The Impact of Internet use frequency on Non-suicidal self injurious behavior and Suicidal Ideation among Chinese Youth: An empirical study based on Gender perspective

Abstract

Background: We attempted to find if there were gender differences in Non-suicidal self injurious (NSSI) behaviors and Suicidal ideation among Chinese youth, then analyze the impact of internet use frequency on these variables among youth of different genders.

Methods: Based on the survey data from 6 high-schools and 4 universities in 4 cities in China, the gender difference in NSSI behaviors and Suicidal ideation and their related factors were analyzed in the study.

Results: There was no significant gender difference in NSSI behaviors among Chinese youth, yet females reported significantly higher intensity of suicidal ideation compared to males; internet use frequency could explain the prevalence of NSSI behaviors and Suicidal ideation by gender, to some categories.

Conclusions: The gender difference of NSSI engagement among Chinese youth was not statistically significant; while females had higher suicidal ideation than males; the overuse of social softwares was found to be a risk factor to both NSSI engagements and suicidal ideations for both genders; males would engage less NSSI behaviors when they spent more time on knowledge sharing softwares while might have more suicidal ideation when they spent too much time on gaming.

Background

Non-suicidal self-injury (NSSI) and suicidal ideation are major health concerns among youth worldwide [1–4]. Although suicidal ideation broadly refers to thoughts about dying or wanting to die as well as the formation of plans to die [5], NSSI is distinctive in that the intention is not to die. Specifically, NSSI refers to deliberate self-inflicted damage to one’ s own body tissue by methods such as cutting, scratching, and self-hitting that leads to tissue damage without conscious suicidal intent and for reasons not socially sanctioned [6]. In China, the problem of suicide and NSSI, especially among youth, is more severe compared to Western studies [3–4], yet much of the literature on life threatening behavior stems from research within Western populations [2, 7]. This has resulted in much of the present theory on life threatening behaviors as well as the clinical implications to be based on Western populations, which largely ignores the nuances found in other cultural contexts [8].

However, in one Chinese study, Fan & Zhang reported the suicide rate among women to be approximately 25.9% among 10000, whereas the rate among males were 30.14% [4]. The authors also reported that adolescent females within rural communities were found to be at greatest risk within China. According to the survey of Shanghai forensic workers, the suicide rate in Shanghai is 30.14% among 10000 for males and 45.16% among 10000 for females [9]. This is consistent with the conclusion of the study organized by the World Health Organization (WHO) which reported a higher rate of suicide attempts among women than men in China [9–11]. Furthermore, the results of suicidal ideation and attempted suicide behavior surveys published after the year 2000 in different cities of China show that the annual prevalence of suicidal ideation was between 13.2%-28.0%, and the prevalence of attempted suicide was between 1.2%-4.0% [12–15]. In addition, Gao surveyed 2,416 primary and middle school students in Shanghai and found that the prevalence of suicidal ideation was 15.23%, suicide plan was 5.84%, and attempted suicide was 1.74% [16]. Unlike most countries where the suicide rate of male youth is higher than that of females, the characteristics of suicidal behavior among Chinese youth were found to be somewhat different whereby the suicide rate is higher among females compared to males, and female adolescents report more suicide ideation than male adolescents [14–16].

Another study surveying nearly 1,000 university students in China revealed that 35.2% have engaged in NSSI behaviors in their lifetime [17], which is nearly double the prevalence rate among university students from the U.S. and Canada [18]. Furthermore, the prevalence of NSSI in China appears quite higher among adolescents, where research has found that 57.4% have engaged in NSSI behaviors [19]. This study also suggests a much higher rate of engagement in NSSI over the past year and an earlier age of onset relative to much of the research from Western contexts (17–19).

As such, there is an urgent need for further investigations aimed at better understanding suicidality and NSSI among Chinese youth, and the possible mechanisms that might contribute to both increased suicidality and greater endorsement of NSSI behaviors. Several studies have found excessive Internet use to be associated with both NSSI and suicidality among young people [20–24], however, the exact mechanism by which Internet use contributes to either NSSI or suicidality remains unclear.

A link between internet use frequency and NSSI/suicidal ideation among youth

Internet use is especially frequent and widespread among youth both in China and the United States, with about 80% of youth using the Internet regularly [25–26]. Adolescents are increasingly relying on the Internet as a primary mode of communication, whether for emails or for social softwares. One particular purpose may be for support from others through discussion forums or private messaging. A review of the Chinese instant messaging software QQ revealed that the popular online platform was hosting more than 600 groups pertaining to suicide and self-injury [27].

Notwithstanding the potential benefits of the Internet such as making communication more accessible, research has found the excessive reliance upon the Internet to be associated with psychological and physical harms (e.g., isolated, extreme and poor communication). For instance, several studies among Chinese middle school students who engaged in excessive internet use reported adverse physical consequences such as shoulder pain caused by prolonged poor posture when sitting, decreased visual perception loss of appetite, decreased sleep quality as well as decreases in immune function [28]. Students also reported psychological consequences including difficulties with self-control, more social avoidance and negative coping [29], increased levels of perceived emotional and social loneliness which lead to lose oneself in social role [30].

Furthermore, research has focused on the effect of Internet use may have on the likelihood of youth engaging in life threatening behaviors [31]. Research suggests that youth who experience suicidal thoughts or engage in NSSI behaviors appear to use the Internet to seek out specific discussion forums for support [32]. However, these forums and online spaces are often not monitored or moderated therefore individuals can be exposed to inaccurate and/or harmful information about suicide and NSSI [33]. As a result, the openness, virtuality and exemption of the Internet make information about NSSI or suicide online easily accessible [34], and discussing online with people who are also interested in suicide and NSSI related topics may lead to the encouragement of suicide and NSSI [20, 35]. Therefore, the Internet may play as a powerful double-edged sword in supporting individuals’ suicidality as well as their endorsement of NSSI behaviors.

