0. 05, respectively). Conclusion The results suggest that the combination measurement of serum levels of IV C, LN and sVCAM-1 in DR patients might better evaluate the development process of diabetic mi-croangiopathy, and be of help for early diagnosis and therapy of diabetic microangiopathy. Serum levels of IVC, LN and sVCAM-1 in DR patients may be reliable clinical markers for assessing the severity and prognosis of diabetic retinopathy.

Objective: To explore cyberbullying and risk factors of middle school students, and to provide a reference for cyberbullying prevention in school settings. Methods: A stratified cluster random sampling method was used to select 12 940 students from three junior high schools and four senior high schools in Yixing City of Jiangsu Province, China, to conduct a questionnaire survey from March 1 to May 31, 2019. The Chi -square test was performed to compare differences in the prevalence of cyberbullying among groups with different sociodemographic characteristics, and the multivariate Logistic regression model was employed to analyze the risk factors. A risk predictive nomogram model was constructed and then verified. Results: Middle school students were found to be victims of cyberbullying at a rate of 12.3%. The Logistic regression results showed that alcohol use ( OR =1.93), lack of emotional management ( OR =1.30), feeling unsafe ( OR =1.70), not trusting people ( OR =1.66), increased daily online time ( OR =1.39), higher frequency of using social software or websites ( OR =2.24), poor relationships with family members ( OR =1.46), parental neglect ( OR =1.50), class leadership ( OR =1.30) and poor relationships with classmates ( OR =1.34) were risk factors for middle school students who were victims of cyberbullying ( P <0.05). Based on these 10 independent risk factors, the nomogram prediction model, had good discrimination ( AUC =0.73). Conclusion Cyberbullying is common among middle school students. Internet use, parental neglect and class leadership all have an impact on cyberbullying.

Objective: To understand current situation epidemiology and associated factors of suicidal ideation among high school students in Yixing, so as to provide basis for targeted intervention. Methods: From March to May 2019, a questionnaire survey was conducted on 12 799 students from 3 junior high schools and 4 senior high schools in Yixing City, Jiangsu Province, using a stratified cluster random sampling method. Latent profile analysis was used to classify suicidal ideation among high school students, the chi square test was used to compare the differences in suicidal ideation among different characteristics of students, multiple Logistic regression was used to analyze influencing factors, a risk predictive nomogram model was constructed and then verified. Results: Three latent classes of suicidal ideation among high school students was divided into three categories were observed: none or mild, moderate, and severe. Among them, 3 034 (23.7%) had moderate suicidal ideation and 753 (5.9%) had severe suicidal ideation. The Logistic regression results showed that gender was female, academic performance was lower midrange, smoking, drinking, popularity with classmates(less popular and unpopularity), family member relationships(general/occasional contradictions/contradictions), trust in others(more trusted/less trusted/less trusted at all), past or current relationships, physical bullying, relationship bullying, verbal bullying, and sexual bullying were the influencing factors for severe suicidal ideation among students ( OR =3.27； 2.18 ；1.63；1.72；2.66, 6.05；3.00,3.29, 6.38；1.71, 6.04, 12.48； 2.50； 1.59； 2.16； 1.45； 1.63, P <0.05). The nomogram prediction model had good discrimination. Conclusions Suicide ideation is influenced by multiple factors. Family and peer situations, as well as being bullied, are all related to the degree the severity of suicidal ideation. Efforts can be made to improve students family and interpersonal relationships, control bullying, then reduce their suicidal ideation which might help prevent suicide ideation among students.

Objective: To explore the mediating effect of anxiety, insomnia, and family cohesion between Internet addiction and non suicidal self injury (NSSI) behavior among junior and senior school students, so as to develop interventions to promote adolescent mental health. Methods: A total of 3 026 junior and senior school students from Yixing, Jiangsu Province, China, were selected by stratified cluster sampling from December 2022 to February 2023, and were administered the Ottawa Self injury Inventory (OSI), Depression, Anxiety and Stress Scale-21 (DASS-21), Family Environment Scale-Chinese Version (FES-CV), Insomnia Severity Index (ISI), and Chinese Internet Addiction Scale Revised (CIAS-R). A mediating effect model was constructed to analyze the mediating effect of anxiety, insomnia, and family cohesion on Internet addiction and NSSI. Results: Internet addiction ( r = 0.24), insomnia ( r =0.28), and anxiety ( r =0.27) were positively correlated with NSSI, while the latter was negatively correlated with family cohesion ( r =-0.23) ( P <0.01). The mediating effect model was well fitted ( CFI=0.999, TLI=0.978, RMSEA = 0.030 ). Anxiety (mediation effect value:0.12, 95% CI =0.08-0.18) and family cohesion (mediation effect value:0.08, 95% CI = 0.03 -0.13) had a separate mediating effect. A chain meditating effect was found in the case of anxiety and insomnia (mediation effect value:0.14, 95% CI =0.10-0.20), family cohesion and anxiety (mediation effect value:0.05, 95% CI =0.03-0.07), family cohesion and insomnia (mediation effect value:0.05, 95% CI =0.03-0.07), and family cohesion, anxiety, and insomnia (mediation effect value:0.06, 95% CI =0.04-0.08). The mediating effect accounted for 14.9%, 10.1%, 17.5%, 6.0%, 5.6%, and 7.1%, respectively. Conclusions Anxiety, insomnia, and family cohesion partially mediate Internet addiction and NSSI. Schools and families should pay attention to Internet addiction among junior and senior school students and develop appropriate interventions to promote adolescent mental health, so as to reduce the prevalence of NSSI.

