Unveiling the Dynamic Mechanisms of Anxiety: A Network Analysis of Negative Life Events and Anxiety Symptoms Among High School Students

Unveiling the Dynamic Mechanisms of Anxiety: A Network Analysis of Negative Life Events and Anxiety Symptoms Among High School Students | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Unveiling the Dynamic Mechanisms of Anxiety: A Network Analysis of Negative Life Events and Anxiety Symptoms Among High School Students Zijun Chen, Ke Zheng, Qiyun Jiang, Jiusheng Wang, Biao Chen, Zihan Wang, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7634586/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 5 You are reading this latest preprint version Abstract Objective: To explore the relationship between negative life events and anxiety in high school students, to identify core symptoms and their interrelationships, and to provide empirical research evidence for the alleviation of anxiety. Methods: A stratified random sampling method was adopted to select 1,576 high school students from some of the central Anhui Province, Anhui Province, China. Questionnaires were administered using the Adolescent Self-Rating Life Events Checklist (ASLEC) and the Self-Rating Anxiety Scale (SAS). The data were analyzed using the statistical software package SPSS 26.0 in conjunction with the R software (Version 4.4.1). Results: The network structure of ASLEC and SAS for high school students comprises a total of 384 effective edges, forming two internal tight sub-networks.In ASLEC, ASLEC-2 (strength of 1.09) and ASLEC-15 (strength of 1.15) have higher strengths, ASLEC-5 (bridge strength of 0.125) and ASLEC-6 (bridge strength of 0.252) have higher bridge strengths; in SAS, SAS-3 (strength of 1.22) and SAS-12 (strength of 1.18) have higher strengths, SAS -3 bridge strength of (0.165) and SAS-4 (bridge strength of 0.164) bridge strengths are higher; the ASLEC-6-SAS-9 sideline carries more weight in connecting the 2 sub-networks. Conclusion: Network analyses provide empirical support for precise interventions for negative life events and anxiety reduction in high school students. Interventions that target core symptoms are beneficial for improving the mental health of high school students and providing a deeper understanding of the dynamics between symptoms. High school students Negative life events Anxiety Network analysis Mental health intervention Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Highlights The analytical method is innovative, employing network analysis to reveal the complex network structure formed by the interactions between latent variables and observed variables. This method is suitable for analyzing the relationship between negative life events and anxiety in adolescents;Through extensive empirical investigations conducted in high schools across central Anhui Province, corresponding conclusions were drawn, yielding results capable of predicting mental health issues among high school students;the present study plans to use network analysis to explore the relationship between symptoms and their interconnections (edges) at each node in the network of negative life events and anxiety, to identify the core node symptoms in the entire network and provide empirical evidence for the development of targeted intervention programs. Introduction High school is a critical period of physiological and psychological development of individual students, and also a period prone to psychological problems (D. Chen, Quan, Ai, Zong, & X, 2020). As students age and grade level rise, they face increased negative life events such as increasing academic pressure and complex interpersonal relationships. It has been shown that negative life events are a kind of life crisis, their occurrence will make students experience more anxiety and tension, which will affect their healthy growth(Tang & Zhou, 2014). It also stimulates the individual's perceptual factors and increases the individual's attention and processing of harmful stimuli, leading to the emotional experience of anxiety(Huang et al., 2021). Anxiety is an emotional disorder, referred to as ‘anxious emotions’, often called ‘anxiety syndrome’ or ‘anxiety disorder’, and is the most common mental illness among adolescents. It is the most common mental illness among adolescents. It is a complex psychological process that involves the expression of nervousness in the face of an impending situation (negative life events) that is likely to cause harm to the person. Symptoms include excessive worry, fear of future events, nervousness, and physical symptoms such as increased heart rate, sweating, and sleep disorders(Vallance, Aaron, K., Fernandez, & Victoria., 2016). Anxiety manifests itself in a variety of forms and may vary according to individual and environmental differences. Although it does not directly lead to physiological diseases, chronic anxiety may complicate health problems such as hypertension and cardiovascular disease, and may also have a sustained, negative impact on adolescents' cognitive behavior ability, academic performance, and personality dignity (Waite & Creswell, 2015). It has been shown that the more negative life events and the greater the stimulation of emotions in a certain period, the more prone to anxiety(H. Y. Liu & Wang, 2017). It shows that there is a significant positive correlation between negative life events and the level of anxiety(K. S. Li, Zhang, Zhang, Mo, & Pan, 2023), which can positively predict students‘anxiety, i.e., the more negative life events, the lower the students’ self-efficacy, the less controllable they are to the events, and the more anxiety they will develop. Research on negative life events and anxiety has focused on correlation analysis or on the mediating model through which they positively or negatively affect adolescents' mental health. According to the Network Theory of Mental Disorders (NTMD) proposed by Borboom(Borsboom & Denny, 2017), mental health is the result of a complex interaction of multiple symptoms rather than a simple manifestation of a single underlying symptom. The core of the network analysis method is to reveal the complex network structure formed by the interactions between latent variables and observation variables, and this method is also suitable for analyzing the relationship between negative life events and anxiety(Ren et al., 2020) . Therefore, the present study plans to use network analysis to explore the relationship between symptoms and their interconnections (edges) at each node in the network of negative life events and anxiety, to identify the core node symptoms in the entire network and provide empirical evidence for the development of targeted intervention programs. 1 Subjects and methods 1.1 Research object In this study, a stratified random sampling method was used from March to June 2024 to select some high school students in central Anhui Province, Anhui Province for a questionnaire survey. All respondents were informed and signed an informed consent. A total of 1700 questionnaires were distributed, and 1576 valid questionnaires were recovered, with an effective recovery rate of 92.7%.Written informed consent was obtained from all participating adolescents. For those under 16 years of age,parental or legal guardian consent was additionally secured. 1.2 Survey instrument 1.2.1 Personal and Family Information Survey Review relevant literature, summarize, generalize and design their questionnaires to investigate basic information (including gender, ethnicity, grade, whether they are an only child, parents' literacy and academic performance). 1.2.2 Adolescent Self-Rating Life Events CheckList The research object of this study was high school students, and the Adolescent Self-Rating Life Events Checklist (ASLEC) compiled by Liu Xianchen(X. C. Liu et al., 1997 )was used, which consists of 27 negative life events that may bring physiopsychological reactions to adolescents, including learning pressure, health adaptation, interpersonal relationship, punishment, loss and other 6 dimensions, and is scored as 0 if it does not occur, and 5-point scale according to the psychological feelings when it occurs, with higher scores indicating that high school students encountered more negative life events. The Cronbach's alpha coefficient of the scale is 0.85, which means that the reliability of the scale is good, and the applicability of the ASLEC scale to the high school student population has been widely verified. 1.2.3 Self-rating Anxiety Scale The Self-rating Anxiety Scale (SAS)(Zung, 1971 )is currently the most widely used and effective standardized quantitative measure for assessing anxiety. It consists of 20 self-assessment items, each representing a specific symptom. Respondents indicate the frequency of each symptom based on their own experiences: 1 point for 'not at all or rarely,' 2 points for 'sometimes,' 3 points for 'often,' and 4 points for 'most of the time.' Among the 20 items in the SAS, every few questions—specifically items 5, 9, 13, 17, and 19—are reverse-scored. After completing the self-assessment, the scores for all items are summed and converted into a percentage (by multiplying by 1.25) to obtain the final score. According to the standard, a score below 50 is considered normal, 50–60 indicates mild anxiety, 60–70 indicates moderate anxiety, and a score above 70 indicates severe anxiety. The scale demonstrates good reliability and validity, with a Cronbach’sαcoefficient of 0.82. 1.3 Statistical method After data entry, mssing values were first processed, and then appropriate statistical tests were selected based on the type of distribution of the data. Parametric tests were used for normal distribution data, and non-parametric tests were used for non-normal distribution data. In this study, SPSS 26.0 and R software (Version 4.4.1) were used for data entry, descriptive statistics analysis, and network model construction. The R-package graph package's EBICglasso function was used to estimate the partial correlation matrix and generate a visual network model, the basic composition of which consists of circular nodes (Node) with edges (Edge) indicating the strength of association between nodes. The centrality metrics of the network nodes are calculated and displayed as Z-scores by the R-package graph package and the R-package network tools package. These metrics include: Strength, which is the sum of the absolute values of all edges connecting a node, the higher its value, the greater the relative importance of the node in the network(Epskamp, Cramer, Waldorp, Schmittmann, & Borsboom, 2012 ); Bridge Strength is the sum of the absolute values of all edges connecting the node to other cluster nodes, the higher the value represents the greater the risk of the node to pass to the other cluster, the more obvious the bridge effect is, this study divided the target variable into two parts. The target variables were divided into 2 clusters in this study, which were the Adolescent Life Events Scale and the Anxiety Self-Rating Scale(Jones, Ma, & Mcnally, 2021 ). Using the R-package botnet package, 95% confidence intervals (1000 bootstrap) were calculated for the edge weights to assess the accuracy of the edge weights, and Correlation Stability (CS) coefficients were calculated to assess the stability of the edge weight values and the expected impact of the nodes(Epskamp, Borsboom, & Fried, 2016 ). The CS coefficients should be at least greater than 0.25 and ideally greater than 0.50, and a cut-off value of 0.25 was set for the CS coefficient in this study(Epskamp & Fried, 2018 ). All statistical analyses were performed at a significance level of α = 0.05. 