Depression and Anxiety最新文献

Background

Adolescence and young age are pivotal periods for the emergence of mental health difficulties, marked by major changes in sleep patterns, including an increase in social jetlag (SJL). SJL is often associated with inadequate sleep, shortened sleep, and greater daytime sleepiness, which could potentially lead to mental health problems. This review and meta-analysis examined the relationships between SJL, depression, and anxiety in this population.

Methods

A systematic search of CINAHL, Embase, PsycINFO, PubMed, and Web of Science identified 14 studies (164,529 participants) examining the association of SJL with depression and anxiety. Pooled associations were calculated using Fisher’s z values within a random-effects model. We assessed heterogeneity with the I² statistic and conducted subgroup and meta-regression analyses to identify possible sources. The robustness of the results was evaluated through sensitivity analyses, and Egger’s test was applied to examine the possibility of publication bias. The certainty of evidence was assessed using the Grading of Recommendations, Assessment, Development, and Evaluation.

Results

SJL was significantly and positively associated with depression (Fisher’s z = 0.27, 95% confidence interval [CI] = 0.16–0.38) and anxiety (Fisher’s z = 0.21, 95% CI = 0.12–0.29). Social jetlag of 1–2 h and >2 h was significantly associated with increased odds of depression, with odds ratios of 1.12 (95% CI = 1.05–1.20) and 1.87 (95% CI = 1.73–2.02), respectively.

Conclusion

This review’s findings demonstrate a possible association between SJL and increased odds of depression and anxiety among adolescents and young people, highlighting the importance of addressing sleep–wake misalignment in this population. However, as the certainty of evidence was rated as very low, the results should be interpreted with caution.

Background

Late-life depression (LLD) is a significant global public health challenge among older adults. Exploring central/influential symptoms with longitudinal study designs can enhance the efficacy of detection, early prevention, and interventions for LLD. This study aimed to identify key symptoms of LLD using a panel graphical vector autoregression (panel-GVAR) model based on longitudinal national survey data.

Methods

Data from the China Health and Retirement Longitudinal Study (CHARLS) between 2013 and 2020, encompassing four waves, were utilized to construct a longitudinal depressive symptom network. Depressive symptoms were assessed using the 10-item Center for Epidemiological Studies Depression Scale (CESD-10). In expected influence (in-EI) and out expected influence (out-EI) were identified to characterize the interaction of symptoms within the temporal network, while expected influence (EI) was used to examine the interaction of symptoms in both the contemporaneous network and the between-subjects network.

Results

A total of 1393 older adults were assessed. A persistently significant increase in the prevalence of depression was observed over time. In the temporal network, “restless sleep” (CESD7) and “could not get going” (CESD10) were the most influential symptom and most influenced symptom, respectively. In both the contemporaneous network and the between-subjects network, “felt depressed” (CESD3) emerged as the most central symptom within the community of depressive symptoms.

Conclusions

Given the challenges associated with treating LLD and its adverse effects on daily life for older adults, timely interventions targeting identified key symptoms may help prevent and mitigate depression in this population.

Background

Depression among graduate students is a growing concern, according to the WHO. However, existing literature lacks multivariable analysis focused specifically on the graduate student populations. This study addresses this gap by investigating the factors contributing to depressive symptoms among science and technology graduate students.

Methods

A cross-sectional study was conducted after ethics committee approval among 387 consenting graduate students selected using stratified random sampling from all 13 departments at the Institute of Science and Technology (IOST), Tribhuvan University (TU), Nepal. The data were collected via a self-administered questionnaire, verifying the outcome variable depression by the Patient Health Questionnaire-9 (PHQ-9) scale (no/low depressive symptoms: 0–9 points; moderate/severe depressive symptoms: 10–27 points). Multivariable logistic regression was used to identify factors associated with moderate/severe depressive symptoms, calculating the adjusted odds ratio (OR) with 95% confidence interval (CI).

Results

The prevalence of moderate/severe depressive symptoms among graduate students was 23% (95% CI: 19–27). Statistically significant (p  < 0.05) associated factors were financial stress (OR: 2.35, 95% CI: 1.30–4.26), relationship dissolution (OR: 2.22, 95% CI: 1.06–4.63), stressful assignments (OR: 5.09, 95% CI: 2.31–11.26), medium self-esteem (OR: 4.73, 95% CI: 2.43–9.18), and low self-esteem (OR: 10.21, 95% CI: 4.71–22.11).

Conclusion

The unique contributors to depressive symptoms identified in this study through multivariable analysis, adjusting for confounding, emphasize the need for targeted mental health support among science and technology graduate students.

Purpose

Adolescents with depressive symptoms are particularly vulnerable and at higher risk for developing co-occurring mental health issues, such as non-suicidal self-injury (NSSI). This study focused on adolescents exhibiting persistent depressive symptoms across three time points and investigated how childhood maltreatment influences NSSI and its changes over time, along with the underlying mechanisms.

Methods

From a larger sample of 3981 students, 317 adolescents with persistent depressive symptoms (M_age = 13.20, SD = 0.82) were identified, and a control group of 317 non-depressed adolescents was selected via propensity score matching. Latent change score (LCS) modeling and longitudinal mediation models were employed to examine the mechanisms linking childhood maltreatment to NSSI and its changes.

