative sample of the Canadian population. We also tested whether childhood maltreatment (CM) exposures and sex would be linked with different symptom patterns.

METHODS

A total of 3296 participants from the Canadian Community Health Survey-Mental Health with complete information on MDD and GAD symptoms and being matched on the studied sociodemographic characteristics were included in the current study. Network analysis was performed to examine the MDD-GAD symptom network, network stability and centrality indices were also estimated. Finally, network comparison in connectivity patterns was conducted to explore the impact of maltreatment experience and sex differences in the MDD-GAD symptom networks.

RESULTS

The CM group had stronger network connections and showed differences in the network structures from the non-CM group. In the CM group, depressed mood and diminished interest were central symptoms and strongly connected with other symptoms. Additionally, females had stronger connections in the MDD-GAD symptom network than males, and sleep disturbance was a central symptom for females, alongside depressed mood and diminished interest.

LIMITATIONS

The cross-sectional design restricts our capacity to establish longitudinal or causal connections between symptoms.

CONCLUSIONS

Depressed mood was the most central node that was strongly connected with other symptoms in the network. Distinct MDD-GAD symptom networks were discovered in the CM and the female group when compared to their counterparts. Noteworthy, individuals with CM had a stronger correlation between worry and suicidal ideation. Clinical management and intervention efforts should pay close attention to these core symptoms to yield optimal treatment effects, particularly for females and individuals with CM.

Association between physical multimorbidity and common mental health disorders in rural and urban Malawian settings: Preliminary findings from Healthy Lives Malawi long-term conditions survey

In low-income Africa, the epidemiology of physical multimorbidity and associated mental health conditions is not well described. We investigated the multimorbidity burden, disease combinations, and relationship between physical multimorbidity and common mental health disorders in rural and urban Malawi using early data from 9,849 adults recruited to an on-going large cross-sectional study on long-term conditions, initiated in 2021. Multimorbidity was defined as having two or more measured (diabetes, hypertension) or self-reported (diabetes, hypertension, disability, chronic pain, HIV, asthma, stroke, heart disease, and epilepsy) conditions. Depression and anxiety symptoms were measured using the 9-item Patient Health Questionnaire (PHQ-9) and the 7-item General Anxiety Disorder scale (GAD-7) and defined by the total score (range 0-27 and 0-21, respectively). We determined age-standardized multimorbidity prevalence and condition combinations. Additionally, we used multiple linear regression models to examine the association between physical multimorbidity and depression and anxiety symptom scores. Of participants, 81% were rural dwelling, 56% were female, and the median age was 30 years (Inter Quartile Range 21-43). The age-standardized urban and rural prevalence of multimorbidity was 14.1% (95% CI, 12.5-15.8%) and 12.2% (95% CI, 11.6-12.9%), respectively. In adults with two conditions, hypertension, and disability co-occurred most frequently (18%), and in those with three conditions, hypertension, disability, and chronic pain were the most common combination (23%). Compared to adults without physical conditions, having one (B-Coefficient (B) 0.79; 95% C1 0.63-0.94%), two- (B 1.36; 95% CI 1.14-1.58%), and three- or more- physical conditions (B 2.23; 95% CI 1.86-2.59%) were associated with increasing depression score, p-trend <0.001. A comparable 'dose-response' relationship was observed between physical multimorbidity and anxiety symptom scores. While the direction of observed associations cannot be determined with these cross-sectional data, our findings highlight the burden of multimorbidity and the need to integrate mental and physical health service delivery in Malawi.

The Impact of COVID-19 on Mental Health in Medical Students: A Cross-Sectional Survey Study in Italy

Background: This study aimed to assess the impact of the COVID-19 pandemic in terms of the prevalence of anxiety, depression and stress symptoms in Italian medical students and to identify the associated factors. Design and Methods: A cross-sectional online survey was administered to second-sixth year medical students of the University of Torino, collecting data on the students' sociodemographics, COVID-19 exposure, anxiety, depression and stress symptoms. Three hierarchical regressions adjusted for age, gender and year of study were executed. Results: The sample size was 1359. The prevalence of anxiety, depression symptoms, moderate perceived stress and severe perceived stress was 47.8%, 52.1%, 56.2% and 28.4%, respectively. The factors associated with mental health symptoms were: being a woman, a family history of psychiatric disorders, living off-site, competitive/hostile climates and unsatisfying friendships among classmates, poor relationships with cohabitants, negative judgment of medical school choice, fear of COVID-19 infection, feelings of loneliness, distressing existential reflections, and a worsening psychological condition related to the pandemic. Being in the fourth or sixth year constituted a protective factor for depression symptoms. Conclusions: Mental health in medical students was associated with both COVID-independent and COVID-related factors. Accessibility to effective interventions must be increased to counteract these changes.

Metabolic Profile and Long-Term Risk of Depression, Anxiety, and Stress-Related Disorders

Importance

Biomarkers of lipid, apolipoprotein, and carbohydrate metabolism have been previously suggested to be associated with the risk for depression, anxiety, and stress-related disorders, but results are inconsistent.

Objective

To examine whether the biomarkers of carbohydrate, lipid, and apolipoprotein metabolism are associated with the risk of depression, anxiety, and stress-related disorders.

Design, Setting, and Participants

This population-based cohort study with longitudinal data collection assessed 211 200 participants from the Apolipoprotein-Related Mortality Risk (AMORIS) cohort who underwent occupational health screening between January 1, 1985, and December 31, 1996, mainly in the Stockholm region in Sweden. Statistical analysis was performed during 2022 to 2023.

Exposures

Lipid, apolipoprotein, and carbohydrate biomarkers measured in blood.

Main Outcomes and Measures

The associations between biomarker levels and the risk of developing depression, anxiety, and stress-related disorders through the end of 2020 were examined using Cox proportional hazards regression models. In addition, nested case-control analyses were conducted within the cohort, including all incident cases of depression, anxiety, and stress-related disorders, and up to 10 control individuals per case who were individually matched to the case by year of birth, sex, and year of enrollment to the AMORIS cohort, using incidence density sampling. Population trajectories were used to illustrate the temporal trends in biomarker levels for cases and controls.

Results

A total of 211 200 individuals (mean [SD] age at first biomarker measurement, 42.1 [12.6] years; 122 535 [58.0%] male; 188 895 [89.4%] born in Sweden) participated in the study. During a mean (SD) follow-up of 21.0 (6.7) years, a total of 16 256 individuals were diagnosed with depression, anxiety, or stress-related disorders. High levels of glucose (hazard ratio [HR], 1.30; 95% CI, 1.20-1.41) and triglycerides (HR, 1.15; 95% CI, 1.10-1.20) were associated with an increased subsequent risk of all tested psychiatric disorders, whereas high levels of high-density lipoprotein (HR, 0.88; 95% CI, 0.80-0.97) were associated with a reduced risk. These results were similar for male and female participants as well as for all tested disorders. The nested case-control analyses demonstrated that patients with depression, anxiety, or stress-related disorders had higher levels of glucose, triglycerides, and total cholesterol during the 20 years preceding diagnosis, as well as higher levels of apolipoprotein A-I and apolipoprotein B during the 10 years preceding diagnosis, compared with control participants.

Conclusions and Relevance

In this cohort study of more than 200 000 participants, high levels of glucose and triglycerides and low levels of high-density lipoprotein were associated with future risk of depression, anxiety, and stress-related disorders. These findings may support closer follow-up of individuals with metabolic dysregulations for the prevention and diagnosis of psychiatric disorders.

Relationships between climate change distress, generalized anxiety, and climate-related symptoms of mental disorders

BACKGROUND AND OBJECTIVE

We examined the possibility that reactions to climate change take two forms: distress, which may be adaptive, and symptoms of mental disorders, which may not be.

DESIGN AND METHOD

In a national sample of Polish adults (n = 1133), we measured climate change distress (experiencing unpleasant emotions and feelings due to climate change), climate-related symptoms of mental disorders (e.g., problems sleeping and problems working and planning), generalized anxiety, and depression.

RESULTS

Zero-inflated Poisson regression analyses of the occurrence of climate-related symptoms of mental disorders found two latent classes: People who experienced symptoms of the disorder and those who did not. For all eight symptoms, climate change distress predicted membership in the latent class of people who experienced a symptom, whereas how often people in the non-zero latent class experienced each symptom was positively related to generalized anxiety but was not related to distress or depression.

CONCLUSIONS

These results suggest that reactions to climate change take two forms. Some people do not experience climate change-related symptoms of mental disorders, and some do. People who experience symptoms have higher levels of climate change distress, and the frequency with which they experience these symptoms is determined by their dispositional, generalized anxiety.

Influence of biopsychosocial factors on self-reported anxiety/depression symptoms among first-generation immigrant population in the U.S

BACKGROUND

Despite increasing studies on mental health among immigrants, there are limited studies using nationally representative samples to examine immigrants' mental health and its potential biopsychosocial contributing factors, especially during the COVID-19 pandemic. We explored and estimated the influence of life satisfaction, social/emotional support, and other biopsychosocial factors on self-reported anxiety/depression symptoms among a nationally representative sample of first-generation immigrants in the U.S.