1.4 Ethics approval and consent to participate This study was conducted in accordance with the ethical principles outlined in the Declaration of Helsinki. The research protocol was reviewed and approved by the relevant school authorities, ensuring that all procedures adhered to ethical standards for research involving human participants. All subjects who participated in the survey signed the informed consent form. All methods were carried out in accordance with relevant guidelines and regulations.The survey has received approval from the Academic Ethics Committee of College. For participants under the age of 16, prior to their participation in the study, they were explicitly informed of the need to obtain a written informed consent from their parent or legal guardian. Additionally, assent was obtained from the minors themselves to ensure their willingness to participate. The study was conducted with the full support and oversight of the school authorities, who ensured that all procedures respected the rights, privacy, and well-being of the participants. 2 Results 2.1 Descriptive Statistics 2.1.1 General information A total of 1,576 secondary school students in central Anhui province were included in this study, with a mean age of 16.8 ± 0.85 years (age range 14–19 years),as shown in Table 1. As can be seen in Table 1, the proportion of only children in the sample was low, which may be related to changes in family structure. Table 1 General Information Variables Categories Numbers(n) Proportion(%) Variables Categories Numbers(n) Proportion(%) Gender Male 872 55.3 Mother's degree Primary school and below 569 36.1 Female 704 44.7 Junior high school 771 48.9 Grade Senior one 484 30.7 High school or technical secondary school 146 9.3 Senior two 455 28.9 University and above 89 5.6 Senior three 637 40.4 Family type Nuclear family 1123 71.3 Whether or not an only child Yes 238 15.1 Single-parent family 100 6.4 No 1338 84.9 Extended family 296 18.8 Nation han nationality 1538 97.6 Reconstituted family 55 3.5 the other 35 2.4 Academic record excellent 107 6.8 Father's degree Primary school and below 407 25.8 Medium upper middle 379 24 Junior high school 852 54.1 Middle 542 34.4 High school or technical secondary school 201 12.8 Lower middle 382 24.2 University and above 116 7.4 Worse 166 10.5 2.1.2 Scores on Dimensions of Adolescent Life Events and Anxiety for High School Students High school students' scores on the dimensions of adolescent life events and anxiety are shown in Table 2 . Higher scores on the Adolescent Life Events and Anxiety item indicate more negative life events experienced and higher levels of anxiety. Table 2 Adolescent Self-Rating Life Events Checklist and Self-rating Anxiety Scale scores Scale Dimension Item Average Scale Item Average Adolescent Self-Rating Life Events Checklist Interpersonal Relationship ASLEC-1 1.91 ± 0.85 Self-rating Anxiety Scale SAS-1 1.67 ± 0.77 ASLEC-2 1.50 ± 0.81 SAS-2 1.74 ± 0.78 ASLEC-4 2.03 ± 0.89 SAS-3 1.76 ± 0.81 ASLEC-15 1.73 ± 0.89 SAS-4 1.40 ± 0.69 ASLEC-25 1.91 ± 1.08 SAS-5 3.17 ± 0.83 ASLEC-26 1.21 ± 0.56 SAS-6 1.42 ± 0.68 Learning Pressure ASLEC-3 2.76 ± 1.03 SAS-7 1.69 ± 0.84 ASLEC-9 2.84 ± 1.09 SAS-8 1.84 ± 0.83 ASLEC-16 1.78 ± 1.02 SAS-9 2.81 ± 0.85 ASLEC-18 1.38 ± 0.82 SAS-10 1.64 ± 0.73 ASLEC-22 2.41 ± 1.28 SAS-11 1.53 ± 0.73 Punished ASLEC-17 1.65 ± 0.94 SAS-12 1.43 ± 0.69 ASLEC-19 1.21 ± 0.58 SAS-13 2.99 ± 1.12 ASLEC-20 1.09 ± 0.41 SAS-14 1.36 ± 0.62 ASLEC-21 1.13 ± 0.48 SAS-15 1.60 ± 0.83 ASLEC-23 1.14 ± 0.49 SAS-16 1.58 ± 0.81 ASLEC-24 1.29 ± 0.66 SAS-17 2.93 ± 0.94 Loss of Family, Friends and Property ASLEC-12 1.40 ± 0.87 SAS-18 1.53 ± 0.72 ASLEC-13 1.29 ± 0.81 SAS-19 2.68 ± 0.98 ASLEC-14 1.51 ± 0.77 SAS-20 1.57 ± 0.73 Health and Adaptation Issues ASLEC-5 1.64 ± 0.87 ASLEC-8 2.02 ± 1.27 ASLEC-11 1.13 ± 0.46 ASLEC-27 1.08 ± 0.42 Other ASLEC-6 2.09 ± 1.17 ASLEC-7 1.27 ± 0.77 ASLEC-10 1.65 ± 0.95 ASLEC-1 :Being misunderstood or wrongly accused. ASLEC-2 :Being subjected to discrimination. ASLEC-3 :Failed or unsatisfactory exams. ASLEC-4 :Disputes with classmates or close friends. ASLEC-5 :Significant changes in living habits (diet,etc.). ASLEC-6 :Dislike of school. ASLEC-7 :Unsuccessful or broken relationships. ASLEC-8 :Being away from family for a long time and not being able to be reunited. ASLEC-9 :Heavy burden of study. ASLEC-10 :Tension with teachers. ASLEC-11 :I am seriously ill. ASLEC-12 :I am seriously ill. ASLEC-13 : Death of a friend or relative. ASLEC-14 :To have something stolen or lost. ASLEC-15 :Losing face in public. ASLEC-16 :Financial difficulties in the family. ASLEC-17 :Conflicts within the family. ASLEC-18 :Failure to participate in the selection (such as the three good students). ASLEC-19 :Being criticized or disciplined. ASLEC-20 :Transferring or suspending from school. ASLEC-21 :Being fined. ASLEC-22 :Pressure to go to higher education. ASLEC-23 :Fighting with others. ASLEC-24 :Being scolded by parents. ASLEC-25 :Pressure from family to study. ASLEC-26 :Accidental scares, accidents. ASLEC-27 :If there are other incidents, please write them down. SAS-1 :I feel more nervous and anxious than usual. SAS-2 :I feel worried for no reason. SAS-3 : I get upset or panic easily. SAS-4 :I feel like my body is in pieces. SAS-5 :I feel that everything is going well and no bad luck will happen. SAS-6 :my limbs shake and tremble. SAS-7 :I am troubled by headaches, neck pain and back pain. SAS-8 :I feel weak and easily fatigued. SAS-9 :I feel calm and can sit quietly. SAS-10 :I feel that my heart beats faster. SAS-11 :I was uncomfortable due to bouts of vertigo.S AS-12 :I have bouts of feeling like I'm going to faint. SAS-13 :I breathe in and out without effort. SAS-14 :I feel numbness and tingling in my fingers and toes. SAS-15 :I suffer from stomach pains and indigestion. SAS-16 :I have to urinate from time to time. SAS-17 :my hands are always warm and dry. SAS-18 :I feel feverish and red in the face. SAS-19 :I fall asleep easily and rest well at night. SAS-20 :I have nightmares. 2.2 Network analysis results 2.2.1 The overall network structure of adolescent life events and anxiety The network structure of the Adolescent Life Events and Anxiety Symptoms is shown in Fig. 1 . The nodes represent each question item in the scale, and the node concatenation indicates the partial correlation coefficients between the symptoms. The 47 nodes in this study were clustered into 2 distinct symptom clusters with a total of 385 nonzero edges. The edges were thicker and denser within symptom clusters compared to between symptom clusters. The connection within each symptom was stronger, and the same symptom cluster tended to cluster together, with both of the 2 sub-networks forming 2 more centralized clusters. 2.2.2 Node characteristics in adolescent life events and anxiety networks The strength centrality and bridge strength centrality of the nodes in the network structure of adolescent life events and anxiety are shown in Figs. 2 and 3 , and for a more intuitive comparison in the graphs, the values of the node intensities are counted in Table 3 . The SAS-3 ‘I get upset or panic easily’(1.22) and SAS-12‘I have bouts of feeling like I am going to faint’(1.18) were high on the Anxiety Self-Rating Scale, and the ASLEC-15‘Losing face in public’(1.15) and ASLEC-2‘Being discriminated against’(1.09) were high on the Adolescent Life Events Scale (ALES). The ASLEC-15‘losing face in public’(strength 1.15) and the ASLEC-2‘being discriminated against’(strength 1.09) showed higher intensities. In the centrality measure of bridge strength, within the Self-Rating Anxiety Scale (SAS), SAS-3, which indicates "I am easily upset or feel panicked" (with a bridge strength of 0.165), and SAS-4, which indicates "I feel as though my body is falling apart into pieces" (with a bridge strength of 0.164), demonstrate the strongest connections within the anxiety symptom cluster. In the Adolescent Self-Rating Life Events Checklist (ASLEC), ASLEC-6, which represents "dislike of school" (with a bridge strength of 0.252), and ASLEC-5, which represents "significant changes in living habits (such as diet)" (with a bridge strength of 0.125), exhibit the strongest connections within the cluster of adolescent life events. The CS coefficients for the strength and bridge strength centrality measures are 0.75 and 0.672, respectively, indicating that the estimated values of node strength are relatively accurate and stable. The significant difference between the strength and bridge strength centrality measures (evidenced by the larger area occupied by the black squares) suggests that the estimated values of node centrality are also relatively accurate and stable, as shown in Fig. 4 – 6 . 2.2.3 Characteristics of the edges in the network of adolescent life events and anxiety. In the Adolescent Self-Rating Life Events Checklist (ASLEC), the edge between ASLEC-12 and ASLEC-13 has the highest weight (weight = 0.33); in the Self-Rating Anxiety Scale (SAS), the edge between SAS-2 and SAS-3 has the highest weight (weight = 0.33); and between the two subnetworks, the edge between ASLEC-6 and SAS-9 has the highest weight (weight = 0.11). The 95% confidence intervals for the edge weights, calculated using the bootstrap method, are relatively narrow, and the differences in weights are significant, indicating that the accuracy of the edge weights in this network is relatively reliable, as shown in Fig. 7 . Table 3 Centrality indicators of negative emotions and parental psychological control network structure at each node 项目 强度 桥强度 ASLEC1 0.96 0.027 ASLEC2 1.09 0.085 ASLEC3 0.94 0.059 ASLEC4 0.88 0.025 ASLEC5 0.91 0.125 ASLEC6 0.99 0.252 ASLEC7 0.51 0.084 ASLEC8 0.56 0.004 ASLEC9 1.04 0.071 ASLEC10 0.95 0.068 ASLEC11 0.88 0.029 ASLEC12 0.74 0.010 ASLEC13 0.58 0 ASLEC14 0.93 0.066 ASLEC15 1.15 0.065 ASLEC16 0.94 0.053 ASLEC17 0.99 0.023 ASLEC18 0.64 0.007 ASLEC19 1.05 0.015 ASLEC20 0.87 0.021 ASLEC21 0.77 0.029 ASLEC22 0.88 0.019 ASLEC23 0.86 0 ASLEC24 1.02 0.066 ASLEC25 1.03 0.002 ASLEC26 0.89 0.098 ASLEC27 0.62 0.018 SAS1 0.98 0.090 SAS2 1.02 0.052 SAS3 1.22 0.165 SAS4 1.09 0.164 SAS5 0.62 0.018 SAS6 1.04 0.048 SAS7 0.98 0.101 SAS8 1.04 0.156 SAS9 0.77 0.105 SAS10 0.81 0.009 SAS11 1.13 0.019 SAS12 1.18 0.014 SAS13 0.58 0 SAS14 1.00 0.073 SAS15 0.86 0.051 SAS16 0.71 0.044 SAS17 0.64 0.003 SAS18 0.84 0.061 SAS19 0.72 0.092 SAS20 0.69 0.055 3 Discussion 3.1 Identification and analysis of core symptoms This study employed network analysis to explore the complex relationship between negative life events and anxiety symptoms in adolescents. The results revealed that the item "I am easily upset or feel panicked" (SAS-3) from the Self-Rating Anxiety Scale exhibited the highest centrality in terms of both strength and expected influence, making it a core symptom within the network. This finding is consistent with previous research(Su et al., 2005 ), indicating that this symptom plays a critical role in the emergence and development of anxiety. From a psychological perspective, the onset of anxiety is closely related to an individual's cognitive patterns. When high school students face stress or uncertainty, a tendency to interpret such situations as threats can easily trigger feelings of upset and panic, thereby affecting their academic performance and quality of life. Additionally, the item "losing face in public" (ASLEC-15) from the Adolescent Self-Rating Life Events Checklist (ASLEC) also demonstrated relatively high centrality, suggesting that this event has a significant impact on the network. High school students are at a stage where self-esteem is particularly important, and losing face in public may lead to feelings of inferiority, which is an independent risk factor for anxiety. This can further undermine adolescents' social confidence and mental health(Miao et al., 2020 ). 