{"paper_id":"4717fc3a-160f-497b-bdb9-262aca5baac6","body_text":"The role of depressive symptoms and social support in the association of internet addiction with non-suicidal self-injury among adolescents: a cohort study in China | 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 The role of depressive symptoms and social support in the association of internet addiction with non-suicidal self-injury among adolescents: a cohort study in China Ying Ma, Yanqi Li, Xinyi Xie, Yi Zhang, Brooke A. Ammerman, Stephen P Lewis, and 4 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-2656091/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 09 May, 2023 Read the published version in BMC Psychiatry → Version 1 posted 8 You are reading this latest preprint version Abstract Background Both internet addiction (IA) and non-suicidal self-injury (NSSI) are major public health concerns among adolescents, however, the association between IA and NSSI was not well understood. In this study we aim to investigate the association between IA and NSSI within a cohort study, and to explore the mediated effect of depressive symptoms and the moderating effect of social support in the association. Methods A total of 1530 adolescents aged 11–14 years who completed both the baseline (T1) and 14-month follow-up (T2) survey of the Chinese Adolescent Health Growth Cohort were included for the current analysis. IA, NSSI, depressive symptoms and social support were measured at T1; depressive symptoms and NSSI were measured again at T2. Structural equation models were employed to estimate the mediated effect of depressive symptoms and the moderating effects of social support in the association between IA and NSSI at T2. Results IA was independently associated with an increased risk of NSSI at T2, with the total effect of 0.113 (95%CI 0.055–0.174). Depressive symptoms mediated the association between IA and NSSI at T2, and social support moderated the indirect but not the direct effect of IA on NSSI at T2. Sex differences were found on the mediated effect of depressive symptoms and the moderated mediation effect of social support. Conclusions Interventions that target adolescents’ NSSI who also struggle with IA may need to focus on reducing depressive symptoms and elevating social support. Internet addiction non-suicidal self-injury depressive symptoms social support Cohort study Adolescent Figures Figure 1 Figure 2 Figure 3 Background Over the past decades, the prevalence of non-suicidal self-injury (NSSI) has become a major public health concern among children and adolescents [ 1 – 2 ]. Data from the latest survey of the World Mental Health International College Students (WMH-ICS) indicates the lifetime and 12-month prevalence of NSSI were 17.7% and 8.4%, respectively, among first year college students [ 3 ]. In China, the prevalence of NSSI among middle and high school students has ranged from 6.4 to 35.6% [ 4 ]. NSSI is associated and comorbid with several mental disorders (e.g., major depression, bipolar disorder, substance and alcohol abuse) [ 3 – 5 ], and increases the risk of both suicide and other causes of mortality [ 6 ]. Given the high prevalence and serious consequences of NSSI, it is critical to further understand its risk and protective factors. Internet addiction (IA), usually defined as the inability to control one's internet use and causes marked distress and/or functional impairment [ 7 ], is also highly prevalent among adolescents worldwide [ 8 – 9 ]. A recent study estimated that the prevalence of IA among children and adolescents in Macau and mainland China was 23.7% [ 10 ]. Our previous study [ 11 ] and other studies [ 12 – 13 ] have suggested that IA may be associated with NSSI among adolescents. However, it is uncertain whether exposure to IA is prospectively associated with an increased risk of NSSI among adolescents given the lack of evidence from longitudinal studies in the field [ 13 ]. In addition to IA, studies involving clinical and general populations have suggested that depressive symptoms may be independent risk factors of NSSI [ 14 – 15 ]. Meanwhile, longitudinal studies have suggested that compulsive internet use may precede the development of emotional dysregulation [ 16 ], and depressive symptoms are one of the most frequent consequences of IA [ 17 ]. It seems that depressive symptoms might mediate the association between IA and NSSI. However, only a paucity of research has specifically investigated the mediated role of depressive symptoms in the association between IA and NSSI. Nevertheless, several previous studies have suggested that depression may mediate the association between interpersonal stressors and NSSI among adolescents [ 18 ]. According to the stress-buffering hypothesis [ 19 ], social support moderates the association between stress and health outcomes. Previous studies have suggested that a high level of social support could help to relieve depressive symptoms and protect against the onset of major depression [ 20 – 21 ], as well as buffer the effect of life stress on NSSI [ 22 ]. In this regard, social support might exert moderating effects on both the associations between IA and depressive symptoms, and between IA and NSSI. However, the moderating role of social support in these associations has not yet been examined. There is merit in research examining the underlying role of depressive symptoms in the association between IA and NSSI, and whether social support could moderate these associations. Indeed, if these possible relations are supported by evidence, it would help scholars and educators to better understand the nature of the association between IA and NSSI among children and adolescents, this has potentially meaningful for health professionals to implement interventions when working with these populations. Using a two-wave longitudinal design, the present study aimed to explore the role of depressive symptoms and social support in the association of IA and NSSI. Given that early adolescence has a high rate of NSSI and this age range represents a typical onset time of NSSI [ 23 ], we investigated a school-based sample of early adolescence to explore these relations. Specifically, we constructed a mediation model and moderated-mediation model and proposed the following hypotheses: (1) IA would be prospectively associated with NSSI among adolescents; (2) depressive symptoms would mediate the association between IA and NSSI; and (3) social support would moderate the association between IA and NSSI, and the association between IA and depressive symptoms in the mediation model of the association between IA and NSSI. Methods Study participants This study used data from the Chinese Adolescent Health Growth Cohort (CAHGC) (register number: CCC2022061901, http://chinacohort.bjmu.edu.cn ). The design, procedure, and implementation are described elsewhere [ 24 ]. In brief, using a cluster random sampling method, a representative sample of 1844 students at grade 7 from 11 middle schools across three areas (Qidong County in Hunan Province, Guangming District in Shenzhen City, Zhongshan City in Guangdong Province) were enrolled to participate in the baseline survey (T1). Participants then completed a follow-up survey that was undertaken at 14 months after baseline (T2, N = 1758). Overall, there were 1543 participants who completed both T1 and T2 surveys. After excluding 13 participants who did not complete the assessment of IA at T1 and/or NSSI at T2, the final sample included 1530 students. No significant differences were found in the variables of interests (i.e., IA, depressive symptoms, social support and NSSI) or other demographic variables, such as age and sex, between adolescents who participated in all assessments and these who did not. The study followed the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guideline and received ethics clearance from the University (NO.2021010002). In each round of data collection, the parents/guardians provided written informed consent that was in a manner consistent with the Declaration of Helsinki. Participants in the study received the equivalent of RMB 150 ( $ 25) in medical examination services after the baseline survey. Instruments IA. At T1, IA was assessed by using the Young Internet Addiction Test (IAT) [ 25 ]. The IAT comprises 20 items using a 5-point Likert scale: 1, rarely; 2, occasionally; 3, frequently; 4, often; 5, always; thus, total scores of the IAT range from 20 to 100. Three types of internet user groups were identified based on the original cutoff points proposed by Young [ 26 ], namely “average online users” (20–49 points), “moderate IA” (50–79 points), and “severe IA” (80–100 points) [ 26 ]. The IAT has been demonstrated to have acceptable internal consistency, with a Cronbach α coefficient of 0.93 in a previous study [ 11 ] and 0.91 in the present study sample. Depressive symptoms. At T1 and T2, a Chinese version of the Center for Epidemiologic Studies Depression Scale (CES-D) was used to measure depressive symptoms [ 27 ], which consists of 9 items using 4-point Likert responses: 0 = never true; 1 = rarely true; 2 = often true; and 3 = always true; thus, the total scores on CES-D range from 0 to 27. Higher scores indicate greater risk of depression due to more severe depressive symptoms. Participants were divided into three groups based on the validated standard cutoff criteria, including ‘no depressive symptoms’ (0–9 points), ‘moderate depressive symptoms’ (10–16 points), and ‘severe depressive symptoms’ (17–27 points). The Cronbach α coefficient of the scale in the present study was 0.83. Social support. At T1, social support was measured by the 17-item Adolescents Social Support Scale [ 28 ], which has 5-point Likert responses for each item (1 = strongly; 2 = agree; 3 = neutral; 4 = somewhat disagree; 5 = strongly disagree). The total scores of the scale ranged from 17 to 85, where higher scores of the scale indicate higher level of social support. The Cronbach α coefficient of the scale in the present study was 0.96. NSSI. At T1 and T2, the Chinese version of the Functional Assessment of Self-mutilation was used to assess the frequencies of 8 different forms of NSSI (hitting, head banging, stabbing, pinching, scratching, biting, burning, and cutting) during the past 12 months [ 29 ]. To distinguish between NSSI and suicidal behaviors, participants were also asked whether any of those behaviors carried suicidal intent. Similar to our previous studies [ 11 , 29 ], NSSI was dichotomized (frequency of five or more acts in the past year = yes; versus fewer than five = no) for analysis. The Cronbach’s alpha of this scale in the present study was α = 0.98. Co-variables. At T1, we used a custom-designed questionnaire to collect demographic characteristics, familial, and parenting variables, including age, sex (male or female), ethnicity (Han or others, meaning, every category of ethnicity except Han), single-child family (yes or no), family structure (core/joint family, single parent/blended family, cross-generation family), education level of the main caregiver (middle school or below, high school or technical school, college or above), family income (< $ 200/month, $ 200–900/month, or > $ 900/month), parenting style (strict, pamper, indulge/rude/frequently changing, or open-minded), family history of psychiatric diseases (yes or no) and perceived academical pressure (high, average, or low). A previous study had shown that the test-retest reliability of the questionnaire was α = 0.83 [ 29 ]. Statistical analysis Frequencies and proportions for categorical variables or mean (SD) for continuous variables were used to describe participant characteristics and NSSI at T2 by study variables. χ 2 tests or 2-tailed, unpaired t tests were used to compare the distribution between participants with or without a history of NSSI at T2 according to studied variables. Pairwise correlation analysis of measurements (IA and social support [T1], depressive symptoms and NSSI [T1 and T2]) was used to test the associations among the variables. Logistic regression models were employed to examine the independent effects of IA at T2 on NSSI at T2, both unadjusted OR and adjusted OR with 95% confidence intervals (CI) were estimated. In the adjusted model, we adjusted for we adjusted for age, sex, ethnicity, study site, family structure, single-child family, education level of main caregiver, parenting style, family income, family history of psychiatric disease, perceived academic pressure, NSSI and depressive symptom at T1. We also conducted subgroup analysis to examine whether the association between IA and NSSI at T2 differed by sex. Significance level was set at P < 0.05 and all tests were 2-sided. Statistical analyses were conducted using IBM SPSS Statistics, version 26.0. We performed a set of structural equation models (SEM) to estimate the mediated effect of depressive symptoms in the association between IA and NSSI at T2, and the moderating effects of social support in the direct and the indirect association between IA and NSSI at T2. In all modelling analyses, both unadjusted and adjusted effects were estimated. In the adjusted model, we adjusted the confounders as we did in logistic regression model. In the moderated mediation analysis, simple slope analyses and conditional indirect effect tests (1 SD above and below the mean of the moderator) were performed when an interaction effect of IA and social support was detected. We also preformed subgroup analysis to examine whether the mediated or moderated mediation effects differed by sex. All SEM analyses were performed using Mplus 8.0. Results Demographic characteristic We included 1530 participants (853 males [55.8%] and 677 females [44.2%]) in the current analysis. At T1, the age of the participants ranged from 11 to 14 years old (mean [SD] age, 12.9 [0.6] years). More than a half (957 [62.5%]) were from Zhongshan City, 1482 (96.9%) were Han ethnicity, 269 (17.6%) were a single child, and 107 (7.0%) were from single parent or blended family. Additional characteristics are summarized in Table 1 . Table 1 