According to Messias and her colleagues, daily use of the Internet for more than 5 hours was closely related with higher levels of depression and suicidality (both ideation and attempts) among youth [33]. Another critical phenomenon is that adolescents with potential NSSI thoughts or suicidal ideation might search the Internet for contents about NSSI or suicide related information. For example, those people who have the history of engaging in NSSI or suicidal behavior can easily connect with people who are now engaging in these health risk behaviors, while those who are curious about NSSI and suicidal behaviors will directly get linked to a unprotected world of content about NSSI and suicidal behaviors [20, 23]. Thus, these related studies above indicate that excessive internet use could be a risk factor for youth’ engagement in NSSI and suicidal behaviors [20, 22–23, 34].

In addition, although NSSI behaviors and suicidal ideation are 2 completely isolated and different concepts, their differences varied in intention, lethalities, methods, cognition, and results [36], studies have revealed that there is a highly similarity and inherent compatibility between NSSI behaviors and suicidal ideation. First, individuals who had history of NSSI or suicidal ideaion had the same psychological characteristics, which may be a negative response to bad emotions, an extreme feedback to various problems in the growing stage, or a means to attract attention and obtain a sense of existence. Second, NSSI behaviors can be an effective power of avoidance and control against suicidal ideation [37].Thirdly, a large number of empirical data showed that there are links existing between NSSI and suicidal ideation. Laye-Gindhu conducted a survey among 424 adolescents in Canada, found that the intensity of suicide ideation among NSSI group was significantly higher than that of non NSSI group [38]. Meanwhile, 89% of the respondents who attempted suicide had experience of NSSI [39]; other research pointed out that many people who had NSSI also had suicidal ideation in the past [40–41]. Finally, Firestone analyzed a negative thought pattern aiming at terminating the coherence of suicidality, then confirmed that there was a direct relationship between NSSI, suicidal ideation and the negative thought pattern [42]. Thus, it is necessary to analyze NSSI behaviors and suicidal ideation as common dependent variables to study the impact mechanism of internet use frequency with them furthermore.

The Gaps

Although Western literature hints that Internet use may be important variable to study when examining NSSI and suicidal behaviors [22–23], little is known about the role of internet use frequency in NSSI and suicidal behaviors among Chinese youth. The consequences of internet use frequency as a risk factor for NSSI engagement and suicidal thoughts and/or behaviors among Chinese youth remains to be investigated.

Meanwhile, findings using gender analysis reported gender differences in the prevalence of NSSI. The prevalence of NSSI behavior among female adolescents was higher than that of males, and therefore was viewed as a “feminine” behavior [43–46]. A recent meta-analysis also found a female bias in NSSI prevalence among adolescents worldwide [47].

For suicidality, Kõlves’s team found that in comparison with female adolescents, the risk of suicidal ideation among males has increased in recent years [48]. According to Freeman and colleagues, suicidal ideations were rated significantly more frequently in males than females [49].

But our recent research on NSSI and suicidality in China found no studies among youth have specifically analyzed gender differences in the context of internet use frequency, NSSI and suicidal ideation. Since NSSI and suicidality have always been the forefront of related psychological, sociological and demographic research [50–56], which helps to explain this gender bias, it is suggested that special attention should be paid to whether there are gender differences in the relation between internet use frequency, NSSI and suicidal ideation under Chinese context.

Thus, the overarching objective of this paper is to examine the relation between gender, internet use frequency, NSSI, and suicidal ideation among youth in China. Specifically, this study seeks to (1) assess whether any gender differences in NSSI and suicidal ideations exist among youth and (2) whether internet use frequency will act as a risk factor for NSSI and suicidal ideation engagement within this group.

2 hypotheses associated which each of the 2 objectives above are as follows:

H1: NSSI engagement and suicidal ideation will be more prevalent among females.

H2: Different categories of internet use frequency will all positively predict engagement in NSSI and suicidal ideation among youth indicating them as risk factors.

Methods

Participants

Participants consisted of a total of 2,018 middle-school and university students (803 males, 1,215 females, M_age = 17.8 years, age range: 12-24 years) who were recruited to complete questionnaires from 6 middle-schools and 4 universities in Xi'an, Yulin, Ankang of Shaanxi Province and Binzhou of Shandong Province in China. Parents or legal guardians gave permission for students’ participation by signing consent forms for those who were younger than 18. The study was approved by the institutional ethics review board within the university and the schools where the survey was conducted.

Measures

NSSI status. In order to assess adolescents' engagement in NSSI behavior, the Non-suicidal Self-Injury Assessment Tool (NSSI-AT) [57], was selected and translated into Chinese. By asking, "have you ever done anything that you didn't intentionally harm yourself for the purpose of suicide?" , measured as "0 = no, 1 = yes". Based on the 14 kinds of NSSI behaviors stipulated by NSSI-AT, this study refers to the relevant research of youth in the Chinese background, and adds 4 kinds of specific NSSI behaviors, including "1. Swallowing items that cannot be digested, such as plastic, stone, etc; 2. Taking or swallowing too much medicine (beyond the medical advice) 3. Burn yourself with cigarette butts ", etc. A total of 18 specific NSSI behaviors are defined. The internal consistency of this scale was found to be adequate for the present study (α = .82).

Suicidal Ideation. The Scale of Suicidal Ideation (SSI) developed by Beck [58] was used to assess adolescents’ suicidal behaviors. This measure consists of 14 items measuring participants’ suicidal ideation (I think suicide can end the current pain, I imagined about taking some strange or dangerous drugs to suicide on purpose, etc) on a 5-point Likert scale from disagree to completely agree. Higher scores indicate higher intensity of suicidal ideation. The SSI (α = .81) showed great reliability.