3.2 The role of bridge symptoms In network analysis, bridge symptoms play a crucial role in connecting two subnetworks. The results indicate that "dislike of school" (ASLEC-6) and "I am easily upset or feel panicked" (SAS-3) are the most influential bridge symptoms, suggesting that the connection between these two symptoms dominates the interaction between negative life events and anxiety symptoms among high school students. Specifically, the edge between "dislike of school" (ASLEC-6) and "I feel restless and cannot sit still" (SAS-9) has the highest weight, indicating a significant positive correlation between academic pressure and anxiety symptoms(L. T. Chen, Yang, Ou, & Guo, 2022 ). This finding aligns with previous research(M. K. Li, 2021 ), demonstrating that academic pressure is a major trigger for anxiety among high school students. When faced with academic stress, a lack of effective coping strategies can easily lead to anxiety, thereby affecting students' learning efficiency and mental health. Additionally, "dislike of school" (ASLEC-6), as a bridge symptom, could be considered an indicator for the early identification of anxiety symptoms. 3.3 The overall characteristics of the network structure The network analysis results reveal that negative life events and anxiety symptoms form two tightly connected subnetworks, indicating a complex interplay between the two. Specifically, ASLEC−2 ("being discriminated against or treated coldly") and ASLEC−15 ("losing face in public") exhibit high strength within the adolescent life events subnetwork, while "I am easily upset or feel panicked" (SAS−3) and "I have spells of feeling like fainting" (SAS−12) show high strength within the anxiety symptoms subnetwork. These core symptoms not only have a significant impact within their respective subnetworks but also interact with symptoms in other subnetworks through bridge symptoms, further exacerbating the development of anxiety. Frequent anxiety among high school students is closely linked to academic pressure, which is considered a significant contributing factor. Scholars attribute the primary causes of academic pressure to four aspects: parental expectations, self-demands, teacher influences, and social interactions. These factors, combined with performance goals, external environments, encountered setbacks, and academic competition, are identified as the main sources of stress for high school students (Xu, Cao, Cui, & Zhu, 2010 ). High school students are in a stage of rapid physical and mental development while simultaneously facing the pressures of college entrance exams, a critical period in their lives. They endure stress from various aspects such as academics and daily life, and concerns about an uncertain future, feelings of panic, and premonitions of misfortune can exacerbate their anxiety (R. Liu et al., 2022 ). This study suggests that the relationship between academic pressure and anxiety is not simply one of cause and effect. High school students can alleviate anxiety through psychological guidance, thereby improving academic performance. However, a moderate level of anxiety might also enhance students' motivation to learn, potentially boosting academic efficiency(Caldwell et al., 2019 ). Additionally, the stability coefficient of the network structure is relatively high, indicating that the results possess a high degree of reliability and stability. 3.4 Suggestions for intervention strategies Based on the aforementioned results, this study provides empirical evidence for precisely intervening in negative life events and alleviating anxiety among high school students. First, targeted psychological counseling and relaxation training can be implemented for the core symptom "I am easily upset or feel panicked" (SAS−3), helping students learn to cope with stress and regulate their emotions. Second, for the bridge symptom "dislike of school" (ASLEC−6), efforts can be made to enhance motivation for learning and improve stress management, assisting students in developing a positive attitude toward learning and setting appropriate academic goals. Additionally, for negative life events such as "losing face in public" (ASLEC−15), social skills training and self-esteem building programs can be introduced to help students improve their social abilities and boost their confidence. Through these intervention measures, it is possible to effectively reduce anxiety levels among high school students and enhance their mental well-being. 3.5 Limitations and future directions of research This study, employing network analysis, reveals the complex relationship between negative life events and anxiety symptoms among high school students, providing empirical evidence for targeted interventions. However, the research has several limitations. First, the cross-sectional design of this study cannot establish a causal relationship between negative life events and anxiety symptoms. Future studies could adopt a longitudinal design to clarify the causal links between the two. Second, this study relies on self-reported data, which may introduce subjective bias. Future research could incorporate objective measurement methods, such as physiological indicators and behavioral observations, to enhance the accuracy of the findings. Additionally, the sample of this study is limited to high school students from the central Anhui region. Future studies could expand the sample size to improve the generalizability and applicability of the results. Finally, this study focuses solely on the relationship between negative life events and anxiety symptoms. Future research could further explore the role of other psychological factors (e.g., depression, coping styles) in this relationship to provide more comprehensive intervention strategies. Declarations Ethics approval and consent to participate All subjects who participated in the survey signed the informed consent form. All methods were carried out in accordance with relevant guidelines and regulations.The survey has received approval from the Academic Ethics Committee of Wannan Medical College. Consent for publication Not applicable. Availability of data and materials The datasets used and/or analysed during the current study available from the corresponding author on reasonable request. Competing interests The authors declare that they have no competing interests. Funding This research was supported by the Humanities and Social Science Major Project of the Anhui Provincial Education Department (2024AH040383) and Research Project on Student Mental Health by the National Center for Mental Health (XS25B029) Authors’ contributions Zijun Chen: Research design, First draft writing, Analyzing data. Ke Zheng: Data collection, Formal analysis. Qiyun Jiang: Data collection. Jiusheng Wang: Data collection. Biao Chen: Data collection. Zihan Wang: Data collection. Zhouyu Wang: Data collection. Liang Yu: Study design, Methodology, Writing, Criticism and Editing. Authors details 1Wannan Medical College,Wuhu, Anhui, China References Borsboom, & Denny. (2017). A network theory of mental disorders. World Psychiatry, 16 (1). Caldwell, D. M., Davies, S. R., Hetrick, S. E., Palmer, J. C., Caro, P., López-López, J. A., . . . Welton, N. J. (2019). School-based interventions to prevent anxiety and depression in children and young people: a systematic review and network meta-analysis. Lancet Psychiatry, 6 (12), 1011-1020. doi:10.1016/s2215-0366(19)30403-1 Chen, D., Quan, Z. X., Ai, M. Y., Zong, C. S., & X, J. N. (2020). Adolescents ' mental health status and its influencing factors. china journal of health psychology, 28 (09), 1402-1409. doi:10.13342/j.cnki.cjhp.2020.09.028 Chen, L. T., Yang, Q. L., Ou, Y. J. J., & Guo, X. (2022). 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Psychosomatics, 12 (6), 371-379. doi:10.1016/s0033-3182(71)71479-0 Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Reviewers invited by journal 10 Oct, 2025 Editor invited by journal 19 Sep, 2025 Editor assigned by journal 17 Sep, 2025 Submission checks completed at journal 17 Sep, 2025 First submitted to journal 16 Sep, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7634586","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":532535303,"identity":"d5b44236-7b12-4e51-8d76-2e59b0cce928","order_by":0,"name":"Zijun Chen","email":"","orcid":"","institution":"Wannan Medical College","correspondingAuthor":false,"prefix":"","firstName":"Zijun","middleName":"","lastName":"Chen","suffix":""},{"id":532535304,"identity":"00e62233-0d69-4426-ae69-9a76fbe32189","order_by":1,"name":"Ke Zheng","email":"","orcid":"","institution":"Wannan Medical 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The connecting lines between nodes represent the partial correlation coefficients between symptoms. Nodes that are closer to each other, with thicker and darker-colored lines, indicate stronger correlations between the items. Conversely, nodes that are farther apart, with thinner and lighter-colored lines, suggest weaker relationships between the items.\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-7634586/v1/4f5d79ed54acf508af0234ef.png"},{"id":94195515,"identity":"0ee1b630-7340-47a5-807c-0f07078fb7db","added_by":"auto","created_at":"2025-10-23 12:55:57","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":124064,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eStrength index of each node bridge in ASLEC and SAS network structure\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-7634586/v1/6878190958713579246711db.png"},{"id":94194636,"identity":"6c09ba46-3607-43eb-a0c9-762f7c2f24de","added_by":"auto","created_at":"2025-10-23 12:47:57","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":205990,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eThe centrality index of each node in the ASLEC and SAS network structures\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-7634586/v1/1ca1af1dca47803255a34436.png"},{"id":94194646,"identity":"6d57d7d2-7f70-44c4-a990-cf526cb1224e","added_by":"auto","created_at":"2025-10-23 12:47:57","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":311447,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eDifferences in Strength Centrality Index between ASLEC and SAS Network Structures\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"floatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-7634586/v1/0481444dfef6f989d6842a21.png"},{"id":94194643,"identity":"9fb23986-6158-48a2-9f36-79646304e53a","added_by":"auto","created_at":"2025-10-23 12:47:57","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":199614,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eDifferences in Bridge Strength Centrality Index between ASLEC and SAS\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"floatimage5.png","url":"https://assets-eu.researchsquare.com/files/rs-7634586/v1/8b635cbadfd8eaf844a8adf3.png"},{"id":94194641,"identity":"c98c98a0-e53b-4795-bb42-ca21ef59b7ff","added_by":"auto","created_at":"2025-10-23 12:47:57","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":42535,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eStability of Centrality Index in ASLEC and SAS Network Structures\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"floatimage6.png","url":"https://assets-eu.researchsquare.com/files/rs-7634586/v1/060b211af4fb9b228374a479.png"},{"id":94195522,"identity":"99a57b15-9c5a-4eb9-ba6d-9fb3f7afdde8","added_by":"auto","created_at":"2025-10-23 12:55:57","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":87666,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eConfidence intervals for edge weights of ASLEC and SAS network structures Network Structures\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"floatimage7.png","url":"https://assets-eu.researchsquare.com/files/rs-7634586/v1/ee7a316c24e225c885bd68eb.png"},{"id":94197119,"identity":"6914d571-7b62-4b51-9992-fa6872c36c7a","added_by":"auto","created_at":"2025-10-23 13:19:59","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2590487,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7634586/v1/d1ec0ea5-a2aa-47c1-a0cc-06c4e2dad9e0.