Background: Internet addiction has become a major global concern and a burden on mental health. However, there is a lack of consensus on its link to mental health outcomes. Objective: The aim of this study was to investigate the associations between internet addiction severity and adverse mental health outcomes. Methods: First-year undergraduates enrolled at Sichuan University during September 2015, 2016, 2017, and 2018 were invited to participate in the current study survey, 85.13% (31,659/37,187) of whom fully responded. Young’s 20-item Internet Addiction Test, Patient Health Questionnaire-15, Patient Health Questionnaire-9, Symptom Checklist 90, Six-Item Kessler Psychological Distress Scale, and Suicidal Behaviors Questionnaire-Revised were used to evaluate internet addiction, four psychopathologies (high somatic symptom severity, clinically significant depression, psychoticism, and paranoia), serious mental illness, and lifetime suicidality. Results: The prevalence of students with mild, moderate, and severe internet addiction was 37.93% (12,009/31,659), 6.33% (2003/31,659), and 0.20% (63/31,659), respectively. The prevalence rates of high somatic symptom severity, clinically significant depression, psychoticism, paranoid ideation, and serious mental illness were 6.54% (2072/31,659), 4.09% (1294/31,659), 0.51% (160/31,659), 0.52% (165/31,659), and 1.88% (594/31,659), respectively, and the lifetime prevalence rates of suicidal ideation, suicidal plan, and suicidal attempt were 36.31% (11,495/31,659), 5.13% (1624/31,659), and 1.00% (315/31,659), respectively. The prevalence rates and odds ratios (ORs) of the four psychopathologies and their comorbidities, screened serious mental illness, and suicidalities in the group without internet addiction were much lower than the average levels of the surveyed population. Most of these metrics in the group with mild internet addiction were similar to or slightly higher than the average rates; however, these rates sharply increased in the moderate and severe internet addiction groups. Among the four psychopathologies, clinically significant depression was most strongly associated with internet addiction after adjusting for the confounding effects of demographics and other psychopathologies, and its prevalence increased from 1.01% (178/17,584) in the students with no addiction to 4.85% (582/12,009), 24.81% (497/2,003), and 58.73% (37/63) in the students with mild, moderate, and severe internet addiction, respectively. The proportions of those with any of the four psychopathologies increased from 4.05% (713/17,584) to 11.72% (1408/12,009), 36.89% (739/2003), and 68.25% (43/63); those with lifetime suicidal ideation increased from 24.92% (4382/17,584) to 47.56% (5711/12,009), 67.70% (1356/2003), and 73.02% (46/63); those with a suicidal plan increased from 2.59% (456/17,584) to 6.77% (813/12,009), 16.72% (335/2003), and 31.75% (20/63); and those with a suicidal attempt increased from 0.50% (88/17,584) to 1.23% (148/12,009), 3.54% (71/2003), and 12.70% (8/63), respectively. Conclusions: Moderate and severe internet addiction were strongly associated with a broad group of adverse mental health outcomes, including somatic symptoms that are the core features of many medical illnesses, although clinically significant depression showed the strongest association. This finding supports the illness validity of moderate and severe internet addiction in contrast to mild internet addiction. These results are important for informing health policymakers and service suppliers from the perspective of resolving the overall human health burden in the current era of “Internet Plus” and artificial intelligence.

Background: Many studies have related biochemical characteristics to violence and have reported schizophrenia could elevated the risk of violent behaviour. However, the metabolic characteristics of schizophrenia patients with violence (V.SC) are unclear.Methods: To explore the metabolic characteristics of schizophrenia with violence and to identify potential biomarkers, untargeted metabolomics was performed by using gas chromatography time-of-flight mass spectrometry to analyse the plasma metabolites of fifty-three V.SC and twenty-four schizophrenia patients without violence (NV.SC). Multivariate and univariate analyses were performed to identify differential metabolites and biomarkers. Violence was assessed by the MacArthur Violence Assessment Study method. Psychiatric symptoms were assessed by the Positive and Negative Syndrome Scale.Results: Multivariate analysis was unable to distinguish V.SC from NV.SC. Glycerolipid metabolism and phenylalanine, tyrosine and tryptophan biosynthesis were the differential metabolic pathways between V.SC and NV.SC. We confirmed ten metabolites and five metabolites as metabolic biomarkers of V.SC by random forest and support vector machine analysis, respectively. The biomarker panel, including the ratio of L-asparagine to L-aspartic acid, vanillylmandelic acid and glutaric acid, yielded an area under the receiver operating characteristic curve of 0.808.Conclusions: This study gives a holistic view of the metabolic phenotype of schizophrenia with violence which is characterized by the dysregulation of lipids and amino acids. These results might provide information for the aetiological understanding and management of violence in schizophrenia; however, this is a preliminary metabolomics study about schizophrenia with violence, which needs to be repeated in future studies.

Background: Mood disorder, impulsivity and aggression are common in drug users compared to healthy controls. However, no study has focused on the difference in various types of drug users. Therefore, the objective of this study was to explore the differences in depression, anxiety, impulsivity, and aggression among methamphetamine, heroin and polysubstance users and to further explore the risk factors for severe depression in the three groups.Methods: Drug users over 18 years old who met the DSM-V diagnostic criteria for substance -related disorders were included in the study. All participants completed a general questionnaire, the Zung Self-Rating Depression Scale (SDS), the Zung Self-Rating Anxiety Scale (SAS), Barratt impulsiveness Scale Version 11 (BIS-11), and the Buss-Perry Aggression Questionnaire (BPAQ). One-way ANOVAs or Chi-square tests were used to test the differences among the groups, correlation analysis was used to test the relationship between drug use and other parameters, and multiple logistic regression was conducted to assess the risk factors for severe depression.Results: A total of 1,486 participants were included, comprising 86.3% males with a mean age of 38.97 years. There was a significant difference in the percentage of severe depression and SDS scores among the three groups, but no significant difference was found in SAS, BIS-11 and BPAQ scores. Using methamphetamines, hostility and anxiety were risk factors for developing severe depression in all the participants and anxiety remained constant in the other three groups. Moreover, methamphetamine use was 2.16 and 3.35 times more likely to cause severe depression than heroin and polysubstance use, respectively. The initial age of substance use was negatively correlated with BPAQ, SAS, and SDS scores, whereas the drug use duration and addiction duration were positively correlated.Conclusions: In this study, we found that the highest prevalence of severe depression was in participants using methamphetamines and that using methamphetamines, hostility, and anxiety were risk factors for developing severe depression. This result addressed an important gap in our knowledge of the different characteristics of depression, anxiety, impulsivity and aggression in various types of substance users and provides clinicians and policy-makers with directions for intervention and preventing relapse.