Depression and Anxiety最新文献

Introduction: Anxiety disorders are among the most prevalent mental illnesses worldwide, with a 12-month prevalence rate of 14%–15.3%. Prior research has demonstrated a correlation between unemployment and impaired mental health. The primary objective of this study is to examine the relationship between anxiety and employment status in Germany.

Methods: The sample consisted of 4885 working-age participants (18–65 years) from the baseline survey of a population-based cohort study. Anxiety was assessed using the General Anxiety Disorder Scale-7 (GAD-7). Employment status was divided into four groups: full-time employment (FTE group), part-time employment (PTE group), ALG I (ALG I group, being unemployed receiving entitlement-based benefits), and ALG II (ALG II group, being unemployed receiving means-tested benefits). Negative binomial regressions were conducted to examine the association between anxiety, employment status, sociodemographic variables (age, sex, marital status, and education), and social resources (Lubben Social Network Scale 6 [LSNS-6]).

Results: The prevalence of anxiety symptoms (FTE group: 5.0%, PTE group: 4.8%, ALG I group: 2.7%, and ALG II group: 17.6%) differed between employment status groups. The ALG II group exhibited a markedly elevated prevalence compared to all other groups (p  < 0.001). The prevalence of anxiety symptoms was higher among females in the FTE group (7.6%) compared to males (2.9%) in the same category (p  < 0.001). The initial regression model indicated a statistically significant association between anxiety symptoms and the ALG II group (p  < 0.001) and the PTE group (p = 0.006). After including additional variables, this effect maintained its statistical significance. Factors associated with a higher risk of anxiety symptoms were female sex (p  < 0.001), low educational level (p = 0.007), and less social resources (p  < 0.001).

Conclusion: Unemployed individuals who receive ALG II are at the highest risk of developing anxiety symptoms among those who are able to work. These findings suggest the need for targeted psychosocial and occupational support for unemployed individuals receiving ALG II.

Suicide is the leading cause of death in people between 15 and 29 years of age, and its increase is worrying. Compared to other disciplines, university students of Health Sciences present a higher risk of suicidal ideation. The aim of this research was to identify which factors are associated with suicidal ideation in these students. A total of 412 university students from different Health Sciences specialties participated. The results indicate that higher levels of self-esteem, resilience, and perceived efficacy are associated with less suicidal ideation, while presenting more exhaustion, cynicism, stress, anxiety, and depression is related to a higher frequency of suicidal thoughts. Not seeking information about suicide and being in the first or second year were associated with more suicidal ideation. Not consuming alcohol or having close experiences of suicide was associated with less suicidal ideation. The profile of the university student with more suicidal ideation is one with high scores in depression and anxiety, and low scores in self-esteem. It is expected that these data can be considered in future suicide prevention programs.

Background and Objective: Generalized anxiety disorder (GAD) is a prevalent mental health condition affecting cognitive functions like response inhibition. The neural mechanisms underlying the interplay between inhibitory ability and anxiety regulation in GAD remain unclear. This study aimed to investigate the prefrontal cortex (PFC) alterations when anxiety regulation shares neural resources with response inhibition in patients with GAD compared to healthy controls and to explore the relationship between anxiety and PFC activity.

Methods: The hemodynamic responses of bihemispheric PFC were measured in 19 GAD patients and 38 healthy controls using functional near-infrared spectroscopy (fNIRS) during the Go/No-Go task and were compared between the groups. The correlations between PFC activity and task performance and those between PFC activity and anxiety levels were analyzed.

Results: The GAD group exhibited lower hemoglobin concentration across the PFC during both baseline and task sessions, with significant hypoactivity in the bihemispheric dorsomedial PFC (DMPFC) at baseline (p = 0.035–0.049), and more widespread hypoactivity during the task in the bihemispheric DMPFC (p < 0.001–0.033) and dorsolateral PFC (DLPFC; p = 0.012–0.042), as well as the right ventromedial PFC (VMPFC; p = 0.019–0.037). Higher baseline prefrontal activity was associated with poorer task accuracy (r = −0.576 to −0.417) and greater trait anxiety (r = 0.441–0.514). When transitioning to the task, better accuracy correlated with increased activation in the left DMPFC (r = 0.405–0.593), whereas higher anxiety levels were linked to reduced activation in the left DMPFC (r = −0.512) and right DMPFC (r = −0.435).