Characteristics of participants according to NSSI at T2 Characteristic Total(n = 1530) NSSI at T2 No (n = 1331) Yes (n = 199) Age ( T1) (M, SD) * 12.9 ± 0.6 12.9 ± 0.6 12.8 ± 0.6 Sex (n, %) * Males 853(55.8) 776(57.6) 87(43.7) Females 677(44.2) 565(42.4) 112(56.3) Regional area (n, %) * Qidong County 383(25.0) 310(23.3) 73(36.7) Guangming District 190(12.4) 173(13.0) 17(8.5) Zhongshan City 957(62.5) 848(63.7) 109(54.8) Ethnicity (n, %) Han 1482(96.9) 1287(96.7) 195(98.0) Others 48(3.1) 44(3.3) 4(2.0) Single child (n, %) No 1261(82.4) 1084(81.4) 177(88.9) Yes 269(17.6) 247(18.6) 22(11.1) Family structure (n, %) * Core/joint family 1333(87.1) 1175(88.3) 158(79.4) Single parent/blended family 107(7.0) 88(6.6) 19(9.5) Cross-generation family 90(5.9) 68(5.1) 22(11.1) Family history of psychiatric diseases (n, %) * No 1510(98.7) 1317(98.9) 193(97.7) Yes 20(1.3) 14(1.1) 6(3.0) Parenting style (n, %) * Strict 500(32.7) 447(33.6) 53(26.6) Open minded 783(51.2) 695(51.4) 88(44.2) Pamper 54(3.5) 42(3.2) 12(6.0) Neglect/rude/frequently changing 193(12.6) 147(11.0) 46(23.1) Monthly household income per capita (n, %) ≤ 1999 RMB 60(3.9) 47(4.13.5) 13(6.5) 2000–6999 RMB 910(59.5) 791(59.4) 119(59.8) ≥7000 RMB 560(36.6) 493(37.0) 67(33.7) Education of main caregiver (n, %) Junior and below 914(59.7) 795(59.7) 119(59.8) Senior or technical school 360(23.5) 307(23.1) 53(26.6) College and above 256(16.7) 229(17.2) 27(13.6) Perceived academic pressure (n, %) * High 706(46.1) 584(43.9) 122(61.3) General 773(50.5) 704(52.9) 69(34.7) low 51(3.3) 43(3.2) 8(4.0) Depressive symptoms (T1) (n, %) * None 1234(80.7) 1132(85.0) 102(51.3) Moderate 230(15.0) 164(12.3) 66(33.2) Severe 66(4.3) 35(2.6) 31(15.6) IA (T1) (n, %) * None 1015(66.3) 934(70.2) 81(70.2) Moderate 461(30.1) 364(27.3) 97(48.7) Severe 54(3.5) 33(2.5) 21(10.6) NSSI(T1) (n, %) * No 1355(88.6) 1224(92.0) 131(65.8) Yes 175(11.4) 107(8.0) 68(34.2) Depressive symptoms(T2) (n, %) * None 1243(81.2) 1135(85.3) 108(81.2) Moderate 235(15.4) 169(12.7) 66(33.2) Severe 52(3.4) 27(2.0) 25(12.6) Social support(T1) (M, SD) * 67.0 ± 13.4 68.2 ± 12.8 59.2 ± 14.5 * P < 0.05. Overall, 461 participants met the criteria of moderate IA, and 54 participants met the criteria of severe IA at T1. The prevalence of moderate IA and severe IA were 30.1% and 3.5%, respectively, and no sex differences were found (χ 2 = 2.281, P = 0.320). Participants who were moderate IA or severe IA were likely to have moderate or severe depressive symptoms at T1 (χ 2 = 19.773, P < 0.001). The prevalence of NSSI was 11.4% at T1 and 13.0% at T2. Univariate analysis on influence factors of NSSI at T2 is also presented in Table 1 . Participants who were female, from single parent or blended family, experienced neglect/rude/frequently changing parenting practices, perceived high academic pressure, had moderate or severe IA, had moderate or severe depressive symptoms and engaged NSSI at T1 were more likely to engage in NSSI at T2 (Table 1 ). The Independent Effect Of Ia On Nssi At T2 After testing the normality of the independent, dependent variable, mediation and moderating variables, Spearman correlation analyses were performed; results are presented in Supplement Table 1 . The unadjusted OR and adjusted OR of IA for NSSI at T2 were presented in Table 2 . After adjusted for the confounders, IA was associated with an increased risk of NSSI at T2. Compared to those who were not IA, participants who were moderate and severe IA had greater odds of NSSI (both P < 0.001). Subgroup analysis showed that the independent effect of IA at T1 on NSSI at T2 not differed by sex (Supplement Table 2 ). Table 2 Association between IA at T1 and NSSI at T2 NSSI at T2 (N, %) Unadjusted OR (95%CI) P Adjusted a OR (95%CI) P No IA 81 (8.0) Ref = 1 Ref = 1 Moderate IA 97 (21.0) 3.07 (2.23, 4.23) < 0.001 2.70 (1.93, 3.75) < 0.001 Severe IA 21 (39.8) 7.34 (4.06, 12.37) < 0.001 4.62 (2.45, 8.71) < 0.001 a. Adjusted for sex, age, ethnicity, regional areas, family structure, single child, family history of psychiatric disease, parenting style, household income per capita, perceived academic pressure, education of main caregiver, baseline NSSI and baseline depressive symptoms. The Indirect Effect Of Ia On Nssi At T2 Mediated Through Depressive Symptoms Figure 1 shows the results of the mediation analyses. After adjusting for potential confounders, the total effect of IA at T1 on NSSI at T2 was significant (standard β = 0.113, 95%CI, 0.055, 0.174). The direct effect of IA at T1 on NSSI at T2 was 0.099 (95%CI 0.042, 0.161) and depressive symptoms at T2 on NSSI at T2 was 0.169 (95%CI 0.100, 0.239). The indirect effect of IA on NSSI at T2 mediated through depressive symptoms was 0.014 (95%CI 0.004, 0.029). The mediation proportion was 12.4% (95%CI 7.3%, 16.7%) (Table 3 ). Goodness-of-fit indices (i.e., CFI = 1.000, TLI = 1.000, RMSEA < 0.001, SRMR < 0.001) indicated satisfactory fit of the model. Subgroup mediation analysis demonstrated that the total and direct effects of IA at T1 on NSSI at T2 among both males and females were significant (all P < 0.001). However, the significant indirect effect of IA at T1 on NSSI at T2 mediated through depressive symptoms was only found for females, with the mediation proportion was 19.0% (95%CI 15.4%, 23.8%) (See Supplement Table 3 ). Table 3 Mediating effect of depressive symptoms between IA(T1) and NSSI(T2) Variables Model 1 a Model 2 b Standard β (95% CI) P Standard β (95% CI) P IA(T1)→Depressive symptoms(T2) 0.200(0.147, 0.258) < 0.001 0.084(0.027, 0.144) 0.005 Depressive symptoms(T2)→NSSI(T2) 0.249(0.181, 0.314) < 0.001 0.169(0.100, 0.239) < 0.001 IA(T1)→NSSI(T2) 0.179(0.120, 0.240) < 0.001 0.099(0.042, 0.161) 0.001 Standardized effect Indirect 0.050(0.032, 0.072) < 0.001 0.014(0.004, 0.029) 0.021 Total 0.229(0.171, 0.286) < 0.001 0.113(0.055, 0.174) < 0.001 Mediating ratio (%) 21.8(18.7, 25.2) -- 12.4(7.3, 16.7) -- a. Unadjusted. b. Adjusted for sex, age, ethnicity, regional areas, family structure, single child, family history of psychiatric disease, parenting style, household income per capita, perceived academic pressure, education of main caregiver, baseline NSSI and baseline depressive symptoms. The moderating effect of social support on the mediation path and the direct path in the association between IA and NSSI The interaction between IA and social support at T1 in predicting depressive symptoms at T2 was significant (standard β=-0.081, 95%CI -0.142, -0.014), but was not significant in predicting NSSI at T2 (β=-0.082, 95%CI -0.067, 0.051) (Fig. 2 , supplemental Table 4). The model of the SEM (Fig. 2 ) also fit the data well. The simple slope test indicated that the association between IA at T1 and depressive symptoms at T2 was significant for participants with low (b = 0.137, 95%CI 0.056, 0.225) or moderate (b = 0.059, 95%CI 0.006, 0.121) level of social support, but not for those with high level of social support (b=-0.019, 95%CI -0.092, 0.067). Compared to participants with low level of social support, the positive links between IA at T1 and depressive symptoms at T2 was stronger for participants who had moderate social support (Fig. 3 ). The indirect effect of IA on NSSI at T2 through depressive symptoms at T2 was conditioned at different levels of social support. Specifically, the indirect effect was strongest when social support was low (standard β = 0.019, 95% CI 0.007, 0.047), moderate at moderate levels of social support (standard β = 0.008, 95% CI 0.001, 0.025), and non-significant at high social support (standard β=-0.003, 95% CI -0.015, 0.009) (Supplemental Table 4). Similarly, the conditional indirect effect of IA on NSSI mediated through depressive symptoms was only found among females but not for males (Supplemental Table 5). Discussion To our knowledge, this is the first longitudinal study examining the mediated effect of depressive symptoms and the moderating effect of social support in the association between IA and NSSI among adolescents. There were two key and novel findings from this study. First, IA had significant effect on NSSI at T2, 12.4% of which was mediated through depressive symptoms at T2. Second, social support moderated the effect of IA on NSSI at T2 through moderating the mediated effects of depressive symptoms. These findings provide new information about the association between IA and NSSI among adolescents, which could benefit educators, scholars and decision-makers to better understand the development of NSSI among children and adolescence and, as such, potentially inform NSSI interventions. More and more social networking and learning are taking place online, especially during the COVID-19 pandemic. This, at the extreme end, could lead to more people depending on the internet and thus be more prone to IA [ 30 ], especially among adolescents. There are a number of studies that have examined the potential effects of IA on adolescents’ mental and conduct difficulties, such as suicidal behaviors, NSSI, depression, anxiety, and attention deficit hyperactivity disorders [ 11 , 31 , 32 ]. In the current study, we found that IA was significantly associated with an increased risk of NSSI at T2 among adolescents. This finding aligns with the only longitudinal study conducted in Taiwan [ 13 ] and most previous cross-sectional studies [ 11 , 33 ], which support a positive association between IA and NSSI. However, there were two studies that suggested a null association between IA and self-harm [ 34 , 35 ], a broader term that includes NSSI but also encompasses suicidal behaviors. The inconsistency across the collective findings may be account for by the various characteristics within the study population. This includes the different prevalence of NSSI and IA that were examined by different measurements and criteria, apart from study design and adjustments. Studies that have not distinguished between self-harm and NSSI may have overestimated the association between IA and NSSI [ 13 , 36 , 37 ]. Therefore, a more-uniform evaluative measurement of NSSI, apart from broader self-harm behavior, will be needed to clarify the association between IA and NSSI. NSSI is often considered as an emotion-regulation strategy to decrease one’s emotional distress by distracting from intense emotion through the sight of blood, the sensation of pain, or focus on the injury itself [ 38 ]. There are also many studies providing support for a mediating role of depression between interpersonal stress and NSSI among adolescents, including peer bullying [ 18 ] and loneliness [ 39 ]. Although previous studies have indicated an association between IA and NSSI, as well as depressive symptoms with NSSI, a dearth of study has explicitly addressed the mechanisms underlying IA, depressive symptoms and NSSI. Our study adds to this literature as we found that depressive symptoms played a mediating role in the association between IA and NSSI. In other words, some adolescents with IA may not present with NSSI directly but instead present with depressive symptoms which then associates with an increased risk of NSSI. Indeed, our finding extends prior research by bridging the associations between IA, depressive symptoms and NSSI, which is in line with studies that have examined the indirect effects of IA on suicidal behaviors [ 40 , 41 ]. Yu and colleagues conducted a cross-sectional study indicating that internet gaming disorders are positively associated with insomnia, which increases depressive symptoms, and, in turn, positively contributed to suicidal ideation [ 40 ]. Similarly, Guo et al conducted a study of 20895 adolescents, finding that sleep disturbance mediated the association between problematic internet use and suicidal behavior [ 41 ]. The mediating role of depressive symptoms in the association between IA and NSSI could be explained in the several ways. First, individuals with IA may be prone to be depression because they spend too much time in the internet virtual world and thus less time on social gatherings, family or peer group activities, this may, in turn, result in unhelpful ways of adapting to their offline lives and greater isolation [ 17 , 42 ]. Second, physiological studies have shown that IA could disrupt dopamine transmission by decreasing the expression of dopamine transporter in the striatum, which may increase the risk of depressive symptoms [ 43 ]. The resultant depressive symptoms may, in turn, lead to NSSI as a means to decrease emotional distress [ 44 ]. Therefore, interventions that focus on reducing depressive symptoms may be a potential strategy for prevention of NSSI. It should be noted that the indirect effect of IA on NSSI mediated through depressive symptoms was significant for females but not males, which may be related to the difference in psychological traits between females and males. Previous studies have reported that females experience higher rates of emotional disorders and tend to ruminate, avoid, and be less active in their coping methods, while males tend to be more impulsive and like to engage in physical and instrumental forms of comping methods directly [ 45 ]. Social support, defined as the extent to which individuals may receive emotional or instrumental help from others, is a noteworthy predictor of adolescents’ positive psychosocial development [ 20 ]. Indeed, having strong social support can protect against negative mental health outcomes such as depression resulting from heightened life stress. For example, a cohort study of 1917 young adults examining associations between neighborhood-level social support and subsequent individual outcomes across 10 years, found that neighborhood-level social support can longitudinally protect against the onset of major depressive disorder in high-stress settings [ 20 ]. Similarly, the Avon Longitudinal Study of Parents and Children study also suggested that strong peer social support at age 15 may reduce the risk of depressive symptoms by the time children reach late adolescence [ 21 ]. Further, a study conducted in China suggested that social support had a moderating effect on the association between bullying and depressive symptoms [ 46 ]. Our