Abstract
Aims
The factors associated with suicidal ideation among adolescents have been extensively characterised, but the mechanisms underlying the complexities of the relationship between experiences of childhood trauma and suicidal ideation have been less studied. This study examined the direct effect of childhood trauma on suicidal ideation on the one hand and whether school bullying victimisation and Internet addiction mediate the association between childhood trauma and suicidal ideation on the other hand.
Methods
This school-based mental health survey was carried out in Qinghai Province in Northwest China in December 2019. We employed standardised questionnaires to collect sociodemographic and target mental health outcomes. Hierarchical multiple logistic regression and structural equation modelling were performed for the data analyses.
Results
This study included 5864 university students. The prevalence of lifetime suicidal ideation and Internet addiction were 34.7% and 21.4%, respectively. Overall, 16.4% and 11.4% of participants reported experiences of childhood trauma and school bullying victimisation, respectively. There were direct effects of childhood trauma, school bullying victimisation and Internet addiction on suicidal ideation. The total effect of childhood trauma on suicidal ideation was 0.201 (p < 0.001). School bullying victimisation and Internet addiction mediated the relationship between childhood trauma and suicidal ideation. Internet addiction played a mediating role between school bullying and suicidal ideation.
Conclusions
Childhood trauma had both direct and indirect effects on suicidal ideation; these effects were mediated by school bullying victimisation and Internet addiction in Chinese university students. Elucidating these relationships will therefore be useful in developing and implementing more targeted interventions and strategies to improve the mental well-being of Chinese university students.
Key words: Childhood trauma, China, Internet addiction, suicidal ideation, school bullying victimisation, university students
Introduction
Suicide occurs across the lifespan and is the second-leading cause of death among 15- to 29-year-olds worldwide (World Health Organization (WHO), 2016). Suicide-related issues among Chinese children and adolescents are repeatedly emphasised (Chen et al., 2018; Guo et al., 2018), such as suicidal ideation which is a significant risk factor for suicidal attempts and death (Barzilay et al., 2017; Kwok et al., 2019). The existing body of research has demonstrated that the prevalence of suicidal ideation among Chinese college students ranges from 1.24% to 26.00% (Li et al., 2014). Socioeconomic adversity, adverse childhood events, bullying victimisation, substance abuse and psychological problems are identifiable predictors that contribute to the development of adolescent suicidal ideation (Barzilay et al., 2017; Tang et al., 2018; Kwok et al., 2019; Kim and Chun, 2020; Wang et al., 2020).
Childhood trauma has been established as the principal predictor of lifetime DSM-IV disorders (Kessler et al., 2010; Kircaburun et al., 2019), and evidence has successively suggested that the likelihood of suicidal ideation among students increased as the probability of childhood trauma experienced increased (Jeon et al., 2009; Clements-Nolle et al., 2018). For instance, a longitudinal study in the USA found that the accumulation of adverse childhood experiences increased the odds of suicidal ideation in adulthood (Thompson et al., 2019). The mechanisms regarding the complexities of the relationship between experiences of childhood trauma and suicidal ideation draw increasing research attention.
In addition, whether an offender or a victim, youth who experienced bullying had more suicidal ideations than those who had not experienced such patterns of peer aggression (Hinduja and Patchin, 2010). One Chinese study with a sample of 4034 university students also revealed an association between bullying experiences during primary and secondary school and a higher risk of suicidal ideation in young adulthood (Wang et al., 2020). Internet addiction among university students became a matter of concern along with the dramatically increased Internet use. It is undeniable that the Internet benefits users to some extent, while it produces several maladaptive and detrimental consequences, such as poor quality of life and suicidal ideation (Guo et al., 2018; Lu et al., 2018). The mitigation of school bullying requires a dedicated team of families, educators, health-care professionals and policymakers (Srabstein and Leventhal, 2010; Shayo and Lawala, 2019); these individuals are also critical in helping youth affected by Internet addiction.
The mediating effects of several factors in the relationship between childhood trauma and suicidal ideation were determined, such as gratitude and interpersonal difficulties in the form of social inhibition, emotion dysregulation, negative schema and rumination (Cui et al., 2019; Kwok et al., 2019; Lemaigre and Taylor, 2019). This leads us to suspect that Internet addiction and school bullying could be mediating factors of interest between experiences of childhood trauma and suicidal ideation. Evidence surrounding the mediating roles of school bullying and Internet addiction in the relationship between childhood trauma and suicide ideation has not yet been probed, specifically at the university student level, which thus requires further clarification. Furthermore, examining the previously described speculation will help disentangle the underlying relationships and yield beneficial information for targeting prevention efforts.
Therefore, the primary objective of the present study is to describe the prevalence of childhood trauma, suicidal ideation, school bullying victimisation and Internet addiction in a population-based sample of Chinese university students in Qinghai-Tibetan areas. A secondary objective is to investigate the degree to which the direct association between childhood trauma and suicidal ideation is valid and to examine the mediating roles of school bullying victimisation and Internet addiction in the relationship between childhood trauma and suicidal ideation using structural equation modelling. Building upon previous research, we hypothesised that childhood trauma would be directly and indirectly related to suicidal ideation via school bullying victimisation and Internet addiction.