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Unveiling the Dynamic Mechanisms of Anxiety: A Network Analysis of Negative Life Events and Anxiety Symptoms Among High School Students","fulltext":[{"header":"Highlights","content":"\u003cp\u003eThe analytical method is innovative, employing network analysis to reveal the complex network structure formed by the interactions between latent variables and observed variables. This method is suitable for analyzing the relationship between negative life events and anxiety in adolescents;Through extensive empirical investigations conducted in high schools across central Anhui Province, corresponding conclusions were drawn, yielding results capable of predicting mental health issues among high school students;the present study plans to use network analysis to explore the relationship between symptoms and their interconnections (edges) at each node in the network of negative life events and anxiety, to identify the core node symptoms in the entire network and provide empirical evidence for the development of targeted intervention programs.\u003c/p\u003e"},{"header":"Introduction","content":"\u003cp\u003eHigh school is a critical period of physiological and psychological development of individual students, and also a period prone to psychological problems (D. Chen, Quan, Ai, Zong, \u0026amp; X, 2020). As students age and grade level rise, they face increased negative life events such as increasing academic pressure and complex interpersonal relationships. It has been shown that negative life events are a kind of life crisis, their occurrence will make students experience more anxiety and tension, which will affect their healthy growth(Tang \u0026amp; Zhou, 2014). It also stimulates the individual's perceptual factors and increases the individual's attention and processing of harmful stimuli, leading to the emotional experience of anxiety(Huang et al., 2021).\u003c/p\u003e\n\u003cp\u003eAnxiety is an emotional disorder, referred to as ‘anxious emotions’, often called ‘anxiety syndrome’ or ‘anxiety disorder’, and is the most common mental illness among adolescents. It is the most common mental illness among adolescents. It is a complex psychological process that involves the expression of nervousness in the face of an impending situation (negative life events) that is likely to cause harm to the person. Symptoms include excessive worry, fear of future events, nervousness, and physical symptoms such as increased heart rate, sweating, and sleep disorders(Vallance, Aaron, K., Fernandez, \u0026amp; Victoria., 2016). Anxiety manifests itself in a variety of forms and may vary according to individual and environmental differences. Although it does not directly lead to physiological diseases, chronic anxiety may complicate health problems such as hypertension and cardiovascular disease, and may also have a sustained, negative impact on adolescents' cognitive behavior ability, academic performance, and personality dignity (Waite \u0026amp; Creswell, 2015).\u003c/p\u003e\n\u003cp\u003eIt has been shown that the more negative life events and the greater the stimulation of emotions in a certain period, the more prone to anxiety(H. Y. Liu \u0026amp; Wang, 2017). It shows that there is a significant positive correlation between negative life events and the level of anxiety(K. S. Li, Zhang, Zhang, Mo, \u0026amp; Pan, 2023), which can positively predict students‘anxiety, i.e., the more negative life events, the lower the students’ self-efficacy, the less controllable they are to the events, and the more anxiety they will develop. Research on negative life events and anxiety has focused on correlation analysis or on the mediating model through which they positively or negatively affect adolescents' mental health. According to the Network Theory of Mental Disorders (NTMD) proposed by Borboom(Borsboom \u0026amp; Denny, 2017), mental health is the result of a complex interaction of multiple symptoms rather than a simple manifestation of a single underlying symptom. The core of the network analysis method is to reveal the complex network structure formed by the interactions between latent variables and observation variables, and this method is also suitable for analyzing the relationship between negative life events and anxiety(Ren et al., 2020) . Therefore, the present study plans to use network analysis to explore the relationship between symptoms and their interconnections (edges) at each node in the network of negative life events and anxiety, to identify the core node symptoms in the entire network and provide empirical evidence for the development of targeted intervention programs.\u003c/p\u003e"},{"header":"1 Subjects and methods","content":"\u003cdiv id=\"Sec2\" class=\"Section2\"\u003e\u003ch2\u003e1.1 Research object\u003c/h2\u003e\u003cp\u003eIn this study, a stratified random sampling method was used from March to June 2024 to select some high school students in central Anhui Province, Anhui Province for a questionnaire survey. All respondents were informed and signed an informed consent. A total of 1700 questionnaires were distributed, and 1576 valid questionnaires were recovered, with an effective recovery rate of 92.7%.Written informed consent was obtained from all participating adolescents. For those under 16 years of age,parental or legal guardian consent was additionally secured.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003e1.2 Survey instrument\u003c/h2\u003e\u003cdiv id=\"Sec4\" class=\"Section3\"\u003e\u003ch2\u003e1.2.1 Personal and Family Information Survey\u003c/h2\u003e\u003cp\u003eReview relevant literature, summarize, generalize and design their questionnaires to investigate basic information (including gender, ethnicity, grade, whether they are an only child, parents' literacy and academic performance).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec5\" class=\"Section3\"\u003e\u003ch2\u003e1.2.2 Adolescent Self-Rating Life Events CheckList\u003c/h2\u003e\u003cp\u003eThe research object of this study was high school students, and the Adolescent Self-Rating Life Events Checklist (ASLEC) compiled by Liu Xianchen(X. C. Liu et al., \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e1997\u003c/span\u003e)was used, which consists of 27 negative life events that may bring physiopsychological reactions to adolescents, including learning pressure, health adaptation, interpersonal relationship, punishment, loss and other 6 dimensions, and is scored as 0 if it does not occur, and 5-point scale according to the psychological feelings when it occurs, with higher scores indicating that high school students encountered more negative life events. The Cronbach's alpha coefficient of the scale is 0.85, which means that the reliability of the scale is good, and the applicability of the ASLEC scale to the high school student population has been widely verified.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec6\" class=\"Section3\"\u003e\u003ch2\u003e1.2.3 Self-rating Anxiety Scale\u003c/h2\u003e\u003cp\u003eThe Self-rating Anxiety Scale (SAS)(Zung, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e1971\u003c/span\u003e)is currently the most widely used and effective standardized quantitative measure for assessing anxiety. It consists of 20 self-assessment items, each representing a specific symptom. Respondents indicate the frequency of each symptom based on their own experiences: 1 point for 'not at all or rarely,' 2 points for 'sometimes,' 3 points for 'often,' and 4 points for 'most of the time.' Among the 20 items in the SAS, every few questions\u0026mdash;specifically items 5, 9, 13, 17, and 19\u0026mdash;are reverse-scored. After completing the self-assessment, the scores for all items are summed and converted into a percentage (by multiplying by 1.25) to obtain the final score. According to the standard, a score below 50 is considered normal, 50\u0026ndash;60 indicates mild anxiety, 60\u0026ndash;70 indicates moderate anxiety, and a score above 70 indicates severe anxiety. The scale demonstrates good reliability and validity, with a Cronbach\u0026rsquo;sαcoefficient of 0.82.\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e\u003ch2\u003e1.3 Statistical method\u003c/h2\u003e\u003cp\u003eAfter data entry, mssing values were first processed, and then appropriate statistical tests were selected based on the type of distribution of the data. Parametric tests were used for normal distribution data, and non-parametric tests were used for non-normal distribution data.\u003c/p\u003e\u003cp\u003eIn this study, SPSS 26.0 and R software (Version 4.4.1) were used for data entry, descriptive statistics analysis, and network model construction. The R-package graph package's EBICglasso function was used to estimate the partial correlation matrix and generate a visual network model, the basic composition of which consists of circular nodes (Node) with edges (Edge) indicating the strength of association between nodes. The centrality metrics of the network nodes are calculated and displayed as Z-scores by the R-package graph package and the R-package network tools package. These metrics include: Strength, which is the sum of the absolute values of all edges connecting a node, the higher its value, the greater the relative importance of the node in the network(Epskamp, Cramer, Waldorp, Schmittmann, \u0026amp; Borsboom, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2012\u003c/span\u003e); Bridge Strength is the sum of the absolute values of all edges connecting the node to other cluster nodes, the higher the value represents the greater the risk of the node to pass to the other cluster, the more obvious the bridge effect is, this study divided the target variable into two parts. The target variables were divided into 2 clusters in this study, which were the Adolescent Life Events Scale and the Anxiety Self-Rating Scale(Jones, Ma, \u0026amp; Mcnally, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Using the R-package botnet package, 95% confidence intervals (1000 bootstrap) were calculated for the edge weights to assess the accuracy of the edge weights, and Correlation Stability (CS) coefficients were calculated to assess the stability of the edge weight values and the expected impact of the nodes(Epskamp, Borsboom, \u0026amp; Fried, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). The CS coefficients should be at least greater than 0.25 and ideally greater than 0.50, and a cut-off value of 0.25 was set for the CS coefficient in this study(Epskamp \u0026amp; Fried, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). All statistical analyses were performed at a significance level of α\u0026thinsp;=\u0026thinsp;0.05.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003e1.4 Ethics approval and consent to participate\u003c/h2\u003e\u003cp\u003e This study was conducted in accordance with the ethical principles outlined in the Declaration of Helsinki. The research protocol was reviewed and approved by the relevant school authorities, ensuring that all procedures adhered to ethical standards for research involving human participants. All subjects who participated in the survey signed the informed consent form. All methods were carried out in accordance with relevant guidelines and regulations.The survey has received approval from the Academic Ethics Committee of College.\u003c/p\u003e\u003cp\u003e For participants under the age of 16, prior to their participation in the study, they were explicitly informed of the need to obtain a written informed consent from their parent or legal guardian. Additionally, assent was obtained from the minors themselves to ensure their willingness to participate. The study was conducted with the full support and oversight of the school authorities, who ensured that all procedures respected the rights, privacy, and well-being of the participants.\u003c/p\u003e\u003c/div\u003e"},{"header":"2 Results","content":"\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e\n \u003ch2\u003e2.1 Descriptive Statistics\u003c/h2\u003e\n \u003cdiv id=\"Sec11\" class=\"Section3\"\u003e\n \u003ch2\u003e2.1.1 General information\u003c/h2\u003e\n \u003cdiv class=\"gridtable\"\u003e\n \u003cdiv align=\"left\" class=\"colspec\"\u003eA total of 1,576 secondary school students in central Anhui province were included in this study, with a mean age of 16.8\u0026thinsp;\u0026plusmn;\u0026thinsp;0.85 years (age range 14\u0026ndash;19 years),as shown in Table 1. As can be seen in Table 1, the proportion of only children in the sample was low, which may be related to changes in family structure.