Gender differences in alcohol drinking among adolescents: a school-based survey in China.

BACKGROUND: Alcohol drinking among adolescents is associated with their health development. However, the prevalence of alcohol drinking among adolescents in Southwestern China remains largely unexplored. This study aimed to investigate the prevalence of alcohol drinking, with a particular focus on gender differences, among primary and middle school students in Zigong, a city in Southwestern China. Additionally, we examined the association between alcohol consumption and demographic and family factors. METHODS: A school-based cross-sectional survey was conducted in a city in Southwestern China, encompassing a total of 89 360 students from 132 different ordinary schools, including both primary and middle schools. Participants were recruited through cluster sampling. The Alcohol Use Disorders Identification Test Consumption was employed to assess alcohol consumption. Gender differences in the prevalence of alcohol drinkers across various schools and grades were analysed. Multivariable logistic regression analysis was used to investigate factors associated with hazardous drinking. RESULTS: Out of the 89 360 participants, 19.0% reported alcohol drinking, with 2.1% classified as hazardous drinkers. There was a higher prevalence of alcohol drinking among boys compared with girls, as well as hazardous drinking. There were significant gender disparities in alcohol drinking observed across various schools and grade levels. A notable divergence between boys and girls was observed starting from grade 10, with a rising prevalence of hazardous drinking among boys and a decline among girls. Additionally, older age, male gender and being left-behind children were identified as risk factors for hazardous drinking, while belonging to a nuclear family and having parents who do not drink were protective factors against hazardous drinking. CONCLUSIONS: Alcohol consumption is prevalent among Chinese adolescents, with some even classified as hazardous drinkers. These findings may offer valuable insights for policymakers and caregivers, guiding them in formulating appropriate interventions and support strategies.

Determination of the cutoff point for Smartphone Application-Based Addiction Scale for adolescents: a latent profile analysis.

BACKGROUNDS: The Smartphone Application-Based Addiction Scale (SABAS) is a validated 6-item measurement tool for assessing problematic smartphone use (PSU). However, the absence of established cutoff points for SABAS hinders its utilities. This study aimed to determine the optimal cutoff point for SABAS through latent profile analysis (LPA) and receiver operating characteristic curve (ROC) analyses among 63, 205. Chinese adolescents. Additionally, the study explored whether PSU screening with SABAS could effectively capture problematic social media use (PSMU) and internet gaming disorder (IGD). METHOD: We recruited 63,205. adolescents using cluster sampling. Validated questionnaires were used to assess PSMU, IGD, and mental health (depression, anxiety, sleep disturbances, well-being, resilience, and externalizing and internalizing problems). RESULTS: LPA identified a 3-class model for PSU, including low-risk users (38.6%, n = 24,388.), middle-risk users (42.5%, n = 26,885.), and high-risk users (18.9%, n = 11,932.). High-risk users were regarded as "PSU cases" in ROC analysis, which demonstrated an optimal cut-off point of 23 (sensitivity: 98.1%, specificity: 96.8%). According to the cutoff point, 21.1% (n = 13,317.) were identified as PSU. PSU adolescents displayed higher PSMU, IGD, and worse mental health. PSU screening effectively captured IGD (sensitivity: 86.8%, specificity: 84.5%) and PSMU (sensitivity: 84.5%, specificity: 80.2%). CONCLUSION: A potential ideal threshold for utilizing SABAS to identify PSU could be 23 (out of 36). Employing SABAS as a screening tool for PSU holds the potential to reliably pinpoint both IGD and PSMU.

Prevalence and associated factors of depressive and anxiety symptoms among Chinese secondary school students.

BACKGROUND: Depressive and anxiety symptoms affect about one-fourth of Chinese secondary school students. However, the prevalence and correlates of mental distress among secondary school students from Western China remain largely unexplored. This study aimed to examine the prevalence and associations of depressive and anxiety symptoms with demographic, family, school, life, and behavior factors in a large, representative sample of secondary school students in Zigong, a city in Western China. METHODS: Secondary school students were recruited using cluster sampling. The 9-item Patient Health Questionnaire, the 7-item Generalized Anxiety Disorder Questionnaire, Multidimensional Peer-Victimization Scale, the Pittsburgh Sleep Quality Index, and Nine-Item Internet Gaming Disorder Scale-Short Form were used. Descriptive statistic was used to describe the sociodemographic characteristics of participants. The clustering effect was adjusted by the "survey" package of R to calculate weighted prevalence. Univariate and multivariate logistic regression were used to explore associated factors of depression and anxiety, respectively. RESULTS: A total of 63,205 participants were involved, in which the weighted prevalence of depression in all subjects was 23.0% (95% CI: 19.6- 27.0%), and the weighted prevalence of anxiety was 13.9% (95% CI: 11.2- 17.0%). Logistic regression results showed girls, being single-child, non-nuclear family, peer bullying, sleep disturbance, and internet gaming disorder symptoms were positively associated with depressive and anxiety symptoms. CONCLUSION: Depressive and anxiety symptoms were prevalent among secondary school students in Western China. Our results can guide policy strategies for the assessment, prevention, and intervention of psychological status among Chinese secondary school students.