Methods
Study design and data collection
This large-scale school-based mental health survey was carried out in Qinghai Province in Northwest China in December 2019. A multistage-stratified cluster sampling method was used to recruit the participants. There are 12 universities or colleges in Qinghai Province. First, a stratified sampling method was used to select universities by taking the affiliation levels and classifications of the universities as the indicators. A total of four universities were selected, including Qinghai University (one of the national ‘211 Project’ universities), Qinghai Nationalities University (a provincial-level ethnic undergraduate university), Qinghai Institute Of Health Sciences (a provincial-level industry supervisor undergraduate college) and Xining Urban Vocational & Technical College (a municipal vocational college). In each university or college, a stratified (according to the majors) random sampling method was used to select the classes, and cluster sampling was then used in each class.
Questionnaires were distributed to participants and collected after completion by our study investigators who were uniformly trained prior to the on-site survey. Students who were fully enrolled in the universities were included. A total of 6500 questionnaires were distributed, and 6200 questionnaires were returned, yielding a response rate of 95.4%. Students from Qinghai University, Qinghai Nationalities University, Qinghai Institute Of Health Sciences and Xining Urban Vocational & Technical College accounted for 30.0%, 27.5%, 26.9% and 15.7% of the sample, respectively. Finally, data from 5864 participants were analysed in this study after cases with ⩾ 20% missing data were deleted.
The Ethics Committee of the Medical College of Qinghai University approved the study protocol. The survey process followed the principles of anonymity and voluntariness, and all university students involved in this survey provided the informed consent. We followed the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines to report this study (Von Elm et al., 2007).
Assessment
Basic characteristics
Basic sociodemographic and clinical information, including age (years), sex (male/female), place of residence prior to entering the university (non-plateau/plateau area), ethnicity (Han/others), self-perceived family economic level (rich/general/poor), only-child status (no/yes), self-perceived weight (underweight/normal/overweight), self-perceived health (good/general/bad), whether in a dating relationship (no/yes) and relationships with classmates, teachers and family (poor/fair/good), was collected.
Suicidal ideation
Suicidal ideation (SI) was assessed using the fourth and fifth items of the Beck Scale for Suicidal Ideation (BSS) (Beck et al., 1979), which is widely used as a self-report screening tool (Brown et al., 2000; van Spijker et al., 2010). Lifetime SI was considered if there was at least one positive response to the questions.
Childhood trauma
Childhood trauma was assessed by the following question, ‘Have you suffered severe psychological trauma or significant life adversity before the age of 16?’ Possible answers were no or yes.
Mediating variables
The Internet Addiction Test (IAT), which has satisfactory psychometric properties (Cronbach's α: 0.713) (Young, 1998, 2008), has been widely validated among countries (Lam et al., 2009; Young, 2013), and its Chinese version was used to examine the presence and severity of IA in our study. A total score of ⩾ 50 indicated moderate and severe dependence on the Internet and was defined as ‘having IA’ (Young, 2008), which has been used in previous studies (Yoo et al., 2004; Karacic and Oreskovic, 2017; Lu et al., 2018). School bullying victimisation was assessed by a ‘yes/no’ question: ‘In the past year, have you been bullied or threatened by others at school (for example, other students tease you on purpose or give you nicknames that you do not like; classmates have deliberately left you out during class breaks or upset you; you have been beaten by others; other students have urged you to do something for them even if you do not want to, etc.)?’
Data analyses
The sociodemographic and clinical characteristics were described with the number (n) and percentage (%) or the mean and standard deviation (s.d.), as appropriate. Hierarchical multiple logistic regression was carried out to examine the associations between experiences of childhood trauma and suicidal ideation. In step 1, the model was unadjusted by setting suicidal ideation as the dependent variable and childhood trauma as the independent variable. In step 2, adjustments were made for age (years), sex, place of residence prior to entering university, ethnicity, self-perceived family economic level, only-child status, self-perceived weight, self-perceived health status, whether in a dating relationship, relationships with classmates, relationships with teachers or relationships with family. In step 3, school bullying victimisation was added, and Internet addiction was added in the last step. At each step, the R2 change (ΔR2) was used to indicate the predictive power of each group of predictor(s) when adjustments were made for previous predictor(s). A post hoc analysis was performed by reversing steps 3 and 4. The results were expressed with odds ratios (ORs) and their 95% confidence intervals (CIs).