Internet Use Frequency. Emotional Health Online Behavior Assessment (EHOBA), developed by De Riggi, Lewis and Heath [59] , was used to assess internet use frequency among adolescents. This scale consists of 6-items measuring one's use of the internet for different categories, items were modified to better fit the Chinese context. Items include: “How often do you use IM softwares (Wechat, QQ, Messenger, etc) ? ”, “How often do you use social softwares (Weibo, Twitter, etc) ? ” , “ How often do you use a video site? (e.g. Youku, Youtube, Bilibili, etc) ? ”, “How often do you use the shopping website? (e.g. Taobao, Amazon, etc) ?” , “How often do you use knowledge sharing software? (e.g. Zhihu, Reddit, Google scholar, etc )” , “How often do you play online games (Fortnite, Call of Duty, etc.)?”, Participants were asked to rate each item on a 5-point Likert scale from “never use” to “use it everyday” whereby higher scores indicating higher internet use frequency. The EHOBA was found to have excellent internal reliability in the present study (α = .91).

Procedure

The present study employed a combination of convenience sampling to recruit teachers within 6 high-schools and professors within 4 universities who expressed interest in having their students participate in this study. Within the schools, stratified sampling was used to recruit participants to complete measures to ensure equal representation of gender as well as different grade levels within middle school (from grade 2 in middle-school to grade 4 in university). All questionnaires were anonymous. A total of 2,400 questionnaires were distributed and 2,018 valid questionnaires were recovered therefore the consent rate in the present study was 87.83%.

Data Analysis

Chi-square test and independent sample t-tests were adopted to analyze the gender differences in NSSI prevalence and suicidal ideation intensity among youth.

Furthermore, a step-wise binary logistic regression was used to examine whether internet use frequency (Step 1), and demographic variables (Step 2) were predictive of NSSI behavior (Model 1-4) for both genders, also a step-wise linear regression was used to examine whether the independent variables above were predictive of suicidal ideation (Model 5-8) for both genders.

Results

The results of the gender comparison for prevalence of NSSI is presented in Table 1. A total of 374 participants reported engaging in NSSI indicating a prevalence rate of 18.5%. Prevalence rates were found to be 17.2% and 19.4% among males and females, respectively. Chi-square test results showed that there was no significant difference in the prevalence of NSSI between male and females.

In table 2 we found that the suicidal ideation intensity of females (M= 101.05) are significantly (χ2 = 3.104, p<0.001) higher than that of males (M=88.37).

Table 3 presents the results from binary logistic regression on factors associated with the prevalence of NSSI behaviors among youth by gender. Model 1 revealed that the use of social softwares positively predicted NSSI engagement among males (social softwares: EXP(β) = 0.987, p < 0.05), while the use of knowledge sharing softwares negatively predicted NSSI engagement among males (knowledge sharing softwares: EXP(β) = -1.091, p < 0.01); When control variables were introduced to model 2, the use of social and knowledge sharing softwares became even more significant, meanwhile, only-child from control variables had significant negative impact on NSSI behaviors among males (only-child: EXP(β) = -0.806, p < 0.01).

As the variables were included into the models step by step, their explanatory power increasingly improved. The Cox & Snell R² and Nagelkerke R² in Model 1 were only 0.003 and 0.005, respectively, while in Model 2, this markedly improved to 0.023 and 0.037 when control variables were included.

In model 3, the use of social softwares positively predicted NSSI engagement among females (social softwares: EXP(β) = 1.067, p < 0.001). After control variables were included in model 4, the use of social softwares remains significant, only-child variable negatively predicted NSSI behaviors among females (only child: EXP(β) = -1.225, p < 0.05).

As the variables were included into the models step by step, their explanatory power increasingly improved. The Cox & Snell R² and Nagelkerke R² in Model 3 were only 0.002 and 0.004, respectively, which improved to 0.025 and 0.040 when control variables were added in model 4.

Table 4 presents the results from linear regression on factors associated with suicidal ideation intensity among youth by gender. In model 5, the use of social softwares and online gaming positively predicted suicidal ideation intensity among males (social softwares: EXP(β) = 0.049, p < 0.001; online gaming: EXP(β) = 0.105, p < 0.05); When control variables were introduced to model 6, the significance of social softwares and online gaming remained almost unchanged in the coefficient size and significance as compared to Model 5; meanwhile, age from control variables negatively predicted suicidal ideation intensity among males (age: EXP(β) = -0.224, p < 0.001).

As the variables were included into the models step by step, their explanatory power increasingly improved. The adjusted R² in Model 5 was only 0.14, respectively, while in Model 6, this markedly improved to 0.45 when control variables were included.

In model 7, the use of social softwares positively predicted suicidal ideation intensity among females (social softwares: EXP(β) = 0.018, p < 0.01). After control variables were included in model 8, the significance of the use of social softwares remained almost unchanged in significance as compared to Model 7 (social softwares: EXP(β) = 0.029, p < 0.01; shopping softwares: EXP(β) = 0.082, p < 0.01). Meanwhile, age from control variables negatively predicted suicidal ideation intensity among females (age: EXP(β) = -0.094, p < 0.05).

As the variables were included into the models step by step, their explanatory power increasingly improved. The adjusted R² in Model 7 was only 0.08, respectively, while in Model 8, this markedly improved to 0.33 when control variables were added.

Discussion

The results revealed that the prevalence of NSSI behaviors was similar among both males (17.2%) and females (19.4%), yet no significant gender difference was found. This finding is consistent with studies in other contexts [17, 38, 60–61].