METHODS

We conducted a secondary data analysis using the 2021 National Health Interview Survey among first-generation adults aged ≥ 18 years (n = 4295). We applied survey weights and developed multivariable logistic regression model to evaluate the study objective.

RESULTS

The prevalence of daily, weekly, or monthly anxiety/depression symptoms was 10.22% in the first-generation immigrant population. There were 2.04% daily, 3.27% weekly, and 4.91% monthly anxiety/depression among the population: about 8.20%, 9.94%, and 9.60% experienced anxiety symptoms, whereas 2.49%, 3.54%, and 5.34% experienced depression symptoms daily, weekly, and monthly, respectively. The first-generation population aged 26-49 years were less likely to experience anxiety/depression daily, weekly, or monthly compared to those aged 18-25. Females (versus males) were more likely to experience anxiety/depression daily, weekly, or monthly. Those who identified as gay/lesbian had higher odds of experiencing anxiety/depression daily, weekly, or monthly compared to heterosexual persons. Relative to non-Hispanic White individuals, non-Hispanic Asian, Black/African American, and Hispanic individuals had lower odds, while other/multi-racial/ethnic groups were more likely to experience anxiety/depression daily, weekly, or monthly. A higher life satisfaction score was associated with lower odds of experiencing anxiety/depression daily, weekly, or monthly. Having social/emotional support sometimes/rarely or using healthcare within the past one/two years was associated with experiencing anxiety/depression daily, weekly, or monthly.

CONCLUSIONS

The findings reveal significant burden of anxiety and depression among first-generation population in the U.S., with higher risks among subgroups like young adults, females, sexual minorities, and non-Hispanic White and other/multi-racial individuals. Additionally, individuals with lower life satisfaction scores, limited social/emotional support, or healthcare utilization in the past one or two years present increased risk. These findings highlight the need for personalized mental health screening and interventions for first-generation individuals in the U.S. based on their diversity and health-related risks.

Anxiety, Depression, and Posttraumatic Stress Disorder in Patients With Induced Laryngeal Obstruction

Importance

Patients with induced laryngeal obstruction (ILO) present with a variety of behavioral health profiles. Identifying these profiles is crucial in that behavioral health conditions may affect treatment duration and outcomes.

Objective

To characterize the prevalence of anxiety, depression, posttraumatic stress disorder (PTSD), and physical somatic symptoms in adult and pediatric patients with ILO and determine the factors associated with anxiety, depression, PTSD, and physical somatic symptoms in patients with ILO?

Design, Setting, and Participants

This cross-sectional study included a nonprobability sample of 83 adult and 81 pediatric patients diagnosed with ILO at outpatient adult and pediatric otolaryngology clinics between 2021 and 2023. Exclusion criteria included a comorbid respiratory diagnosis other than asthma, head or neck cancer, or neurological impairments. Recruitment took place between September 2021 and March 2023. The analyses were run in January 2024.

Main Outcome Measures

Patients were prospectively screened for anxiety, depression, PTSD, and somatic physical symptoms. In addition, any past behavioral health diagnoses were extracted from the medical record. Comorbidities, ILO symptoms triggers, and onset details were gathered from ILO evaluations. Adult patients completed the Screen for Adult Anxiety Related Disorders (SCAARED), depression (Patient Health Questionnaire [PHQ]-9), and somatic physical symptoms portions of the Patient Health Questionnaires (PHQ-15), and the PTSD Checklist for the Diagnostic and Statistical Manual of Mental Disorders (Fifth Edition) (PCL-5). Pediatric patients completed the Screen for Child Anxiety Related Disorders (SCARED), depression (PHQ-9A) and somatic physical symptoms portions of the Patient Health Questionnaires for Adolescents (PHQ-15A), and the UCLA PTSD Reaction Index brief screeners.

Results

Eighty-three adult patients participated in this study (mean [SD] age, 45.8 [14.3] years; 64 female, 19 male). Eighty-one pediatric patients participated (mean [SD] age, 13.83 [2.55] years; 67 female, 14 male). Adult and pediatric patients with ILO screened positive for elevated rates of anxiety (53 adults [63%]; 49 children [60%]), depression (27 adults [32%]; 25 children [30%]), and PTSD (29 adults [34%]; 13 children [16%]). Most of the patients with anxiety and depression symptoms were formally diagnosed prior to ILO evaluation, with rates of previously diagnosed anxiety, depression, and PTSD also above published norms. Adults were twice as likely as children to present with PTSD (odds ratio, 2.1; 95% CI, 0.05-4.48). Elevated rates of physical somatic symptoms were also evident, with 38 adults (45%) and 32 children (39%) scoring in the moderate to severe range.

Conclusions and Relevance

This study found high rates of adult and pediatric patients with ILO screened positive for anxiety, depression, and PTSD symptoms. Future work should investigate how behavioral health and ILO treatments can best be coordinated to maximize treatment outcomes.

Can flow proneness be protective against mental and cardiovascular health problems? A genetically informed prospective cohort study

Flow is a phenomenon where one experiences optimal challenge, marked by an intense, effortless, and rewarding concentration on a task. Past research shows that flow proneness is associated with good mental and cardiovascular health. However, this research has been primarily cross-sectional, based on self-report data, and has not controlled for potential confounding effects of neuroticism. In a large, longitudinal twin sample (N = 9361), we used nationwide patient registry data to test whether flow proneness predicted registry-based diagnoses of depression, anxiety, schizophrenia, bipolar disorder, stress-related disorders, or cardiovascular diseases. We used survival analyses taking time to diagnosis into account to test if (a) there is a relationship between flow proneness and health diagnoses over time, (b) neuroticism confounds this relationship, and (c) the relationship remains present within discordant monozygotic twin pairs (N = 952), thereby controlling for genetic and shared environmental confounding. Individuals with higher flow proneness had a decreased risk of receiving diagnoses for depression (16%; CI [14%, 18%]), anxiety (16%; CI [13%, 18%]), schizophrenia (15%; CI [4%, 25%]), bipolar (12%; CI [6%, 18%]), stress-related (9%; CI [9%, 12%]), and cardiovascular disorders (4%; CI [1%, 8%]). When controlling for neuroticism, higher flow proneness still decreased the risk of depression (6%; CI [3%, 9%]) and anxiety diagnoses (5%; CI [1%, 8%]). Monozygotic twins who experienced more flow than their co-twin had a lower risk for depression (16%; CI [5%, 26%]) and anxiety (13%; CI [1%, 24%]), though only the association with depression remained significant when also controlling for neuroticism (13%; CI [1%, 24%]). Findings are in line with a causal protective role of flow experiences on depression and potentially anxiety and highlight that neuroticism and familial factors are notable confounding factors in observed associations between flow proneness and health outcomes.

Glycitein prevents reserpine-induced depression and associated comorbidities in mice: modulation of lipid peroxidation and TNF-α levels

Depression is a debilitating mood disorder affecting millions worldwide and continues to pose a significant global health burden. Due to the multifaceted nature of depression, the current treatment regimens are not up to mark in terms of their multitargeting potential and least side effect profile. Molecules within the isoflavone class demonstrate promising potential in alleviating depression and associated conditions, offering a multifaceted approach to manage mental health concerns. Therefore, the current study was designed to explore the potential of glycitein, an isoflavone in managing reserpine-induced depression and associated comorbidities in mice. Reserpine (0.5 mg/kg; i.p.) administration for the first 3 days induced depression and associated comorbidities as evidenced by increased immobility time in forced swim test (FST) and tail suspension test (TST), along with reduced locomotor activity in the open field test (OFT) and increased latency to reach the platform in the Morris water maze (MWM) test. Reserpine treatment also upregulated and downregulated the brain thiobarbituric acid reactive substance (TBARS) and glutathione (GSH) levels, respectively. Furthermore, reserpine administration also uplifted the level of TNF-α in the serum samples. Glycitein (3 mg/kg and 6 mg/kg; p.o.) treatment for 5 days prevented the depressive effect of reserpine. It also improved the spatial memory at both dose levels. Moreover, in biochemical analysis, glycitein also reduced the brain TBARS and serum tumor necrosis factor-alpha (TNF-α) levels. Whereas, no significant effect was seen on the brain GSH level. Glycitein (6 mg/kg) was found to be more effective than the 3 mg/kg dose of glycitein. Overall results delineate that glycitein has the potential to manage depression and impaired memory by inhibiting lipid peroxidation and inflammatory stress.

The Role of Artificial Intelligence in Identifying Depression and Anxiety: A Comprehensive Literature Review

This narrative literature review undertakes a comprehensive examination of the burgeoning field, tracing the development of artificial intelligence (AI)-powered tools for depression and anxiety detection from the level of intricate algorithms to practical applications. Delivering essential mental health care services is now a significant public health priority. In recent years, AI has become a game-changer in the early identification and intervention of these pervasive mental health disorders. AI tools can potentially empower behavioral healthcare services by helping psychiatrists collect objective data on patients' progress and tasks. This study emphasizes the current understanding of AI, the different types of AI, its current use in multiple mental health disorders, advantages, disadvantages, and future potentials. As technology develops and the digitalization of the modern era increases, there will be a rise in the application of artificial intelligence in psychiatry; therefore, a comprehensive understanding will be needed. We searched PubMed, Google Scholar, and Science Direct using keywords for this. In a recent review of studies using electronic health records (EHR) with AI and machine learning techniques for diagnosing all clinical conditions, roughly 99 publications have been found. Out of these, 35 studies were identified for mental health disorders in all age groups, and among them, six studies utilized EHR data sources. By critically analyzing prominent scholarly works, we aim to illuminate the current state of this technology, exploring its successes, limitations, and future directions. In doing so, we hope to contribute to a nuanced understanding of AI's potential to revolutionize mental health diagnostics and pave the way for further research and development in this critically important domain.