We performed a structural equation model (SEM) to evaluate the hypothesis of the mediating effects of Internet addiction and school bullying victimisation in the relationship between childhood trauma and suicide ideation. Sociodemographic and clinical characteristics that showed statistical significance in step 4 in hierarchical multiple logistic regression were adjusted in the SEM. We used the R lavaan package (Rosseel, 2012), and a comparative fit index (CFI) ⩾ 0.90, a Tucker–Lewis index (TLI) ⩾ 0.95, a root mean square error of approximation (RMSEA) < 0.08 and a standardised root mean square residual (SRMR) < 0.08 indicate satisfactory goodness of fit (Hooper et al., 2008; Kline, 2015). In all models, only those cases without missing data were analysed. All data were analysed with RStudio software (Version 1.2.1335, ©2009–2019 RStudio, Inc.), with a significant α threshold of 0.05 (two tailed) .
Results
Sample characteristics
A total of 5864 university students with an average age of 19.9 years (s.d. = 1.52) were included in this study. Among the participants, 62.4% were (3657) female, 44.8% (2629) were of Han ethnicity and 79.4% (4656) lived in high-altitude areas prior to entering the university. Table 1 shows the basic characteristics of the participants.
Table 1.
Basic characteristics of the participants
Variables | Categories | SI (n = 2037) | Overall (n = 5864) |
---|---|---|---|
Age years (mean ± s.d.) | 19.8 ± 1.53 | 19.9 ± 1.52 | |
Sex (N = 5750) | Female | 1374 (67.5%) | 3657 (62.4%) |
Male | 631 (31.0%) | 2093 (35.7%) | |
Place of residence prior to entering the university (N = 5659) | Non plateau | 343 (16.8%) | 1003 (17.1%) |
Plateau | 1626 (79.8%) | 4656 (79.4%) | |
Ethnicity (N = 5795) | Han | 997 (48.9%) | 2629 (44.8%) |
Other | 1019 (50.0%) | 3166 (54.0%) | |
Family economy (N = 5844) | Rich | 106 (5.2%) | 352 (6.0%) |
General | 1512 (74.2%) | 4449 (75.9%) | |
Poor | 413 (20.3%) | 1043 (17.8%) | |
Only-child status (N = 5536) | No | 1487 (73.0%) | 4350 (74.2%) |
Yes | 444 (21.8%) | 1186 (20.2%) | |
Self-perceived weight (N = 5849) | Underweight | 264 (13.0%) | 751 (12.8%) |
Normal | 1110 (54.5%) | 3535 (60.3%) | |
Overweight | 660 (32.4%) | 1563 (26.7%) | |
Self-perceived health (N = 5848) | Good | 640 (31.4%) | 2692 (45.9%) |
General | 1265 (62.1%) | 2954 (50.4%) | |
Bad | 126 (6.2%) | 202 (3.4%) | |
Whether in a dating relationship (N = 5811) | No | 1334 (65.5%) | 3742 (63.8%) |
Yes | 687 (33.7%) | 2069 (35.3%) | |
Relationship with classmates (N = 5856) | Good | 757 (37.2%) | 2807 (47.9%) |
General | 1224 (60.1%) | 2962 (50.5%) | |
Poor | 53 (2.6%) | 87 (1.5%) | |
Relationship with teachers (N = 5852) | Good | 552 (27.1%) | 2183 (37.2%) |
General | 1405 (69.0%) | 3533 (60.2%) | |
Poor | 78 (3.8%) | 136 (2.3%) | |
Relationship with family (N = 5828) | Good | 1569 (77.0%) | 5055 (86.2%) |
General | 421 (20.7%) | 716 (12.2%) | |
Poor | 33 (1.6%) | 57 (1.0%) | |
School bullying victimisation (N = 5832) | No | 1699 (83.4%) | 5170 (88.2%) |
Yes | 320 (15.7%) | 662 (11.3%) | |
Internet addiction (N = 5757) | No | 1393 (68.4%) | 4624 (78.9%) |
Yes | 640 (31.4%) | 1233 (21.0%) | |
Experiences of childhood trauma (N = 5718) | No | 1459 (71.6%) | 4782 (81.5%) |
Yes | 526 (25.8%) | 936 (16.0%) |
The prevalence of lifetime suicidal ideation and Internet addiction were 34.7% (2037/5864; 95% CI 33.5–36.0%) and 21.4% (1233/5757; 95% CI 20.4–22.5%), respectively. Overall, 16.4% (936/5718; 95% CI 15.4–17.4%) and 11.4% (662/5832; 95% CI 10.5–12.2%) of university students reported experiences of childhood trauma and school bullying, respectively.