\u003c/div\u003e\n \u003cdiv align=\"left\" class=\"colspec\"\u003e\u003cbr\u003e\u003c/div\u003e\n \u003ctable id=\"Taba\" border=\"1\"\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" colspan=\"8\"\u003e\n \u003cp\u003eTable 1 General Information\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"1\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eVariables\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCategories\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNumbers(n)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eProportion(%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eVariables\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eCategories\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNumbers(n)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eProportion(%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eGender\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e872\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e55.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"4\"\u003e\n \u003cp\u003eMother\u0026apos;s degree\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003ePrimary school and below\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e569\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e36.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e704\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e44.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eJunior high school\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e771\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e48.9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"3\"\u003e\n \u003cp\u003eGrade\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSenior one\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e484\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e30.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eHigh school or technical secondary school\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e146\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9.3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSenior two\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e455\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e28.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eUniversity and above\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e89\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5.6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSenior three\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e637\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e40.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFamily type\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eNuclear family\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1123\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e71.3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eWhether or not an only child\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e238\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e15.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\" rowspan=\"3\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSingle-parent family\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6.4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1338\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e84.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eExtended family\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e296\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e18.8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eNation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ehan nationality\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1538\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e97.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eReconstituted family\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e55\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ethe other\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\" rowspan=\"5\"\u003e\n \u003cp\u003eAcademic record\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eexcellent\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e107\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6.8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"4\"\u003e\n \u003cp\u003eFather\u0026apos;s degree\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePrimary school and below\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e407\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e25.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMedium upper middle\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e379\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e24\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eJunior high school\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e852\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e54.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMiddle\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e542\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e34.4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHigh school or technical secondary school\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e201\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e12.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLower middle\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e382\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e24.2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eUniversity and above\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e116\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eWorse\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e166\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10.5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003c/div\u003e\n \u003cdiv id=\"Sec12\" class=\"Section3\"\u003e\n \u003ch2\u003e2.1.2 Scores on Dimensions of Adolescent Life Events and Anxiety for High School Students\u003c/h2\u003e\n \u003cp\u003eHigh school students\u0026apos; scores on the dimensions of adolescent life events and anxiety are shown in Table \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e. Higher scores on the Adolescent Life Events and Anxiety item indicate more negative life events experienced and higher levels of anxiety.\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\n \u003ctable id=\"Tab1\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eAdolescent Self-Rating Life Events Checklist and Self-rating Anxiety Scale scores\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eScale\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eDimension\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eItem\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eAverage\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eScale\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eItem\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eAverage\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"27\"\u003e\n \u003cp\u003eAdolescent Self-Rating Life Events Checklist\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"6\"\u003e\n \u003cp\u003eInterpersonal Relationship\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eASLEC-1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.91\u0026thinsp;\u0026plusmn;\u0026thinsp;0.85\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"27\"\u003e\n \u003cp\u003eSelf-rating Anxiety Scale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSAS-1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.67\u0026thinsp;\u0026plusmn;\u0026thinsp;0.77\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eASLEC-2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.50\u0026thinsp;\u0026plusmn;\u0026thinsp;0.81\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSAS-2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.74\u0026thinsp;\u0026plusmn;\u0026thinsp;0.78\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eASLEC-4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.03\u0026thinsp;\u0026plusmn;\u0026thinsp;0.89\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSAS-3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.76\u0026thinsp;\u0026plusmn;\u0026thinsp;0.81\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eASLEC-15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.73\u0026thinsp;\u0026plusmn;\u0026thinsp;0.89\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSAS-4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.40\u0026thinsp;\u0026plusmn;\u0026thinsp;0.69\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eASLEC-25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.91\u0026thinsp;\u0026plusmn;\u0026thinsp;1.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSAS-5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.17\u0026thinsp;\u0026plusmn;\u0026thinsp;0.83\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eASLEC-26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.21\u0026thinsp;\u0026plusmn;\u0026thinsp;0.56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSAS-6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.42\u0026thinsp;\u0026plusmn;\u0026thinsp;0.68\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"5\"\u003e\n \u003cp\u003eLearning Pressure\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eASLEC-3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.76\u0026thinsp;\u0026plusmn;\u0026thinsp;1.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSAS-7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.69\u0026thinsp;\u0026plusmn;\u0026thinsp;0.84\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eASLEC-9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.84\u0026thinsp;\u0026plusmn;\u0026thinsp;1.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSAS-8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.84\u0026thinsp;\u0026plusmn;\u0026thinsp;0.83\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eASLEC-16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.78\u0026thinsp;\u0026plusmn;\u0026thinsp;1.