Meanwhile, we found that females reported higher intensity of suicidal ideation compared to males’ reports. This finding is in accordance with existing studies [3, 62–63] indicating that females have a greater risk of suicidal ideation. This finding also suggests that China is the only country in which the suicide rate among females is higher than males [64–65]. This finding is also aligned with studies that have established significant links between depressive symptomatology and suicidal ideation [66], including the link between depression and suicides and suicidal attempts [67–68]. However, more recent data is needed to further explore the contributors to these findings.

The prevalence of NSSI engagement among youth was significantly associated with the frequency of certain types of internet use. Specifically, the use of social softwares had significantly predicted higher prevalence of NSSI engagement among both male and females, that is, individuals who spend more time on social softwares were more likely to engage NSSI behaviors. This shows that over dependence on social softwares can be a risk factor for youth' engagement in NSSI. This finding might be explained by the stigma associated with NSSI; individuals who self-injure often do not discuss this behavior with others, including their family or friends [20]. Therefore, social softwares can play an important role in meeting individuals’ need for social support and connection [69–70], including mitigating feelings of social isolation and even encourage healthier behaviours [71]. According to a related study, photos containing NSSI imagery and content pertaining to NSSI are often posted on social softwares, which may have a negative impact on vulnerable audiences [72] such as youth. It has been found that it is often the most graphic images of NSSI with higher severity of wounds get the attract greater attention and gain more comments [73]. Harmful effects of these images can include encouragement of NSSI engagement and the popularization of the behavior [73]. This issue can be exacerbated by the challenges experienced by social softwares platforms as they attempt to find novel and more effective methods to moderate this online content [72].

Contrastingly, the use of knowledge sharing softwares significantly predicted lower prevalence of NSSI engagement among males, indicating that males were less likely to engage in NSSI behaviors when they spent more time on knowledge sharing softwares. Based on an analysis of user composition of a popular online knowledge sharing platform in China called Zhihu, male users accounted for 72.4% and females accounted for 27.6% of users among a sample of 30,000 [74]. This indicates that males are more likely to use this platform compared to females. Meanwhile, according to related studies, young generation often use knowledge sharing softwares such as Reddit, Zhihu, etc., as a way of finding support and validation with regards to their emotional needs and NSSI in particular, which can help individuals connect to others, obtain support, and gain knowledge leading them to find healthier ways to cope [75–77].

The prevalence of suicidal ideation among youth was also correlated with some variables of internet use frequency. Similar to the relationship between the use of social softwares and NSSI behaviors among youth, the use of social softwares also positively predicted suicidal ideation among both males and females, which means individuals were more likely to have greater suicidal ideation when they spend more time on social softwares. This demonstrates that excessive use of social softwares may be a risk factor for youth’s suicidal ideation as well. Social softwares play as an important platform of interpersonal communication, especially with a high prevalence among young Internet users. In recent years, the negative influence of overusing social softwares on individual psychological and social adaptation has gradually become the focus of researchers, which not only endangers youth’s mental health, but also increases the possibility of suicides [78]. One example is the emergence of negative social software that threatens youth’s health in the guise of online social networking lately, such as the “Blue whale challenge” taught adolescents with “no value”should commit suicide in the same way as whales kill themselves by stranding [79]. A number of adolescents were exposed to the suicide rules of these life-threatning activities through the negative influence of social softwares [80]. The “Blue whale challenge” might be vanished already, but adolescents still can get access to these similar social softwares to spend their time on which harm youth’s mental and physical health in China and other countries [81–85].

Similarly, excessive online gaming was also a positive predictor of suicidal ideation. Although moderate online gaming can be beneficial to brain function, excessive or online gaming addiction is harmful to both mental and physical health among youth [78], which also leads to loneliness which can be associated with suicidal thoughts or attempts [86].

Limitations

This study has several limitations. First, this study relied only on self-report questionnaires to examine NSSI behavior and suicidal ideation. Further investigations are needed to understand the contributors to the patterns of youth’s engagement in NSSI and suicidal ideation. Second, the study is cross-sectional and the relationships between the variables are not causal. Third, effect sizes are quite small so the results should be interpreted with caution.

Implications And Contributions

This is the first evidence-based study revealed differences by gender in the relationship between internet use frequency, NSSI engagement and suicidal ideation among youth in China. The results revealed a gender pattern in the relationship of internet use frequency with NSSI behaviors and suicidal ideation among Chinese youth. We found gender difference in suicidal ideation and different categories of internet use frequency will change into different protective or risk factors; specifically, females were more likely to have more suicidal ideation, males would engage less NSSI behaviors when they spend more time on knowledge sharing softwares while might have more suicidal ideation when they spend too much time on gaming. The findings will be helpful to enrich existing literature on internet use frequency, NSSI and suicidal behaviors among Chinese youth, and emphasize the need for continued efforts to explore NSSI and Suicidal behaviors across various cultures and societies. Results also emphasized the need for gender-specific interventions for Chinese youth.

Conclusions

To conclude, the gender difference of NSSI engagement among Chinese youth is not statistically significant; While females had more suicidal ideation than males as hypothesized.

Second, not as hypothesized, just a few categories of internet use frequency were sufficient to become risk factors to both NSSI and suicidal ideations engagements among youth, specifically, the overuse of social softwares was found to be a risk factor to both NSSI and suicidal ideations engagements for both genders. In addition, males would engage less NSSI behaviors when they spend more time on knowledge sharing softwares while might have more suicidal ideation when they spend too much time on gaming.

Abbreviations

NSSI: Non-suicidal self-injury; SI: Suicidal Ideation; IUF: Internet Use Frequency; NSSI-AT: Non-suicidal Self-Injury Assessment Tool; SSI: The Scale of Suicidal Ideation; EHOBA: Emotional Health Online Behavior Assessment.