Hierarchical regression analyses
Table 2 displays the results of hierarchical regression analyses. In total, basic sociodemographic and clinical indicators accounted for 14.8% of the variance in the outcomes beyond the effects of experiences of childhood trauma (step 2) (adjusted R2 = 0.201, ΔR2 = 0.148). School bullying victimisation, tested in step 3, captured an additional 0.8% of variance in suicidal ideation beyond the effects of basic sociodemographic and clinical factors and the experiences of childhood trauma (adjusted R2 = 0.209, ΔR2 = 0.008). When Internet addiction was added in the last step, it yielded an additional 0.8% of the variance (adjusted R2 = 0.217, ΔR2 = 0.008, p < 0.001), showing that experiences of childhood trauma (OR = 2.13, 95% CI 1.80–2.52), Internet addiction (OR = 1.87, 95% CI 1.61–2.17) and school bullying victimisation (OR = 1.58, 95% CI 1.29–1.92) were positively associated with suicidal ideation. When we reversed the order of entry in the regression model, entering Internet addiction in the third step, school bullying victimisation predicted suicide ideation over and above Internet addiction in the fourth step (ΔR2 = 0.005, p < 0.001).
Table 2.
Results of hierarchical regression analyses in Chinese university students
Variables | Step 1 | Step 2 | Step 3 | Step 4 |
---|---|---|---|---|
Age years | 0.91 (0.87–0.94)*** | 0.90 (0.87–0.94)*** | 0.90 (0.87–0.94)*** | |
Sex (male) | 0.75 (0.65–0.86)*** | 0.74 (0.65–0.85)*** | 0.73 (0.63–0.84)*** | |
Place of residence prior to entering the university (plateau) | 1.13 (0.96–1.34) | 1.14 (0.97–1.35) | 1.16 (0.98–1.38) | |
Ethnicity (other) | 0.91 (0.80–1.04) | 0.91 (0.80–1.04) | 0.89 (0.78–1.01) | |
Family economy | ||||
Rich | 0.71 (0.52–0.96)* | 0.72 (0.53–0.97)* | 0.72 (0.53–0.97)* | |
Poor | 1.05 (0.89–1.23) | 1.05 (0.89–1.23) | 1.03 (0.88–1.22) | |
Only-child status (yes) | 1.05 (0.90–1.23) | 1.05 (0.90–1.23) | 1.07 (0.91–1.24) | |
Self-perceived weight | ||||
Underweight | 1.08 (0.88–1.31) | 1.06 (0.87–1.29) | 1.04 (0.85–1.27) | |
Overweight | 1.26 (1.09–1.45)** | 1.24 (1.08–1.43)** | 1.19 (1.03–1.38)* | |
Self-perceived health | ||||
General | 0.50 (0.36–0.69)*** | 0.51 (0.36–0.71)*** | 0.53 (0.38–0.73)*** | |
Good | 0.26 (0.19–0.36)*** | 0.27 (0.19–0.37)*** | 0.28 (0.20–0.39)*** | |
Whether in a dating relationship (yes) | 0.87 (0.76–0.99)* | 0.86 (0.76–0.99)* | 0.87 (0.76–0.99)* | |
Relationship with classmates | ||||
General | 0.75 (0.44–1.25) | 0.78 (0.46–1.31) | 0.83 (0.49–1.41) | |
Good | 0.59 (0.35–0.99)* | 0.63 (0.38–1.06) | 0.69 (0.40–1.18) | |
Relationship with teachers | ||||
General | 0.77 (0.50–1.18) | 0.77 (0.51–1.19) | 0.84 (0.55–1.30) | |
Good | 0.61 (0.39–0.95)* | 0.61 (0.39–0.96)* | 0.69 (0.44–1.08) | |
Relationship with family | ||||
General | 1.55 (0.81–2.96) | 1.63 (0.84–3.17) | 1.60 (0.82–3.13) | |
Good | 0.72 (0.38–1.36) | 0.76 (0.40–1.46) | 0.76 (0.39–1.47) | |
School bullying victimisation (yes) | 1.72 (1.42–2.10)*** | 1.58 (1.29–1.92)*** | ||
Internet addiction (yes) | 1.87 (1.61–2.17)*** | |||
Experiences of childhood trauma (yes) | 2.91 (2.53–3.37)*** | 2.25 (1.91–2.66)*** | 2.17 (1.83–2.56)*** | 2.13 (1.80–2.52)*** |
Adjusted R2 | 0.053 | 0.201 | 0.209 | 0.217 |
ΔR2 | 0.148 | 0.008 | 0.008 |
Step 1 (N = 5637): unadjusted.
Step 2 (N = 5040): adjusted for age years, sex, place of residence prior to entering the university, ethnicity, self-perceived family economic level, only-child status, self-perceived weight, self-perceived health status, whether in a dating relationship, relationship with classmates, relationship with teachers, relationship with family.
Step 3 (N = 5017): Model 2 variables + school bullying victimisation.
Step 4 (N = 5017): Model 3 variables + Internet addiction.
*p < 0.05, **p < 0.01, ***p < 0.001 (two-tailed).