Demographic characteristics, family environment and psychosocial factors affecting internet addiction in Chinese adolescents.

BACKGROUND: Internet addiction of adolescents has aroused social concern recently. The present study aims to identify predicting factors of internet addiction on adolescents. METHODS: The demographic characteristics and psychological characteristics of 50, 855 middle school students were investigated through Internet Gaming Disorder Scale- Short Form(IGDS9-SF), Smartphone Application-Based Addiction Scale (SABAS), Bergen Social Media Addiction Scale (BSMAS), Strengths and Difficulties Questionnaire-students (SDQS), 16-Item Version of the Prodromal Questionnaire (PQ-16), Patient Health Questionnaire-9 (PHQ-9), Generalized Anxiety Disorder 7-item (GAD-7), Multidimensional Peer Victimization Scale (MPVS), Warwick-Edinburgh Mental Well-being Scale (WEMWBS), and Connor-Davidson Resilience Scale (CD-RISC10) were used to analyze factors associated with internet addiction by Pearson correlation coefficient and multiple hierarchical regression. RESULTS: IGDS9-SF, SABAS and BSMAS are positively correlated with SDQS, PQ-16, PHQ-9, GAD-7 and MPVS (r-values ranging from 0.180 to 0.488, p < 0.01). IGDS9-SF, SABAS and BSMAS are negatively correlated with WEMWB and CD-RISC (r-values ranging from -0.242 ~ -0.338, p < 0.01). Multiple hierarchical regression shown gender, one-child, twins, left-behind, rural, education (father), drink (father), smoke (father), CD-RISC-10, SDQS, PQ-16, PHQ-9, GAD-7 and MPVS predicted 32.7 % of the variance in internet gaming disorder (IGD) (F = 1174.949, p < 0.001). Group (junior and senior), Gender, Age, One-Child, Twins, Village, Education (father), Drink (father), Drink (mother), Smoke (father), WEMWBS, CD-RISC-10, SDQS, PQ-16, PHQ-9, GAD-7 and MPVS predicted 28.9 % of the total variance in social media addiction (SMA) (F = 982.932, p < 0.001). Fifteen variables [Gender, Age, Twins, Left-behind, Residence, Residence, Education (mother), Drink(father), Drink (mother), Smoke (father), WEMWBS, CD-RISC-10, PHQ-9, GAD-7 and MPVS] predicted 30.7 % of the variance in smartphone addiction (SA) (F = 1076.02, p < 0.001). CONCLUSION: The present study found that demographic characteristics, family environment and psychosocial factors were associated with internet gaming addiction, social media addiction and smartphone addiction. Negative psychological factors (such as anxiety and depression) play an important role in different behavioral addictions.

A Study of The Clinical Effect and Dropout Rate of Drugs Combined with Group Integrated Psychotherapy on Elderly Patients with Depression.

BACKGROUND: Relevant studies have shown that group cognitive behavioral therapy is effective in treating patients with depressive disorder, but the dropout rate is high. The present study is aimed to explore the patterns of integrated group psychotherapy. AIMS: This study investigated the clinical effects of integrated group psychotherapy for elderly patients with senile depression. METHODS: One hundred elderly patients with senile depression were divided into the experiment group (n=50) and the control group (n=50) randomly. The experiment group was given regular pharmacological treatments combined with integrated group psychotherapy, while the control group was given regular pharmacological treatments combined with integrated group cognitive behavioral therapy. These two groups were assessed with the Hamilton Depression Scale (HAMD-24) and Geriatric Depression Scale (GDS-15) before the study and at two weeks, four weeks and eight weeks after the treatments. RESULTS: According to the comparisons within these two groups, it was found that the HAMD and GDS total scores before treatments were all significantly higher than those after treatments (F=102.50, p=0.001; F=55.94, p<0.001). We found that the HAMD total scores after four weeks and eight weeks were significantly different between the two groups (F=3.82, p=0.021). The differences between two groups' GDS total scores after two weeks, four weeks and eight weeks were also significantly different (F=4.49, p=0.009). Seven cases dropped out in the experiment group, while sixteen cases dropped out in the control group. The difference of dropout rates was statistically significant (x2 =4.57, p=0.032). CONCLUSION: Medication treatments combined with the group integrated psychotherapy significantly improve the clinical effect for elderly patients with senile depression. The compliance is improved and the dropout rate declines.