findings expand this literature by demonstrating that social support may mitigate the consequences of IA on depressive symptoms and the indirect effect of IA on NSSI through depressive symptoms. The possible stress buffer mechanism in this context may be depicted that when individuals encounter a stressful event, adequate social support may mitigate the experience of stress and the onset of adverse outcomes by reducing or eliminating the stress reaction through calming the neuroendocrine system [ 19 ]. Specifically, social support has been found to buffer the effects of life stress on dopamine deficit and dysfunction and diminish the raised cortisol responses to social stressors [ 47 – 48 ]. Contrary to our hypothesis, we did not find social support to buffer the direct effect of IA on NSSI. Previous studies have suggested that different sources of social support had a mixed stress-buffering effect. For instance, a study using data from the Adolescent Development of Emotions and Personality Traits found that only parental support, rather than peer support, protected adolescents from NSSI following a stressor [ 22 ], while another study conducted in China found that only friend support buffered the relationship between maltreatment and NSSI [ 49 ]. Therefore, it is possible that only specific sources of social support play a buffering role in term of the direct effect of IA on NSSI; this possibility warrants further research. Taken together, findings from the current study showed that social support serve as a protective factor, shielding adolescents from the detriment of IA, especially in female adolescents. One major strength of our study is the sample representativeness. For this cohort study, we recruited a large sample size of adolescent across 3 cities, with the social, economic, and cultures reflecting the status in China. In addition, the adjustment for a variety of potential confounders in the SEM, as well as in subsequent analyses, ensured the validity and robustness of our findings. What is more, this is the first study to examine the role of depressive symptoms and social support in association between IA and NSSI, which may be helpful in later informing the development and preventive interventions to address these concerns among adolescents, particularly for IA and NSSI. Limitations Several limitations should be noted. Firstly, our study used adolescent self-reports to collect data, which could be subject to bias. Therefore, in the future, studies should attempt to also collect data from adolescents’ parents and caregivers. Secondly, we did not assess the source of social support (such as family support, peer support, community support), which hampered us from analyzing the moderating effect of different sources of social support on NSSI. Therefore, further studies are needed to distinguish the moderating effect of different source of social support on NSSI. Thirdly, although the sample participants are representative, we only included adolescents in grade seven in the present study. We, therefore, are not able to assume that the present results would generalize to other study phases or other age groups. This is important because the prevalence of IA, depressive symptoms and NSSI, and source of social support may change with study phases or ages. Replication of our findings using other populations would help to determine their generalizability. Likewise, examining the relations focused upon in this study across other populations (e.g., youth in other countries) would also help to determine how generalizable the present findings are. Hence, caution should be exercised when applying to the findings to all populations of adolescents. Conclusions In this study, involving a representative sample of adolescents at seventh grade, the mediation effect of depressive symptoms and the moderating effect of social support in the association between IA and NSSI were observed. Hence, interventions targeting NSSI among adolescents should focus on reducing IA, depressive symptoms and elevating social support. Abbreviations NSSI Non-suicidal self-injury IA Internet addiction IAT Internet Addiction Test CES-D Center for Epidemiologic Studies Depression Scale SEM structural equation models COVID-19 Coronavirus disease 2019. Declarations Ethics approval and consent to participate. The present study has obtained the ethics clearance from Guangzhou Medical University (NO.2021010002) and therefore been performed in accordance with ethical standard laid down in the 1964 Declaration of Helsinki and its later amendments. And all parents/guardians of the participants provided written informed consent prior to their inclusion in the study. Consent for publication Not applicable. Availability of data and materials The data that support the findings of this study are not openly available due to the intellectual property of the datasets belonging to the corresponding author and are available from the corresponding author upon reasonable request. Competing interests The authors declare that they have no competing interests. Funding Founding for this study was provided by grants from National Natural Science Foundation of China (82204065 to YM; 82073571 & 81773457 to JT). The funding bodies had no role in the design of the study and collection, analysis, and interpretation of data and in writing the manuscript. Authors' contributions Ying Ma, Yanqi Li, and Xinyi Xie took part in the design and investigation, conducted the basic analysis, and wrote the first draft of the manuscript. Yi Zhang took part in the investigation and conducted the statistical analysis. Fenghua Li organized the investigation. Brooke A. Ammerman and Stephen P Lewis revised the manuscript. Ruoling Chen conducted the formal analysis. Yizhen Yu provided with the resources. Jie Tang supervised the investigation, validated the final manuscript, and provided with funding. All authors contributed to and have approved the final manuscript. Acknowledgements The authors would like to thank all the schools, parents and students who participated in this study. References Duffy ME, Twenge JM, Joiner TE. 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Additional Declarations No competing interests reported. Supplementary Files supplementalTables.docx Cite Share Download PDF Status: Published Journal Publication published 09 May, 2023 Read the published version in BMC Psychiatry → Version 1 posted Editorial decision: Major revision 20 Mar, 2023 Reviews received at journal 19 Mar, 2023 Reviewers agreed at journal 14 Mar, 2023 Reviewers invited by journal 14 Mar, 2023 Editor assigned by journal 14 Mar, 2023 Editor invited by journal 14 Mar, 2023 Submission checks completed at journal 14 Mar, 2023 First submitted to journal 04 Mar, 2023 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. 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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-2656091\",\"acceptedTermsAndConditions\":true,\"allowDirectSubmit\":false,\"archivedVersions\":[],\"articleType\":\"Research Article\",\"associatedPublications\":[],\"authors\":[{\"id\":183361994,\"identity\":\"7c17c5a6-f68e-443f-8b77-a1e301159994\",\"order_by\":0,\"name\":\"Ying Ma\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"Guangzhou Women and Children’s Medical Center, Guangzhou Medical University\",\"correspondingAuthor\":false,\"submittingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Ying\",\"middleName\":\"\",\"lastName\":\"Ma\",\"suffix\":\"\"},{\"id\":183361995,\"identity\":\"8fb04c5d-1036-4934-bb2f-3102347cc5da\",\"order_by\":1,\"name\":\"Yanqi Li\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"Guangzhou Medical University\",\"correspondingAuthor\":false,\"submittingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Yanqi\",\"middleName\":\"\",\"lastName\":\"Li\",\"suffix\":\"\"},{\"id\":183361996,\"identity\":\"0d5139da-b264-44ab-b15a-2d36f3c1e42b\",\"order_by\":2,\"name\":\"Xinyi Xie\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"Guangzhou Medical University\",\"correspondingAuthor\":false,\"submittingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Xinyi\",\"middleName\":\"\",\"lastName\":\"Xie\",\"suffix\":\"\"},{\"id\":183361997,\"identity\":\"6ff5b17c-a55e-4f96-ad61-9073e2098981\",\"order_by\":3,\"name\":\"Yi Zhang\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"Guangzhou Medical University\",\"correspondingAuthor\":false,\"submittingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Yi\",\"middleName\":\"\",\"lastName\":\"Zhang\",\"suffix\":\"\"},{\"id\":183361998,\"identity\":\"4176126a-358b-4371-b32c-9c319c6069c7\",\"order_by\":4,\"name\":\"Brooke A. 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The model adjusted for sex, age, ethnicity, regional areas, family structure, single child, family history of psychiatric disease, parenting style, monthly household income per capita, perceived academic pressure, education of main caregiver, baseline NSSI and baseline depressive symptoms. \\u003csup\\u003e**\\u003c/sup\\u003e \\u003cem\\u003ep\\u003c/em\\u003e \\u0026lt; 0.01,\\u003csup\\u003e***\\u003c/sup\\u003e \\u003cem\\u003ep\\u003c/em\\u003e \\u0026lt; 0.001.\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"floatimage1.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-2656091/v1/bede1f1f7263516ffac44157.png\"},{\"id\":34441821,\"identity\":\"f2d0488a-231a-4187-a629-53a90bc14099\",\"added_by\":\"auto\",\"created_at\":\"2023-03-17 21:35:06\",\"extension\":\"png\",\"order_by\":2,\"title\":\"Figure 2\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":25328,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003e\\u003cstrong\\u003eThe moderating effect of social support on the indirect association between IA and NSSI mediated through depressive symptoms\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eAdjusted β coefficients are presented. The model adjusted for gender, age, ethnicity, regional areas, family structure, single child, family history of psychiatric disease, parenting style, monthly household income per capita, perceived academic pressure, education of main caregiver, baseline NSSI and baseline depressive symptoms. \\u003csup\\u003e*\\u003c/sup\\u003e \\u003cem\\u003ep\\u003c/em\\u003e \\u0026lt; 0.05, \\u003csup\\u003e**\\u003c/sup\\u003e \\u003cem\\u003ep\\u003c/em\\u003e \\u0026lt; 0.01, \\u003csup\\u003e***\\u003c/sup\\u003e \\u003cem\\u003ep\\u003c/em\\u003e \\u0026lt; 0.001\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"floatimage2.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-2656091/v1/180b5bb84e139432cec7aaab.png\"},{\"id\":34440559,\"identity\":\"3c4ec6c1-576d-43ac-a17f-41b4510e1773\",\"added_by\":\"auto\",\"created_at\":\"2023-03-17 21:27:06\",\"extension\":\"png\",\"order_by\":3,\"title\":\"Figure 3\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":13134,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003e\\u003cstrong\\u003eInteractive effect of IA(T1) and social support on depressive symptoms(T2)\\u003c/strong\\u003e\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"Onlinedrawingimage1.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-2656091/v1/c7dc63fb1b16524222276dff.png\"},{\"id\":44728997,\"identity\":\"2c20d787-ab32-4f7d-8117-895937d348ec\",\"added_by\":\"auto\",\"created_at\":\"2023-10-16 21:09:59\",\"extension\":\"pdf\",\"order_by\":0,\"title\":\"\",\"display\":\"\",\"copyAsset\":false,\"role\":\"manuscript-pdf\",\"size\":792416,\"visible\":true,\"origin\":\"\",\"legend\":\"\",\"description\":\"\",\"filename\":\"manuscript.pdf\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-2656091/v1/9c9c92f8-0a0e-4765-bf8b-e2c80f90d578.pdf\"},{\"id\":34440556,\"identity\":\"131e8ea2-c080-4156-b6dc-d70665d5cf78\",\"added_by\":\"auto\",\"created_at\":\"2023-03-17 21:27:05\",\"extension\":\"docx\",\"order_by\":1,\"title\":\"\",\"display\":\"\",\"copyAsset\":false,\"role\":\"supplement\",\"size\":29117,\"visible\":true,\"origin\":\"\",\"legend\":\"\",\"description\":\"\",\"filename\":\"supplementalTables.docx\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-2656091/v1/fbc46bf7fe9483543fe11151.docx\"}],\"financialInterests\":\"No competing interests reported.\",\"formattedTitle\":\"The role of depressive symptoms and social support in the association of internet addiction with non-suicidal self-injury among adolescents: a cohort study in China\",\"fulltext\":[{\"header\":\"Background\",\"content\":\"\\u003cp\\u003eOver the past decades, the prevalence of non-suicidal self-injury (NSSI) has become a major public health concern among children and adolescents [\\u003cspan citationid=\\\"CR1\\\" class=\\\"CitationRef\\\"\\u003e1\\u003c/span\\u003e\\u0026ndash;\\u003cspan citationid=\\\"CR2\\\" class=\\\"CitationRef\\\"\\u003e2\\u003c/span\\u003e]. Data from the latest survey of the World Mental Health International College Students (WMH-ICS) indicates the lifetime and 12-month prevalence of NSSI were 17.7% and 8.4%, respectively, among first year college students [\\u003cspan citationid=\\\"CR3\\\" class=\\\"CitationRef\\\"\\u003e3\\u003c/span\\u003e]. In China, the prevalence of NSSI among middle and high school students has ranged from 6.4 to 35.6% [\\u003cspan citationid=\\\"CR4\\\" class=\\\"CitationRef\\\"\\u003e4\\u003c/span\\u003e]. NSSI is associated and comorbid with several mental disorders (e.g., major depression, bipolar disorder, substance and alcohol abuse) [\\u003cspan additionalcitationids=\\\"CR4\\\" citationid=\\\"CR3\\\" class=\\\"CitationRef\\\"\\u003e3\\u003c/span\\u003e\\u0026ndash;\\u003cspan citationid=\\\"CR5\\\" class=\\\"CitationRef\\\"\\u003e5\\u003c/span\\u003e], and increases the risk of both suicide and other causes of mortality [\\u003cspan citationid=\\\"CR6\\\" class=\\\"CitationRef\\\"\\u003e6\\u003c/span\\u003e]. Given the high prevalence and serious consequences of NSSI, it is critical to further understand its risk and protective factors.