Structural equation modelling
Figure 1 shows the results of structural equation modelling. There were direct effects of childhood trauma (β = 0.160, p < 0.001), school bullying victimisation (β = 0.129, p < 0.001) and Internet addiction (β = 0.198, p < 0.001) on suicidal ideation. The total effect of childhood trauma on suicidal ideation was 0.201 (p < 0.001). The final SEM also revealed the mediating effects of school bullying victimisation and Internet addiction on the association between childhood trauma and suicidal ideation (β = 0.018, p < 0.001 and β = 0.015, p < 0.001, respectively). School bullying victimisation also had an indirect effect on suicidal ideation which was mediated by Internet addiction (β = 0.052, p < 0.001). Goodness-of-fit indices (i.e. CFI = 1.000; TLI = 1.000; RMSEA = 0; SRMR = 0.006) indicated satisfactory fit of the SEM.
Fig. 1.
Final model with the standardised coefficients (β), and unstandardised coefficients (β) presented in the parentheses (N = 5420). ***p < 0.001. CFI = 1.000; TLI = 1.000; RMSEA = 0; SRMR = 0.006.
Discussion
This study, based on a sample of 5864 university students from parts of the Chinese Tibetan Plateau (i.e. Qinghai Province), allowed us to identify the following: (1) our mental health problems of interest were common among Chinese university students; (2) childhood trauma, school bullying victimisation and Internet addiction had associations with suicidal ideation among the population of interest; (3) there were indirect effects of childhood trauma on suicidal ideation, which were mediated by school bullying victimisation and Internet addiction; and (4) Internet addiction played a mediating role in the relationship between school bullying victimisation and suicidal ideation.
At present, suicidal ideation among adolescents is widely concerned around the world (Mortier et al., 2018). The lifetime prevalence of suicidal ideation among our participants (34.7%; 95% CI 33.5–36.0%) was approximately 1.5 times that of the worldwide prevalence among college students (22.3%, 95% CI 19.5–25.3%) estimated in one meta-analysis (Mortier et al., 2018). Our figure was also greater than those presented in other Chinese surveys in the same targeted population, such as 7.3% in a study of 5972 university students from Wuhan, Hubei Province (Tang et al., 2018) and 9.9% in a study of 4034 university students from Anhui Province (Wang et al., 2020). These discrepancies may be partially attributed to the different assessment instruments used as well as the evaluated durations of suicidal ideation, for example, the other two Chinese studies assessed the prevalence in the last 12 and 6 months, respectively, while we evaluated the lifetime prevalence. In addition, sociodemographic differences (Nock et al., 2008) and disparities in college-specific factors (Eisenberg et al., 2013) may simultaneously play potential roles.
After adjustments were made for the control variables, hierarchical regression models indicated that childhood trauma, school bullying victimisation and Internet addiction increased the likelihood of having suicidal ideation. We thus conducted SEM by adjusting for sociodemographic factors, personal health factors and dating status, and we identified the direct effect as well as the indirect effect of childhood trauma on suicidal ideation, the latter of which was mediated by school bullying victimisation. Consistently, the direct effect of childhood trauma on suicidal ideation was demonstrated in another Chinese study including 922 freshmen (Shi et al., 2020). A moderately significant degree of correlation between suicidal ideation and exposure to early trauma was also identified among Indian college students (Singh et al., 2012). In terms of the role of school bullying victimisation, the strong relationship between adverse childhood experiences and the probability of on-campus victimisation was identified among high school students (Forster et al., 2020), and the latter can independently predict the likelihood of suicidal ideation among school adolescents (Barzilay et al., 2017; Wang et al., 2018; Shayo and Lawala, 2019), which can support our finding.
Internet addiction also played a mediating role in the relationship between childhood trauma and suicidal ideation. Childhood trauma and its subtypes, such as emotional, physical and sexual abuse, were reported as factors associated with Internet addiction or Internet gaming disorders in different populations (Dalbudak et al., 2014; Schimmenti et al., 2014; Kircaburun et al., 2019; Shi et al., 2020). Internet use could be a more popular coping strategy to avoid concentrating on experiences of trauma or bullying and stressful life events or to elevate mood (Park et al., 2013; Shi et al., 2020). For example, students with childhood traumatic experiences or being bullied would prefer to share their experiences and obtain comfort through communicating with netizens from social networking platforms instead of the familiar individuals in the real world, especially those with borderline personality features (Dalbudak et al., 2014), lower social support (Karaer and Akdemir, 2019) or increased loneliness (AJ et al., 2014), etc., which also explained the relationship between school bullying and Internet addiction. Furthermore, in line with our results, one survey in China (Guo et al., 2018) and another in South Korea (Park et al., 2013) with 20 895 and 795 high school students, respectively, both suggested the direct effects of Internet addiction on suicidal ideation. Mobile phones are one of the major modes of access to the Internet, and adolescents' dependence on their phones is also a predictor of suicidal ideation (Chen et al., 2020). Consequently, childhood trauma can be indirectly linked with suicidal ideation through Internet addiction. However, only a few relevant studies concerning the above findings that were available and focused on university students, and our study extended this literature.
