Introduction

The popularity of the Internet has brought great convenience to people’s life and study. However, it may bring inappropriate or excessive use of the Internet, which harms physical, psychological and social adaptation (Seyrek et al., 2017; Tang et al., 2014). Internet addiction (IA), also known as problematic Internet use or pathological Internet use, is an uncontrollable, compulsive, and excessive use of the Internet by individuals (Rachubinska et al., 2021; Young, Pistner, O’mara, & Buchanan, 1999). A Meta-analysis of the epidemiological characteristics of IA found that the average prevalence of IA was 7.02% and increased over time (Pan et al., 2020). A study on the prevalence of IA showed that the prevalence rate among adolescents in mainland China was 19.8% (Xu et al., 2020). Adolescents with IA have worse academic performance (Wu et al., 2016). At the same time, IA is associated with physical and mental health problems such as weight gain, impaired vision, sleep disorders, difficulties in emotional regulation, serious mental illness and even suicide attempts among adolescents (Guo et al., 2020; Lissak, 2018). Adolescents are in a period of growth and development, with immature neurological and impulsiveness, which makes them more likely to indulge in Internet consumption (Pallanti et al., 2006). It is of great significance to explore the causes and influencing mechanisms of Internet addiction among students for effective prevention or intervention.

Middle school students may experience negative life events (NLE) because of their poor social cognitive ability, as well as the inevitability of academic stress and interpersonal problems. NLE, as a source of psychological stress, can lead to physiological, psychological and cognitive behavioral changes, undermine adolescents’ psychological well-being, and adversely affect their physical and mental development (McMahon et al., 2020; Rabkin & Struening, 1976). Moreover, Due to the hidden and entertaining features of the Internet, middle school students are more likely to use the Internet to escape NLE, which increases the risk of excessive use of the internet. It has also been found that NLE are negatively associated with mental health problems among college students, and college students who experience NLE are more likely to be anxious, depressed, and stressed (Lee et al., 2019). In addition, negative life events can positively predict internet addiction, which is an important risk factor for adolescent IA (Li et al., 2021) .

Coping are the cognitive strategies and behaviors that individuals adopt to relieve stress (Chu et al., 2016), which are divided into positive coping and negative coping styles (NCS). Positive coping is facing up to stress, such as asking for help and solving problems, while NCS is adopting strategies such as avoidance and self-blame to cope with the problem (Ren et al., 2021; Tang & Dai, 2018). Previous research (Ikeda et al., 2022) has found that NCS is associated with higher levels of IA, and When faced with negative life events, college students who use NCS are more likely to overuse the Internet (Chou et al., 2018) .

Coping styles may play an intermediary role in NLE and IA. On the one hand, NLE are related to NCS. NLE can lead to changes in individual cognitive behavior and thus affect individual coping styles (Veisani et al., 2021). On the other hand, individuals with NCS were more likely to develop IA. Therefore, NLE are related to NCS, which in turn are related to IA. Ithas been reported that studies on the relationship between NLE and IA, as well as the relationship between coping and IA (Shan et al., 2021; Wei et al., 2022). However, there is no longitudinal study on the mediating effect of NCS in the relationship between NLE and IA. In addition, most existing studies have focused on college and high school students (Lei et al., 2018; Yan & Cheng, 2017). In contrast, middle school students have not yet formed a sound personality. Coupled with academic pressure and adolescent rebellion, they are more susceptible to NLE, thus more likely to excessive Internet use (Zhang et al., 2022). Meanwhile, literature have found that earlier exposure to or excessive use of the Internet may have more detrimental effects on the formation of good lifestyles and psychological health of adolescents (Smahel et al., 2012).

To fill these gaps, we conducted this large two-year follow-up study among middle school students, to investigate the effects of NLE on IA and the potential mediating effects of NCS between NLE and IA.

Methods

Participants

Through survey, we collected data from two middle schools, one public and one private, in Ganzhou City, Jiangxi Province, southeastern China. The ethical review committee of Gannan Medical University approved the study. We conducted the baseline survey in October 2018 using a whole-group sampling method with grade level sampling. We recruited all first-year students in both schools to participate in the questionnaire. Prior to the survey, trained investigators obtained informed consents (IC) from school administrators, teachers, participating students, and their parents. Students completed the questionnaire independently in the classroom, and the surveyors collected the questionnaires on site. Two years later, we conducted the second survey on the same sample.

Measurement Tools

This study focused on investigating middle school students’ NLE, NCS, and IA, and we selected the best measurement tools available in Chinese version to measure these outcomes. A brief description of these measurement tools is followed.

The Adolescent Self-Rating Life Events Check List (ASLEC)

ASLEC was developed by Liu et al. (Liu et al., 1997). It is a revised 27-item scale that measures NLE that have occurred in the past 12 months in adolescents. The scale is scored on a six-point Likert scale, with a score of 0 if the event did not occur, and if the event did occur, it is scored according to the degree of impact (1 = “no impact”, 5 = “extreme impact”).

