Non-suicidal self-injury (NSSI) in adolescents is a significant mental health problem around the world. Here, we performed a meta-analysis to systematically delineate the risk factors for NSSI. We searched Medline, Embase, Web of Science and Cochrane for relevant articles and abstracts published prior to 12 November 2021. Pooled odds ratios (ORs) and 95% confident intervals (CIs) were used to assess various risk factors, and publication bias was assessed by Egger's test, the trim and fill method and meta-regression. This study is registered with PROSPERO, CRD42021265885. A total of 25 articles were eventually included in the analysis. Eighty risk factors were identified and classified into 7 categories: mental disorders (ORs, 1·89; 95% CI, 1·60–2·24), bullying (ORs, 1·98; 95% CI, 1·32–2·95), low health literacy (ORs, 2·20; 95% CI, 1·63–2·96), problem behaviours (ORs, 2·36; 95% CI, 2·00–2·77), adverse childhood experiences (ORs, 2·49; 95% CI, 1·85–3.34), physical symptoms (ORs, 2·85; 95% CI, 1·36–5·97) and the female gender (ORs, 2·89; 95% CI, 2·43–3·43). The range of heterogeneity (I²) was from 20·3% to 99·2%. This meta-analysis found that mental disorders, low health literacy, adverse childhood experiences, bullying, problem behaviours, the female gender and physical symptoms appear to be risk factors for NSSI.

Background and Aims: This three-wave longitudinal study investigated the effects of stressful life events on problematic smartphone use and the mediating roles of mental health problems (i.e., depressive symptoms, poor sleep quality, and suicidal ideation) in Chinese undergraduate students.Methods: A total of 197 undergraduate students completed the three-wave surveys. Their severity of stressful life events, mental health problems, and problematic smartphone use were assessed.Results: Regression analyses revealed that stressful life events at T1 was significantly associated with problematic smartphone use at T3. Mediation analyses showed that mental health problems (i.e., depressive symptoms, poor sleep quality, and suicidal ideation) at T2 fully mediated the association between stressful life events at T1 and problematic smartphone use at T3 (B = 0.042, 0.034, and 0.022, respectively).Conclusions: The present study revealed that stressful life events and mental health problems (i.e., depressive symptoms, poor sleep quality, and suicidal ideation) are predictors of problematic smartphone use in Chinese college students.

Left-behind children(LBC) in rural China are at increased risk for mental health problems, including depression. This study aimed to estimate the prevalence of depression and identify key associate factors among Chinese rural LBC. A cross-sectional study was conducted using data from 36,612 LBC aged 6 to 18 years old across 596 data collection sites in Nanchong, Sichuan Province, China. Participants completed questionnaires assessing individual factors, family parenting situation, living events, and health-related data. Depression was measured using the Center for Epidemiological Studies-Depression Scale (CES-D). T-tests, chi-square, and logistic regression were performed to identify factors associated with depression. The overall prevalence of depression among LBC was 6.75%. Logistic regression analysis revealed that family parenting situations, such as being from blended families (OR = 1.45) or being cared for by other family members (OR = 1.64), and dissatisfaction with the parenting situation (OR = 1.57) were significantly associated with higher odds of depression. Living events, including being misunderstood (OR = 1.82) and having disputes (OR = 1.48), and health-related factors, such as chronic diseases and regular medication use (OR = 2.38), also increased the risk of depression. This study highlights the high prevalence of depression among Chinese rural LBC and identifies key associate factors, including family parenting situation, negative living events and health-related factors. Targeted interventions and policies addressing these factors are needed to promote the mental health of this vulnerable population.

Background: Sleep disturbance and neuropsychiatric symptoms are common clinical symptoms of cerebral small vessel disease (CSVD), but the underlying mechanism is unclear. Here, we investigated the relationship between sleep quality and neuropsychiatric performance in patients with CSVD.Methods: A total of 30 patients with CSVD and 35 healthy controls (HCs) were recruited. The 13-item Beck Depression Inventory (BDI-13), Beck Anxiety Inventory (BAI), and Symptom Check List 90 (SCL90) were used to assess depression, anxiety, and other psychological symptoms, respectively. Sleep quality was assessed using Pittsburgh Sleep Quality Index (PSQI), and cognitive function was tested using Montreal Cognitive Assessment (MoCA).Results: When compared to the HC group, the patients with CSVD showed increased anxiety and neuropsychiatric symptoms, worse sleep quality, and impaired cognition (p < 0.05). The prevalence of comorbid poor sleep quality in the patients with CSVD was approximately 46%. The patients with CSVD with poor sleep quality also had more severe neuropsychiatric symptoms. After controlling for demographic variables, sex and anxiety significantly predicted sleep quality.Conclusion: This study suggests that the prevalence of CSVD with poor sleep quality is high, and that sex and anxiety are independent risk factors for CSVD comorbid sleep quality.

This research builds on the understanding that low self-acceptance is an important feature of adolescent depression, and that social comparison is a critical factor in self-concept formation during adolescence. However, there are gaps in our understanding of their interactive effects and the non-linear features between these factors in influencing adolescent depression. The study attempts to test two main hypotheses: (1) increased levels of self-acceptance will correlate with reduced depressive symptoms and moderate the negative effects of social comparison on depression; and (2) the relationship between social comparison and depression will exhibit nonlinearity at different levels of self-acceptance. The study involved 243 adolescents undergoing psychiatric assessment, using dyadic polynomial regression analysis and response surface analysis. These methods were used to assess linearity or nonlinearity and interaction effects between self-acceptance, social comparison and depression. Significant findings included a strong negative correlation between self-acceptance and depression. Self-acceptance also showed a negative correlation with social comparison. Polynomial regression revealed a non-linear relationship between social comparison and depression, with moderate levels being beneficial but excessive levels being detrimental. The interaction effect suggested that high self-acceptance might buffer the negative effects of intense social comparison. Furthermore, response surface analysis revealed complex, non-linear interactions between these variables. This study highlights the protective role of self-acceptance against depression and the complex, non-linear effects of social comparison. It highlights the importance of promoting self-acceptance and a balanced approach to social comparison in adolescent mental health interventions.