The findings underscore the importance and necessity of implementing suicide intervention strategies and preventing adverse childhood events and invisible or visible on-campus bullying and Internet addiction. Professional levels of psychological counselling and guidance, mental health education courses, campus safety management and other interventions should be considered and practically implemented (Jimerson and Furlong, 2006; Chen et al., 2018; Strom et al., 2018). However, there were several limitations that should be noted. First, the cross-sectional nature of our study makes it impossible to capture the causality, and future research might benefit from longitudinal studies. Second, the potential recall bias cannot be avoided which could produce the potential estimation errors. Additionally, the mental health outcomes of interest were assessed using self-reported screening questionnaires or questions rather than clinical diagnostics, which could be less helpful in clinical significance. However, our results have still provided evidence from epidemiological and screening perspectives. Finally, the target population volunteered to participate in this survey, and approximately two out of every three participants in our sample were female university students. Therefore, the study results may not be generalisable to all Chinese university students.
In conclusion, this study extended the findings of previous literature by elucidating the direct effects of childhood trauma, school bullying victimisation and Internet addiction on suicidal ideation among university students, as well as the mediating roles of school bullying victimisation and Internet addiction in the relationship between childhood trauma and suicidal ideation. Integrally targeted interventions and strategies that can eliminate and alleviate school bullying events, Internet addiction and the influences of childhood trauma should be developed and implemented to reduce the risk of suicidal ideation and improve the comprehensive mental well-being of Chinese university students.
Acknowledgements
We thank all the students who participated in this survey and the research investigators for their great help on the data collection.
Financial support
The study was supported by the National Natural Science Foundation of China (81860606), the Natural Science Foundation of Qinghai Province (2019-ZJ-906) and the Qinghai Province Government on the Plan of Thousands of High Level of Innovative Talents.
Ethical standards
The Ethics Committee of Medical College of Qinghai University approved the study.
Data
For more information, email to liushou2004@aliyun.com.
Conflict of interest
None.
References
- AJ VANR, Kuss DJ, Griffiths MD, Shorter GW, Schoenmakers MT and Van De Mheen D (2014) The (co-)occurrence of problematic video gaming, substance use, and psychosocial problems in adolescents. Journal of Behavioral Addictions 3,157–165. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Barzilay S, Brunstein Klomek A, Apter A, Carli V, Wasserman C, Hadlaczky G, Hoven CW, Sarchiapone M, Balazs J, Kereszteny A, Brunner R, Kaess M, Bobes J, Saiz P, Cosman D, Haring C, Banzer R, Corcoran P, Kahn JP, Postuvan V, Podlogar T, Sisask M, Varnik A and Wasserman D (2017) Bullying victimization and suicide ideation and behavior among adolescents in Europe: a 10-country study. Journal of Adolescent Health 61, 179–186. [DOI] [PubMed] [Google Scholar]
- Beck AT, Kovacs M and Weissman A (1979) Assessment of suicidal intention: the Scale for Suicide Ideation. Journal of Consulting and Clinical Psychology 47, 343–352. [DOI] [PubMed] [Google Scholar]
- Brown GK, Beck AT, Steer RA and Grisham JR (2000) Risk factors for suicide in psychiatric outpatients: a 20-year prospective study. Journal of Consulting and Clinical Psychology 68, 371–377. [PubMed] [Google Scholar]
- Chen R, An J and Ou J (2018) Suicidal behaviour among children and adolescents in China. The Lancet Child & Adolescent Health 2, 551–553. [DOI] [PubMed] [Google Scholar]
- Chen RS, Liu JB, Cao XL, Duan SQ, Wen SY, Zhang SM, Xu JC, Lin L, Xue ZP and Lu JP (2020) The relationship between mobile phone use and suicide-related behaviors among adolescents: the mediating role of depression and interpersonal problems. Journal of Affective Disorders 269, 101–107. [DOI] [PubMed] [Google Scholar]
- Clements-Nolle K, Lensch T, Baxa A, Gay C, Larson S and Yang W (2018) Sexual identity, adverse childhood experiences, and suicidal behaviors. Journal of Adolescent Health 62, 198–204. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Cui Y, Kim SW, Lee BJ, Kim JJ, Yu JC, Lee KY, Won S, Lee SH, Kim SH, Kang SH, Kim E, Piao YH, Kang NI and Chung YC (2019) Negative schema and rumination as mediators of the relationship between childhood trauma and recent suicidal ideation in patients with early psychosis. Journal of Clinical Psychiatry 80, 17m12088. [DOI] [PubMed] [Google Scholar]