In this study, to better reflect the actual characteristics of middle school students, we modified some items of the scale. Specifically, we changed item 4 “close friends” to “classmates or close friends”, item 10 “conflict with teachers” to “tension with teachers”, item 21 “disciplinary or illegal” to “fined”, and item 25 “family pressure” to “family-imposed pressure to learn”. The Confirmatory Factor Analysis (CFA) results of the ASLEC on this sample are suboptimal, with root mean square residual (RMR) = 0.10 (> 0.08), and goodness of fit index (GFI) = 0.81 (< 0.90). The total Cronbach’s alpha of this scale was 0.90 in this study. The total score of ASLEC ranges 0-135, with a higher score indicating more severe NLE.

Coping Style Questionnaire (CSQ, Version 3)

The coping style questionnaire was revised by Xiao et al. (Xiao et al., 1996). In our study, we only used the NCS subscale of the coping style questionnaire. This subscale consists of 30 items, which were divided into three dimensions: self-reproach, fantasy, and evasion. To better match the characteristics and actual situation of middle school students, we modified the options of the scale as follows: 1 = no, 2 = valid, 3 = relatively valid, 4 = invalid. We also changed the scoring method: ① “1” (i.e., “No”) for each subscale was scored as “0”; ② “2, 3, 4” (i.e., “Yes”) was scored as “1”.

In this study, the CFA results of NCS are adequate, with RMR = 0.01 (< 0.08), and GFI = 0.89 (close to 0.90). For total NCS score, the Cronbach’s alpha was 0.87, and three dimensions Cronbach’s alphas were 0.71 for self-reproach, 0.74 for fantasy, and 0.74 for evasion. The total score of NCS ranges 0-–30, with a higher score indicating more severe NCS.

Internet Addiction Test (IAT)

The Young’s (Young, 2004) Internet Addiction Test was developed to measure Internet addiction symptoms. The scale has 20 entries. A five-point Likert scale score (1="never”, 5="always”) was used, with scores of 50 and above defining Internet addiction and scores below 50 defining non-Internet addiction (Cao et al., 2010). In our study, the CFA results of IAT are adequate, with RMR = 0.05 (< 0.08), and GFI = 0.88 (close to 0.90). The total Cronbach’s alpha coefficient for this scale was 0.92. The total score of IAT ranges 20-100, with a higher score indicating more severe Internet addiction symptoms.

Data Analysis

We used the SPSS 24.0 software package for all data analysis. Chi-square tests were used to analyze whether there were differences in the sociodemographic characteristics of the respondents who participated in the follow-up and those who did not. We applied Spearman correlation analysis to assess the correlation between NLE, NCS and IA, and multiple linear regression analysis to examine the predictive role of NLE and NCS on IA. Finally, we implemented structural equation modeling (SEM) using the AMOS 24.0 software package to further examine the pathway relationship between NLE, NCS, and IA, as well as the potential mediating effect of NCS between NLE and IA. All p values were two-sided and p < 0.05 was considered statistically significant. For SEM, to assess the fitness of the model to our data, we used the following model fit indexes and cut-off values: GFI > 0.90, Adjusted Goodness of Fit Index (AGFI) > 0.90,Tucker-Lewis index (TLI) > 0.90, Comparative Fit Index (CFI) > 0.90, and Root Mean Square Error of Approximation (RMSEA) < 0.05 (Dou & Shek, 2021).

Results

Sample Characteristics

A total of 2,845 students completed the baseline survey, and 2,306 (81.1%) of them completed the follow-up survey 2 years later. Chi-square tests showed that there were no statistically significant differences in gender, family types, parental education, place of residence, and time of initial Internet access between those finished follow-up and those did not (Table 1).

Table 1 Baseline demographic information for non-followers and followers
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Correlation Between Variables

Table 2 shows the results of the Spearman correlation coefficients between the three key variables (NLE, NCS, and IA). NLE experienced at baseline were positively correlated with NCS style at follow-up (r = 0.16, p < 0.01), NCS was positively correlated with IA (r = 0.35, p < 0.01), and NLE at baseline were also positively correlated with IA at follow-up (r = 0.19, p < 0.01). In addition, IAT defines the score of the scale greater than or equal to 50 as Internet addiction. The results of this study show that the Internet addiction rate is 2.4% at T1 and 12.3% at T2, the Internet addiction rate has increased in the two-year follow-up.

Table 2 Correlation analysis between variables
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Structural Equation Modeling (SEM)

SEM results were illustrated in Fig. 1 and summarized in Table 3. Overall, the SEM model fit our date very well, with χ2 = 228.65, GFI = 0.982, AGFI = 0.971, TLI = 0.983, CFI = 0.987, and RMSEA = 0.045. The results indicated that NLE in the first survey were statistically significantly associated with increased NCS in the second survey (β = 0.17, p < 0.01), NLE in the first survey were statistically significantly associated with increased risk of IA in the second survey (β = 0.16, p < 0.01), and NCS in the second survey was statistically significantly associated with increased risk of IA in the second round of survey (β = 0.33, p < 0.01).