Hypnosis with depressed children and teens: Building skills, creating connection

Depression in children and teens has been on the rise for several years. Recent increases in anxiety and loneliness, both contributors to the development of depression, are putting more young people at risk for chronic and comorbid mental health struggles. The use of hypnosis with depressed children offers the opportunity to target the identified skills depressed and anxious children need and is a modality clinicians should embrace. This article describes how to create hypnotic interventions focusing on improved emotional and cognitive management, better sleep, and the ability to make positive social connections. Such interventions serve to not only build the resources depressed children need for recovery, but also support a paradigm shift toward prevention in children and families.

A new network analysis model in anorexia nervosa patients based on self-reported eating disorder symptoms, psychological distress, and cognitive flexibility

OBJECTIVES

Cognitive flexibility and psychological distress, such as depression and anxiety, have been implicated in the aetiology of Anorexia Nervosa (AN). Despite the known associations between eating disorder (ED) symptoms, depression, anxiety, and cognitive flexibility, the specific pathways that connect these constructs are unclear. We therefore used network analysis to examine the relationship between these symptoms in an AN sample.

METHODS

One hundred and ninety-three treatment-seeking individuals diagnosed with AN (95.6% female, M = 26.89 [SD = 9.45] years old) completed self-report measures assessing depression, anxiety, cognitive flexibility, and ED symptoms. To determine each symptom's influence in the network, we calculated the expected influence.

RESULTS

The two relationships with the greatest edges were those between (1) weight/shape concerns and eating/dietary restraint and (2) weight/shape concerns and psychological distress (a measure that combined depression and anxiety). Cognitive flexibility was not connected to weight/shape concerns but had negative partial associations with eating concerns/dietary restraint and psychological distress. There was also a slight, non-zero connection between eating concerns/dietary restraint and psychological distress.

CONCLUSIONS

The findings underscore the importance of weight/shape, eating/dietary concerns, and psychological distress in the AN network and suggest that addressing cognitive flexibility may be a useful target for eating concerns/dietary restraint and psychological distress. Future studies assessing the longitudinal course of psychopathology within the AN network structure may help in identifying whether specific symptoms function as risk factors or maintaining factors for this co-occurrence.

Prevalence and coping of depression and anxiety among college students during COVID-19 lockdowns in China

BACKGROUND

This study sought to investigate the prevalence of anxiety, depression and mixed anxiety-depression disorder among college students during COVID-19 shelter-in-place lockdowns in China.

METHODS

Participants (N = 2818) were selected from 8 provincial regions across the country in areas that were under lockdown mandates. The dependent variables were anxiety and depression. Multiple regression models were tested using anxiety and depression as the respective outcome variables, and binary logistic regression was conducted with anxiety-depression comorbidity as the dependent variable. Explanatory variables were changes in (social) media use and communication behaviors, perceived effectiveness of daily activity involvements as well as a number of demographic and environmental factors.

RESULTS

Being a college senior, prior anxiety/depression history, having family members and residents in neighborhood tested positive with COVID were all important predictors of elevated anxiety, depression and their comorbidity. Increased face-to-face family communication and reading more e-books were associated with reduced anxiety, depression and their comorbidity. Listening to music and playing video games were correlated with lower anxiety but not depression.

CONCLUSIONS

Draconian shelter-in-place lockdowns as strictly enforced in China within a short notice could be detrimental to individual mental health and psychological well-being. Findings in this research can provide practical guidance for college counselors and health professionals in targeting particular segments of the student population in providing tailored psychological, therapeutic and material services during disruptive moments and public health crises. The central role of family communication in the emotional and social support process deserves critical contemplation.

Investigating Factors Associated with the Development of Postnatal Depression After Cesarean Delivery: A Validation Cohort Study

Purpose

This study aimed to validate a proposed association model previously published to determine the clinical relevance of pre-operative determinants in the development of PND after Cesarean delivery (CD).

Patients and Methods

Parturients undergoing elective CD under neuraxial anesthesia were recruited for a prospective cohort study between Oct 2021 and Oct 2022 at KK Women's and Children's Hospital, Singapore. Predelivery pain, psychological and mechanical temporal summation, and demographic data were recorded. A follow-up survey was conducted at 6 to 10 weeks after CD. The primary outcome was the incidence of PND, defined as an Edinburgh Postnatal Depression Scale (EPDS) score ≥ 10.

Results

A total of 180 patients were recruited for validation. PND 6 to 10 weeks post-delivery occurred in 18.9% of recruited parturients. Multivariate regression analyses showed that higher pre-operative CSI scores (p=0.0156), higher anxiety levels about upcoming surgery (p=0.0429), increased pre-operative pain scores on movement (p=0.0110), and higher pre-operative HADS subscale scores on anxiety (p=0.0041) were independently associated with the development of PND weeks post-CD. Lower anticipation of pain medication needs (p=0.0038) was independently associated with the development of PND post-CD. The area under curve (AUC) of this multivariable model (training cohort), internal cross validation (training cohort) and external cross validation (validation cohort) were 0.818 (95% CI, 0.746 to 0.889), 0.785 (95% CI, 0.707 to 0.864) and 0.604 (95% CI, 0.497 to 0.710) respectively.

Conclusion

The proposed model performed well in a local population. Further refinement is necessary to test the proposed model in populations with social and cultural differences.

Overreporting of adherence to hepatitis C direct-acting antiviral therapy and sustained virologic response among people who inject drugs in the HERO study

BACKGROUND

Self-reported adherence to direct-acting antivirals (DAAs) to treat hepatitis C virus (HCV) among persons who inject drugs (PWID) is often an overreport of objectively measured adherence. The association of such overreporting with sustained virologic response (SVR) is understudied. This study among PWID aimed to determine a threshold of overreporting adherence that optimally predicts lower SVR rates, and to explore correlates of the optimal overreporting threshold.

METHODS

This study analyzed per-protocol data of participants with adherence data (N = 493) from the HERO (Hepatitis C Real Options) study. Self-reported and objective adherence to a 12-week DAA regimen were measured using visual analogue scales and electronic blister packs, respectively. The difference (Δ) between self-reported and objectively measured adherence was calculated. We used the Youden index based on receiver operating characteristic (ROC) curve analysis to identify an optimal threshold of overreporting for predicting lower SVR rates. Factors associated with the optimal threshold of overreporting were identified by comparing baseline characteristics between participants at/above versus those below the threshold.

RESULTS

The self-reported, objective, and Δ adherence averages were 95.1% (SD = 8.9), 75.9% (SD = 16.3), and 19.2% (SD = 15.2), respectively. The ≥ 25% overreporting threshold was determined to be optimal. The SVR rate was lower for ≥ 25% vs. < 25% overreporting (86.7% vs. 95.8%, p <.001). The factors associated with ≥ 25% Δ adherence were unemployment; higher number of days and times/day of injecting drugs; higher proportion of positive urine drug screening for amphetamine, methamphetamine, and oxycodone, and negative urine screening for THC (tetrahydrocannabinol)/cannabis.

CONCLUSIONS

Self-reported DAA adherence was significantly greater than objectively measured adherence among PWID by 19.2%. Having ≥ 25% overreported adherence was associated with optimal prediction of lower SVR rates. PWID with risk factors for high overreporting may need to be more intensively managed to promote actual adherence.

A cross-sectional study on the analysis of the current situation of depression and anxiety among primary and secondary school students in Urumqi City in 2021: A case study of S district

BACKGROUND

Depression and anxiety in children and adolescents have become one of the major public health threats. This study aimed to provide a comprehensive and accurate understanding of the current status of depression and anxiety in primary and secondary school students in Urumqi and to provide a basis for early intervention in depressed and anxious individuals.

METHODS

All primary and secondary school students in 13 schools in the Urumqi S district were surveyed from March 2021 to November 2021, and depression and anxiety were screened using the Self-rating Depression Scale (SDS) and the Self-rating Anxiety Scale (SAS).