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSAS-9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.81\u0026thinsp;\u0026plusmn;\u0026thinsp;0.85\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eASLEC-18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.38\u0026thinsp;\u0026plusmn;\u0026thinsp;0.82\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSAS-10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.64\u0026thinsp;\u0026plusmn;\u0026thinsp;0.73\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eASLEC-22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.41\u0026thinsp;\u0026plusmn;\u0026thinsp;1.28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSAS-11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.53\u0026thinsp;\u0026plusmn;\u0026thinsp;0.73\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"6\"\u003e\n \u003cp\u003ePunished\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eASLEC-17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.65\u0026thinsp;\u0026plusmn;\u0026thinsp;0.94\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSAS-12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.43\u0026thinsp;\u0026plusmn;\u0026thinsp;0.69\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eASLEC-19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.21\u0026thinsp;\u0026plusmn;\u0026thinsp;0.58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSAS-13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.99\u0026thinsp;\u0026plusmn;\u0026thinsp;1.12\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eASLEC-20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.09\u0026thinsp;\u0026plusmn;\u0026thinsp;0.41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSAS-14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.36\u0026thinsp;\u0026plusmn;\u0026thinsp;0.62\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eASLEC-21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.13\u0026thinsp;\u0026plusmn;\u0026thinsp;0.48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSAS-15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.60\u0026thinsp;\u0026plusmn;\u0026thinsp;0.83\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eASLEC-23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.14\u0026thinsp;\u0026plusmn;\u0026thinsp;0.49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSAS-16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.58\u0026thinsp;\u0026plusmn;\u0026thinsp;0.81\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eASLEC-24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.29\u0026thinsp;\u0026plusmn;\u0026thinsp;0.66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSAS-17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.93\u0026thinsp;\u0026plusmn;\u0026thinsp;0.94\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"3\"\u003e\n \u003cp\u003eLoss of Family, Friends and Property\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eASLEC-12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.40\u0026thinsp;\u0026plusmn;\u0026thinsp;0.87\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSAS-18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.53\u0026thinsp;\u0026plusmn;\u0026thinsp;0.72\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eASLEC-13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.29\u0026thinsp;\u0026plusmn;\u0026thinsp;0.81\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSAS-19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.68\u0026thinsp;\u0026plusmn;\u0026thinsp;0.98\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eASLEC-14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.51\u0026thinsp;\u0026plusmn;\u0026thinsp;0.77\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSAS-20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.57\u0026thinsp;\u0026plusmn;\u0026thinsp;0.73\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"4\"\u003e\n \u003cp\u003eHealth and Adaptation Issues\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eASLEC-5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.64\u0026thinsp;\u0026plusmn;\u0026thinsp;0.87\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eASLEC-8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.02\u0026thinsp;\u0026plusmn;\u0026thinsp;1.27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eASLEC-11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.13\u0026thinsp;\u0026plusmn;\u0026thinsp;0.46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eASLEC-27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.08\u0026thinsp;\u0026plusmn;\u0026thinsp;0.42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"3\"\u003e\n \u003cp\u003eOther\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eASLEC-6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.09\u0026thinsp;\u0026plusmn;\u0026thinsp;1.17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eASLEC-7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.27\u0026thinsp;\u0026plusmn;\u0026thinsp;0.77\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eASLEC-10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.65\u0026thinsp;\u0026plusmn;\u0026thinsp;0.95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cp\u003e\u003cstrong\u003eASLEC-1\u003c/strong\u003e:Being misunderstood or wrongly accused.\u003cstrong\u003eASLEC-2\u003c/strong\u003e:Being subjected to discrimination.\u003cstrong\u003eASLEC-3\u003c/strong\u003e:Failed or unsatisfactory exams.\u003cstrong\u003eASLEC-4\u003c/strong\u003e:Disputes with classmates or close friends.\u003cstrong\u003eASLEC-5\u003c/strong\u003e:Significant changes in living habits (diet,etc.).\u003cstrong\u003eASLEC-6\u003c/strong\u003e:Dislike of school.\u003cstrong\u003eASLEC-7\u003c/strong\u003e:Unsuccessful or broken relationships.\u003cstrong\u003eASLEC-8\u003c/strong\u003e:Being away from family for a long time and not being able to be reunited.\u003cstrong\u003eASLEC-9\u003c/strong\u003e:Heavy burden of study.\u003cstrong\u003eASLEC-10\u003c/strong\u003e:Tension with teachers.\u003cstrong\u003eASLEC-11\u003c/strong\u003e:I am seriously ill.\u003cstrong\u003eASLEC-12\u003c/strong\u003e:I am seriously ill.\u003cstrong\u003eASLEC-13\u003c/strong\u003e: Death of a friend or relative.\u003cstrong\u003eASLEC-14\u003c/strong\u003e:To have something stolen or lost. \u003cstrong\u003eASLEC-15\u003c/strong\u003e:Losing face in public.\u003cstrong\u003eASLEC-16\u003c/strong\u003e:Financial difficulties in the family.\u003cstrong\u003eASLEC-17\u003c/strong\u003e:Conflicts within the family.\u003cstrong\u003eASLEC-18\u003c/strong\u003e:Failure to participate in the selection (such as the three good students).\u003cstrong\u003eASLEC-19\u003c/strong\u003e:Being criticized or disciplined.\u003cstrong\u003eASLEC-20\u003c/strong\u003e:Transferring or suspending from school.\u003cstrong\u003eASLEC-21\u003c/strong\u003e:Being fined.\u003cstrong\u003eASLEC-22\u003c/strong\u003e:Pressure to go to higher education.\u003cstrong\u003eASLEC-23\u003c/strong\u003e:Fighting with others.\u003cstrong\u003eASLEC-24\u003c/strong\u003e:Being scolded by parents.\u003cstrong\u003eASLEC-25\u003c/strong\u003e:Pressure from family to study.\u003cstrong\u003eASLEC-26\u003c/strong\u003e:Accidental scares, accidents.\u003cstrong\u003eASLEC-27\u003c/strong\u003e:If there are other incidents, please write them down.\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eSAS-1\u003c/strong\u003e:I feel more nervous and anxious than usual.\u003cstrong\u003eSAS-2\u003c/strong\u003e:I feel worried for no reason.\u003cstrong\u003eSAS-3\u003c/strong\u003e: I get upset or panic easily.\u003cstrong\u003eSAS-4\u003c/strong\u003e:I feel like my body is in pieces.\u003cstrong\u003eSAS-5\u003c/strong\u003e:I feel that everything is going well and no bad luck will happen.\u003cstrong\u003eSAS-6\u003c/strong\u003e:my limbs shake and tremble.\u003cstrong\u003eSAS-7\u003c/strong\u003e:I am troubled by headaches, neck pain and back pain.\u003cstrong\u003eSAS-8\u003c/strong\u003e:I feel weak and easily fatigued.\u003cstrong\u003eSAS-9\u003c/strong\u003e:I feel calm and can sit quietly.\u003cstrong\u003eSAS-10\u003c/strong\u003e:I feel that my heart beats faster.\u003cstrong\u003eSAS-11\u003c/strong\u003e:I was uncomfortable due to bouts of vertigo.S\u003cstrong\u003eAS-12\u003c/strong\u003e:I have bouts of feeling like I\u0026apos;m going to faint.\u003cstrong\u003eSAS-13\u003c/strong\u003e:I breathe in and out without effort.\u003cstrong\u003eSAS-14\u003c/strong\u003e:I feel numbness and tingling in my fingers and toes.\u003cstrong\u003eSAS-15\u003c/strong\u003e:I suffer from stomach pains and indigestion.\u003cstrong\u003eSAS-16\u003c/strong\u003e:I have to urinate from time to time.\u003cstrong\u003eSAS-17\u003c/strong\u003e:my hands are always warm and dry.\u003cstrong\u003eSAS-18\u003c/strong\u003e:I feel feverish and red in the face.\u003cstrong\u003eSAS-19\u003c/strong\u003e:I fall asleep easily and rest well at night.\u003cstrong\u003eSAS-20\u003c/strong\u003e:I have nightmares.\u003c/p\u003e\n \u003c/div\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\n \u003ch2\u003e2.2 Network analysis results\u003c/h2\u003e\n \u003cdiv id=\"Sec14\" class=\"Section3\"\u003e\n \u003ch2\u003e2.2.1 The overall network structure of adolescent life events and anxiety\u003c/h2\u003e\n \u003cp\u003eThe network structure of the Adolescent Life Events and Anxiety Symptoms is shown in Fig. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e. The nodes represent each question item in the scale, and the node concatenation indicates the partial correlation coefficients between the symptoms. The 47 nodes in this study were clustered into 2 distinct symptom clusters with a total of 385 nonzero edges. The edges were thicker and denser within symptom clusters compared to between symptom clusters. The connection within each symptom was stronger, and the same symptom cluster tended to cluster together, with both of the 2 sub-networks forming 2 more centralized clusters.\u003c/p\u003e\n \u003c/div\u003e\n \u003cdiv id=\"Sec15\" class=\"Section3\"\u003e\n \u003ch2\u003e2.2.2 Node characteristics in adolescent life events and anxiety networks\u003c/h2\u003e\n \u003cp\u003eThe strength centrality and bridge strength centrality of the nodes in the network structure of adolescent life events and anxiety are shown in Figs. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e and \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e, and for a more intuitive comparison in the graphs, the values of the node intensities are counted in Table \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e.\u003c/p\u003e\n \u003cp\u003eThe SAS-3 \u0026lsquo;I get upset or panic easily\u0026rsquo;(1.22) and SAS-12\u0026lsquo;I have bouts of feeling like I am going to faint\u0026rsquo;(1.18) were high on the Anxiety Self-Rating Scale, and the ASLEC-15\u0026lsquo;Losing face in public\u0026rsquo;(1.15) and ASLEC-2\u0026lsquo;Being discriminated against\u0026rsquo;(1.09) were high on the Adolescent Life Events Scale (ALES). The ASLEC-15\u0026lsquo;losing face in public\u0026rsquo;(strength 1.15) and the ASLEC-2\u0026lsquo;being discriminated against\u0026rsquo;(strength 1.09) showed higher intensities.\u003c/p\u003e\n \u003cp\u003eIn the centrality measure of bridge strength, within the Self-Rating Anxiety Scale (SAS), SAS-3, which indicates \u0026quot;I am easily upset or feel panicked\u0026quot; (with a bridge strength of 0.165), and SAS-4, which indicates \u0026quot;I feel as though my body is falling apart into pieces\u0026quot; (with a bridge strength of 0.164), demonstrate the strongest connections within the anxiety symptom cluster. In the Adolescent Self-Rating Life Events Checklist (ASLEC), ASLEC-6, which represents \u0026quot;dislike of school\u0026quot; (with a bridge strength of 0.252), and ASLEC-5, which represents \u0026quot;significant changes in living habits (such as diet)\u0026quot; (with a bridge strength of 0.125), exhibit the strongest connections within the cluster of adolescent life events.\u003c/p\u003e\n \u003cp\u003eThe CS coefficients for the strength and bridge strength centrality measures are 0.75 and 0.672, respectively, indicating that the estimated values of node strength are relatively accurate and stable. The significant difference between the strength and bridge strength centrality measures (evidenced by the larger area occupied by the black squares) suggests that the estimated values of node centrality are also relatively accurate and stable, as shown in Fig. \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e\u0026ndash;\u003cspan class=\"InternalRef\"\u003e6\u003c/span\u003e.\u003c/p\u003e\n \u003c/div\u003e\n \u003cdiv id=\"Sec16\" class=\"Section3\"\u003e\n \u003ch2\u003e2.2.3 Characteristics of the edges in the network of adolescent life events and anxiety.\u003c/h2\u003e\n \u003cp\u003eIn the Adolescent Self-Rating Life Events Checklist (ASLEC), the edge between ASLEC-12 and ASLEC-13 has the highest weight (weight\u0026thinsp;=\u0026thinsp;0.33); in the Self-Rating Anxiety Scale (SAS), the edge between SAS-2 and SAS-3 has the highest weight (weight\u0026thinsp;=\u0026thinsp;0.33); and between the two subnetworks, the edge between ASLEC-6 and SAS-9 has the highest weight (weight\u0026thinsp;=\u0026thinsp;0.11). The 95% confidence intervals for the edge weights, calculated using the bootstrap method, are relatively narrow, and the differences in weights are significant, indicating that the accuracy of the edge weights in this network is relatively reliable, as shown in Fig. \u003cspan class=\"InternalRef\"\u003e7\u003c/span\u003e.