Declarations

Ethics approval and consent to participate

Writtren ethics approval was obtained from School of Public Policy and Management, Xi’an Jiaotong University (Protocol Number: 18225; approved on May 1, 2017; exempt protocol approval expiry–May 1, 2022). Participant Information Sheets and Consent forms were approved by the committee and in line with the standardized documents for the University. All participants were approached as healthy volunteers participating in different groups. All were deemed to have capacity to consent to participation and due to the fact that the study included young students below 18, the parents of all participants provided written informed consent for all aspects of the study.

Consent for publication

Written informed consent for publication was obtained from all participants.

Availability of data and materials

All of the data generated or analysed during this study are included in this article.

Competing interests

The authors (one of the authors named Xueyan Yang is a member of the editorial board of this journal) all declare that they have no competing interests.

Funding

The study was jointly funded by The Chinese Ministry of Education of Humanities and Social Science project (grant number 13YJAZH118), the Fundamental Research Funds for the Central Universities (grant number SK2013025). The funders had no role in the study design, data collection, data analysis, data interpretation, or writing of this article.

Authors’ Contributions

MYX contributed to the conceptualization of this study as well as data collection, translation, and drafted the manuscript. XYY contributed to the conceptualization of this study and partially funded this project. KL contributed to data collection and analysis. BNB contributed to reviewing and editing manuscript content. All Authors had read and approved the manuscript as well as agreed about its content and the decision to submit for publication.

Acknowledgements

Special thanks to all participants as well as the whole team members of Dr.Nancy Heath from McGill University and China Scholarship Council (CSC).

References

Whitlock J, Exner-Cortens D, Purington A. Assessment of nonsuicidal self-injury:Development and initial validation of the Non-Suicidal Self-Injury–Assessment Tool (NSSI-AT). Psychological assessment. 2014;26(3):935. https://doi.org/10.1037/a0036611

Taliaferro LA , Muehlenkamp JJ . Risk Factors Associated With Self-injurious Behavior Among a National Sample of Undergraduate College Students. Journal of American College Health. 2015. 63(1):40-48. https://doi.org/10.1080/07448481.2014.953166

Ma X, Xiang Y-T, Cai Z-J, Li, S-R, Xiang, Y-Q, Guo, H-L, Dang, W-M.Lifetime prevalence of suicidal ideation, suicide plans and attempts in rural and urban regions of Beijing, China. Australian and New Zealand Journal of Psychiatry.  2009;158-166. https://doi.org/10.1080/00048670802607170

Fan F, & Zhang T. . Suicide and its prevention and intervention. Tsinghua University Press. 2009.

Plutchik R, Van Praag H M, Picard S, et al. Is there a relation between the seriousness of suicidal intent and the lethality of the suicide attempt?. Psychiatry research. 1989;27(1):71-79.https://doi.org/10.1016/0165-1781(89)90011-5

Nock, M. K. . Self-injury. Annual review of clinical psychology. 2010:6, 339-363.

Whitlock J, Muehlenkamp J, Eckenrode J, et al. Nonsuicidal self-injury as a gateway to suicide in young adults. Journal of Adolescent Health. 2013;52(4):486-492. https://doi.org/10.1016/j.jadohealth.2012.09.010

Gholamrezaei M, De Stefano J, Heath N L. Nonsuicidal self‐injury across cultures and ethnic and racial minorities:A review. International journal of psychology. 2017;52(4):316-326. https://doi.org/10.1002/ijop.12230

Tong Y, Lan Z, Xu D, Wang H, Li X, Yang C. Gender differences in suicide rate, attempted suicide rate and suicide mortality. Chinese Journal of Psychiatry, 2013;46 (4):227-232. https://doi.org/10.3760/cma.j.issn.1006-7884.2013.04.008

Wei L , Xue D , Fei L , Zhu F , Yang G. Crisis Intervention and Suicide Prevention (2) - - Analysis of the Characteristics of Suicide Death in Elderly and Young People in China. Journal of Clinical Psychiatry . 2005. https://doi.org/10.3760/cma.j.issn.1043-7861.2005.04.008

Li X, Fei L, Hui Y, Xu Y, He F. Why is the attempted suicide rate of women significantly higher than that of men? Chinese Journal of Mental Health. 2003;191-195. https://doi.org/10.3760/cma.j.issn.1025-7861.2003.06.002

Xing Y , Ji C , Ji H , Yang X, Wang L , Ma Jl.. Prevalence of injury-related behaviors among middle school students in Shijingshan District, Beijing. School Health in China. 2003;24 (1), 28-29. https://doi.org/10.3969/j.issn.1673-7830.2010.01.010

Zhang Z, Guo L.. Survey of suicide attempts among middle school students in Chengdu. Chinese Journal of Epidemiology. 2003;24 (3):189-191. https://doi.org/10.3760/j.issn:0254-6450.2003.03.007

Luo C, Peng N, Zhu Wi, Zhou Y, Gao G.. Study on the Current Situation of Dangerous Behavior among youth in Shanghai (5) - Suicide Tendency and Runaway Behavior. School Physicians of China. 2003;17 (3):197-199. https://doi.org/10.3969/j.issn.1001-7062.2003.03.002

Sun Y, Tao F, Gao M. Research on suicide behavior and some psychological factors among middle school students in Hefei. Chinese Journal of Epidemiology. 2006;27 (1):33-36. https://doi.org/10.3760/j.issn:0254-6450.2006.01.009

Gao H, Wu Q, Deng W, Yang Z, Huang Y. Study on suicidal behavior and psychosocial factors of primary and secondary school students in Shanghai. Chinese Journal of Evidence-based Pediatrics. 2007;(1). https://doi.org/10.3969/j.issn.1673-5501.2007.01.006