- Dalbudak E, Evren C, Aldemir S and Evren B (2014) The severity of Internet addiction risk and its relationship with the severity of borderline personality features, childhood traumas, dissociative experiences, depression and anxiety symptoms among Turkish university students. Psychiatry Research 219, 577–582. [DOI] [PubMed] [Google Scholar]
- Eisenberg D, Hunt J and Speer N (2013) Mental health in American colleges and universities: variation across student subgroups and across campuses. The Journal of Nervous and Mental Disease 201, 60–67. [DOI] [PubMed] [Google Scholar]
- Forster M, Gower AL, McMorris BJ and Borowsky IW (2020) Adverse childhood experiences and school-based victimization and perpetration. Journal of Interpersonal Violence 35, 662–681. [DOI] [PubMed] [Google Scholar]
- Guo L, Luo M, Wang WX, Huang GL, Xu Y, Gao X, Lu CY and Zhang WH (2018) Association between problematic Internet use, sleep disturbance, and suicidal behavior in Chinese adolescents. Journal of Behavioral Addictions 7, 965–975. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Hinduja S and Patchin JW (2010) Bullying, cyberbullying, and suicide. Archives of Suicide Research 14, 206–221. [DOI] [PubMed] [Google Scholar]
- Hooper D, Coughlan J and Mullen MR (2008) Structural equation modelling: guidelines for determining model fit. Electronic Journal of Business Research Methods 6, 53–60. [Google Scholar]
- Jeon HJ, Roh MS, Kim KH, Lee JR, Lee D, Yoon SC and Hahm BJ (2009) Early trauma and lifetime suicidal behavior in a nationwide sample of Korean medical students. Journal of Affective Disorders 119, 210–214. [DOI] [PubMed] [Google Scholar]
- Jimerson SR and Furlong MJ (Eds.) (2006) The handbook of school violence and school safety: From research to practice. Lawrence Erlbaum Associates Publishers. [Google Scholar]
- Karacic S and Oreskovic S (2017) Internet addiction and mental health status of adolescents in Croatia and Germany. Psychiatria Danubina 29, 313–321. [DOI] [PubMed] [Google Scholar]
- Karaer Y and Akdemir D (2019) Parenting styles, perceived social support and emotion regulation in adolescents with internet addiction. Comprehensive Psychiatry 92, 22–27. [DOI] [PubMed] [Google Scholar]
- Kessler RC, McLaughlin KA, Green JG, Gruber MJ, Sampson NA, Zaslavsky AM, Aguilar-Gaxiola S, Alhamzawi AO, Alonso J, Angermeyer M, Benjet C, Bromet E, Chatterji S, de Girolamo G, Demyttenaere K, Fayyad J, Florescu S, Gal G, Gureje O, Haro JM, Hu CY, Karam EG, Kawakami N, Lee S, Lepine JP, Ormel J, Posada-Villa J, Sagar R, Tsang A, Ustun TB, Vassilev S, Viana MC and Williams DR (2010) Childhood adversities and adult psychopathology in the WHO World Mental Health Surveys. British Journal of Psychiatry 197, 378–385. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Kim HH and Chun J (2020) Bullying victimization, school environment, and suicide ideation and plan: focusing on youth in low- and middle-income countries. Journal of Adolescent Health 66, 115–122. [DOI] [PubMed] [Google Scholar]
- Kircaburun K, Griffiths MD and Billieux J (2019) Psychosocial factors mediating the relationship between childhood emotional trauma and internet gaming disorder: a pilot study. European Journal of Psychotraumatology 10, 1565031. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Kline RB (2015). Principles and Practice of Structural Equation Modeling. New York: Guilford Publications. [Google Scholar]
- Kwok S, Gu M and Cheung A (2019) A longitudinal study on the relationship among childhood emotional abuse, gratitude, and suicidal ideation of Chinese adolescents. Child Abuse & Neglect 94, 104031. [DOI] [PubMed] [Google Scholar]
- Lam LT, Peng ZW, Mai JC and Jing J (2009) Factors associated with Internet addiction among adolescents. CyberPsychology & Behavior 12, 551–555. [DOI] [PubMed] [Google Scholar]
- Lemaigre C and Taylor EP (2019) Mediators of childhood trauma and suicidality in a cohort of socio-economically deprived Scottish men. Child Abuse & Neglect 88, 159–170. [DOI] [PubMed] [Google Scholar]
- Li ZZ, Li YM, Lei XY, Zhang D, Liu L, Tang SY and Chen L (2014) Prevalence of suicidal ideation in Chinese college students: a meta-analysis. PLoS ONE 9, e104368. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Lu L, Xu DD, Liu HZ, Zhang L, Ng CH, Ungvari GS, An FR and Xiang YT (2018) Internet addiction in Tibetan and Han Chinese middle school students: prevalence, demographics and quality of life. Psychiatry Research 268, 131–136. [DOI] [PubMed] [Google Scholar]
- Mortier P, Cuijpers P, Kiekens G, Auerbach RP, Demyttenaere K, Green JG, Kessler RC, Nock MK and Bruffaerts R (2018) The prevalence of suicidal thoughts and behaviours among college students: a meta-analysis. Psychological Medicine 48, 554–565. [DOI] [PubMed] [Google Scholar]