RESULTS

Overall, 17,086 students participated, with 16,462 valid questionnaires and an effective rate of 96.3%; the numbers of primary, middle, and high school students were 3351, 10,469, and 2642, respectively, with 8493 male students and 7969 female students. The overall depression and anxiety detection rates of primary and secondary school students were 10.74 % and 14.85 %, respectively; the depression detection rates were 5.97 %, 12.05 %, and 11.62 % in elementary, middle, and high schools, respectively=114.8, P < 0.001), while that of anxiety were 9.16 %, 16.75 %, and 14.53 %, respectively (x2=127.5, P < 0.001); the overall depression combined with anxiety detection rate was 8.61 %, and the depression combined with anxiety detection rates in elementary, middle, and high school were 0.95 %, 6.27 %, and 1.39 %, respectively=86.34, P < 0.001). SDS scores in elementary, middle, and high school were (33.21 ± 10.16), (36.66 ± 12.83), and (36.90 ± 11.97), respectively, and SAS scores were (39.64 ± 8.41), (41.88 ± 10.03), (40.71 ± 9.26), respectively. The depression and anxiety scores of primary and secondary school students in Urumqi were lower than those of domestic norm; female students in the middle school group had the highest depression and anxiety scores among all school periods. The SDS and SAS individual scores showed differences in the frequency of specific symptoms and subjective feelings of depression and anxiety among students of different sex and school periods. Depression and anxiety detection rates were highest in secondary school and lowest in primary school; the detection rates of depression and anxiety were significantly higher in female students than in male students. Depression and anxiety scores were significantly lower in the primary school group than in the middle and high school groups, and depression and anxiety levels were significantly higher in female than in male students in each academic period. Female students were 2.045 (95 % confidence interval [CI]: 1.845-2.267) and 2.006 (95 % CI: 1.835-2.193) times more likely to have symptoms of depression and anxiety than male students, respectively. Middle school students were 7.112 (95 % CI: 3.639-13.898) and 5.499 (95 % CI: 3.302-9.155) times and high school students were 7.504(95 % CI: 3.740-15.058) and 5.093 (95 % CI: 2.966-8.744) times more likely to have symptoms of depression and anxiety than elementary school students, respectively.

LIMITATIONS

The pandemic may have impacted the results of the study, and this study did not explore the influencing factors of anxiety and depression.

CONCLUSION

Depression and anxiety symptoms exist in some primary and secondary school students in S District, Urumqi.

Relationship between subjective and objective fatigue and sleep characteristics in individuals with anxiety and mood disorders: An exploratory study

OBJECTIVE

Fatigue and sleep disturbances are important symptoms of anxiety and mood disorders (AMD). Studies about the relationship between these variables usually rely on self-report assessments. Therefore, the aim of our exploratory study was to investigate the independent correlations between subjective and objective fatigue and sleep characteristics in individuals with AMD.

METHODS

In sum, 233 individuals with AMD attending a stress-related disorders day care unit (78.5 % females, mean age 39.0 years old) participated in a cross-sectional study. Participants completed the Patient Health Questionnaire-9, Generalized Anxiety Disorder-7, Multidimensional Fatigue Inventory-20, and Pittsburgh Sleep Quality Index self-report questionnaires, as well as an exercise capacity workload test for assessing objective fatigue and polysomnography monitoring for evaluation of sleep structure.

RESULTS

In individuals with AMD, exercise capacity workload was associated with lower percent of stage 1 sleep (β = - 0.17, p = 0.006), REM latency (β = -0.13, p = 0.042), and wake after sleep onset (β = -0.12, p = 0.039). General fatigue was associated with a higher percent of body movements (β = 0.12, p = 0.047), as well as mental fatigue was associated with a higher percent of body movements (β = 0.13, p = 0.029), and a higher score on the PSQI (β = 0.21, p = 0.002).

CONCLUSIONS

Objective sleep characteristics were associated with objective assessment of fatigue, while subjective sleep quality was associated with subjectively assessed mental fatigue.

Gender differences in brain region activation during verbal fluency task as detected by fNIRS in patients with depression

BACKGROUND

Gender plays a role in the mechanisms of depression, but fewer studies have focused on gender differences in the abnormal activation of brain regions when patients perform specific cognitive tasks.

METHODS

A total of 110 major depressive disorder (MDD) patients and 106 healthy controls were recruited. The relative change in oxygen-haemoglobin (oxy-Hb) concentration during the verbal fluency task were measured by a 52-channel near-infra-red spectroscopy (NIRS) system. Differences in brain region activation between patients and healthy controls and between genders of depression patients were compared.

RESULTS

MDD patients demonstrated significantly decreased [oxy-Hb] changes in the right inferior frontal gyrus (p = 0.043) compared to healthy controls. A marked increase in leftward functional language lateralisation in the inferior frontal gyrus was observed in the MDD group in contrast to the HC group (p = 0.039). Furthermore, female patients in the MDD group exhibited significant reductions in [oxy-Hb] changes in the right frontal region (specifically, the superior and middle frontal gyrus; p = 0.037) compared with male patients.

CONCLUSIONS

Gender impacts depression-related brain activation during cognitive tasks, potentially influencing depression's pathogenesis.

The anterior cingulate cortex controls the hyperactivity in subthalamic neurons in male mice with comorbid chronic pain and depression

Neurons in the subthalamic nucleus (STN) become hyperactive following nerve injury and promote pain-related responses in mice. Considering that the anterior cingulate cortex (ACC) is involved in pain and emotion processing and projects to the STN, we hypothesize that ACC neurons may contribute to hyperactivity in STN neurons in chronic pain. In the present study, we showed that ACC neurons enhanced activity in response to noxious stimuli and to alterations in emotional states and became hyperactive in chronic pain state established by spared nerve injury of the sciatic nerve (SNI) in mice. In naïve mice, STN neurons were activated by noxious stimuli, but not by alterations in emotional states. Pain responses in STN neurons were attenuated in both naïve and SNI mice when ACC neurons were inhibited. Furthermore, optogenetic activation of the ACC-STN pathway induced bilateral hyperalgesia and depression-like behaviors in naive mice; conversely, inhibition of this pathway is sufficient to attenuate hyperalgesia and depression-like behaviors in SNI mice and naïve mice subjected to stimulation of STN neurons. Finally, mitigation of pain-like and depression-like behaviors in SNI mice by inhibition of the ACC-STN projection was eliminated by activation of STN neurons. Our results demonstrate that hyperactivity in the ACC-STN pathway may be an important pathophysiology in comorbid chronic pain and depression. Thus, the ACC-STN pathway may be an intervention target for the treatment of the comorbid chronic pain and depression.

Influence of β-catenin signaling on neurogenesis in neuropsychiatric disorders: Anxiety and depression

It has been proven that stress, mainly in the early years of life, can lead to anxiety and mood problems. Current treatments for psychiatric disorders are not enough, and some of them show intolerable side effects, emphasizing the urgent need for new treatment targets. Hence, a better understanding of the different brain networks, which are involved in the response to anxiety and depression, may evoke treatments with more specific targets. One of these targets is β-catenin that regulates brain circuits. β-Catenin has a dual response toward stress, which may influence coping or vulnerability to stress response. Indeed, β-catenin signaling involves several processes such as inflammation-directed brain repair, inflammation-induced brain damage, and neurogenesis. Interestingly, β-catenin reduction is accompanied by low neurogenesis, which leads to anxiety and depression. However, in another state, this reduction activates a compensatory mechanism that enhances neurogenesis to protect against depression but may precipitate anxiety. Thus, understanding the molecular mechanism of β-catenin could enhance our knowledge about anxiety and depression's pathophysiology, potentially improving clinical results by targeting it. Herein, the different states of β-catenin were discussed, shedding light on possible drugs that showed action on psychiatric disorders through β-catenin.

Prospective exploration of the role of combined internalizing symptoms in self-reported memory among older adults during the COVID-19 pandemic

OBJECTIVES

A growing literature suggests depression and anxiety increase risk of cognitive decline. However, few studies have examined their combined effects on cognition, among older adults, especially during periods of high stress.

METHOD

Based on a sample of community dwelling older adults (N = 576), we evaluated the effects of pre-pandemic anxiety and depressive symptoms, obtained in September 2018, to changes in self-reported memory (SRM) assessed 3 months into the COVID-19 pandemic.

RESULTS

In separate models, we found participants with depression scores at least 1-SD above the mean and participants with anxiety scores at least 2-SD above the mean to report a significant decline in SRM. Moderation analyses revealed those with high depressive symptoms (at or above the mean) showed a decrease in SRM regardless of anxiety. The extent to which high pre-pandemic anxiety symptoms influenced SRM is dependent on whether pre-pandemic depression was at or above the mean.

CONCLUSIONS

Pre-pandemic depression predicted a decline in SRM regardless of anxiety. Moderation analyses revealed that the extent to which anxiety symptoms influenced SRM was dependent on depression being at or above the mean. Those with high anxiety and depression are at highest risk of experiencing cognitive consequences related to stressful exposures like COVID-19.

Anxiety and Depression in Adults With Congenital Heart Disease

BACKGROUND

A comprehensive understanding of adult congenital heart disease outcomes must include psychological functioning. Our multisite study offered the opportunity to explore depression and anxiety symptoms within a global sample.

OBJECTIVES

In this substudy of the APPROACH-IS (Assessment of Patterns of Patient-Reported Outcomes in Adults With Congenital Heart Disease-International Study), the authors we investigated the prevalence of elevated depression and anxiety symptoms, explored associated sociodemographic and medical factors, and examined how quality of life (QOL) and health status (HS) differ according to the degree of psychological symptoms.