Conclusion: This study reveals that patients with GAD exhibit significant hypoactivity in the PFC during response inhibition, correlating with both task performance and anxiety levels. These findings emphasize the importance of targeting PFC dysfunction in the development of diagnostic tools and therapeutic interventions for GAD.

Objective: Nursing students’ perceptions of obstetric violence and moral sensitivity can affect their pre-pregnancy fear of childbirth levels. This study was conducted to examine the relationship between nursing students’ moral sensitivity, perception of obstetric violence, and pre-pregnancy fear of childbirth.

Methods: The research was designed as a cross-sectional study. This study was conducted between November 1, 2024, and November 15, 2024, with the participation of 315 nursing students. Data were collected face-to-face using the Personal Information Form, Pre-pregnancy Fear of Childbirth Scale, Obstetric Violence Perception Scale, and Moral Sensitivity Questionnaire (MSQ). Ethical committee approval and institutional permission were obtained before starting the study. Parametric data were analyzed using t-tests and one-way ANOVA, while nonparametric tests were analyzed using the Mann–Whitney U test and Kruskal–Wallis test. Pearson correlation analysis and linear regression analysis were also conducted. Statistical significance was set at p  < 0.05.

Results: The average age of the students included in the study was 21.67 ± 1.37, with 50.5% being 4th-year students, 79.7% being female, and 66% choosing nursing as their profession voluntarily. It was determined that 66% of the participants preferred vaginal birth, 38.1% had previously heard the term obstetric violence, 18.1% had witnessed someone being subjected to obstetric violence, and 89.2% thought that nurses or midwives needed communication knowledge and skills. A weak correlation was found between the Pre-pregnancy Fear of Childbirth Scale and the Obstetric Violence Perception Scale (r = 0.134, p = 0.018). It was also determined that the predictor of pre-pregnancy fear of childbirth was the students’ perception of obstetric violence (R = 0.170, R² = 0.028, p = 0.013).

Conclusion: The study concluded that the perception of obstetric violence is a predictor of pre-pregnancy fear of childbirth. Additionally, a negative and weak relationship was found between students’ moral sensitivity scores and ‘intrapartum mistreatment.

Background: Depressive symptoms in older adults are associated with adverse psychosocial outcomes. Understanding how depressive symptoms interrelate can enhance intervention strategies. While network analysis has advanced our comprehension of depressive symptom structure, few studies have explored dynamic interactions in older populations. This study examined both cross-sectional and longitudinal networks of depressive symptoms in older adults to identify core symptoms and symptom interactions over time.

Methods: Participants aged 60 and older with complete two-wave data (baseline: 2018; follow-up: 2020) from the China Health and Retirement Longitudinal Study (CHARLS) were included (N = 6621). Depressive symptoms were assessed using the 10-item Center for Epidemiologic Studies Depression Scale (CESD-10), administered face-to-face by trained interviewers. Cross-sectional networks were estimated using the Ising model for each time point, and a cross-lagged panel network (CLPN) model was applied to examine longitudinal symptom interactions over time. Network accuracy and stability were assessed through bootstrap procedures.

Results: Participants had a mean age of 67.34 years, 52% male, and 93.7% Han ethnicity. “Felt depressed” (r_s = 1.244 at Wave 1, r_s = 1.251 at Wave 2) demonstrated the highest strength centrality in both cross-sectional networks. Node strength exhibited strong stability (correlation stability [CS]-coefficient = 0.75 for both waves). The presence of edges (φ = 0.802; p < 0.001) and edge weights (ρ = 0.921, p < 0.001) across two cross-sectional networks showed high reproducibility. In the longitudinal network, “lack of happiness” showed the highest out-expected influence (out-EI; r = 1.404), followed by “felt depressed” (r = 0.994). Both in-expected influence (in-EI) and out-EI showed acceptable stability (CS-coefficient = 0.594).

Conclusions: Targeting core symptoms, such as “felt depressed” and “lack of happiness” may disrupt depressive symptom networks and reduce overall depression severity, informing precision interventions in older adults. Clinicians could prioritize these symptoms in screening and treatment. Future research should explore whether symptom-targeted interventions can reshape network structures over time.