Objective: To explore the association between negative emotion (depression, anxiety and stress), family intimacy and Internet addiction, so as to provide a basis for the intervention of Internet addiction among junior and senior high school students. Methods: Students were selected by stratified random cluster sampling method from junior high schools and senior high schools from December 2022 to February 2023 in Yixing City, Jiangsu Provicne. A total of 3 026 students completed the questionnaire survey, including the demographic characteristics, Depression, Anxiety and Stress Scale-21 (DASS-21), Family Environment Scale-Chinese Version (FES-CV), and Chinese Internet Addiction Scale Revised (CIAS-R). Bivariate correlation was used to analyzed the association of family intimacy, depression, anxiety, stress, and Internet addiction. Mediating effect model was used to analyzed the mediating effect of negative emotion between family intimacy and Internet addiction. Results: The average score of Internet addiction among junior and senior high school students was (46.26±15.58), and there were statistical differences in the average scores of Internet addiction across different grades ( F=87.15, P <0.01). Depression ( r =0.57), anxiety ( r =0.56), stress ( r = 0.57) were positively correlated with Internet addiction, and family intimacy ( r =-0.34) was negatively correlated with Internet diction ( P <0.01). In the mediating effect model, family intimacy negatively predicted negative emotion ( β =-0.48) and Internet addiction ( β =-0.10), and negative emotion positively predicted Internet addiction ( β =0.45) ( P <0.01). Negative emotion played a partial mediating role between family intimacy and Internet addiction (the mediation value:-1.71, 95% CI =-1.96--1.49, mediation ratio:67.9%, P <0.05). Conclusions There are associations between negative emotion, family intimacy and Internet addiction among junior and senior school students. Family intimacy indirectly affects Internet addiction mainly through negative emotion. It suggests that family education is in need of attention to reduce the prevalence rate of Internet addiction among junior and senior high school students, especially family intimacy.

Objective: To understand different types of depression and anxiety among primary and secondary school students, as well as their influencing factors, so as to provide a basis for the development of future intervention programs for adolescent mental health. Methods: From December 2022 to February 2023, a self administered questionnaire survey was administered among grades 4 to 6 students and junior school, senior school students in Yixing City using Depression Anxiety and Stress Scale-21 (DASS-21), Insomnia Severity Index (ISI), Family Environment Scale (FES), and modified Yale Food Addiction Scale 2.0 (mYFAS 2.0), Ottawa Self injury Inventory (OSI). A total of 4 180 students were included in the analysis. Different types of depression and anxiety in students and their influencing factors were analyzed by the Chi squaretest and multivariate Logistic regression. Results: The overall prevalence of depression and anxiety among primary and secondary school students were 16.6% and 22.4%, respectively, with 14.0% of depression and anxiety comorbidities. The Logistic regression results showed that, compared to students with low depression-low anxiety, students of depression and anxiety who had parents in conflicts ( OR =3.06), smoked ( OR =3.16), exhibited moderate food addiction ( OR =3.56), and had non suicidal self injury (NSSI) ( OR =2.26) were more likely to be classified as a depression predominant-depression anxiety type. Students of depression and anxiety who consumed alcohol ( OR =2.00), had serious food addiction ( OR =5.44), moderate to severe insomnia ( OR =3.25), and mild insomnia ( OR =1.88) were more likely to be classified as anxiety predominant-depression anxiety type. Students of depression and anxiety with low mood ( OR =10.87), mild food addiction ( OR =2.00), moderate food addiction ( OR =4.32), and severe food addiction ( OR =7.35), mild ( OR =2.96) or moderate to severe ( OR =16.52) insomnia, and NSSI ( OR =4.24) were more likely to be classified as the severe depression anxiety type( P < 0.05 ). Conclusions There are significant differences between different depression-anxiety types among primary and secondary school students with respect to food addiction, insomnia, NSSI, smoking, and alcohol use. Relevant departments should engage with schools and families to adopt targeted interventions for students to reduce the occurrence of mental health problems.