Chao Q, Yang X, Luo C. Boy crisis? Sex differences in self-injurious behaviors and the effects of gender role conflicts among college students in china. American journal of men's health. 2016;10(6), NP1-NP10. https://doi.org/10.1177/1557988315579096

Yang X, Feldman MW. A reversed gender pattern? A meta-analysis of gender differences in the prevalence of non-suicidal self-injurious behaviour among Chinese youth. BMC public health. 2018;18(1):66. https://doi.org/10.1186/s12889-017-4614-z

Wang L, Wang D. Study on Self-injurious Behavior and Related Factors of Middle School Students. Chinese Journal of Health Psychology. 2009;17 (3):314-316. https://doi.org/10.3760/j.issn:0254-6450.2009.01.009

Whitlock JL., Powers JL., Eckenrode J. The virtual cutting edge:the internet and adolescent self-injury. Developmental psychology. 2006;42(3):407. https://doi.org/10.1037/0012-1649.42.3.407

Mars B, Heron J., Biddle L., Donovan J. L., Holley R., Piper M., Gunnell D. Exposure to, and searching for, information about suicide and self-harm on the Internet:Prevalence and predictors in a population based cohort of young adults. Journal of Affective Disorders. 2015;185:239-245. https://doi.org/10.1016/j.jad.2015.06.001

Derouin A., Bravender T. Living on the edge:The current phenomenon of self-mutilation in youth. MCN:The American Journal of Maternal/Child Nursing. 2004;29(1):12-18.

Moyer M., Haberstroh S., & Marbach C. . Self-injurious behaviors on the net:A survey of resources for school counselors. Professional School Counseling;2008:11(5). https://doi.org/10.1177/2156759X0801100501

Messias E., Castro J, Saini A, Usman M, Peeples D. Sadness, suicide, and their association with video game and internet overuse among teens:results from the youth risk behavior survey 2007 and 2009. Suicide and Life‐Threatening Behavior, 2011;41(3):307-315. https://doi.org/10.1111/j.1943-278X.2011.00030.x

Lenhart A., Madden M, & Hitlin P. Teens and technology:Youth are leading the transition to a fully wired and mobile nation. Pew Internet & American Life Project. 2005. 

CNNIC. China Internet Information Center (CNNIC) released "Research Report on Internet Behavior of Chinese Youth in 2014". China Information Security. 2015;(6):68-70.

He J. Preventive Measures against Internet-induced Suicide Crime:Taking "Blue Whale" Death Game as an Example. Journal of Liaoning Police College. 2017;(06):68-74. https://doi.org/10.3969/j.issn.1008-5378.2017.06.013

Wang X, Zhang Y, Gao X. Study on the injury and influencing factors of Internet addiction among middle school students in Xuzhou City. Practical preventive medicine. 2017;(05):30-33. https://doi.org/10.3969/j.issn.1006-3110.2017.05.007

Yi H, Chen J, Du X. A study on the Internet dependence, content preference and social development of middle school students. China Special Education. 2006;(11):69-73. https://doi.org/10.3969/j.issn.1007-3728.2006.11.016

Huang L, Wang, Chen J, Yu Q, Xu X, Wang L. Analysis of Internet Addiction Tendency and influencing factors of high school students. Chinese Journal of behavioral medicine and brain Science. 2006;(8):https://doi.org/10.3760/j.issn:0254-6450.2006.01.009

Daine K, Hawton K, Singaravelu V, Stewart A, Simkin S, Montgomery, P.The power of the web:a systematic review of studies of the influence of the internet on self-harm and suicide in young people. PloS one. 2013; 8(10), e77555. https://doi.org/10.1371/journal.pone.0077555

Lewis, SP, Rosenrot, SA, Messner, MA. Seeking validation in unlikely places:the nature of online questions about non-suicidal self-injury. Archives of Suicide Research. 2012;16(3):263-272. https://doi.org/10.1080/13811118.2012.695274

Messina, ES, Iwasaki, Y. Internet use and self-injurious behaviors among youth and young adults:An interdisciplinary literature review and implications for health professionals. Cyberpsychology, Behavior, and Social Networking. 2011;14(3):161-168. https://doi.org/10.1089/cyber.2010.0025

Kirmayer, LJ, Raikhel, E, Rahimi, S.. Cultures of the Internet:Identity, community and mental health. 2013.

Fortune SA, Hawton K. Suicide and deliberate self-harm in children and youth. Current Paediatrics. 2005;15(7): 575-580. https://doi.org/10.1097/01.yco.0000172059.55778.c9

Walsh BW.Distinguishing self-mutilation from suicide:A review and commentary. Self-Mutilation.1988.

Messer JM, & Fremouw WJ. A critical review of explanatory models for self-mutilating behaviors in youth. Clinical Psychology Review. 2008;28(1):162-178. https://doi.org/10.1016/j.cpr.2007.04.006

Laye-Gindhu A , Schonert-Reichl K A . Nonsuicidal Self-Harm Among Community Adolescents: Understanding the “Whats” and “Whys” of Self-Harm[J]. Journal of Youth & Adolescence. 2005; 34(5):447-457. https://doi.org/10.1007/s10964-005-7262-z

Klonsky ED, Muehlenkamp JJ. Self‐injury:A research review for the practitioner. Journal of clinical psychology. 2007;63(11):1045-1056. https://doi.org/10.1002/jclp.20412

Muehlenkamp JJ, Gutierrez PM. Risk for suicide attempts among youth who engage in non-suicidal self-injury. Archives of suicide research. 2007;11(1):69-82. https://doi.org/10.1080/13811110600992902