\\u003c/p\\u003e \\u003cp\\u003eInternet addiction (IA), usually defined as the inability to control one's internet use and causes marked distress and/or functional impairment [\\u003cspan citationid=\\\"CR7\\\" class=\\\"CitationRef\\\"\\u003e7\\u003c/span\\u003e], is also highly prevalent among adolescents worldwide [\\u003cspan citationid=\\\"CR8\\\" class=\\\"CitationRef\\\"\\u003e8\\u003c/span\\u003e\\u0026ndash;\\u003cspan citationid=\\\"CR9\\\" class=\\\"CitationRef\\\"\\u003e9\\u003c/span\\u003e]. A recent study estimated that the prevalence of IA among children and adolescents in Macau and mainland China was 23.7% [\\u003cspan citationid=\\\"CR10\\\" class=\\\"CitationRef\\\"\\u003e10\\u003c/span\\u003e]. Our previous study [\\u003cspan citationid=\\\"CR11\\\" class=\\\"CitationRef\\\"\\u003e11\\u003c/span\\u003e] and other studies [\\u003cspan citationid=\\\"CR12\\\" class=\\\"CitationRef\\\"\\u003e12\\u003c/span\\u003e\\u0026ndash;\\u003cspan citationid=\\\"CR13\\\" class=\\\"CitationRef\\\"\\u003e13\\u003c/span\\u003e] have suggested that IA may be associated with NSSI among adolescents. However, it is uncertain whether exposure to IA is prospectively associated with an increased risk of NSSI among adolescents given the lack of evidence from longitudinal studies in the field [\\u003cspan citationid=\\\"CR13\\\" class=\\\"CitationRef\\\"\\u003e13\\u003c/span\\u003e].\\u003c/p\\u003e \\u003cp\\u003eIn addition to IA, studies involving clinical and general populations have suggested that depressive symptoms may be independent risk factors of NSSI [\\u003cspan citationid=\\\"CR14\\\" class=\\\"CitationRef\\\"\\u003e14\\u003c/span\\u003e\\u0026ndash;\\u003cspan citationid=\\\"CR15\\\" class=\\\"CitationRef\\\"\\u003e15\\u003c/span\\u003e]. Meanwhile, longitudinal studies have suggested that compulsive internet use may precede the development of emotional dysregulation [\\u003cspan citationid=\\\"CR16\\\" class=\\\"CitationRef\\\"\\u003e16\\u003c/span\\u003e], and depressive symptoms are one of the most frequent consequences of IA [\\u003cspan citationid=\\\"CR17\\\" class=\\\"CitationRef\\\"\\u003e17\\u003c/span\\u003e]. It seems that depressive symptoms might mediate the association between IA and NSSI. However, only a paucity of research has specifically investigated the mediated role of depressive symptoms in the association between IA and NSSI. Nevertheless, several previous studies have suggested that depression may mediate the association between interpersonal stressors and NSSI among adolescents [\\u003cspan citationid=\\\"CR18\\\" class=\\\"CitationRef\\\"\\u003e18\\u003c/span\\u003e].\\u003c/p\\u003e \\u003cp\\u003eAccording to the stress-buffering hypothesis [\\u003cspan citationid=\\\"CR19\\\" class=\\\"CitationRef\\\"\\u003e19\\u003c/span\\u003e], social support moderates the association between stress and health outcomes. Previous studies have suggested that a high level of social support could help to relieve depressive symptoms and protect against the onset of major depression [\\u003cspan citationid=\\\"CR20\\\" class=\\\"CitationRef\\\"\\u003e20\\u003c/span\\u003e\\u0026ndash;\\u003cspan citationid=\\\"CR21\\\" class=\\\"CitationRef\\\"\\u003e21\\u003c/span\\u003e], as well as buffer the effect of life stress on NSSI [\\u003cspan citationid=\\\"CR22\\\" class=\\\"CitationRef\\\"\\u003e22\\u003c/span\\u003e]. In this regard, social support might exert moderating effects on both the associations between IA and depressive symptoms, and between IA and NSSI. However, the moderating role of social support in these associations has not yet been examined. There is merit in research examining the underlying role of depressive symptoms in the association between IA and NSSI, and whether social support could moderate these associations. Indeed, if these possible relations are supported by evidence, it would help scholars and educators to better understand the nature of the association between IA and NSSI among children and adolescents, this has potentially meaningful for health professionals to implement interventions when working with these populations.\\u003c/p\\u003e \\u003cp\\u003eUsing a two-wave longitudinal design, the present study aimed to explore the role of depressive symptoms and social support in the association of IA and NSSI. Given that early adolescence has a high rate of NSSI and this age range represents a typical onset time of NSSI [\\u003cspan citationid=\\\"CR23\\\" class=\\\"CitationRef\\\"\\u003e23\\u003c/span\\u003e], we investigated a school-based sample of early adolescence to explore these relations. Specifically, we constructed a mediation model and moderated-mediation model and proposed the following hypotheses: (1) IA would be prospectively associated with NSSI among adolescents; (2) depressive symptoms would mediate the association between IA and NSSI; and (3) social support would moderate the association between IA and NSSI, and the association between IA and depressive symptoms in the mediation model of the association between IA and NSSI.\\u003c/p\\u003e\"},{\"header\":\"Methods\",\"content\":\"\\u003cdiv id=\\\"Sec3\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003eStudy participants\\u003c/h2\\u003e \\u003cp\\u003eThis study used data from the Chinese Adolescent Health Growth Cohort (CAHGC) (register number: CCC2022061901, \\u003cspan class=\\\"ExternalRef\\\"\\u003e \\u003cspan class=\\\"RefSource\\\"\\u003ehttp://chinacohort.bjmu.edu.cn\\u003c/span\\u003e \\u003cspan address=\\\"http://chinacohort.bjmu.edu.cn\\\" targettype=\\\"URL\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e \\u003c/span\\u003e). The design, procedure, and implementation are described elsewhere [\\u003cspan citationid=\\\"CR24\\\" class=\\\"CitationRef\\\"\\u003e24\\u003c/span\\u003e]. In brief, using a cluster random sampling method, a representative sample of 1844 students at grade 7 from 11 middle schools across three areas (Qidong County in Hunan Province, Guangming District in Shenzhen City, Zhongshan City in Guangdong Province) were enrolled to participate in the baseline survey (T1). Participants then completed a follow-up survey that was undertaken at 14 months after baseline (T2, N\\u0026thinsp;=\\u0026thinsp;1758). Overall, there were 1543 participants who completed both T1 and T2 surveys. After excluding 13 participants who did not complete the assessment of IA at T1 and/or NSSI at T2, the final sample included 1530 students. No significant differences were found in the variables of interests (i.e., IA, depressive symptoms, social support and NSSI) or other demographic variables, such as age and sex, between adolescents who participated in all assessments and these who did not. The study followed the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guideline and received ethics clearance from the University (NO.2021010002). In each round of data collection, the parents/guardians provided written informed consent that was in a manner consistent with the Declaration of Helsinki. Participants in the study received the equivalent of RMB 150 (\\u003cspan\\u003e$\\u003c/span\\u003e25) in medical examination services after the baseline survey.\\u003c/p\\u003e \\u003c/div\\u003e\\n\\u003ch3\\u003eInstruments\\u003c/h3\\u003e\\n\\u003cp\\u003eIA. At T1, IA was assessed by using the Young Internet Addiction Test (IAT) [\\u003cspan citationid=\\\"CR25\\\" class=\\\"CitationRef\\\"\\u003e25\\u003c/span\\u003e]. The IAT comprises 20 items using a 5-point Likert scale: 1, rarely; 2, occasionally; 3, frequently; 4, often; 5, always; thus, total scores of the IAT range from 20 to 100. Three types of internet user groups were identified based on the original cutoff points proposed by Young [\\u003cspan citationid=\\\"CR26\\\" class=\\\"CitationRef\\\"\\u003e26\\u003c/span\\u003e], namely \\u0026ldquo;average online users\\u0026rdquo; (20\\u0026ndash;49 points), \\u0026ldquo;moderate IA\\u0026rdquo; (50\\u0026ndash;79 points), and \\u0026ldquo;severe IA\\u0026rdquo; (80\\u0026ndash;100 points) [\\u003cspan citationid=\\\"CR26\\\" class=\\\"CitationRef\\\"\\u003e26\\u003c/span\\u003e]. The IAT has been demonstrated to have acceptable internal consistency, with a Cronbach α coefficient of 0.93 in a previous study [\\u003cspan citationid=\\\"CR11\\\" class=\\\"CitationRef\\\"\\u003e11\\u003c/span\\u003e] and 0.91 in the present study sample.\\u003c/p\\u003e \\u003cp\\u003eDepressive symptoms. At T1 and T2, a Chinese version of the Center for Epidemiologic Studies Depression Scale (CES-D) was used to measure depressive symptoms [\\u003cspan citationid=\\\"CR27\\\" class=\\\"CitationRef\\\"\\u003e27\\u003c/span\\u003e], which consists of 9 items using 4-point Likert responses: 0\\u0026thinsp;=\\u0026thinsp;never true; 1\\u0026thinsp;=\\u0026thinsp;rarely true; 2\\u0026thinsp;=\\u0026thinsp;often true; and 3\\u0026thinsp;=\\u0026thinsp;always true; thus, the total scores on CES-D range from 0 to 27. Higher scores indicate greater risk of depression due to more severe depressive symptoms. Participants were divided into three groups based on the validated standard cutoff criteria, including \\u0026lsquo;no depressive symptoms\\u0026rsquo; (0\\u0026ndash;9 points), \\u0026lsquo;moderate depressive symptoms\\u0026rsquo; (10\\u0026ndash;16 points), and \\u0026lsquo;severe depressive symptoms\\u0026rsquo; (17\\u0026ndash;27 points). The Cronbach α coefficient of the scale in the present study was 0.83.\\u003c/p\\u003e \\u003cp\\u003eSocial support. At T1, social support was measured by the 17-item Adolescents Social Support Scale [\\u003cspan citationid=\\\"CR28\\\" class=\\\"CitationRef\\\"\\u003e28\\u003c/span\\u003e], which has 5-point Likert responses for each item (1\\u0026thinsp;=\\u0026thinsp;strongly; 2\\u0026thinsp;=\\u0026thinsp;agree; 3\\u0026thinsp;=\\u0026thinsp;neutral; 4\\u0026thinsp;=\\u0026thinsp;somewhat disagree; 5\\u0026thinsp;=\\u0026thinsp;strongly disagree). The total scores of the scale ranged from 17 to 85, where higher scores of the scale indicate higher level of social support. The Cronbach α coefficient of the scale in the present study was 0.96.\\u003c/p\\u003e \\u003cp\\u003eNSSI. At T1 and T2, the Chinese version of the Functional Assessment of Self-mutilation was used to assess the frequencies of 8 different forms of NSSI (hitting, head banging, stabbing, pinching, scratching, biting, burning, and cutting) during the past 12 months [\\u003cspan citationid=\\\"CR29\\\" class=\\\"CitationRef\\\"\\u003e29\\u003c/span\\u003e]. To distinguish between NSSI and suicidal behaviors, participants were also asked whether any of those behaviors carried suicidal intent. Similar to our previous studies [\\u003cspan citationid=\\\"CR11\\\" class=\\\"CitationRef\\\"\\u003e11\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR29\\\" class=\\\"CitationRef\\\"\\u003e29\\u003c/span\\u003e], NSSI was dichotomized (frequency of five or more acts in the past year\\u0026thinsp;=\\u0026thinsp;yes; versus fewer than five\\u0026thinsp;=\\u0026thinsp;no) for analysis. The Cronbach\\u0026rsquo;s alpha of this scale in the present study was α\\u0026thinsp;=\\u0026thinsp;0.98.\\u003c/p\\u003e \\u003cp\\u003eCo-variables. At T1, we used a custom-designed questionnaire to collect demographic characteristics, familial, and parenting variables, including age, sex (male or female), ethnicity (Han or others, meaning, every category of ethnicity except Han), single-child family (yes or no), family structure (core/joint family, single parent/blended family, cross-generation family), education level of the main caregiver (middle school or below, high school or technical school, college or above), family income (\\u0026lt; \\u003cspan\\u003e$\\u003c/span\\u003e200/month, \\u003cspan\\u003e$\\u003c/span\\u003e200\\u0026ndash;900/month, or \\u0026gt; \\u003cspan\\u003e$\\u003c/span\\u003e900/month), parenting style (strict, pamper, indulge/rude/frequently changing, or open-minded), family history of psychiatric diseases (yes or no) and perceived academical pressure (high, average, or low). A previous study had shown that the test-retest reliability of the questionnaire was α\\u0026thinsp;=\\u0026thinsp;0.83 [\\u003cspan citationid=\\\"CR29\\\" class=\\\"CitationRef\\\"\\u003e29\\u003c/span\\u003e].\\u003c/p\\u003e \\u003cdiv id=\\\"Sec5\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003eStatistical analysis\\u003c/h2\\u003e \\u003cp\\u003eFrequencies and proportions for categorical variables or mean (SD) for continuous variables were used to describe participant characteristics and NSSI at T2 by study variables. χ\\u003csup\\u003e2\\u003c/sup\\u003e tests or 2-tailed, unpaired \\u003cem\\u003et\\u003c/em\\u003e tests were used to compare the distribution between participants with or without a history of NSSI at T2 according to studied variables. Pairwise correlation analysis of measurements (IA and social support [T1], depressive symptoms and NSSI [T1 and T2]) was used to test the associations among the variables. Logistic regression models were employed to examine the independent effects of IA at T2 on NSSI at T2, both unadjusted OR and adjusted OR with 95% confidence intervals (CI) were estimated. In the adjusted model, we adjusted for we adjusted for age, sex, ethnicity, study site, family structure, single-child family, education level of main caregiver, parenting style, family income, family history of psychiatric disease, perceived academic pressure, NSSI and depressive symptom at T1. We also conducted subgroup analysis to examine whether the association between IA and NSSI at T2 differed by sex. Significance level was set at \\u003cem\\u003eP\\u003c/em\\u003e\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.05 and all tests were 2-sided. Statistical analyses were conducted using IBM SPSS Statistics, version 26.0.\\u003c/p\\u003e \\u003cp\\u003eWe performed a set of structural equation models (SEM) to estimate the mediated effect of depressive symptoms in the association between IA and NSSI at T2, and the moderating effects of social support in the direct and the indirect association between IA and NSSI at T2. In all modelling analyses, both unadjusted and adjusted effects were estimated. In the adjusted model, we adjusted the confounders as we did in logistic regression model. In the moderated mediation analysis, simple slope analyses and conditional indirect effect tests (1 SD above and below the mean of the moderator) were performed when an interaction effect of IA and social support was detected. We also preformed subgroup analysis to examine whether the mediated or moderated mediation effects differed by sex. All SEM analyses were performed using Mplus 8.0.