We used the trust interval method (Bootstrapping) to analyze the mediating effect of NCS style between NLE and IA, with negative life events as independent variable, negative coping styles as mediating variable and Internet addiction as dependent variable. Table 3 also showed the standardized path coefficients and the results of mediating effects of this structural equation model. The results show that NLE has a significant indirect effect on IA through NCS, and it plays a partial mediating role in NLE and Internet addiction (β = 0.17, p < 0.01).

Fig. 1
figure 1

Structural equation modeling of the relationship between NLE, NCS, and IA and standardized path coefficients. Note: *** p < 0.01

NLE: negative life events; NCS: negative coping styles; IA: Internet addiction; IR: interpersonal relationships; SS: study stress; BP: being published; HA: health adaptation; SR: self-reproach; FA: fantasy; EV: evasion; TAT: tolerance and time management; WR: withdrawal reaction; IHA: interpersonal, health and academic; CAP: compulsion and prominence

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Table 3 Structural Equation Modeling (SEM) analysis results
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Discussion

This study used a longitudinal method that aimed to investigate the relationship between NLE, NCS, and IA among middle school students. It was found that NLE were positively associated with IA, and higher levels of NLE were associated with an increased risk of IA. This result is consistent with the results of existing studies (Li et al., 2016; Zheng et al., 2022) that suggest NLE are a significant predictor of IA. It also confirms the general stress theory (Agnew, 1992), which reveals that negative events are a stressor that can lead to negative emotions,which may produce addictive behaviors. In the light of this theory, experiencing NLE is almost unavoidable in real life, and it can increase negative emotions in middle school students, when middle school students choose to use the Internet with its invisibility and convenience to escape reality and self-regulate, it may lead to excessive use of the Internet (Jun & Choi, 2015) .

In addition, this study found that middle school students who adopted immature coping were more likely to develop IA during the two-year follow-up period. Previous cross-sectional findings suggest that adolescent IA is linked to the NCS style chosen, that NCS is positively associated with IA, and that the use of NCS is considered a strategy for individuals to protect themselves and release stress (Chwaszcz et al., 2018; ). The “risk enhancement model” (Gong & Zhang, 2016) suggests that when a risk factor is enhanced, the effect of another risk factor is increased. NCS is positively associated with IA, when middle school students adopt more NCS, the risk of IA increases.

Furthermore, the present study found that NCS partially mediated the effect of NLE and IA in middle school students. The mediating effect of coping in Internet addiction has been confirmed by several cross-sectional studies, such as a cross-sectional study on depression, anxiety, and IA, which concluded that coping mediated the relationship between anxiety, depression, and IA (McNicol & Thorsteinsson, 2017). Zhou et al.'s (Zhou et al., 2017) cross-sectional study indicates that coping mediate the role of personality traits and IA. NCS is a coping strategy that negatively affects the individual’s physical and psychological adaptation. When using NCS, the risk of individual bad behavior increases. In accordance with the stress coping model (Wagner et al., 1999), Individuals experiencing NLE preferred to use NCS to manage their emotions and behaviors, thereby mitigating the effects of NLE. However, when using negative coping strategies, individuals were more likely to indulge in the virtual world, increasing the risk of IA. IA is a bad behavior due to individual maladjustment as a result of stress relief by applying NCS to NLE. Ye et al. (Ye et al., 2015) argued that when there is an accumulation of multiple risk factors for IA, the adverse effects on the individual are no longer a simple superposition of the individual risks, but lead to more serious harm to the individual. It is inferred that when middle school students experience NLE and choose to cope in a negative way, two risk factors accumulate, thus, they are more likely to become addicted to the Internet. Second, the choice of coping of middle school students may be related to their psychological development. The more they experienced, the lower their satisfaction with life, and the higher their psychological burden and negative reaction will be. Moreover, due to their immature psychological development and cognitive limitation, they may tend to choose NCS, which will lead to Internet addictive behaviors (Chen et al., 2021; Yang et al., 2021).

The proper use of the network should be part of the educational and practical work. In psychological practice, clinicians may consider coping strategies as a method to prevent or interfere with middle school students’ IA. Specifically, clinicians can encourage middle school students with internet addiction to establish healthy and positive coping styles and actively seek help from parents, friends and teachers when facing negative events, or timely seek help from professionals to reduce or avoid the use of negative coping styles and promote physical and mental health.

This study lasted for two years, from October 2018 to October 2020. Two confirmed cases of COVID-19 were found in Gannan area on January 24th, 2020. From February 13th, 2020 to October, 2020, there were no new cases and no large-scale infection and outbreak. The internet addiction rate observed in this study ranges from 2.4 to 12.3%, which may be related to the online learning of middle school students in Gannan during this period, but the details need further study.

Conclusion

Our findings indicated that NLE experienced by middle school students have a positive effect on IA, NCS partially mediate the association between NLE and IA. This study provides longitudinal research evidence for the prevention and intervention of IA among middle school students, suggesting that interventions for Internet addicted students should focus on the occurrence of NLE, to minimize the harmful effects on their physical and mental health and to help middle school students develop correct coping. It should be taken seriously to NLE and IA among the middle school students.