Nock MK, Joiner Jr TE, Gordon, KH, Lloyd-Richardson E, Prinstein MJ. Non-suicidal self-injury among youth:Diagnostic correlates and relation to suicide attempts. Psychiatry research. 2006; 144(1): 65-72. https://doi.org/10.1016/j.psychres.2006.05.010

Firestone RW, Seiden RH.Suicide and the continuum of self-destructive behavior. Journal of American College Health. 1990;38(5):207-213. https://doi.org/10.1080/07448481.1990.9936189

Ross S, Heath N. A study of the frequency of self-mutilation in a community sample of youth. Journal of youth and Adolescence. 2002;31(1):67-77. https://doi.org/10.1023/A:1014089117419

Whitlock J., Eckenrode J, Silverman D. Self-injurious behaviors in a college population. Pediatrics. 2006;117(6):1939-1948. https://doi.org/10.1542/peds.2005-2543

Moehler E., Kagan J, Parzer P, Brunner R, Reck C, Wiebel A, Resch F. Childhood behavioral inhibition and maternal symptoms of depression. Psychopathology. 2007;40(6):446-452. https://doi.org/10.1159/000107429

Van Camp I, Desmet M, Verhaeghe P. Gender differences in non-suicidal self-injury:are they on the. In 2nd International Conference on Behavioral, Cognitive and Psychological Sciences. 2011;(BCPS 2011) (Vol. 23, pp. 28-34). IACSIT Press. http://hdl.handle.net/1854/LU-4392611

Bresin K., Schoenleber M. Gender differences in the prevalence of nonsuicidal self-injury:A meta-analysis. Clinical Psychology Review. 2015;38:55-64. https://doi.org/10.1016/j.cpr.2015.02.009

Kõlves K., Ide N, & De Leo D. Suicidal ideation and behaviour in the aftermath of marital separation:Gender differences. Journal of Affective Disorders. 2010;120(1-3):48-53. https://doi.org/10.1016/j.jad.2009.04.019

Freeman A, Mergl R, Kohls E, Székely A, Gusmao R, Arensman E, Rummel-Kluge C. A cross-national study on gender differences in suicide intent. BMC psychiatry. 2017;17(1):234. https://doi.org/10.1186/s12888-017-1398-8

Sornberger MJ, Heath NL, Toste JR, McLouth R. Nonsuicidal self‐injury and gender:Patterns of prevalence, methods, and locations among youth. Suicide and Life‐Threatening Behavior. 2012;42(3):266-278. https://doi.org/10.1111/j.1943-278X.2012.0088.x

Tatnell R., Kelada L., Hasking P, Martin G. Longitudinal analysis of adolescent NSSI:The role of intrapersonal and interpersonal factors. Journal of abnormal child psychology. 2014;42(6):885-896. https://doi.org/10.1007/s10802-013-9837-6

Bresin K, Schoenleber M. Gender differences in the prevalence of nonsuicidal self-injury:A meta-analysis. Clinical Psychology Review. 2015;38:55-64. https://doi.org/10.1016/j.cpr.2015.02.009

Bakken NW, Gunter WD. Self-cutting and suicidal ideation among youth:Gender differences in the causes and correlates of self-injury. Deviant Behavior. 2012;33(5):339-356. https://doi.org/10.1080/01639625.2011.584054

Stephenson H, Pena-Shaff J, Quirk P. Predictors of college student suicidal ideation:Gender differences. College Student Journal. 2006;40(1):109.

Rich AR, Kirkpatrick‐Smith J, Bonner RL, Jans F. Gender differences in the psychosocial correlates of suicidal ideation among youth. Suicide and Life‐Threatening Behavior. 1992;22(3): 364-373. https://doi.org/10.1111/j.1943-278X.1992.tb00741.x

Swahn MH, Bossarte RM. Gender, early alcohol use, and suicide ideation and attempts:findings from the 2005 youth risk behavior survey. Journal of adolescent health. 2007;41(2):175-181. https://doi.org/10.1016/j.jadohealth.2007.03.003

Whitlock J, Purington A. The non-suicidal self-injury assessment tool. Cornell University (Cornell research program on self-injurious behaviors in youth and young adults).Available online at:http://www. selfinjury. bctr. cornell. edu.2007.

Beck AT, Kovacs M, Weissman A. Assessment of suicidal intention:the Scale for Suicide Ideation. Journal of consulting and clinical psychology. 1979;47(2):343. https://doi.org/10.1037/0022-006X.47.2.343

De Riggi ME, Lewis SP, Heath NL. Brief report:nonsuicidal self-injury in adolescence:turning to the Internet for support. Counselling Psychology Quarterly. 2018;31(3):397-405. https://doi.org/10.1080/09515070.2018.1427556

Gratz KL, Conrad, SD, Roemer, L. Risk factors for deliberate self‐harm among college students. American journal of Orthopsychiatry. 2002;72(1): 128-140.  https://doi.org/10.1037/0002-9432.72.1.128

Yang X, Xin, M. “Boy Crisis” or “Girl Risk”? The Gender Difference in Nonsuicidal Self-Injurious Behavior Among Middle-School Students in China and its Relationship to Gender Role Conflict and Violent Experiences. American journal of men's health. 2018;12(5):1275-1285. https://doi.org/10.1177/1557988318763522

Zhang J, Jin S. Determinants of suicide ideation:A comparison of Chinese and American college students. Adolescence. 1996;31(122):451.

Bridge JA, Goldstein TR, Brent DA. Adolescent suicide and suicidal behavior. Journal of child psychology and psychiatry. 2006;47(3‐4):372-394. https://doi.org/10.1111/j.1469-7610.2006.01615.x

Phillips MR, Li X, Zhang Y. Suicide rates in China, 1995–99. The Lancet. 2002;359(9309):835-840. https://doi.org/10.1016/S0140-6736(02)07954-0

World Health Organization. Suicide rates Data by country. 2012. http://apps. who.int/gho/data/node.main.MHSUICIDE?lang=en. Retrieved 18 August, 2015.