\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\n \u003ctable id=\"Tab2\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eCentrality indicators of negative emotions and parental psychological control network structure at each node\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e项目\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e强度\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e桥强度\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eASLEC1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.96\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.027\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eASLEC2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.085\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eASLEC3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.94\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.059\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eASLEC4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.025\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eASLEC5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.91\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.125\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eASLEC6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.252\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eASLEC7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.084\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eASLEC8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.004\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eASLEC9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.071\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eASLEC10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.068\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eASLEC11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.029\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eASLEC12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.74\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.010\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eASLEC13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eASLEC14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.93\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.066\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eASLEC15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.065\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eASLEC16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.94\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.053\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eASLEC17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.023\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eASLEC18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.007\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eASLEC19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.015\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eASLEC20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.87\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.021\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eASLEC21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.77\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.029\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eASLEC22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.019\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eASLEC23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.86\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eASLEC24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.066\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eASLEC25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eASLEC26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.89\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.098\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eASLEC27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.62\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.018\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSAS1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.98\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.090\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSAS2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.052\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSAS3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.165\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSAS4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.164\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSAS5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.62\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.018\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSAS6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.048\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSAS7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.98\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.101\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSAS8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.156\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSAS9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.77\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.105\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSAS10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.81\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.009\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSAS11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.019\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSAS12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.014\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSAS13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSAS14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.073\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSAS15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.86\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.051\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSAS16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.71\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.044\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSAS17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.003\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSAS18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.84\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.061\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSAS19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.092\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSAS20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.69\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.055\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003c/div\u003e\n\u003c/div\u003e"},{"header":"3 Discussion","content":"\u003cp\u003e\u003cb\u003e3.1 Identification and analysis of core symptoms\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThis study employed network analysis to explore the complex relationship between negative life events and anxiety symptoms in adolescents. The results revealed that the item \"I am easily upset or feel panicked\" (SAS-3) from the Self-Rating Anxiety Scale exhibited the highest centrality in terms of both strength and expected influence, making it a core symptom within the network. This finding is consistent with previous research(Su et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2005\u003c/span\u003e), indicating that this symptom plays a critical role in the emergence and development of anxiety. From a psychological perspective, the onset of anxiety is closely related to an individual's cognitive patterns. When high school students face stress or uncertainty, a tendency to interpret such situations as threats can easily trigger feelings of upset and panic, thereby affecting their academic performance and quality of life. Additionally, the item \"losing face in public\" (ASLEC-15) from the Adolescent Self-Rating Life Events Checklist (ASLEC) also demonstrated relatively high centrality, suggesting that this event has a significant impact on the network. High school students are at a stage where self-esteem is particularly important, and losing face in public may lead to feelings of inferiority, which is an independent risk factor for anxiety. This can further undermine adolescents' social confidence and mental health(Miao et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cb\u003e3.2 The role of bridge symptoms\u003c/b\u003e\u003c/p\u003e\u003cp\u003eIn network analysis, bridge symptoms play a crucial role in connecting two subnetworks. The results indicate that \"dislike of school\" (ASLEC-6) and \"I am easily upset or feel panicked\" (SAS-3) are the most influential bridge symptoms, suggesting that the connection between these two symptoms dominates the interaction between negative life events and anxiety symptoms among high school students. Specifically, the edge between \"dislike of school\" (ASLEC-6) and \"I feel restless and cannot sit still\" (SAS-9) has the highest weight, indicating a significant positive correlation between academic pressure and anxiety symptoms(L. T. Chen, Yang, Ou, \u0026amp; Guo, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). This finding aligns with previous research(M. K. Li, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), demonstrating that academic pressure is a major trigger for anxiety among high school students. When faced with academic stress, a lack of effective coping strategies can easily lead to anxiety, thereby affecting students' learning efficiency and mental health. Additionally, \"dislike of school\" (ASLEC-6), as a bridge symptom, could be considered an indicator for the early identification of anxiety symptoms.\u003c/p\u003e\u003cp\u003e\u003cb\u003e3.3 The overall characteristics of the network structure\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe network analysis results reveal that negative life events and anxiety symptoms form two tightly connected subnetworks, indicating a complex interplay between the two. Specifically, ASLEC\u0026minus;2 (\"being discriminated against or treated coldly\") and ASLEC\u0026minus;15 (\"losing face in public\") exhibit high strength within the adolescent life events subnetwork, while \"I am easily upset or feel panicked\" (SAS\u0026minus;3) and \"I have spells of feeling like fainting\" (SAS\u0026minus;12) show high strength within the anxiety symptoms subnetwork. These core symptoms not only have a significant impact within their respective subnetworks but also interact with symptoms in other subnetworks through bridge symptoms, further exacerbating the development of anxiety.\u003c/p\u003e\u003cp\u003eFrequent anxiety among high school students is closely linked to academic pressure, which is considered a significant contributing factor. Scholars attribute the primary causes of academic pressure to four aspects: parental expectations, self-demands, teacher influences, and social interactions. These factors, combined with performance goals, external environments, encountered setbacks, and academic competition, are identified as the main sources of stress for high school students (Xu, Cao, Cui, \u0026amp; Zhu, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). High school students are in a stage of rapid physical and mental development while simultaneously facing the pressures of college entrance exams, a critical period in their lives. They endure stress from various aspects such as academics and daily life, and concerns about an uncertain future, feelings of panic, and premonitions of misfortune can exacerbate their anxiety (R. Liu et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). This study suggests that the relationship between academic pressure and anxiety is not simply one of cause and effect. High school students can alleviate anxiety through psychological guidance, thereby improving academic performance. However, a moderate level of anxiety might also enhance students' motivation to learn, potentially boosting academic efficiency(Caldwell et al., \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2019\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eAdditionally, the stability coefficient of the network structure is relatively high, indicating that the results possess a high degree of reliability and stability.