- Nock MK, Borges G, Bromet EJ, Alonso J, Angermeyer M, Beautrais A, Bruffaerts R, Chiu WT, de Girolamo G, Gluzman S, de Graaf R, Gureje O, Haro JM, Huang Y, Karam E, Kessler RC, Lepine JP, Levinson D, Medina-Mora ME, Ono Y, Posada-Villa J and Williams D (2008) Cross-national prevalence and risk factors for suicidal ideation, plans and attempts. British Journal of Psychiatry 192, 98–105. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Park S, Hong KE, Park EJ, Ha KS and Yoo HJ (2013) The association between problematic internet use and depression, suicidal ideation and bipolar disorder symptoms in Korean adolescents. Australian and New Zealand Journal of Psychiatry 47, 153–159. [DOI] [PubMed] [Google Scholar]
- Rosseel Y (2012) Lavaan: an R package for structural equation modeling and more. Version 0.5–12 (BETA). Journal of Statistical Software 48, 1–36. [Google Scholar]
- Schimmenti A, Passanisi A, Gervasi AM, Manzella S and Fama FI (2014) Insecure attachment attitudes in the onset of problematic Internet use among late adolescents. Child Psychiatry & Human Development 45, 588–595. [DOI] [PubMed] [Google Scholar]
- Shayo FK and Lawala PS (2019) Does bullying predict suicidal behaviors among in-school adolescents? A cross-sectional finding from Tanzania as an example of a low-income country. BMC Psychiatry 19, 400. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Shi L, Wang Y, Yu H, Wilson A, Cook S, Duan Z, Peng K, Hu Z, Ou J, Duan S, Yang Y, Ge J, Wang H, Chen L, Zhao K and Chen R (2020) The relationship between childhood trauma and Internet gaming disorder among college students: a structural equation model. Journal of Behavioral Addictions 9, 175–180. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Singh S, Manjula M and Philip M (2012) Suicidal risk and childhood adversity: a study of Indian college students. Asian Journal of Psychiatry 5, 154–159. [DOI] [PubMed] [Google Scholar]
- Srabstein JC and Leventhal BL (2010) Prevention of bullying-related morbidity and mortality: a call for public health policies. SciELO Public Health. [DOI] [PMC free article] [PubMed]
- Strom IF, Aakvaag HF, Birkeland MS, Felix E and Thoresen S (2018) The mediating role of shame in the relationship between childhood bullying victimization and adult psychosocial adjustment. European Journal of Psychotraumatology 9, 1418570. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Tang F, Byrne M and Qin P (2018) Psychological distress and risk for suicidal behavior among university students in contemporary China. Journal of Affective Disorders 228, 101–108. [DOI] [PubMed] [Google Scholar]
- Thompson MP, Kingree JB and Lamis D (2019) Associations of adverse childhood experiences and suicidal behaviors in adulthood in a U.S. nationally representative sample. Child: Care, Health and Development 45, 121–128. [DOI] [PubMed] [Google Scholar]
- van Spijker BA, van Straten A and Kerkhof AJ (2010) The effectiveness of a web-based self-help intervention to reduce suicidal thoughts: a randomized controlled trial. Trials 11, 25. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Von Elm E, Altman DG, Egger M, Pocock SJ, Gotzsche PC, Vandenbroucke JP and Initiative S (2007) The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement: guidelines for reporting observational studies. Preventive Medicine 45, 247–251. [DOI] [PubMed] [Google Scholar]
- Wang H, Du H, Bragg F, Zhong J and Yu M (2018) Relationship of being threatened or injured with a weapon in school with suicidal ideation and attempt among school students: a school-based study in Zhejiang Province, China. BMC Public Health 18, 1405. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Wang GF, Han AZ, Zhang GB, Xu N, Xie GD, Chen LR, Yuan MY and Su PY (2020) Sensitive periods for the effect of bullying victimization on suicidal behaviors among university students in China: the roles of timing and chronicity. Journal of Affective Disorders 268, 12–19. [DOI] [PubMed] [Google Scholar]
- World Health Organization (WHO) (2016) Mental health. Suicide data. Available at https://www.who.int/mental_health/prevention/suicide/suicideprevent/en/ (Accessed 5 May 2020).
- Yoo HJ, Cho SC, Ha J, Yune SK, Kim SJ, Hwang J, Chung A, Sung YH and Lyoo IK (2004) Attention deficit hyperactivity symptoms and internet addiction. Psychiatry and Clinical Neurosciences 58, 487–494. [DOI] [PubMed] [Google Scholar]
- Young KS (1998) Internet addiction: the emergence of a new clinical disorder. CyberPsychology & Behavior 1, 237–244. [Google Scholar]
- Young KS (2008) The Internet Addiction Test. Center for On-Line Addictions. Bradford, PA. Available at http://www.netaddiction.com/resources/Internet_addiction_test.htm (Accessed 30 November 2008).
- Young KS (2013) Treatment outcomes using CBT-IA with Internet-addicted patients. Journal of Behavioral Addictions 2, 209–215. [DOI] [PMC free article] [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
For more information, email to liushou2004@aliyun.com.