Systemic inflammation is associated with depression. Certain oral bacterial species contribute to inflammation; however their potential association with mental disorders remains unclear. This study investigated the associations between oral microbiota pathogens and depressive and anxiety symptoms. Data came from 436 men from the Geelong Osteoporosis Study. Oral microbiota was characterized using 16S rRNA sequencing, and an oral pathogen composite was created comprising Porphyromonas gingivalis, Treponema denticola, Fusobacterium nucleatum, and Prevotella nigrescens species relative abundances. Binary variables were created representing elevated depressive and anxiety symptoms using the Hospital Anxiety and Depression Scale. Logistic regression was used to investigate associations between oral pathogens and elevated depressive/anxiety symptoms. Models were adjusted for confounders: age, socioeconomic status, diet, smoking, alcohol, exercise, obesity, and hypertension. We report a modest (nonsignificant) association between the pathogen composite and elevated depressive (OR 1.35 [95% CI 0.974, 1.87]) but not anxiety symptoms. Moreover, some of the comprising species were significantly associated with elevated depressive symptoms, including P. nigrescens (1.61 [1.21, 2.13]). Our exploratory analyses revealed that several other taxa were significantly associated with depression and anxiety symptoms. The findings suggest that specific oral bacteria may contribute to symptoms of depression, warranting further research through larger and longitudinal investigations.

Objective: While traditional psychometric approaches, such as latent variable modeling, have primarily focused on the association between bedtime procrastination and anxiety, they often fail to capture symptom-level temporal and directional relationships. Therefore, this study aims to explore the temporal dynamics of symptom-level associations between bedtime procrastination and anxiety, examining both within-person and between-person variations over time in an adolescent population.

Methods: This study utilized panel data-based network analyses to examine both within-person effects (temporal and contemporaneous networks) and between-person dynamics across 3,296 adolescents. Specifically, we examined symptom-to-symptom associations of bedtime procrastination and anxiety using both cross-sectional and temporal network analyses and assessed the symptom centrality to identify key drivers of symptom dynamics.

Results: At the within-person level, the temporal network analysis indicated that restlessness (GAD5) was the most stable and predictive node across time. Additionally, nervousness (GAD1) and going to bed later than intended (BPS1) had the most significant influence on other symptoms in the T1→T2 and T2→T3 networks, respectively. In the contemporaneous network, inability to control worry (GAD2), excessive worry (GAD3), and trouble relaxing (GAD4) were identified as the central symptoms. At the between-person level, positive relationships between specific bedtime procrastination symptoms were consistently observed.

Conclusions: Our findings elucidate the potential complex interactions between bedtime procrastination and anxiety symptoms, highlighting central symptoms that vary across temporal and contemporaneous networks. The identification of central symptoms and their dynamic associations within these networks can inform the causal mechanisms underlying bedtime procrastination and anxiety, thereby guiding the design of targeted interventions for adolescents.

Objective: This study aimed to investigate the pathways of emotional suppression among women aged 35 years and older undergoing in vitro fertilization-embryo transfer (IVF-ET) and to provide a theoretical basis for developing personalized programs to reduce emotional suppression.

Methods: A convenience sample of 225 women aged ≥35 years undergoing IVF-ET at a reproductive centre between May 1st and September 30th, 2023, was selected. The participants completed a self-designed general information questionnaire, the Emotional Inhibition Scale (EIS), the Locke-Wallace Marriage Adjustment Test (MAT), and the Self-Compassion Scale (SCS). Data were analysed using SPSS 27.0 and AMOS 24.0. Normality and homogeneity of variance were assessed, with normally distributed data described as mean ± standard deviation (SD). Pearson correlation, structural equation modeling (SEM), and bootstrap resampling (5000 iterations, 95% confidence intervals [CIs]) were employed to test the mediation effects, with a bootstrap analysis used to assess the stability and significance of indirect effects through repeated sampling.

Results: The cohort comprised predominantly Han Chinese (82.2%), first-married (60.9%), urban-dwelling (60.4%) women with secondary infertility (68.0%). Over 40.0% of the total held a tertiary educational level, and 67.1% reported per capita monthly income of the family (3001–10,000 RMB). The mean emotional suppression score was 28.65 ± 6.74. Emotional suppression was negatively correlated with marital adjustment (r = −0.442, p  < 0.01) and self-compassion (r = −0.393, p  < 0.01). SEM with bootstrap validation demonstrated that marital adjustment mediated the relationship between emotional suppression and self-compassion (mediating effect proportion: 24.89%, 95% CI: −0.115 to −0.027).