METHODS

Participants completed the Hospital Anxiety and Depression Scale, which includes subscales for symptoms of anxiety (HADS-A) and depression (HADS-D). Subscale scores of 8 or higher indicate clinically elevated symptoms and can be further categorized as mild, moderate, or severe. Participants also completed analogue scales on a scale of 0 to 100 for QOL and HS. Analysis of variance was performed to investigate whether QOL and HS differed by symptom category.

RESULTS

Of 3,815 participants from 15 countries (age 34.8 ± 12.9 years; 52.7% female), 1,148 (30.1%) had elevated symptoms in one or both subscales: elevated HADS-A only (18.3%), elevated HADS-D only (2.9%), or elevations on both subscales (8.9%). Percentages varied among countries. Both QOL and HS decreased in accordance with increasing HADS-A and HADS-D symptom categories (P < 0.001).

CONCLUSIONS

In this global sample of adults with congenital heart disease, almost one-third reported elevated symptoms of depression and/or anxiety, which in turn were associated with lower QOL and HS. We strongly advocate for the implementation of strategies to recognize and manage psychological distress in clinical settings. (Patient-Reported Outcomes in Adults With Congenital Heart Disease [APPROACH-IS]; NCT02150603).

Postpartum symptoms of anxiety, depression and stress: differential relationships to women's cortisol profiles

PURPOSE

Women are at high risk of stress, anxiety, and depression during the postpartum but the ways in which these different types of psychological distress are related to cortisol regulation is not clear. We examined the distinct association of each type of distress with women's average cortisol level, cortisol awakening response (CAR), cortisol decline across the day (diurnal slope), and overall amount of cortisol secretion across the day (AUCG).

METHODS

At 6 months postpartum, a diverse group of 58 women completed measures of depression, anxiety, perceived stress, and life stressors. Each woman provided 4 salivary samples for cortisol assay from waking to bedtime on each of 2 consecutive days. Linear regressions were used to examine associations of stress, anxiety and depression to each of the 4 cortisol measures, controlling for number of stressful life events.

RESULTS

Depressive symptoms were associated with less of a rise in the CAR (β = -.46, p = 0.01), steeper diurnal slope (β = .51, p = 0.006), and higher average cortisol level (β = .42, p = .01). Women who met the clinical cutoff for an anxiety disorder had lower overall cortisol output (β = -.29, p = 0.03). Stress was not related to any cortisol metric.

CONCLUSIONS

Findings suggest that stress is less associated with cortisol alterations in the postpartum than are more severe types of psychological distress. Anxiety and depression may have distinct and opposite profiles of cortisol dysregulation. Results indicate that mental health assessment is critical even in the later postpartum so that interventions can be initiated to reduce emotional suffering and the risk of impaired cortisol regulation.

Do Self-Processes and Parenting Mediate the Effects of Anxious Parents' Psychopathology on Youth Depression and Suicidality?

To understand how anxious parents' global psychopathology increases children's risks for depression and suicidality, we tested mediational pathways through which parent global psychopathology was associated with youth depression and suicidality over a six-year period. Parents (n = 136) who had an anxiety disorder at baseline reported global psychopathology and youth internalizing problems. Youth did not have any psychiatric disorder at baseline and they reported self-esteem, perceived control, and perceived parental warmth and rejection at baseline and 1-year follow-up. At 6-year follow-up, youth depression and suicidality were assessed via multiple reporters including the self, parent, and/or an independent evaluator. Results showed that parental psychopathology had an indirect but not direct effect on youth depression and suicidality via perceived control. No associations were found for the other hypothesized mediators. Perceived control might be a transdiagnostic intervention target in depression and suicide prevention programs for youth exposed to parental anxiety.

Venciendo la Depresión: A Pilot Study of Telehealth-Delivered Behavioral Activation for Depressed Spanish-Speaking Latinxs

Latinxs are substantially impacted by depression. The research literature has documented barriers (e.g., stigma, limited English proficiency, and lack of transportation) contributing to the underutilization of behavioral health services among Spanish-speaking Latinxs (SSLs). Telehealth can be broadly defined as the provision of healthcare information and services through the use of telecommunications technology. Behavioral Activation (BA) has well established empirical support for reducing symptoms of depression among ethnic minority groups. The unprecedent challenges associated with accessing in-person behavioral health services during the COVID-19 pandemic have underscored the need to examine alternate methods for treatment delivery. Thus, the proposed study aimed to conduct a feasibility study to determine the viability of telehealth-delivered BA for SSLs. Twenty-five SSL participants met eligibility criteria and were enrolled in the intervention and 17 participants completed treatment. The majority of participants experienced significant improvements in depressive symptoms and positive affect. These treatment gains were sustained at one-month follow-up. The present study offers promising preliminary data to support the acceptability and feasibility of telehealth-delivered BA, with the potential to lessen barriers to care by offering readily accessible behavioral health services for depressed individuals in underserved communities.

Depression among Brazilian medical students exposed to remote learning and the role of scopophobia

Medical education was greatly affected by the COVID-19 pandemic, and remote teaching through lectures and classes through videoconferencing was heavily used. However, the need to use cameras led to scopophobia, which is the fear of being watched, which can lead to psychological symptoms. Despite the relevance and prevalence of depression and the increase in the use of cameras for learning, research evaluating the impact of scopophobia on students' mental health is surprisingly scarce. Hence, to fill up this gap, a cross-sectional study was carried out in medical schools in Brazil. To assess the presence of depressed mood, the Patient Health Questionnaire-9 (PHQ-9) was applied. We used logistic regression models to verify the associations. The overall prevalence of positive PHQ9 found in our study was 62%. By studying the factors associated with a high risk of scopophobia, we could identify that the PHQ was statistically associated with scopophobia (odds ratio 2.43 (confidence interval 1.11-5.26), adjusted p value = .0269). Also, a lower family income, a higher number of household inhabitants, and female gender were associated. These results suggest that scopophobia is associated with depression, leading us to believe that interventions to mitigate this risk in students are opportune, especially if targeted at lower-income students.

The Characteristics and HIV-Related Outcomes of People Living with Co-occurring HIV and Mental Health Conditions in the United States: A Systematic Review of Literature from 2016 to 2021

Considering advances in HIV prevention and treatment, jurisdictional efforts to end the HIV/AIDS epidemic, and reduced stigma towards people living with HIV infection and mental health conditions, the authors systematically reviewed studies published between 2016 and 2021 and identified 45 studies that met the eligibility criteria. The review found that stigma towards mental health conditions still acts as a barrier to accessing HIV treatment, which impacts treatment outcomes. Additionally, social determinants of health, such as housing instability and poverty, appear to impact mental health and, therefore, HIV-related outcomes. The review also highlighted the mutually reinforcing effects of HIV, mental health, and substance use conditions, providing valuable insights into the syndemic effects of these co-occurring conditions. Overall, the review highlights the need to address stigma and social determinants of health in HIV prevention and treatment efforts and to integrate mental health services into HIV care to improve outcomes for people living with both HIV and mental health conditions.

How do the sleep features that characterise depression impact memory?

Depression is associated with general sleep disturbance and abnormalities in sleep physiology. For example, compared with control subjects, depressed patients exhibit lower sleep efficiency, longer rapid eye movement (REM) sleep duration, and diminished slow-wave activity during non-REM sleep. A separate literature indicates that depression is also associated with many distinguishing memory characteristics, including emotional memory bias, overgeneral autobiographical memory, and impaired memory suppression. The sleep and memory features that hallmark depression may both contribute to the onset and maintenance of the disorder. Despite our rapidly growing understanding of the intimate relationship between sleep and memory, our comprehension of how sleep and memory interact in the aetiology of depression remains poor. In this narrative review, we consider how the sleep signatures of depression could contribute to the accompanying memory characteristics.

Anxiety and Depression Symptoms During the COVID-19 Pandemic: A Cluster Analysis of Individuals Living in Portugal

INTRODUCTION

The COVID-19 pandemic is an illustration of how a physical illness can damage people's minds. In this regard, the goal of this study was to see how different sociodemographic and behavioral factors were linked to anxiety and depression symptoms in a group of individuals living in Portugal.

METHODS

Between November 2020 and February 2021, a cross-sectional, snowball online study was conducted. The study's target population was adults over the age of 18, residents of the country. For the statistical analysis, the clustering technique - K-means algorithm was applied. The chi-squared test was used to determine the relationships between clusters and sociodemographic and behavioral characteristics. Statistical analyses were conducted in R language, with a significance level of 0.05. A total of 453 participants were included.

RESULTS

The majority were female (69.8%), under the age of 40 (60.8%), with a higher education degree (75.3%), and not married (54.4%). Furthermore, the majority were from the country's north region (66%). Cluster 1 (n = 194) was characterized by low or nonexistent levels of anxiety and depression symptoms, which means normal; cluster 2 by severe symptoms (n = 82), meaning case; and cluster 3 by mild symptoms (n = 177), which means borderline. Younger participants (p-value 0.024), female (p-value 0.041), with drinking habits (p-value 0.002), food insecurity (p-value < 0.001), food affordability exacerbation (p-value < 0.001), comorbidity (p-value < 0.001), use of anxiolytics (p-value < 0.001), insufficient household income (p-value 0.017) and income change (p-value < 0.001) were significantly associated with the anxiety-depression clusters. From the three clusters, cluster 2 was mainly represented by younger participants, with more persons stating that their household income was insufficient and that their income has changed as a result of COVID-19 and that they had the highest probability of food insecurity.