Vandivort DS, Locke BZ. Suicide ideation:Its relation to depression, suicide and suicide attempt. Suicide and Life‐Threatening Behavior. 1979;9(4):205-218. https://doi.org/10.1111/j.1943-278X.1979.tb00439.x

Robin AA, Brooke EM, Freeman-Browne DL. Some aspects of suicide in psychiatric patients in Southend. The British Journal of Psychiatry. 1968;114(511): 739-747. https://doi.org/10.1192/bjp.114.511.739

Paykel ES, Myers JK, Lindenthal JJ, Tanner J. Suicidal feelings in the general population:a prevalence study. The British Journal of Psychiatry. 1974;124(582): 460-469. https://doi.org/10.1192/bjp.124.5.460

Lewis, SP, Rosenrot SA, Messner MA. Seeking validation in unlikely places:the nature of online questions about non-suicidal self-injury. Archives of Suicide Research. 2012;16(3):263-272. https://doi.org/10.1080/13811118.2012.695274

Lewis SP, Mahdy JC, Michal NJ, Arbuthnott AE. Googling Self-injury:the state of health information obtained through online searches for self-injury. JAMA pediatrics. 2014;168(5):443-449. https://doi.org/10.1001/jamapediatrics.2014.187

Lewis SP, Seko Y. A double‐edged sword:A review of benefits and risks of online nonsuicidal self‐injury activities. Journal of clinical psychology. 2016;72(3):249-262. https://doi.org/10.1002/jclp.22242

Baker TG, Lewis SP. Responses to online photographs of non-suicidal self-injury:A thematic analysis. Archives of Suicide Research. 2013;17(3):223-235. https://doi.org/10.1080/13811118.2013.805642

Brown, RC, Fischer T, Goldwich AD, Keller F, Young R, Plener PL. cutting:Non-suicidal self-injury (NSSI) on Instagram. Psychological medicine. 2018;48(2):337-346.

Peng J. Data report of Zhihu core users. Zhihu. 2017, January 23;Retrieved November, 11, 2019, from https://zhuanlan.zhihu.com/p/24960279

Murray CD, Fox J. Do Internet self-harm discussion groups alleviate or exacerbate self-harming behaviour?. Australian e-Journal for the Advancement of Mental Health. 2006;5(3):225-233. https://doi.org/10.5172/jamh.5.3.225

Rodham K, Gavin J, Miles M. I hear, I listen and I care:A qualitative investigation into the function of a self-harm message board. Suicide and life-threatening behavior. 2007;37(4):422-430.

Liu H. How to alleviate the ideation of self-injury. Zhihu. 2019, November 2;Retrived November, 11, 2019, from https://www.zhihu.com/answer/879146624

Chen W, Qin A, Zhang F, Zhao Y. Survey on Internet addiction behavior of students in Heilongjiang University and middle school. China public health. 2008;24 (5):609-611.

Balhara YPS, Bhargava R, Pakhre A, Bhati, N. The “Blue Whale Challenge”?:The first report on a consultation from a health care setting for carrying out “tasks” accessed through a mobile phone application. Asia‐Pacific Psychiatry. 2018;10(3):e12317. https://doi.org/10.1111/appy.12317

Lupariello F, Curti SM, Coppo E, Racalbuto SS, Di Vella G. Self‐harm Risk Among youth and the Phenomenon of the “Blue Whale Challenge”:Case Series and Review of the Literature. Journal of forensic sciences. 2019; 64(2):638-642. https://doi.org/10.1111/1556-4029.13880

Mitchell KJ, Ybarra ML. Online behavior of youth who engage in self-harm provides clues for preventive intervention. Preventive medicine. 2007;45(5):392-396. https://doi.org/10.1016/j.ypmed.2007.05.008

Song C. "Blue whale game" caused by the network security law enforcement issues. Journal of Liaoning Public Security judicial management cadre college. 2018;(1):27-30.

Yan Z. Seizing the "blue whale" to block the temptation:psychological interpretation of the blue whale game and analysis of parents' coping strategies. Hebei Education (Moral Education Edition). 2018;(12):27.

Teng M. On the identification, prevention and intervention of adolescent suicide behavior from the perspective of "blue whale game". Mental health education in primary and secondary schools. 2018; (5):6. https://doi.org/10.3969/j.issn.1671-2684.2018.05.005

Zhang H. Analysis of China's legislation on children's protection from harmful information from the impact of blue whale games. Guangdong sericulture. 2017;51(4):85-86. https://doi.org/10.3969/j.issn.2095-1205.2017.04.64

Allison SE, Von Wahlde L, Shockley T, Gabbard GO.  The development of the self in the era of the internet and role-playing fantasy games. American Journal of Psychiatry. 2006;163(3):381-385. https://doi.org/10.1176/appi.ajp.163.3.381

Tables

Table 1 Comparison of the prevalence of NSSI between male and females

Table 2 Comparison of Suicidal Ideation intensity between male and females 

Note.+，p<0.1；*，p<0.05；**，p<0.01；***，p<0.001；

Table 3 The Impact of Internet Use Frequency on the Prevalence of NSSI Behavior Among youth by Gender

Note.+p < 0.1；*p < 0.05；**p < 0.01；***p < 0.001；

Table 4 The Impact of Internet Use Frequency on the Intensity of Suicidal Ideation Among youth by Gender

Note.+p < 0.1；*p < 0.05；**p < 0.01；***p < 0.001；