\\u003c/p\\u003e \\u003c/div\\u003e\"},{\"header\":\"Results\",\"content\":\"\\u003cdiv id=\\\"Sec7\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003eDemographic characteristic\\u003c/h2\\u003e \\u003cp\\u003eWe included 1530 participants (853 males [55.8%] and 677 females [44.2%]) in the current analysis. At T1, the age of the participants ranged from 11 to 14 years old (mean [SD] age, 12.9 [0.6] years). More than a half (957 [62.5%]) were from Zhongshan City, 1482 (96.9%) were Han ethnicity, 269 (17.6%) were a single child, and 107 (7.0%) were from single parent or blended family. Additional characteristics are summarized in Table\\u0026nbsp;\\u003cspan refid=\\\"Tab1\\\" class=\\\"InternalRef\\\"\\u003e1\\u003c/span\\u003e.\\u003c/p\\u003e \\u003cp\\u003e \\u003cdiv class=\\\"gridtable\\\"\\u003e\\u003ctable float=\\\"Yes\\\" id=\\\"Tab1\\\" border=\\\"1\\\"\\u003e \\u003ccaption language=\\\"En\\\"\\u003e \\u003cdiv class=\\\"CaptionNumber\\\"\\u003eTable 1\\u003c/div\\u003e \\u003cdiv class=\\\"CaptionContent\\\"\\u003e \\u003cp\\u003eCharacteristics of participants according to NSSI at T2\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/caption\\u003e \\u003ccolgroup cols=\\\"4\\\"\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c1\\\" colnum=\\\"1\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c2\\\" colnum=\\\"2\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c3\\\" colnum=\\\"3\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c4\\\" colnum=\\\"4\\\"\\u003e\\u003c/div\\u003e \\u003cthead\\u003e \\u003ctr\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c1\\\" morerows=\\\"1\\\" rowspan=\\\"2\\\"\\u003e \\u003cp\\u003eCharacteristic\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c2\\\" morerows=\\\"1\\\" rowspan=\\\"2\\\"\\u003e \\u003cp\\u003eTotal(n\\u0026thinsp;=\\u0026thinsp;1530)\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c4\\\" namest=\\\"c3\\\"\\u003e \\u003cp\\u003eNSSI at T2\\u003c/p\\u003e \\u003c/th\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003eNo (n\\u0026thinsp;=\\u0026thinsp;1331)\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003eYes (n\\u0026thinsp;=\\u0026thinsp;199)\\u003c/p\\u003e \\u003c/th\\u003e \\u003c/tr\\u003e \\u003c/thead\\u003e \\u003ctbody\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003eAge\\u003c/b\\u003e (\\u003cb\\u003eT1)\\u003c/b\\u003e (M, SD) \\u003csup\\u003e*\\u003c/sup\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e12.9\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;0.6\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e12.9\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;0.6\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e12.8\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;0.6\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003eSex\\u003c/b\\u003e (n, %) \\u003csup\\u003e*\\u003c/sup\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eMales\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e853(55.8)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e776(57.6)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e87(43.7)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eFemales\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e677(44.2)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e565(42.4)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e112(56.3)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003eRegional area\\u003c/b\\u003e (n, %) \\u003csup\\u003e*\\u003c/sup\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eQidong County\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e383(25.0)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e310(23.3)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e73(36.7)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eGuangming District\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e190(12.4)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e173(13.0)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e17(8.5)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eZhongshan City\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e957(62.5)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e848(63.7)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e109(54.8)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003eEthnicity\\u003c/b\\u003e (n, %)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eHan\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e1482(96.9)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e1287(96.7)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e195(98.0)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eOthers\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e48(3.1)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e44(3.3)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e4(2.0)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003eSingle child\\u003c/b\\u003e (n, %)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eNo\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e1261(82.4)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e1084(81.4)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e177(88.9)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eYes\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e269(17.6)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e247(18.6)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e22(11.1)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003eFamily structure\\u003c/b\\u003e (n, %) *\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eCore/joint family\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e1333(87.1)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e1175(88.3)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e158(79.4)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eSingle parent/blended family\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e107(7.0)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e88(6.6)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e19(9.5)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eCross-generation family\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e90(5.9)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e68(5.1)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e22(11.1)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"4\\\" nameend=\\\"c4\\\" namest=\\\"c1\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003eFamily history of psychiatric diseases\\u003c/b\\u003e (n, %) *\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eNo\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e1510(98.7)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e1317(98.9)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e193(97.7)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eYes\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e20(1.3)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e14(1.1)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e6(3.0)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003eParenting style\\u003c/b\\u003e (n, %) *\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eStrict\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e500(32.7)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e447(33.6)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e53(26.6)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eOpen minded\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e783(51.2)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e695(51.4)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e88(44.2)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003ePamper\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e54(3.5)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e42(3.2)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e12(6.0)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eNeglect/rude/frequently changing\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e193(12.6)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e147(11.0)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e46(23.1)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"4\\\" nameend=\\\"c4\\\" namest=\\\"c1\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003eMonthly household income per capita\\u003c/b\\u003e (n, %)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003e\\u0026le;\\u0026thinsp;1999 RMB\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e60(3.9)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e47(4.13.5)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e13(6.5)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003e2000\\u0026ndash;6999 RMB\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e910(59.5)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e791(59.4)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e119(59.8)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003e\\u0026ge;7000 RMB\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e560(36.6)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e493(37.0)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e67(33.7)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003eEducation of main caregiver\\u003c/b\\u003e (n, %)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eJunior and below\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e914(59.7)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e795(59.7)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e119(59.8)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eSenior or technical school\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e360(23.5)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e307(23.1)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e53(26.6)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eCollege and above\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e256(16.7)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e229(17.2)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e27(13.6)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c2\\\" namest=\\\"c1\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003ePerceived academic pressure\\u003c/b\\u003e (n, %) *\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eHigh\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e706(46.1)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e584(43.9)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e122(61.3)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eGeneral\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e773(50.5)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e704(52.9)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e69(34.7)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003elow\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e51(3.3)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e43(3.2)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e8(4.0)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003eDepressive symptoms (T1) (n, %)\\u003c/b\\u003e\\u003csup\\u003e*\\u003c/sup\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eNone\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e1234(80.7)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e1132(85.0)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e102(51.3)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eModerate\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e230(15.0)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e164(12.3)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e66(33.2)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eSevere\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e66(4.3)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e35(2.6)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e31(15.6)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003eIA (T1) (n, %)\\u003c/b\\u003e\\u003csup\\u003e*\\u003c/sup\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eNone\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e1015(66.3)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e934(70.2)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e81(70.2)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eModerate\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e461(30.1)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e364(27.3)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e97(48.7)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eSevere\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e54(3.5)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e33(2.5)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e21(10.6)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003eNSSI(T1) (n, %)\\u003c/b\\u003e\\u003csup\\u003e*\\u003c/sup\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eNo\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e1355(88.6)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e1224(92.0)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e131(65.8)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eYes\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e175(11.4)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e107(8.0)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e68(34.2)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003eDepressive symptoms(T2) (n, %)\\u003c/b\\u003e\\u003csup\\u003e*\\u003c/sup\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eNone\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e1243(81.2)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e1135(85.3)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e108(81.2)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eModerate\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e235(15.4)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e169(12.7)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e66(33.2)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eSevere\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e52(3.4)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e27(2.0)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e25(12.6)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003eSocial support(T1)\\u003c/b\\u003e (M, SD) \\u003csup\\u003e*\\u003c/sup\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e67.0\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;13.4\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e68.2\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;12.8\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e59.2\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;14.5\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003c/tbody\\u003e \\u003c/colgroup\\u003e \\u003ctfoot\\u003e \\u003ctr\\u003e\\u003ctd colspan=\\\"4\\\"\\u003e*\\u003cem\\u003eP\\u003c/em\\u003e\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.05.