Results

The univariate LCS model revealed an increasing trend in NSSI behaviors among adolescents with depressive symptoms over the measurement period. T1 childhood maltreatment indirectly influenced T2 NSSI through T2 self-esteem and T2 emotional reactivity. Additionally, T1 childhood maltreatment significantly predicted changes in NSSI through T2 emotional reactivity.

Conclusions

This study underscores the importance of addressing NSSI in adolescents with depressive symptoms and highlights the necessity of screening for childhood maltreatment histories in this population. The findings provide a foundation for future prevention and intervention efforts, suggesting that enhancing self-esteem and reducing emotional reactivity could mitigate the impact of childhood maltreatment on NSSI in depressed adolescents.

Background

The underlying mechanism of pain-depression comorbidity is not well understood. This study aims to analyze the abnormal brain activity in adolescents with pain-depression comorbidity, and to provide imaging evidence for the understanding of brain neural mechanisms of pain-depression comorbidity.

Methods

Depression in adolescents with (n = 31) and without (n = 26) comorbid pain symptoms and 28 healthy controls matched for age, gender, and education level underwent resting-state functional magnetic resonance imaging (rs-fMRI) and completed the Hamilton depression scale and visual analog scale (VAS) of pain. The whole-brain amplitude of low-frequency fluctuation (ALFF) and regional homogeneity (ReHo) values were compared across groups. The brain regions with significant differences in ALFF values between groups were used as seed points for whole-brain functional connectivity.

Results

Compared with the depression group, the comorbidity group showed increased ALFF values in the right amygdala and right middle frontal gyrus, decreased ALFF values in the left middle occipital gyrus, right inferior temporal gyrus and right superior temporal gyrus, increased ReHo values in the right insula, and elevated functional connectivity between the right inferior temporal gyrus and right angular gyrus (Gaussian random field [GRF] corrected, p  < 0.05).

Conclusion

Compared with adolescents with depression without pain, adolescents with pain-depression comorbidity have differences in neuronal activity and functional connectivity in the middle frontal gyrus, amygdala, insular lobe, temporoparietal and occipital lobes, suggesting that abnormal neuronal activity in these brain regions may be the neural basis of pain-depression comorbidity.

Background

Cognitive-behavioral therapy (CBT) with exposure and response prevention (ERP) is a recommended treatment for obsessive-compulsive disorder (OCD), although many patients who undergo this regimen do not achieve satisfactory symptom relief, and maintaining long-term remission is challenging. Concentrated exposure therapy (cET) has emerged as a potential treatment for treatment-resistant OCD. However, the role of insight as a predictor of treatment outcomes in this context remains underexplored.

Methods

We conducted a secondary analysis of a randomized controlled trial (RCT) including 163 adults diagnosed with treatment-resistant OCD. This study used linear regression models to evaluate whether pre-treatment levels of insight and changes in insight—measured by the Yale-Brown Obsessive Compulsive Scale (Y-BOCS) insight item—were associated with outcomes after 4 days of cET and whether insight levels changed post-treatment.

Results

Baseline insight did not predict OCD severity at post-treatment or 3-month follow-up but was associated with greater OCD severity at the 12-month follow-up. Insight scores improved significantly from pre- to post-treatment but worsened during the follow-up period. Notably, a change in insight during cET was a significant predictor of OCD symptom severity at all follow-up intervals.

Conclusions

Baseline insight was not a strong predictor of short-term treatment outcomes following cET but was related to long-term OCD severity. Improvements in insight during cET were associated with achieving and maintaining reduced symptoms over time. These results suggest that improvements in OCD and enhanced insight are associated.

Trial Registration: ClinicalTrials.gov identifier: NCT02656342.

Objective

To investigate the associations between meeting the new Canadian 24-h movement guidelines and symptoms of depression, anxiety, and stress among Chinese medical students, thus providing empirical and theoretical support for targeted mental health interventions.

Methods

A total of 3679 medical students were recruited through multicenter convenience sampling in November 2022. A self-administered standardized questionnaire assessed three 24-h movement behaviors—moderate-to-vigorous physical activity (MVPA), sedentary time, and sleep—as well as symptoms of depression, anxiety, and stress. Logistic regression models were applied to analyze the association between meeting new 24-h movement guidelines and symptoms of depression, anxiety, and stress.

Results

A total of 3228 valid responses were obtained. The proportions of students who met all 24-h movement behavior recommendations were low, at 4.01% among clinical students and 7.14% among nursing students. The overall prevalence of negative emotional symptoms was 60.9% in clinical students and 46.7% in nursing students. A clear dose–response relationship was evident between the number of recommendations met and a lower risk of depression, anxiety, and stress. Medical students who fully met all recommendations had a significantly lower risk of negative emotional symptoms compared with those who met none (stress odds ratio [OR] = 0.239, 95% confidence interval [CI]: 0.101–0.568, p = 0.001; anxiety OR = 0.601, 95% CI: 0.407–0.889, p = 0.011; depression OR = 0.450, 95% CI: 0.290–0.700, p  < 0.001). Similar protective associations were found in both clinical and nursing subgroups. All associations remained generally consistent after false discovery rate (FDR) correction, supporting the robustness of the results. A significant three-way interaction among MVPA, sedentary behavior, and sleep was observed for stress.

Conclusion

Adherence to the 24-h movement behavior recommendations was suboptimal among Chinese medical students. However, greater adherence was associated with a lower risk of symptoms of depression, anxiety, and stress, highlighting the need for integrated lifestyle interventions targeting physical activity, sedentary time, and sleep balance.