CONCLUSION

The impacts of a crisis on mental health extend longer than the event itself. We were able to observe that younger women with insufficient household income who suffered a change in income due to COVID-19 and were classified as food insecure presented higher levels of anxiety and depression symptoms. These results highlight the presence of a social gradient where we saw that people who were less advantaged in terms of socioeconomic position presented worse mental health outcomes, stressing, in this sense, the need to bring the best public health responses for these specific groups of the population.

Current prevalence and determinants of generalized anxiety disorder from a nationally representative, population-based survey of India

Introduction

Generalized anxiety disorder (GAD) is one of the common anxiety disorders leading to impairment and burden. However, GAD remains the least studied anxiety disorder. There is a need for nationally representative epidemiological data of GAD to understand the current burden and plan the mental health policies and programs to attain their unmet needs. Hence, this study focuses on epidemiology, socio-demographic correlates, disability, and treatment gap of GAD from India's National Mental Health Survey (NMHS) 2016.

Materials and Methods

NMHS 2016 was a nationally representative epidemiological survey of adult respondents from 12 states of India. NMHS is a multi-stage, stratified, random cluster sampling with random selection based on probability proportional to size at each stage. The Mini-International Neuropsychiatric Interview 6.0.0 used to diagnose psychiatric disorders. Sheehan disability scale was used to assess the disability. The current weighted prevalence of GAD was estimated. Association between GAD and socio-demographic factors was done using Firth's penalized logistic regression. The treatment gap and disability in GAD also calculated.

Results

The current weighted prevalence of GAD is 0.57%. The male gender and higher education groups have significantly lesser odds with current GAD. Urban metro and the married group have significantly higher odds with current GAD. The most common comorbid psychiatric disorders are depression (15.8%) followed by agoraphobia (9.4%). Among respondents with current GAD in the past 6 months across three domains, around 2/5th has mild and moderate disability, 1/10th has a severe disability, and 1/20th has an extreme disability. The overall treatment gap of current GAD is 75.7%.

Conclusion

NMHS 2016 has provided valuable insights into the epidemiology and burden of GAD among the general population. The available findings provide a glimpse of the current scenario in GAD to aid policymakers in targeting interventions.

Nationally representative epidemiological study of social anxiety disorder from India

Background

Social anxiety disorder (SAD), also termed as social phobia, is a disabling psychiatric condition with limited epidemiological research on it in India. This study, using data from the National Mental Health Survey (NMHS), 2016, is the first to explore its current prevalence and associated factors in India.

Materials and Methods

The NMHS in India used a comprehensive population-based study with subjects selected through a multistage stratified random cluster sampling technique across 12 states. The study included 34,802 adults interviewed with the Mini-International Psychiatric Interview 6.0.0. Firth penalized logistic regression (FPLR) was used to estimate covariate odds ratios (ORs), and the treatment gap for SAD and disability measured using Sheehan's disability scale was calculated.

Results

The study found a 0.47% prevalence of SAD, with an average age of 35.68 years (standard deviation (SD) = 15.23) among those affected. Factors, such as male gender, unemployment, and living in urban areas, were associated with higher odds of SAD, while the elderly had lower odds. A significant proportion of individuals with SAD experienced disability in work (63%), social life (77%), and family life (68%). They spent a median of ₹ 2500 per month on treatment and had a high rate of comorbid psychiatric disorders (58%). The treatment gap was substantial at 82%.

Conclusions

A considerable portion of India's population (approximately >65 lakhs) is affected by SAD. Surprisingly, the NMHS 2016 report indicates a higher risk of SAD among males compared with females, a trend that warrants further investigation. SAD in India is linked to significant disability and a considerable treatment gap, emphasizing the need for innovative approaches to address this large, affected population, especially in light of the scarcity of mental health professionals.

Screening for Psychological Distress in Healthcare Workers Using Machine Learning: A Proof of Concept

The purpose of this study was to train and test preliminary models using two machine learning algorithms to identify healthcare workers at risk of developing anxiety, depression, and post-traumatic stress disorder. The study included data from a prospective cohort study of 816 healthcare workers collected using a mobile application during the first two waves of COVID-19. Each week, the participants responded to 11 questions and completed three screening questionnaires (one for anxiety, one for depression, and one for post-traumatic stress disorder). Then, the research team selected two questions (out of the 11), which were used with biological sex to identify whether scores on each screening questionnaire would be positive or negative. The analyses involved a fivefold cross-validation to test the accuracy of models based on logistic regression and support vector machines using cross-sectional and cumulative measures. The findings indicated that the models derived from the two questions and biological sex accurately identified screening scores for anxiety, depression, and post-traumatic stress disorders in 70% to 80% of cases. However, the positive predictive value never exceeded 50%, underlining the importance of collecting more data to train better models. Our proof of concept demonstrates the feasibility of using machine learning to develop novel models to screen for psychological distress in at-risk healthcare workers. Developing models with fewer questions may reduce burdens of active monitoring in practical settings by decreasing the weekly assessment duration.

Exploring Patterns of COPD Exacerbations and Comorbid Flare-Ups

Background

Comorbidities are known to complicate disease management in patients with Chronic Obstructive Pulmonary Disease (COPD). This is partly due to lack of insight into the interplay of acute exacerbations of COPD (AECOPD) and comorbid flare-ups. This study aimed to explore patterns of AECOPDs and comorbid flare-ups.

Methods

Data of increased symptoms were extracted from a 12-month daily symptom follow-up database including patients with COPD and comorbidities (chronic heart failure (CHF), anxiety, depression) and transformed to visualizations of AECOPDs and comorbid flare-up patterns over time. Patterns were subsequently categorized using an inductive approach, based on both predominance (ie, which occurs most often) of AECOPDs or comorbid flare-ups, and their simultaneous (ie, simultaneous start in ≥ 50%) occurrence.

Results

We included 48 COPD patients (68 ± 9 years; comorbid CHF: 52%, anxiety: 40%, depression: 38%). In 25 patients with AECOPDs and CHF flare-ups, the following patterns were identified: AECOPDs predominant (n = 14), CHF flare-ups predominant (n = 5), AECOPDs nor CHF flare-ups predominant (n = 6). Of the 24 patients with AECOPDs and anxiety and/or depression flare-ups, anxiety and depression flare-ups occurred simultaneously in 15 patients. In 9 of these 24 patients, anxiety or depression flare-ups were observed independently from each other. In 31 of the included 48 patients, AECOPDs and comorbid flare-ups occurred mostly simultaneously.

Conclusion

Patients with COPD and common comorbidities show a variety of patterns of AECOPDs and comorbid flare-ups. Some patients, however, show repetitive patterns that could potentially be used to improve personalized disease management, if recognized.

Effects of GHRH Deficiency and GHRH Antagonism on Emotional Disorders in Mice

Growth hormone (GH)-releasing hormone (GHRH) has been suggested to play a crucial role in brain function. We aimed to further investigate the effects of a novel GHRH antagonist of the Miami (MIA) series, MIA-602, on emotional disorders and explore the relationships between the endocrine system and mood disorders. In this context, the effects induced by MIA-602 were also analyzed in comparison to vehicle-treated mice with GH deficiency due to generalized ablation of the GHRH gene (GHRH knock out (GHRHKO)). We show that the chronic subcutaneous administration of MIA-602 to wild type (+/+) mice, as well as generalized ablation of the GHRH gene, is associated with anxiolytic and antidepressant behavior. Moreover, immunohistochemical and Western blot analyses suggested an evident activation of Nrf2, HO1, and NQO1 in the prefrontal cortex of both +/+ mice treated with MIA-602 (+/+ MIA-602) and homozygous GHRHKO (-/- control) animals. Finally, we also found significantly decreased COX-2, iNOS, NFkB, and TNF-α gene expressions, as well as increased P-AKT and AKT levels in +/+ MIA-602 and -/- control animals compared to +/+ mice treated with vehicle (+/+ control). We hypothesize that the generalized ablation of the GHRH gene leads to a dysregulation of neural pathways, which is mimicked by GHRH antagonist treatment.

Validating the Unmind Index as a measure of mental health and wellbeing among adults in USA, Australia, and New Zealand

BACKGROUND

The Unmind Index is a 26-item, 7-subscale measure of mental health and wellbeing designed for use on the Unmind digital workplace mental health platform. The Unmind Index was developed and validated in the UK but is used internationally. This paper reports further psychometric validation of this measure for use in USA, Australia, and New Zealand (ANZ).

METHODS

Participants in four countries completed the Unmind Index and a battery of existing measures. In Study 1 (N = 770), we validated the Unmind Index separately in USA and in ANZ. In Study 2 (N = 600), we used multiple group confirmatory factor analysis to test the measurement invariance of the Unmind Index across the UK, USA, and ANZ.