\\u003c/td\\u003e\\u003c/tr\\u003e \\u003c/tfoot\\u003e \\u003c/table\\u003e\\u003c/div\\u003e \\u003c/p\\u003e \\u003cp\\u003eOverall, 461 participants met the criteria of moderate IA, and 54 participants met the criteria of severe IA at T1. The prevalence of moderate IA and severe IA were 30.1% and 3.5%, respectively, and no sex differences were found (χ\\u003csup\\u003e2\\u003c/sup\\u003e\\u0026thinsp;=\\u0026thinsp;2.281, \\u003cem\\u003eP\\u003c/em\\u003e\\u0026thinsp;=\\u0026thinsp;0.320). Participants who were moderate IA or severe IA were likely to have moderate or severe depressive symptoms at T1 (χ\\u003csup\\u003e2\\u003c/sup\\u003e\\u0026thinsp;=\\u0026thinsp;19.773, \\u003cem\\u003eP\\u003c/em\\u003e\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.001). The prevalence of NSSI was 11.4% at T1 and 13.0% at T2. Univariate analysis on influence factors of NSSI at T2 is also presented in Table\\u0026nbsp;\\u003cspan refid=\\\"Tab1\\\" class=\\\"InternalRef\\\"\\u003e1\\u003c/span\\u003e. Participants who were female, from single parent or blended family, experienced neglect/rude/frequently changing parenting practices, perceived high academic pressure, had moderate or severe IA, had moderate or severe depressive symptoms and engaged NSSI at T1 were more likely to engage in NSSI at T2 (Table\\u0026nbsp;\\u003cspan refid=\\\"Tab1\\\" class=\\\"InternalRef\\\"\\u003e1\\u003c/span\\u003e).\\u003c/p\\u003e \\u003c/div\\u003e\\n\\u003ch3\\u003eThe Independent Effect Of Ia On Nssi At T2\\u003c/h3\\u003e\\n\\u003cp\\u003eAfter testing the normality of the independent, dependent variable, mediation and moderating variables, Spearman correlation analyses were performed; results are presented in Supplement Table\\u0026nbsp;\\u003cspan refid=\\\"Tab1\\\" class=\\\"InternalRef\\\"\\u003e1\\u003c/span\\u003e. The unadjusted OR and adjusted OR of IA for NSSI at T2 were presented in Table\\u0026nbsp;\\u003cspan refid=\\\"Tab2\\\" class=\\\"InternalRef\\\"\\u003e2\\u003c/span\\u003e. After adjusted for the confounders, IA was associated with an increased risk of NSSI at T2. Compared to those who were not IA, participants who were moderate and severe IA had greater odds of NSSI (both \\u003cem\\u003eP\\u003c/em\\u003e\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.001). Subgroup analysis showed that the independent effect of IA at T1 on NSSI at T2 not differed by sex (Supplement Table\\u0026nbsp;\\u003cspan refid=\\\"Tab2\\\" class=\\\"InternalRef\\\"\\u003e2\\u003c/span\\u003e).\\u003c/p\\u003e \\u003cp\\u003e \\u003cdiv class=\\\"gridtable\\\"\\u003e\\u003ctable float=\\\"Yes\\\" id=\\\"Tab2\\\" border=\\\"1\\\"\\u003e \\u003ccaption language=\\\"En\\\"\\u003e \\u003cdiv class=\\\"CaptionNumber\\\"\\u003eTable 2\\u003c/div\\u003e \\u003cdiv class=\\\"CaptionContent\\\"\\u003e \\u003cp\\u003eAssociation between IA at T1 and NSSI at T2\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/caption\\u003e \\u003ccolgroup cols=\\\"7\\\"\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c1\\\" colnum=\\\"1\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"char\\\" char=\\\".\\\" class=\\\"colspec\\\" colname=\\\"c2\\\" colnum=\\\"2\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c3\\\" colnum=\\\"3\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"char\\\" char=\\\".\\\" class=\\\"colspec\\\" colname=\\\"c4\\\" colnum=\\\"4\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c5\\\" colnum=\\\"5\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c6\\\" colnum=\\\"6\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"char\\\" char=\\\".\\\" class=\\\"colspec\\\" colname=\\\"c7\\\" colnum=\\\"7\\\"\\u003e\\u003c/div\\u003e \\u003cthead\\u003e \\u003ctr\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u0026nbsp;\\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003eNSSI at T2 (N, %)\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003eUnadjusted\\u003c/p\\u003e \\u003cp\\u003eOR (95%CI)\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003eP\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003eAdjusted \\u003csup\\u003ea\\u003c/sup\\u003e\\u003c/p\\u003e \\u003cp\\u003eOR (95%CI)\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003eP\\u003c/p\\u003e \\u003c/th\\u003e \\u003c/tr\\u003e \\u003c/thead\\u003e \\u003ctbody\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eNo IA\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e81 (8.0)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003eRef\\u0026thinsp;=\\u0026thinsp;1\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003eRef\\u0026thinsp;=\\u0026thinsp;1\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eModerate IA\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e97 (21.0)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e3.07 (2.23, 4.23)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e\\u0026lt;\\u0026thinsp;0.001\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e2.70 (1.93, 3.75)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003e\\u0026lt;\\u0026thinsp;0.001\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eSevere IA\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e21 (39.8)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e7.34 (4.06, 12.37)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e\\u0026lt;\\u0026thinsp;0.001\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e4.62 (2.45, 8.71)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003e\\u0026lt;\\u0026thinsp;0.001\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003c/tbody\\u003e \\u003c/colgroup\\u003e \\u003ctfoot\\u003e \\u003ctr\\u003e\\u003ctd colspan=\\\"7\\\"\\u003ea. Adjusted for sex, age, ethnicity, regional areas, family structure, single child, family history of psychiatric disease, parenting style, household income per capita, perceived academic pressure, education of main caregiver, baseline NSSI and baseline depressive symptoms.\\u003c/td\\u003e\\u003c/tr\\u003e \\u003c/tfoot\\u003e \\u003c/table\\u003e\\u003c/div\\u003e \\u003c/p\\u003e\\n\\u003ch3\\u003eThe Indirect Effect Of Ia On Nssi At T2 Mediated Through Depressive Symptoms\\u003c/h3\\u003e\\n\\u003cp\\u003eFigure \\u003cspan refid=\\\"Fig1\\\" class=\\\"InternalRef\\\"\\u003e1\\u003c/span\\u003e shows the results of the mediation analyses. After adjusting for potential confounders, the total effect of IA at T1 on NSSI at T2 was significant (standard β\\u0026thinsp;=\\u0026thinsp;0.113, 95%CI, 0.055, 0.174). The direct effect of IA at T1 on NSSI at T2 was 0.099 (95%CI 0.042, 0.161) and depressive symptoms at T2 on NSSI at T2 was 0.169 (95%CI 0.100, 0.239). The indirect effect of IA on NSSI at T2 mediated through depressive symptoms was 0.014 (95%CI 0.004, 0.029). The mediation proportion was 12.4% (95%CI 7.3%, 16.7%) (Table\\u0026nbsp;\\u003cspan refid=\\\"Tab3\\\" class=\\\"InternalRef\\\"\\u003e3\\u003c/span\\u003e). Goodness-of-fit indices (i.e., CFI\\u0026thinsp;=\\u0026thinsp;1.000, TLI\\u0026thinsp;=\\u0026thinsp;1.000, RMSEA\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.001, SRMR\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.001) indicated satisfactory fit of the model. Subgroup mediation analysis demonstrated that the total and direct effects of IA at T1 on NSSI at T2 among both males and females were significant (all \\u003cem\\u003eP\\u003c/em\\u003e\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.001). However, the significant indirect effect of IA at T1 on NSSI at T2 mediated through depressive symptoms was only found for females, with the mediation proportion was 19.0% (95%CI 15.4%, 23.8%) (See Supplement Table\\u0026nbsp;\\u003cspan refid=\\\"Tab3\\\" class=\\\"InternalRef\\\"\\u003e3\\u003c/span\\u003e).\\u003c/p\\u003e \\u003cp\\u003e \\u003cdiv class=\\\"gridtable\\\"\\u003e\\u003ctable float=\\\"Yes\\\" id=\\\"Tab3\\\" border=\\\"1\\\"\\u003e \\u003ccaption language=\\\"En\\\"\\u003e \\u003cdiv class=\\\"CaptionNumber\\\"\\u003eTable 3\\u003c/div\\u003e \\u003cdiv class=\\\"CaptionContent\\\"\\u003e \\u003cp\\u003eMediating effect of depressive symptoms between IA(T1) and NSSI(T2)\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/caption\\u003e \\u003ccolgroup cols=\\\"6\\\"\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c1\\\" colnum=\\\"1\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"char\\\" char=\\\".\\\" class=\\\"colspec\\\" colname=\\\"c2\\\" colnum=\\\"2\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c3\\\" colnum=\\\"3\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c4\\\" colnum=\\\"4\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"char\\\" char=\\\".\\\" class=\\\"colspec\\\" colname=\\\"c5\\\" colnum=\\\"5\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c6\\\" colnum=\\\"6\\\"\\u003e\\u003c/div\\u003e \\u003cthead\\u003e \\u003ctr\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c1\\\" morerows=\\\"1\\\" rowspan=\\\"2\\\"\\u003e \\u003cp\\u003eVariables\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c3\\\" namest=\\\"c2\\\"\\u003e \\u003cp\\u003eModel 1 \\u003csup\\u003ea\\u003c/sup\\u003e\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/th\\u003e \\u003cth align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c6\\\" namest=\\\"c5\\\"\\u003e \\u003cp\\u003eModel 2 \\u003csup\\u003eb\\u003c/sup\\u003e\\u003c/p\\u003e \\u003c/th\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003eStandard β (95% CI)\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e\\u003cem\\u003eP\\u003c/em\\u003e\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003eStandard β (95% CI)\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e\\u003cem\\u003eP\\u003c/em\\u003e\\u003c/p\\u003e \\u003c/th\\u003e \\u003c/tr\\u003e \\u003c/thead\\u003e \\u003ctbody\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eIA(T1)\\u0026rarr;Depressive symptoms(T2)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e0.200(0.147, 0.258)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e\\u0026lt;\\u0026thinsp;0.001\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e0.084(0.027, 0.144)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e0.005\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eDepressive symptoms(T2)\\u0026rarr;NSSI(T2)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e0.249(0.181, 0.314)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e\\u0026lt;\\u0026thinsp;0.001\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e0.169(0.100, 0.239)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e\\u0026lt;\\u0026thinsp;0.001\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eIA(T1)\\u0026rarr;NSSI(T2)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e0.179(0.120, 0.240)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e\\u0026lt;\\u0026thinsp;0.001\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e0.099(0.042, 0.161)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e0.001\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eStandardized effect\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eIndirect\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e0.050(0.032, 0.072)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e\\u0026lt;\\u0026thinsp;0.001\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e0.014(0.004, 0.029)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e0.021\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eTotal\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e0.229(0.171, 0.286)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e\\u0026lt;\\u0026thinsp;0.001\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e0.113(0.055, 0.174)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e\\u0026lt;\\u0026thinsp;0.001\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eMediating ratio (%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e21.8(18.7, 25.2)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e--\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e12.4(7.3, 16.7)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e--\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003c/tbody\\u003e \\u003c/colgroup\\u003e \\u003ctfoot\\u003e \\u003ctr\\u003e\\u003ctd colspan=\\\"6\\\"\\u003ea. Unadjusted.\\u003c/td\\u003e\\u003c/tr\\u003e \\u003ctr\\u003e\\u003ctd colspan=\\\"6\\\"\\u003eb. Adjusted for sex, age, ethnicity, regional areas, family structure, single child, family history of psychiatric disease, parenting style, household income per capita, perceived academic pressure, education of main caregiver, baseline NSSI and baseline depressive symptoms.