\u003c/p\u003e\u003cp\u003e\u003cb\u003e3.4 Suggestions for intervention strategies\u003c/b\u003e\u003c/p\u003e\u003cp\u003eBased on the aforementioned results, this study provides empirical evidence for precisely intervening in negative life events and alleviating anxiety among high school students. First, targeted psychological counseling and relaxation training can be implemented for the core symptom \"I am easily upset or feel panicked\" (SAS\u0026minus;3), helping students learn to cope with stress and regulate their emotions. Second, for the bridge symptom \"dislike of school\" (ASLEC\u0026minus;6), efforts can be made to enhance motivation for learning and improve stress management, assisting students in developing a positive attitude toward learning and setting appropriate academic goals. Additionally, for negative life events such as \"losing face in public\" (ASLEC\u0026minus;15), social skills training and self-esteem building programs can be introduced to help students improve their social abilities and boost their confidence. Through these intervention measures, it is possible to effectively reduce anxiety levels among high school students and enhance their mental well-being.\u003c/p\u003e\u003cp\u003e\u003cb\u003e3.5 Limitations and future directions of research\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThis study, employing network analysis, reveals the complex relationship between negative life events and anxiety symptoms among high school students, providing empirical evidence for targeted interventions. However, the research has several limitations. First, the cross-sectional design of this study cannot establish a causal relationship between negative life events and anxiety symptoms. Future studies could adopt a longitudinal design to clarify the causal links between the two. Second, this study relies on self-reported data, which may introduce subjective bias. Future research could incorporate objective measurement methods, such as physiological indicators and behavioral observations, to enhance the accuracy of the findings. Additionally, the sample of this study is limited to high school students from the central Anhui region. Future studies could expand the sample size to improve the generalizability and applicability of the results. Finally, this study focuses solely on the relationship between negative life events and anxiety symptoms. Future research could further explore the role of other psychological factors (e.g., depression, coping styles) in this relationship to provide more comprehensive intervention strategies.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAll subjects who participated in the survey signed the informed consent form. All methods were carried out in accordance with relevant guidelines and regulations.The survey has received approval from the Academic Ethics Committee of Wannan Medical College.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe datasets used and/or analysed during the current study available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research was supported by the Humanities and Social Science Major Project of the Anhui Provincial Education Department (2024AH040383) and Research Project on Student Mental Health by the National Center for Mental Health (XS25B029)\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors’ contributions\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eZijun Chen: Research design, First draft writing, Analyzing data.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eKe Zheng: Data collection, Formal analysis.\u003c/p\u003e\n\u003cp\u003eQiyun Jiang: Data collection.\u003c/p\u003e\n\u003cp\u003eJiusheng Wang: Data collection.\u003c/p\u003e\n\u003cp\u003eBiao Chen: Data collection.\u003c/p\u003e\n\u003cp\u003eZihan Wang: Data collection.\u003c/p\u003e\n\u003cp\u003eZhouyu Wang: Data collection.\u003c/p\u003e\n\u003cp\u003eLiang Yu: Study design, Methodology, Writing, Criticism and Editing.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors details\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e1Wannan Medical College,Wuhu, Anhui, China\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eBorsboom, \u0026amp; Denny. 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(2021). \u003cem\u003eThe relationship between negative life events, resilience and life satisfaction of junior high school students and intervention research\u003c/em\u003e. \u003c/li\u003e\n\u003cli\u003eLiu, H. Y., \u0026amp; Wang, W. (2017). The relationship between negative life events and state anxiety in college students-the mediating effect of rumination and the moderating effect of self-affirmation. \u003cem\u003echinese mental health journal, 31\u003c/em\u003e(09), 728-733. \u003c/li\u003e\n\u003cli\u003eLiu, R., Chen, X., Qi, H., Feng, Y., Su, Z., Cheung, T., . . . Xiang, Y. T. (2022). Network analysis of depressive and anxiety symptoms in adolescents during and after the COVID-19 outbreak peak. \u003cem\u003eJ Affect Disord, 301\u003c/em\u003e, 463-471. doi:10.1016/j.jad.2021.12.137\u003c/li\u003e\n\u003cli\u003eLiu, X. C., Liu, L. Q., Yang, J., Chai, F. X., Wang, A. Z., Sun, L. M., . . . Ma, D. D. (1997). Reliability and validity test of adolescent life events scale. \u003cem\u003eChinese Journal of ClinicalPsychology\u003c/em\u003e(01), 39-41.\u003c/li\u003e\n\u003cli\u003eMiao, L. J., Sun, H. L., Zhang, Y. Y., Chen, S. M., Ke, Y., \u0026amp; Yang, Y. H. (2020). The effect of parent-child separation on bullying victimization and inferiority of left-behind children. \u003cem\u003ethe chinese health service management, 37\u003c/em\u003e(12), 943-945+960.\u003c/li\u003e\n\u003cli\u003eRen, L., Guo, L., Ma, Z. J., Zhang, Q. T., Dai, H., Liu, B., . . . Yang, Q. (2020). A network analysis of generalized anxiety symptoms in military personnel. \u003cem\u003eoccupation and health, 36\u003c/em\u003e(10), 1336-1341. doi:10.13329/j.cnki.zyyjk.2020.0356\u003c/li\u003e\n\u003cli\u003eSu, L. Y., Liu, J., Su, Q. R., Huang, G. W., Cao, F. L., \u0026amp; Ren, Y. (2005). Clinical study on comorbidity of anxiety and depression in children and adolescents. \u003cem\u003echinese journal of psychiatry, 38\u003c/em\u003e(4), 4. \u003c/li\u003e\n\u003cli\u003eTang, H. B., \u0026amp; Zhou, m. (2014). The relationship between college students \u0026apos; life events, cognitive emotion regulation and psychological resilience. \u003cem\u003echina journal of health psychology, 22\u003c/em\u003e(03), 441-443. doi:10.13342/j.cnki.cjhp.2014.03.054\u003c/li\u003e\n\u003cli\u003eVallance, Aaron, K., Fernandez, \u0026amp; Victoria. (2016). Anxiety disorders in children and adolescents: aetiology, diagnosis and treatment. \u003cem\u003eBJPsych Advances\u003c/em\u003e. \u003c/li\u003e\n\u003cli\u003eWaite, P., \u0026amp; Creswell, C. (2015). Observing Interactions between Children and Adolescents and their Parents: The Effects of Anxiety Disorder and Age. \u003cem\u003eJ Abnorm Child Psychol, 43\u003c/em\u003e(6), 1079-1091. doi:10.1007/s10802-015-0005-z\u003c/li\u003e\n\u003cli\u003eXu, J. J., Cao, J. F., Cui, L. Z., \u0026amp; Zhu, P. (2010). The preliminary preparation of middle school students \u0026apos; learning pressure questionnaire. \u003cem\u003eJournal of Chinese School Health, 31\u003c/em\u003e(01), 68-69. doi:10.16835/j.cnki.1000-9817.2010.01.032\u003c/li\u003e\n\u003cli\u003eZung, W. W. (1971). A rating instrument for anxiety disorders. \u003cem\u003ePsychosomatics, 12\u003c/em\u003e(6), 371-379. doi:10.1016/s0033-3182(71)71479-0\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-psychology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"psyo","sideBox":"Learn more about [BMC Psychology](http://bmcpsychology.biomedcentral.com/)","snPcode":"","submissionUrl":"","title":"BMC Psychology","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"High school students, Negative life events, Anxiety, Network analysis, Mental health intervention","lastPublishedDoi":"10.21203/rs.3.rs-7634586/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7634586/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eObjective: \u003c/strong\u003eTo explore the relationship between negative life events and anxiety in high school students, to identify core symptoms and their interrelationships, and to provide empirical research evidence for the alleviation of anxiety.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods: \u003c/strong\u003eA stratified random sampling method was adopted to select 1,576 high school students from some of the central Anhui Province, Anhui Province, China. Questionnaires were administered using the Adolescent Self-Rating Life Events Checklist (ASLEC) and the Self-Rating Anxiety Scale (SAS). The data were analyzed using the statistical software package SPSS 26.0 in conjunction with the R software (Version 4.4.1).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults: \u003c/strong\u003eThe network structure of ASLEC and SAS for high school students comprises a total of 384 effective edges, forming two internal tight sub-networks.In ASLEC, ASLEC-2 (strength of 1.09) and ASLEC-15 (strength of 1.15) have higher strengths, ASLEC-5 (bridge strength of 0.125) and ASLEC-6 (bridge strength of 0.252) have higher bridge strengths; in SAS, SAS-3 (strength of 1.22) and SAS-12 (strength of 1.18) have higher strengths, SAS -3 bridge strength of (0.165) and SAS-4 (bridge strength of 0.164) bridge strengths are higher; the ASLEC-6-SAS-9 sideline carries more weight in connecting the 2 sub-networks.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion: \u003c/strong\u003eNetwork analyses provide empirical support for precise interventions for negative life events and anxiety reduction in high school students. Interventions that target core symptoms are beneficial for improving the mental health of high school students and providing a deeper understanding of the dynamics between symptoms.\u003c/p\u003e","manuscriptTitle":"Unveiling the Dynamic Mechanisms of Anxiety: A Network Analysis of Negative Life Events and Anxiety Symptoms Among High School Students","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-10-23 12:47:52","doi":"10.21203/rs.3.rs-7634586/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"reviewersInvited","content":"","date":"2025-10-10T09:18:18+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-09-19T13:18:16+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-09-17T08:20:41+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-09-17T08:20:36+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Psychology","date":"2025-09-17T01:49:09+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-psychology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"psyo","sideBox":"Learn more about [BMC Psychology](http://bmcpsychology.biomedcentral.com/)","snPcode":"","submissionUrl":"","title":"BMC Psychology","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"ceee8797-2fbd-4f1f-894a-ce648a294b0b","owner":[],"postedDate":"October 23rd, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2025-10-23T12:47:53+00:00","versionOfRecord":[],"versionCreatedAt":"2025-10-23 12:47:52","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7634586","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7634586","identity":"rs-7634586","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}