RESULTS

Study 1 establishes the factor structure, reliability, convergent and discriminant validity, and measurement invariance by age and gender of the Unmind Index separately for USA and for ANZ. Study 2 further demonstrates measurement invariance across locations, and establishes benchmark scores by location, age, and gender.

CONCLUSIONS

We conclude that the Unmind Index is valid and reliable as a measure of mental health and wellbeing in these locations.

Higher physical activity level and perceived social support is associated with less psychological distress in people with anxiety

Introduction

Anxiety is one of the most prevalent mental illnesses in first world societies, generating discomfort in the people who suffer from it, and high expenses and economic losses in the society. The physical activity (PA) performed, together with the perceived social support (PSS) by people with anxiety could be related to the psychological distress of people with anxiety.

Objectives

To study the relationships between mental health and its dimensions, through Golberg's General Health Questionnaire (GHQ12), and the level of PA (PAL) and the PSS in the Spanish adult population with anxiety.

Hypothesis

A higher PAL, and a higher PSS, is related to a lower psychological distress in this population.

Design and Methodology

This study included 1,661 adults with anxiety, residents in Spain. It was a cross-sectional study with data obtained from the Spanish National Health Survey. A Kolmogorov-Smirnov test was applied to examine the data distribution of the variables. The median and interquartile range were used to characterize the sample for continuous variables, and absolute and relative frequencies were used for categorical variables. The Mann-Whitney U test was used to examine the differences between sexes. Dependence between PAL and sex was studied using the chi-square statistic. A Krustal-Wallis test was used to evaluate the existence of differences in the baseline medians on the GHQ-12, according to PAL level. Finally, the correlations between mental health and its dimensions with PAL and the Duke-UNC-11 scores were analysed, obtaining Spearman's rho and Pearson's correlation coefficient.

Results

Moderate inverse correlations were found between the GHQ-12 and: PAL (rho: -0.219); PSS (r: -0.347). PAL and PSS presented moderate inverse correlations with successful coping (rho: -0.206 and r: -0.325), self-esteem (rho: -0.222 and r: -0.333) and stress (rho: -0.158 and r: -0.288).

Conclusions

Greater PAL and social support are associated with reduced psychological distress in people with anxiety.

Sex differences in the symptom network structure of depression: Findings from a nationwide sample of the Spanish adult population

BACKGROUND

Sex differences in the prevalence and clinical features of depression have been widely described. However, some authors argue that categorical diagnostic systems do not adequately capture the complexity of depression. The aim of this study was to examine sex differences in the symptom network structure of depressive symptoms among individuals with a major depressive episode.

METHODS

The study sample consisted of 510 participants (age 62.17 ± 14.43, 71.96 % women) from a nationwide study of the Spanish non-institutionalised adult population (Edad con Salud). To estimate the presence of a 12-month major depressive episode according to DSM-IV criteria, participants were administered an adapted version of the Composite International Diagnostic Interview (CIDI 3.0). A network analysis was carried out to determine possible interrelationships between different depressive symptoms by sex.

RESULTS

Men and women showed a similar overall structure and network strength. However, sex-specific variations emerged in relation to individual symptom associations and symptom centrality. Specifically, for individual symptom associations "loss of confidence" and "suicide attempts" were more strongly related in women, and "suicidal ideation" and "impaired thinking" in men. For symptom centrality, "anxiety" played a central role in men's symptomatology, whereas "hopelessness", "loss of confidence", "distress" and "slowness of movement" were the most central symptoms in the women's group.

LIMITATIONS

Reliance on cross-sectional data precludes us from determining the direction and temporality of the association between different symptoms.

CONCLUSIONS

This study suggests that specific symptoms should be prioritised in the prevention, diagnosis assessment and treatment of depressed patients based on sex.

Comparing survival rates for clusters of depressive symptoms found by Network analysis' community detection algorithms: Results from a prospective population-based study among 9774 cancer survivors from the PROFILES-registry

OBJECTIVES

Previous studies have shown that depression is associated with mortality in patients with cancer. Depression is however a heterogeneous construct and it may be more helpful to look at different (clusters) of depressive symptoms than to look at depression as a discrete condition. The aim of the present study is to investigate whether clusters of depressive symptoms can be identified using advanced statistics and to investigate how these symptom clusters are associated with all-cause mortality in a large group of patients with cancer.

METHOD

Data from a large population-based cohort study (PROFILES) including various cancer types were used. Eligible patients completed self-report questionnaires (i.e. Fatigue assessment scale, Hospital anxiety and depression scale, EORTC QOL-C30) after diagnosis. Survival status was determined on 31 January 2022.

RESULTS

In total, 9744 patients were included. Network analyses combining different community detection algorithms showed that clusters of depressive symptoms could be detected that correspond with motivational anhedonia, consummatory anhedonia and negative affect. Survival analyses using the variables that represented these clusters best showed that motivational and consummatory anhedonia were associated with survival. Even after controlling for clinical and sociodemographic variables items assessing motivational anhedonia were significantly associated with mortality over time.

CONCLUSION

Separate clusters of symptoms that correspond with motivational and consummatory anhedonia and negative affect can be distinguished and anhedonia may be associated with mortality more than negative affect. Looking at particular (clusters of) depressive symptoms may be more informative and clinically relevant than using depression as a single construct (i.e. syndrome).

Associations between paternal versus maternal parenting behaviors and child and adolescent internalizing problems: A systematic review and meta-analysis

There is a large evidence base supporting an important role of parenting behavior in influencing youth mental health; however, this literature often fails to capture the potentially unique and interactive role of mothers and fathers. This systematic review and meta-analysis aimed to investigate the role of maternal and paternal parenting behaviors in relation to child and adolescent internalizing problems. Following PRISMA (2020) guidelines, 88 studies were identified. Of these, 47 studies and upward of 65 parent-behavior and child-outcome combinations were examined. Findings indicated a unique role of maternal overprotection in the prediction of child anxiety symptoms. For other parenting behaviors, largely similar associations were found for maternal and paternal parenting behaviors with child and adolescent anxiety, depressive symptoms and broader internalizing problems. There was preliminary support for the interaction of maternal and paternal parenting being important in predicting youth symptoms. Although findings did not strongly substantiate differences in the effects of maternal and paternal parenting practices, with only one significant difference identified, further research would benefit from stronger representation of fathers, to enable a more rigorous and comprehensive understanding of each parent's role, and their interactive influence on internalizing outcomes of their children.

Increased risk of depression in patients with discoid lupus erythematosus: a nested, case-control study in the All of Us Research Program

In this nested case–control study, we found a twofold increased risk of major depressive disorder in patients with discoid lupus erythematosus (DLE) vs. controls without DLE, using the All of Us database, a National Institutes of Health (USA) research programme that prioritizes recruitment from demographic groups under-represented in biomedical research. This is the first large-scale study of this association in a heterogeneous population and highlights the importance vigilance regarding the increased risk of depression in patients with DLE.

Intermittent Fasting as a Potential Therapeutic Instrument for Major Depression Disorder: A Systematic Review of Clinical and Preclinical Studies

Recent studies have reported positive effects of Intermittent Fasting (IF) on metabolic parameters, cognition, and mood. However, regarding depressive symptoms, the effect of IF is not clear. The purpose of this review was to assess the available evidence on IF interventions for depression in both clinical and preclinical studies. Of the 23 included studies, 15 were performed on humans and 8 on animal models. The studies on rodents suggested that IF acts as a circadian regulator, improving neurotransmitter availability and increasing the levels of neurotrophic factors in the brain. However, the investigations on humans mainly evaluated healthy volunteers and showed a great heterogeneity regarding both the IF regimen studied and the observed effects on mood. Most available clinical trials have specific limitations, such as small sample sizes and uncontrolled designs. A comprehensive systematic review was conducted on five databases, PubMed, Cochrane, the Central Register of Controlled Trials, Web of Science databases, BVS and Scopus, identifying 23 relevant studies up to 6 October 2022. IF has potentially relevant physiological effects for the treatment of mood disorders, but better designed studies and controlled evaluations are needed to evaluate its efficiency in the treatment of major depression.

Income inequality and mental health in adolescents during COVID-19, results from COMPASS 2018-2021

INTRODUCTION

Understanding the inequitable impacts of the ongoing COVID-19 pandemic on youth mental health are leading priorities. Existing research has linked income inequality in schools to adolescent depression, however, it is unclear if the onset of the pandemic exacerbated the effects of income inequality on adolescent mental health. The current study aimed to quantify the association between income inequality and adolescent mental health during COVID-19.

MATERIAL AND METHODS

Longitudinal data were taken from three waves (2018/19 to 2020/21) of the Cannabis, Obesity, Mental health, Physical activity, Alcohol, Smoking, and Sedentary behaviour (COMPASS) school-based study. Latent Growth Curve modelling was used to assess the association between Census District (CD)-level income inequality and depressive symptoms before and after the onset of COVID-19.

RESULTS

The study sample included 29,722 students across 43 Census divisions in British Columbia, Alberta, Ontario, and Quebec. The average age of the sample at baseline was 14.9 years [standard deviation (SD) = 1.5] and ranged between 12 and 19 years of age. Most of the sample self-reported as white (76.3%) and female (54.4%). Students who completed the COMPASS survey after the onset of COVID reported 0.20-unit higher depressive scores (95% CI = 0.16, 0.24) compared to pre-COVID. The adjusted analyses indicated that the association between income inequality on anxiety scores was strengthened following the onset of COVID-19 (β = 0.02, 95% CI = 0.0004, 0.03), indicating that income inequality was associated with a greater increase in anxiety scores during COVID-19.