\\u003c/td\\u003e\\u003c/tr\\u003e \\u003c/tfoot\\u003e \\u003c/table\\u003e\\u003c/div\\u003e \\u003c/p\\u003e \\u003cp\\u003e \\u003cb\\u003eThe moderating effect of social support on the mediation path and the direct path in the association between IA and NSSI\\u003c/b\\u003e \\u003c/p\\u003e \\u003cp\\u003eThe interaction between IA and social support at T1 in predicting depressive symptoms at T2 was significant (standard β=-0.081, 95%CI -0.142, -0.014), but was not significant in predicting NSSI at T2 (β=-0.082, 95%CI -0.067, 0.051) (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig2\\\" class=\\\"InternalRef\\\"\\u003e2\\u003c/span\\u003e, supplemental Table\\u0026nbsp;4). The model of the SEM (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig2\\\" class=\\\"InternalRef\\\"\\u003e2\\u003c/span\\u003e) also fit the data well. The simple slope test indicated that the association between IA at T1 and depressive symptoms at T2 was significant for participants with low (b\\u0026thinsp;=\\u0026thinsp;0.137, 95%CI 0.056, 0.225) or moderate (b\\u0026thinsp;=\\u0026thinsp;0.059, 95%CI 0.006, 0.121) level of social support, but not for those with high level of social support (b=-0.019, 95%CI -0.092, 0.067). Compared to participants with low level of social support, the positive links between IA at T1 and depressive symptoms at T2 was stronger for participants who had moderate social support (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig3\\\" class=\\\"InternalRef\\\"\\u003e3\\u003c/span\\u003e).\\u003c/p\\u003e \\u003cp\\u003eThe indirect effect of IA on NSSI at T2 through depressive symptoms at T2 was conditioned at different levels of social support. Specifically, the indirect effect was strongest when social support was low (standard β\\u0026thinsp;=\\u0026thinsp;0.019, 95% CI 0.007, 0.047), moderate at moderate levels of social support (standard β\\u0026thinsp;=\\u0026thinsp;0.008, 95% CI 0.001, 0.025), and non-significant at high social support (standard β=-0.003, 95% CI -0.015, 0.009) (Supplemental Table\\u0026nbsp;4). Similarly, the conditional indirect effect of IA on NSSI mediated through depressive symptoms was only found among females but not for males (Supplemental Table\\u0026nbsp;5).\\u003c/p\\u003e\"},{\"header\":\"Discussion\",\"content\":\"\\u003cp\\u003eTo our knowledge, this is the first longitudinal study examining the mediated effect of depressive symptoms and the moderating effect of social support in the association between IA and NSSI among adolescents. There were two key and novel findings from this study. First, IA had significant effect on NSSI at T2, 12.4% of which was mediated through depressive symptoms at T2. Second, social support moderated the effect of IA on NSSI at T2 through moderating the mediated effects of depressive symptoms. These findings provide new information about the association between IA and NSSI among adolescents, which could benefit educators, scholars and decision-makers to better understand the development of NSSI among children and adolescence and, as such, potentially inform NSSI interventions.\\u003c/p\\u003e \\u003cp\\u003eMore and more social networking and learning are taking place online, especially during the COVID-19 pandemic. This, at the extreme end, could lead to more people depending on the internet and thus be more prone to IA [\\u003cspan citationid=\\\"CR30\\\" class=\\\"CitationRef\\\"\\u003e30\\u003c/span\\u003e], especially among adolescents. There are a number of studies that have examined the potential effects of IA on adolescents\\u0026rsquo; mental and conduct difficulties, such as suicidal behaviors, NSSI, depression, anxiety, and attention deficit hyperactivity disorders [\\u003cspan citationid=\\\"CR11\\\" class=\\\"CitationRef\\\"\\u003e11\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR31\\\" class=\\\"CitationRef\\\"\\u003e31\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR32\\\" class=\\\"CitationRef\\\"\\u003e32\\u003c/span\\u003e]. In the current study, we found that IA was significantly associated with an increased risk of NSSI at T2 among adolescents. This finding aligns with the only longitudinal study conducted in Taiwan [\\u003cspan citationid=\\\"CR13\\\" class=\\\"CitationRef\\\"\\u003e13\\u003c/span\\u003e] and most previous cross-sectional studies [\\u003cspan citationid=\\\"CR11\\\" class=\\\"CitationRef\\\"\\u003e11\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR33\\\" class=\\\"CitationRef\\\"\\u003e33\\u003c/span\\u003e], which support a positive association between IA and NSSI. However, there were two studies that suggested a null association between IA and self-harm [\\u003cspan citationid=\\\"CR34\\\" class=\\\"CitationRef\\\"\\u003e34\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR35\\\" class=\\\"CitationRef\\\"\\u003e35\\u003c/span\\u003e], a broader term that includes NSSI but also encompasses suicidal behaviors. The inconsistency across the collective findings may be account for by the various characteristics within the study population. This includes the different prevalence of NSSI and IA that were examined by different measurements and criteria, apart from study design and adjustments. Studies that have not distinguished between self-harm and NSSI may have overestimated the association between IA and NSSI [\\u003cspan citationid=\\\"CR13\\\" class=\\\"CitationRef\\\"\\u003e13\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR36\\\" class=\\\"CitationRef\\\"\\u003e36\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR37\\\" class=\\\"CitationRef\\\"\\u003e37\\u003c/span\\u003e]. Therefore, a more-uniform evaluative measurement of NSSI, apart from broader self-harm behavior, will be needed to clarify the association between IA and NSSI.\\u003c/p\\u003e \\u003cp\\u003eNSSI is often considered as an emotion-regulation strategy to decrease one\\u0026rsquo;s emotional distress by distracting from intense emotion through the sight of blood, the sensation of pain, or focus on the injury itself [\\u003cspan citationid=\\\"CR38\\\" class=\\\"CitationRef\\\"\\u003e38\\u003c/span\\u003e]. There are also many studies providing support for a mediating role of depression between interpersonal stress and NSSI among adolescents, including peer bullying [\\u003cspan citationid=\\\"CR18\\\" class=\\\"CitationRef\\\"\\u003e18\\u003c/span\\u003e] and loneliness [\\u003cspan citationid=\\\"CR39\\\" class=\\\"CitationRef\\\"\\u003e39\\u003c/span\\u003e]. Although previous studies have indicated an association between IA and NSSI, as well as depressive symptoms with NSSI, a dearth of study has explicitly addressed the mechanisms underlying IA, depressive symptoms and NSSI. Our study adds to this literature as we found that depressive symptoms played a mediating role in the association between IA and NSSI. In other words, some adolescents with IA may not present with NSSI directly but instead present with depressive symptoms which then associates with an increased risk of NSSI. Indeed, our finding extends prior research by bridging the associations between IA, depressive symptoms and NSSI, which is in line with studies that have examined the indirect effects of IA on suicidal behaviors [\\u003cspan citationid=\\\"CR40\\\" class=\\\"CitationRef\\\"\\u003e40\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR41\\\" class=\\\"CitationRef\\\"\\u003e41\\u003c/span\\u003e]. Yu and colleagues conducted a cross-sectional study indicating that internet gaming disorders are positively associated with insomnia, which increases depressive symptoms, and, in turn, positively contributed to suicidal ideation [\\u003cspan citationid=\\\"CR40\\\" class=\\\"CitationRef\\\"\\u003e40\\u003c/span\\u003e]. Similarly, Guo et al conducted a study of 20895 adolescents, finding that sleep disturbance mediated the association between problematic internet use and suicidal behavior [\\u003cspan citationid=\\\"CR41\\\" class=\\\"CitationRef\\\"\\u003e41\\u003c/span\\u003e].\\u003c/p\\u003e \\u003cp\\u003eThe mediating role of depressive symptoms in the association between IA and NSSI could be explained in the several ways. First, individuals with IA may be prone to be depression because they spend too much time in the internet virtual world and thus less time on social gatherings, family or peer group activities, this may, in turn, result in unhelpful ways of adapting to their offline lives and greater isolation [\\u003cspan citationid=\\\"CR17\\\" class=\\\"CitationRef\\\"\\u003e17\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR42\\\" class=\\\"CitationRef\\\"\\u003e42\\u003c/span\\u003e]. Second, physiological studies have shown that IA could disrupt dopamine transmission by decreasing the expression of dopamine transporter in the striatum, which may increase the risk of depressive symptoms [\\u003cspan citationid=\\\"CR43\\\" class=\\\"CitationRef\\\"\\u003e43\\u003c/span\\u003e]. The resultant depressive symptoms may, in turn, lead to NSSI as a means to decrease emotional distress [\\u003cspan citationid=\\\"CR44\\\" class=\\\"CitationRef\\\"\\u003e44\\u003c/span\\u003e]. Therefore, interventions that focus on reducing depressive symptoms may be a potential strategy for prevention of NSSI. It should be noted that the indirect effect of IA on NSSI mediated through depressive symptoms was significant for females but not males, which may be related to the difference in psychological traits between females and males. Previous studies have reported that females experience higher rates of emotional disorders and tend to ruminate, avoid, and be less active in their coping methods, while males tend to be more impulsive and like to engage in physical and instrumental forms of comping methods directly [\\u003cspan citationid=\\\"CR45\\\" class=\\\"CitationRef\\\"\\u003e45\\u003c/span\\u003e].\\u003c/p\\u003e \\u003cp\\u003eSocial support, defined as the extent to which individuals may receive emotional or instrumental help from others, is a noteworthy predictor of adolescents\\u0026rsquo; positive psychosocial development [\\u003cspan citationid=\\\"CR20\\\" class=\\\"CitationRef\\\"\\u003e20\\u003c/span\\u003e]. Indeed, having strong social support can protect against negative mental health outcomes such as depression resulting from heightened life stress. For example, a cohort study of 1917 young adults examining associations between neighborhood-level social support and subsequent individual outcomes across 10 years, found that neighborhood-level social support can longitudinally protect against the onset of major depressive disorder in high-stress settings [\\u003cspan citationid=\\\"CR20\\\" class=\\\"CitationRef\\\"\\u003e20\\u003c/span\\u003e]. Similarly, the Avon Longitudinal Study of Parents and Children study also suggested that strong peer social support at age 15 may reduce the risk of depressive symptoms by the time children reach late adolescence [\\u003cspan citationid=\\\"CR21\\\" class=\\\"CitationRef\\\"\\u003e21\\u003c/span\\u003e]. Further, a study conducted in China suggested that social support had a moderating effect on the association between bullying and depressive symptoms [\\u003cspan citationid=\\\"CR46\\\" class=\\\"CitationRef\\\"\\u003e46\\u003c/span\\u003e]. Our findings expand this literature by demonstrating that social support may mitigate the consequences of IA on depressive symptoms and the indirect effect of IA on NSSI through depressive symptoms.\\u003c/p\\u003e \\u003cp\\u003eThe possible stress buffer mechanism in this context may be depicted that when individuals encounter a stressful event, adequate social support may mitigate the experience of stress and the onset of adverse outcomes by reducing or eliminating the stress reaction through calming the neuroendocrine system [\\u003cspan citationid=\\\"CR19\\\" class=\\\"CitationRef\\\"\\u003e19\\u003c/span\\u003e]. Specifically, social support has been found to buffer the effects of life stress on dopamine deficit and dysfunction and diminish the raised cortisol responses to social stressors [\\u003cspan citationid=\\\"CR47\\\" class=\\\"CitationRef\\\"\\u003e47\\u003c/span\\u003e\\u0026ndash;\\u003cspan citationid=\\\"CR48\\\" class=\\\"CitationRef\\\"\\u003e48\\u003c/span\\u003e]. Contrary to our hypothesis, we did not find social support to buffer the direct effect of IA on NSSI. Previous studies have suggested that different sources of social support had a mixed stress-buffering effect. For instance, a study using data from the Adolescent Development of Emotions and Personality Traits found that only parental support, rather than peer support, protected adolescents from NSSI following a stressor [\\u003cspan citationid=\\\"CR22\\\" class=\\\"CitationRef\\\"\\u003e22\\u003c/span\\u003e], while another study conducted in China found that only friend support buffered the relationship between maltreatment and NSSI [\\u003cspan citationid=\\\"CR49\\\" class=\\\"CitationRef\\\"\\u003e49\\u003c/span\\u003e]. Therefore, it is possible that only specific sources of social support play a buffering role in term of the direct effect of IA on NSSI; this possibility warrants further research. Taken together, findings from the current study showed that social support serve as a protective factor, shielding adolescents from the detriment of IA, especially in female adolescents.\\u003c/p\\u003e \\u003cp\\u003eOne major strength of our study is the sample representativeness. For this cohort study, we recruited a large sample size of adolescent across 3 cities, with the social, economic, and cultures reflecting the status in China. In addition, the adjustment for a variety of potential confounders in the SEM, as well as in subsequent analyses, ensured the validity and robustness of our findings. What is more, this is the first study to examine the role of depressive symptoms and social support in association between IA and NSSI, which may be helpful in later informing the development and preventive interventions to address these concerns among adolescents, particularly for IA and NSSI.