Conclusion: Marital adjustment mediates emotional suppression and self-compassion in women aged ≥35 years undergoing IVF-ET. Fostering positive marital dynamics may alleviate emotional suppression and enhance self-compassion, promoting psychological resilience during treatment. These findings support targeted interventions to improve patient satisfaction and treatment success rates.

Background: Anxiety disorders pose a considerable global health challenge, ranking as the most prevalent type of mental illness. This study delineates the trends in incidence, prevalence, and years lived with disability (YLDs) for anxiety disorders at global, regional, and national levels between 1992 and 2021, with an emphasis on the independent effects of age, period, and birth cohort.

Methods: Incidence, prevalence, and YLDs were selected as burden indicators of anxiety disorders, following the standardized methodologies of the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021, with data presented as numerical counts and age-standardized rates (ASRs) per 100,000 population. An age-period-cohort (APC) model was applied to estimate the overall annual percentage change (net drift), annual percentage change within each age group (local drift), and the relative risks associated with age, period, and cohort.

Results: From 1992 to 2021, the global age-standardized incidence rate (ASIR), age-standardized prevalence rate (ASPR) and age-standardized YLDs rate (ASYR) for anxiety disorders showed an overall increase. The APC model estimated a global net drift of 0.16% (95% confidence interval [CI]: 0.03%, 0.30%) for incidence, 0.07% (95% CI: 0.02%, 0.12%) for prevalence, and 0.07% (95% CI: 0.01%, 0.12%) for YLDs. Regionally, the highest ASIR, ASPR, and ASYR were recorded in the high SDI region in 2021, with the Region of the Americas (AMR) showing the highest rates across all three metrics. Among 204 countries/territories, Portugal, Brazil, Lebanon, Iran, and Paraguay ranked as the top five highest for ASIR, ASPR, and ASYR. The age effects on incidence, prevalence, and YLDs followed similar global and regional patterns, with risk initially increasing before declining in older age. The most substantial increase in the period risk of incidence from 1992 to 2021 occurred in high SDI and AMR countries, while prevalence and YLDs saw the largest rise in low-middle SDI region and AMR. A steady increase in the risk of incidence, prevalence, and YLDs was observed across successive birth cohorts globally and regionally.

Conclusion: The global burden of anxiety disorders demonstrated an overall upward trend, with considerable regional, demographic, and temporal variations. These findings provide critical insights for optimizing resource allocation and developing tailored public health strategies to address anxiety disorders.

Background: Internet addiction and depression frequently co-occur among university students, resulting in amplified functional deterioration and treatment resistance. Despite established bidirectional relationships, existing research has predominantly examined linear associations and treated these conditions as single global constructs. This study integrated person-centered and network-based approaches to identify distinct symptom profiles of Internet addiction and depressive symptoms, examine sociodemographic predictors of profile membership, and uncover interconnected symptom networks within high-risk populations among Chinese university students.

Methods: A multicenter cross-sectional study was conducted from April to July 2024. Data were collected through a web-based survey incorporating validated instruments for Internet addiction, depression, and suicide risk assessment. Latent profile analysis was employed to identify distinct symptom profiles, followed by multivariate logistic regression to examine sociodemographic predictors. Network analysis was performed within the high-risk profile to unveil symptom interactions, central symptoms, bridge symptoms, and symptomatic pathways to suicide risk.

Results: Among 30,992 participants, latent profile analysis identified three distinct groups: Healthy profile (59.31%), at-risk profile (35.06%), and comorbidity profile (5.63%). Students who were female, ethnic minorities, in higher grade levels, and had prolonged Internet use showed increased risks of problematic profiles. Conversely, enrollment in bachelor’s programs, science and medical majors, higher household income, and regular physical activity demonstrated protective effects. Network analysis revealed Internet preoccupation and fatigue as central symptoms, identified key bridge symptoms (e.g., offline negative affect, difficulty concentrating) linking the symptom clusters, and highlighted Internet withdrawal symptoms and depressed mood as critical pathways to suicide risk within the comorbidity profile.

Conclusion: This study identified distinct profiles of Internet addiction and depression comorbidity, with specific sociodemographic and lifestyle predictors informing targeted screening strategies. Network analysis revealed central symptoms and specific bridge symptoms connecting the conditions, while also identifying critical pathways to suicide risk in the Comorbidity profile, providing empirical evidence for developing precise and effective interventions.