DISCUSSION

The adjusted results indicate that the association between income inequality and adolescent anxiety persisted and was heightened at the onset of COVID-19. Future studies should use quasi-experimental methods to strengthen this finding. The current study can inform policy and program discussions regarding the effects of the COVID-19 pandemic and pandemic recovery for young Canadians and relevant social policies for improving adolescent mental health.

Subjective social status and functional and mobility impairments among older adults: life satisfaction and depression as mediators and moderators

BACKGROUND

While functional and mobility impairments (FMIs) have garnered the attention of health researchers in low and middle-income countries (LMICs), including India, research has yet to explore whether and to what extent the perception of one's social status is associated with FMIs. We fill this gap in the literature by examining (1) the association between subjective social status (SSS) and FMIs among older adults in India and (2) whether this association between SSS and FMIs is mediated and moderated by life satisfaction and depression.

METHODS

Data come from the 2017-18 wave 1 of the Longitudinal Aging Study in India (LASI) with a sample of 31,464 older adults aged 60 years and above. FMIs were assessed using established scales on impairments in activities of daily living (ADLs), instrumental activities of daily living (IADLs), and mobility. SSS was assessed using the Macarthur scale. Life satisfaction was measured using responses to five statements gauging respondent's overall satisfaction with life. Depression was calculated using the shortened version of the Composite International Diagnostic Interview (CIDI-SF). Multivariable regression was employed to examine the association between variables, and the interaction terms and Karlson-Holm-Breen (KHB) method were used separately to test the mediation and moderation effects.

RESULTS

39.11% of the sample had a low SSS, 8.26% were depressed, and 32.07% reported low life satisfaction. A total of 8.74%, 10.91%, and 8.45% of the study population reported at least one impairment in ADL, IADL, and mobility, respectively. Older adults in the higher SSS group were less likely to have ADL impairment (beta: -0.017, CI: -0.030, -0.0032) and mobility impairment (beta: -0.044, CI: -0.076, -0.013). Depression moderated the association between SSS and mobility impairment (p-value: 0.025), and life satisfaction moderated the association between SSS and ADL impairments (p-value: 0.041) and SSS and IADL impairments (p-value: 0.037). Depression mediated 20.28%, 31.88%, and 18.39% of the associations of SSS with ADL, IADL, and mobility impairments, respectively. Similarly, life satisfaction mediated 23.24%, 52.69%, and 27.22% of the associations of SSS with ADL, IADL, and mobility impairments.

CONCLUSIONS

That SSS is associated with FMIs among older Indians, even after considering their objective socioeconomic status (SES), suggests that the use of SSS is relevant to the study of health inequalities in India. The finding that life satisfaction and depression mediate and moderate this association is crucial in pinpointing those older Indians at risk of the functional and mobility-related repercussions of lower SSS.

Mental health, study skills, social support, and barriers to seeking psychological help among university students: a call for mental health support in higher education

Introduction

Poor mental health among youths is a complex worldwide issue. Many countries with medium-to-low levels of development, particularly those in Southern Europe, have not introduced appropriate mental health and educational strategies to identify the key factors influencing wellbeing, promote psychological wellbeing, and prevent poor mental health among youths. In response to these trends, we sought to uncover insights for developing interventions for youth mental wellbeing. We assessed mental health, study skills, barriers to seeking psychological help, and perceived social support among Kosovar university students, and investigated their experiences with professional mental health services and their needs and perceptions regarding the importance of professional mental health services on campus.

Methods

The study used a parallel mixed-methods design. Participants included 234 university students. Quantitative data were gathered through validated questionnaires, including the Depression, Anxiety, and Stress Scale, Multidimensional Scale of Perceived Social Support, Academic Anxiety Scale, Study Skills Assessment Questionnaire, and the Barriers to Seeking Psychological Help Scale. Qualitative data on the students' experiences with mental health services and their perceptions regarding the importance of professional university mental health services were explored through open-ended questions.

Results

Most students experienced anxiety and depression, more than half were stressed, and most reported poor or moderate study skills. Lack of trust in mental health professionals was a major barrier to seeking psychological help, followed by difficulties in self-disclosure. Perceived social support and academic anxiety were significant predictors of barriers to seeking psychological help. The participants believed that mental health and academic support from the university would help improve their mental wellbeing, study skills, self-esteem, self-perception, and attitudes toward social support; raise awareness regarding mental health; and help them overcome personal and academic challenges.

Discussion

Our findings highlight the need for more comprehensive and accessible mental health services on campuses. By providing adequate support and resources to address various personal and academic factors that contribute to mental health issues in university students, universities can enhance students' academic success and personal growth.

Exploring Adaptive Graph Topologies and Temporal Graph Networks for EEG-Based Depression Detection

In recent years, Graph Neural Networks (GNNs) based on deep learning techniques have achieved promising results in EEG-based depression detection tasks but still have some limitations. Firstly, most existing GNN-based methods use pre-computed graph adjacency matrices, which ignore the differences in brain networks between individuals. Additionally, methods based on graph-structured data do not consider the temporal dependency information of brain networks. To address these issues, we propose a deep learning algorithm that explores adaptive graph topologies and temporal graph networks for EEG-based depression detection. Specifically, we designed an Adaptive Graph Topology Generation (AGTG) module that can adaptively model the real-time connectivity of the brain networks, revealing differences between individuals. In addition, we designed a Graph Convolutional Gated Recurrent Unit (GCGRU) module to capture the temporal dynamical changes of brain networks. To further explore the differential features between depressed and healthy individuals, we adopt Graph Topology-based Max-Pooling (GTMP) module to extract graph representation vectors accurately. We conduct a comparative analysis with several advanced algorithms on both public and our own datasets. The results reveal that our final model achieves the highest Area Under the Receiver Operating Characteristic Curve (AUROC) on both datasets, with values of 83% and 99%, respectively. Furthermore, we perform extensive validation experiments demonstrating our proposed method's effectiveness and advantages. Finally, we present a comprehensive discussion on the differences in brain networks between healthy and depressed individuals based on the outputs of our final model's AGTG and GTMP modules.

Abnormal multi-layered dynamic cortico-subcortical functional connectivity in major depressive disorder and generalized anxiety disorder

Comorbidity has been frequently observed between generalized anxiety disorder (GAD) and major depressive disorder (MDD), however, common and distinguishable alterations in the topological organization of functional brain networks remain poorly understood. We sought to determine a robust and sensitive functional connectivity marker for diagnostic classification and symptom severity prediction. Multi-layered dynamic functional connectivity including whole brain, network-node and node-node layers via graph theory and gradient analyses were applied to functional MRI resting-state data obtained from 31 unmedicated GAD and 34 unmedicated MDD patients as well as 33 age and education matched healthy controls (HC). GAD and MDD symptoms were assessed using Penn State Worry Questionnaire and Beck Depression Inventory II, respectively. Three network measures including global properties (i.e., global efficiency, characteristic path length), regional nodal property (i.e., degree) and connectivity gradients were computed. Results showed that both patient groups exhibited abnormal dynamic cortico-subcortical topological organization compared to healthy controls, with MDD > GAD > HC in degree of randomization. Furthermore, our multi-layered dynamic functional connectivity network model reached 77% diagnostic accuracy between GAD and MDD and was highly predictive of symptom severity, respectively. Gradients of functional connectivity for superior frontal cortex-subcortical regions, middle temporal gyrus-subcortical regions and amygdala-cortical regions contributed more in this model compared to other gradients. We found shared and distinct cortico-subcortical connectivity features in dynamic functional brain networks between GAD and MDD, which together can promote the understanding of common and disorder-specific topological organization dysregulations and facilitate early neuroimaging-based diagnosis.

Network Analysis of Depression Using Magnetoencephalogram Based on Polynomial Kernel Granger Causality

Depression is a psychiatric disorder characterized by anxiety, pessimism, and suicidal tendencies, which has serious impact on human's life. In this paper, we use Granger causality index based on polynomial kernel as network node connectivity coefficient to construct brain networks from the magnetoencephalogram (MEG) of 5 depressed patients and 11 healthy individuals under positive, neutral, and negative emotional stimuli, respectively. We found that depressed patients had more information exchange between the frontal and occipital regions compared to healthy individuals and less causal connections in the parietal and central regions. We further analyzed the topological properties of the network revealed and found that depressed patients had higher average degrees under negative stimuli (p = 0.008) and lower average clustering coefficients than healthy individuals (p = 0.034). When comparing the average degree and average clustering coefficient of the same sample under different emotional stimuli, we found that depressed patients had a higher average degree and average clustering coefficient under negative stimuli than neutral and positive stimuli. We also found that the characteristic path lengths of patients under negative and neutral stimuli significantly deviated from small-world network. Our results suggest that the analysis of polynomial kernel Granger causality brain networks can effectively characterize the pathology of depression.