\\u003c/p\\u003e\"},{\"header\":\"Limitations\",\"content\":\"\\u003cp\\u003eSeveral limitations should be noted. Firstly, our study used adolescent self-reports to collect data, which could be subject to bias. Therefore, in the future, studies should attempt to also collect data from adolescents\\u0026rsquo; parents and caregivers. Secondly, we did not assess the source of social support (such as family support, peer support, community support), which hampered us from analyzing the moderating effect of different sources of social support on NSSI. Therefore, further studies are needed to distinguish the moderating effect of different source of social support on NSSI. Thirdly, although the sample participants are representative, we only included adolescents in grade seven in the present study. We, therefore, are not able to assume that the present results would generalize to other study phases or other age groups. This is important because the prevalence of IA, depressive symptoms and NSSI, and source of social support may change with study phases or ages. Replication of our findings using other populations would help to determine their generalizability. Likewise, examining the relations focused upon in this study across other populations (e.g., youth in other countries) would also help to determine how generalizable the present findings are. Hence, caution should be exercised when applying to the findings to all populations of adolescents.\\u003c/p\\u003e\"},{\"header\":\"Conclusions\",\"content\":\"\\u003cp\\u003eIn this study, involving a representative sample of adolescents at seventh grade, the mediation effect of depressive symptoms and the moderating effect of social support in the association between IA and NSSI were observed. Hence, interventions targeting NSSI among adolescents should focus on reducing IA, depressive symptoms and elevating social support.\\u003c/p\\u003e\"},{\"header\":\"Abbreviations\",\"content\":\"\\u003cdiv class=\\\"DefinitionList\\\"\\u003e \\u003cdiv class=\\\"DefinitionListEntry\\\"\\u003e \\u003cdiv class=\\\"Term\\\"\\u003eNSSI\\u003c/div\\u003e \\u003cdiv class=\\\"Description\\\"\\u003e \\u003cp\\u003eNon-suicidal self-injury\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/div\\u003e \\u003cdiv class=\\\"DefinitionListEntry\\\"\\u003e \\u003cdiv class=\\\"Term\\\"\\u003eIA\\u003c/div\\u003e \\u003cdiv class=\\\"Description\\\"\\u003e \\u003cp\\u003eInternet addiction\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/div\\u003e \\u003cdiv class=\\\"DefinitionListEntry\\\"\\u003e \\u003cdiv class=\\\"Term\\\"\\u003eIAT\\u003c/div\\u003e \\u003cdiv class=\\\"Description\\\"\\u003e \\u003cp\\u003eInternet Addiction Test\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/div\\u003e \\u003cdiv class=\\\"DefinitionListEntry\\\"\\u003e \\u003cdiv class=\\\"Term\\\"\\u003eCES-D\\u003c/div\\u003e \\u003cdiv class=\\\"Description\\\"\\u003e \\u003cp\\u003eCenter for Epidemiologic Studies Depression Scale\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/div\\u003e \\u003cdiv class=\\\"DefinitionListEntry\\\"\\u003e \\u003cdiv class=\\\"Term\\\"\\u003eSEM\\u003c/div\\u003e \\u003cdiv class=\\\"Description\\\"\\u003e \\u003cp\\u003estructural equation models\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/div\\u003e \\u003cdiv class=\\\"DefinitionListEntry\\\"\\u003e \\u003cdiv class=\\\"Term\\\"\\u003eCOVID-19\\u003c/div\\u003e \\u003cdiv class=\\\"Description\\\"\\u003e \\u003cp\\u003eCoronavirus disease 2019.\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/div\\u003e \\u003c/div\\u003e\"},{\"header\":\"Declarations\",\"content\":\"\\u003cp\\u003e\\u003cstrong\\u003eEthics approval and consent to participate.\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eThe present study has obtained the ethics clearance from Guangzhou Medical University (NO.2021010002) and therefore been performed in accordance with ethical standard laid down in the 1964 Declaration of Helsinki and its later amendments. And all parents/guardians of the participants provided written informed consent prior to their inclusion in the study.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eConsent for publication\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eNot applicable.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eAvailability of data and materials\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eThe data that support the findings of this study are not openly available due to the intellectual property of the datasets belonging to the corresponding author and are available from the corresponding author upon reasonable request.\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eCompeting interests\\u003c/strong\\u003e\\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\\u003eFounding for this study was provided by grants from National Natural Science Foundation of China (82204065 to YM; 82073571 \\u0026amp; 81773457 to JT). The funding bodies had no role in the design of the study and collection, analysis, and interpretation of data and in writing the manuscript.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eAuthors\\u0026apos; contributions\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eYing Ma, Yanqi Li, and Xinyi Xie took part in the design and investigation, conducted the basic analysis, and wrote the first draft of the manuscript. Yi Zhang took part in the investigation and conducted the statistical analysis. Fenghua Li organized the investigation. Brooke A. Ammerman and Stephen P Lewis revised the manuscript. Ruoling Chen conducted the formal analysis. Yizhen Yu provided with the resources. Jie Tang supervised the investigation, validated the final manuscript, and provided with funding. All authors contributed to and have approved the final manuscript.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eAcknowledgements\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eThe authors would like to thank all the schools, parents and students who participated in this study.\\u003c/p\\u003e\"},{\"header\":\"References\",\"content\":\"\\u003col\\u003e\\n\\u003cli\\u003eDuffy ME, Twenge JM, Joiner TE. Trends in mood and anxiety symptoms and suicide-related outcomes among U.S. undergraduates, 2007-2018: evidence from two national surveys. J Adolesc Health. 2019; 65(5):590-598. https://doi:10.1016/j.jadohealth.2019.04.033.\\u003c/li\\u003e\\n\\u003cli\\u003eMannekote TS, Shankarapura NM, Gude JG, Voyiaziakis E, Patwa S, Birur B, et al. Non-suicidal self-injury in developing countries: A review. Int J Soc Psychiatry. 2021; 67(5):472-482. https://doi:10.1177/0020764020943627.\\u003c/li\\u003e\\n\\u003cli\\u003eKiekens G. 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Community-Level Social support infrastructure and adult onset of major depressive disorder in a south Asian postconflict setting. JAMA Psychiatry. 2022; 79(3):243-249. https://doi:10.1001/jamapsychiatry.2021.4052.\\u003c/li\\u003e\\n\\u003cli\\u003eGlickman EA, Choi KW, Lussier AA, Smith BJ, Dunn EC. Childhood emotional neglect and adolescent depression: assessing the protective role of peer social support in a longitudinal birth cohort. Front Psychiatry. 2021; 12:681176. https://doi:10.3389/fpsyt.2021.681176.\\u003c/li\\u003e\\n\\u003cli\\u003eMackin DM, Perlman G, Davila J, Kotov R, Klein DN. Social support buffers the effect of interpersonal life stress on suicidal ideation and self-injury during adolescence. Psychol Med. 2017; 47(6):1149-1161. https://doi:10.1017/S0033291716003275.\\u003c/li\\u003e\\n\\u003cli\\u003eAmmerman BA, Jacobucci R, Kleiman EM, Uyeji LL, McCloskey MS. The relationship between nonsuicidal self‐injury age of onset and severity of self‐harm. 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Friend support buffers the relationship between maltreatment and nonsuicidal self-injury in adolescence. Suicide Life Threat Behav. 2022; 52(4):802-81. https://doi:10.1111/sltb.12864.\\u003c/li\\u003e\\n\\u003c/ol\\u003e\"}],\"fulltextSource\":\"\",\"fullText\":\"\",\"funders\":[],\"hasAdminPriorityOnWorkflow\":false,\"hasManuscriptDocX\":true,\"hasOptedInToPreprint\":true,\"hasPassedJournalQc\":\"\",\"hasAnyPriority\":false,\"hideJournal\":false,\"highlight\":\"\",\"institution\":\"\",\"isAcceptedByJournal\":true,\"isAuthorSuppliedPdf\":false,\"isDeskRejected\":\"\",\"isHiddenFromSearch\":false,\"isInQc\":false,\"isInWorkflow\":false,\"isPdf\":false,\"isPdfUpToDate\":true,\"isWithdrawnOrRetracted\":false,\"journal\":{\"display\":true,\"email\":\"info@researchsquare.com\",\"identity\":\"bmc-psychiatry\",\"isNatureJournal\":false,\"hasQc\":true,\"allowDirectSubmit\":false,\"externalIdentity\":\"bpsy\",\"sideBox\":\"Learn more about [BMC Psychiatry](http://bmcpsychiatry.biomedcentral.com/)\",\"snPcode\":\"\",\"submissionUrl\":\"https://www.editorialmanager.com/bpsy/default.aspx\",\"title\":\"BMC Psychiatry\",\"twitterHandle\":\"@BMC_series\",\"acdcEnabled\":true,\"dfaEnabled\":false,\"editorialSystem\":\"em\",\"reportingPortfolio\":\"BMC Series\",\"inReviewEnabled\":true,\"inReviewRevisionsEnabled\":true},\"keywords\":\"Internet addiction, non-suicidal self-injury, depressive symptoms, social support, Cohort study, Adolescent\",\"lastPublishedDoi\":\"10.21203/rs.3.rs-2656091/v1\",\"lastPublishedDoiUrl\":\"https://doi.org/10.21203/rs.3.rs-2656091/v1\",\"license\":{\"name\":\"CC BY 4.0\",\"url\":\"https://creativecommons.org/licenses/by/4.0/\"},\"manuscriptAbstract\":\"\\u003ch2\\u003eBackground\\u003c/h2\\u003e \\u003cp\\u003eBoth internet addiction (IA) and non-suicidal self-injury (NSSI) are major public health concerns among adolescents, however, the association between IA and NSSI was not well understood. In this study we aim to investigate the association between IA and NSSI within a cohort study, and to explore the mediated effect of depressive symptoms and the moderating effect of social support in the association.\\u003c/p\\u003e\\u003ch2\\u003eMethods\\u003c/h2\\u003e \\u003cp\\u003eA total of 1530 adolescents aged 11\\u0026ndash;14 years who completed both the baseline (T1) and 14-month follow-up (T2) survey of the Chinese Adolescent Health Growth Cohort were included for the current analysis. IA, NSSI, depressive symptoms and social support were measured at T1; depressive symptoms and NSSI were measured again at T2. Structural equation models were employed to estimate the mediated effect of depressive symptoms and the moderating effects of social support in the association between IA and NSSI at T2.\\u003c/p\\u003e\\u003ch2\\u003eResults\\u003c/h2\\u003e \\u003cp\\u003eIA was independently associated with an increased risk of NSSI at T2, with the total effect of 0.113 (95%CI 0.055\\u0026ndash;0.174). Depressive symptoms mediated the association between IA and NSSI at T2, and social support moderated the indirect but not the direct effect of IA on NSSI at T2. Sex differences were found on the mediated effect of depressive symptoms and the moderated mediation effect of social support.\\u003c/p\\u003e\\u003ch2\\u003eConclusions\\u003c/h2\\u003e \\u003cp\\u003eInterventions that target adolescents\\u0026rsquo; NSSI who also struggle with IA may need to focus on reducing depressive symptoms and elevating social support.\\u003c/p\\u003e\",\"manuscriptTitle\":\"The role of depressive symptoms and social support in the association of internet addiction with non-suicidal self-injury among adolescents: a cohort study in China\",\"msid\":\"\",\"msnumber\":\"\",\"nonDraftVersions\":[{\"code\":1,\"date\":\"2023-03-17 21:27:01\",\"doi\":\"10.21203/rs.3.rs-2656091/v1\",\"editorialEvents\":[{\"type\":\"communityComments\",\"content\":0},{\"type\":\"decision\",\"content\":\"Major revision\",\"date\":\"2023-03-20T13:10:21+00:00\",\"index\":\"\",\"fulltext\":\"\"},{\"type\":\"editorInvitedReview\",\"content\":\"\",\"date\":\"2023-03-19T04:50:18+00:00\",\"index\":\"hide\",\"fulltext\":\"\"},{\"type\":\"reviewerAgreed\",\"content\":\"1efc619d-0a4f-455e-9fdd-bdb29ad50417\",\"date\":\"2023-03-14T14:02:43+00:00\",\"index\":\"hide\",\"fulltext\":\"\"},{\"type\":\"reviewersInvited\",\"content\":\"\",\"date\":\"2023-03-14T13:51:09+00:00\",\"index\":\"\",\"fulltext\":\"\"},{\"type\":\"editorAssigned\",\"content\":\"\",\"date\":\"2023-03-14T12:19:08+00:00\",\"index\":\"\",\"fulltext\":\"\"},{\"type\":\"editorInvited\",\"content\":\"\",\"date\":\"2023-03-14T10:10:14+00:00\",\"index\":\"\",\"fulltext\":\"\"},{\"type\":\"checksComplete\",\"content\":\"\",\"date\":\"2023-03-14T10:07:35+00:00\",\"index\":\"\",\"fulltext\":\"\"},{\"type\":\"submitted\",\"content\":\"BMC Psychiatry\",\"date\":\"2023-03-05T01:17:14+00:00\",\"index\":\"\",\"fulltext\":\"\"}],\"status\":\"published\",\"journal\":{\"display\":true,\"email\":\"info@researchsquare.com\",\"identity\":\"bmc-psychiatry\",\"isNatureJournal\":false,\"hasQc\":true,\"allowDirectSubmit\":false,\"externalIdentity\":\"bpsy\",\"sideBox\":\"Learn more about [BMC Psychiatry](http://bmcpsychiatry.biomedcentral.com/)\",\"snPcode\":\"\",\"submissionUrl\":\"https://www.editorialmanager.com/bpsy/default.aspx\",\"title\":\"BMC Psychiatry\",\"twitterHandle\":\"@BMC_series\",\"acdcEnabled\":true,\"dfaEnabled\":false,\"editorialSystem\":\"em\",\"reportingPortfolio\":\"BMC Series\",\"inReviewEnabled\":true,\"inReviewRevisionsEnabled\":true}}],\"origin\":\"\",\"ownerIdentity\":\"54723575-421d-4655-a21a-4f0f73fa08e8\",\"owner\":[],\"postedDate\":\"March 17th, 2023\",\"published\":true,\"recentEditorialEvents\":[],\"rejectedJournal\":[],\"revision\":\"\",\"amendment\":\"\",\"status\":\"published-in-journal\",\"subjectAreas\":[],\"tags\":[],\"updatedAt\":\"2023-10-16T20:58:33+00:00\",\"versionOfRecord\":{\"articleIdentity\":\"rs-2656091\",\"link\":\"https://doi.org/10.1186/s12888-023-04754-4\",\"journal\":{\"identity\":\"bmc-psychiatry\",\"isVorOnly\":false,\"title\":\"BMC Psychiatry\"},\"publishedOn\":\"2023-05-09 20:47:00\",\"publishedOnDateReadable\":\"May 9th, 2023\"},\"versionCreatedAt\":\"2023-03-17 21:27:01\",\"video\":\"\",\"vorDoi\":\"10.1186/s12888-023-04754-4\",\"vorDoiUrl\":\"https://doi.org/10.1186/s12888-023-04754-4\",\"workflowStages\":[]},\"version\":\"v1\",\"identity\":\"rs-2656091\",\"journalConfig\":\"researchsquare\"},\"__N_SSP\":true},\"page\":\"/article/[identity]/[[...version]]\",\"query\":{\"redirect\":\"/article/rs-2656091\",\"identity\":\"rs-2656091\",\"version\":[\"v1\"]},\"buildId\":\"FbvkV6FR0MCFSLy54lSbu\",\"isFallback\":false,\"isExperimentalCompile\":false,\"dynamicIds\":[84888],\"gssp\":true,\"scriptLoader\":[]}","source_license":"CC-BY-4.0","license_restricted":false}