Skip to main content

ORIGINAL RESEARCH article

Front. Public Health, 26 January 2023
Sec. Digital Public Health
This article is part of the Research Topic New Addictions in the Era of Digitalization View all 8 articles

Zhongyong thinking (doctrine of the mean) and internet addiction: The mediation of maladaptive cognition and the moderation of subject

  • 1Department of Psychology, Normal College, Qingdao University, Qingdao, China
  • 2School of Educational Science, Xinyang Normal University, Xinyang, China
  • 3School of Marxism, Wuhan University, Wuhan, China

Based on the cognitive-behavioral model of pathological internet use, this study explored the relationship between zhongyong thinking (doctrine of the mean) and internet addiction, and examined the mediation of maladaptive cognition and the moderation of subject. Convenience sampling was used to select 1,518 college students for the questionnaire. The participants were 15–26 years old (M = 19.77; SD = 1.45), including 776 male and 742 female students. The results showed that zhongyong thinking was significantly negatively correlated with maladaptive cognition (r = −0.19, p < 0.001) and internet addiction (r = −0.14, p < 0.001). Maladaptive cognition was significantly positively correlated with internet addiction (r = 0.46, p < 0.001). After controlling for age, gender, zhongyong thinking negatively predicted internet addiction (B = −0.06, p < 0.05), maladaptive cognition positively predicted Internet addiction (B = 0.45, p < 0.001). Zhongyong thinking negatively predicted maladaptive cognition (B = −0.19, p < 0.001). Moreover, the bias-corrected bootstrapping mediation test indicated that the process by which zhongyong thinking predicted Internet addiction through maladaptive cognition was significant, indirect effect = −0.08, SE = 0.01, 95% CI = [−0.11, −0.06]. Subject has no moderating effect on the relationship between zhongyong thinking and maladaptive cognition. The interaction between zhongyong thinking and subject was not a significant predictor of maladaptive cognition (B = 0.05, p > 0. 05). The present results suggest that zhongyong thinking as a traditional Chinese wisdom can still play an important role in regulating young people's behavior in the digital age.

Introduction

The well-developed information technology has fully integrated into people's everyday lives. Although the internet brings benefits, it has repercussions especially for young people (14), for instance, internet addiction. Internet addition among young people has become a serious world wide public health concern with its prevalence estimated to be 0.8% in Iceland, 6.3% in China, and 22.2% in Iran (5, 6). An increasing body of research has revealed that young people who are addicted to the internet are more likely to experience physical and psychological difficulties (710). Specifically, young people's higher score of internet addition is positively associated with theirsleep disturbance, anxiety, depression and loneliness (7, 9, 10). Therefore, it is significant to explore and test the factors that influence internet addiction.

Previous studies have found that both environmental factors (e.g., school, family, social support, and peer interactions) and individual factors (e.g., personality, emotion, and cognition) have an impact on internet addiction (6, 11, 12). Although previous studies have been copious, few studies have examined internet addiction in relation to zhongyong thinking (doctrine of the mean), a particular way of thinking within the circle of Confucius culture (13, 14).

Zhongyong thinking indicates the tendency to consider things from different perspectives, take tactics to coordinate with other people and try to evade potential conflicts with others (15, 16). Researchers have created three inter-correlated dimensions of zhongyong thinking: multi-thinking, holism, and harmoniousness (15). Multi-thinking indicates the tendency to take manifold perspectives into consideration before making a decision in a discussion group. Holism indicates the tendency to balance between external information and internal needs and harmoniousness is using indirect interpersonal social skills to express their opinions so as not to cause conflicts. Since zhongyong thinking derives from traditional Confucius culture, it is a cultural commonality in traditional Chinese society. Although the contemporary society pools a mixture of western and Chinese culture, zhongyong thinking still epitomizes Chinese people's group thinking, determining people's attitude, way of doing and decision making. Nevertheless, the degree of holding this thinking style is of individual difference, meaning that some people may be more inclined to take up this thinking style than others.

Zhongyong thinking is specifically important for young people at university, helping them adapt more easily to campus life. Empirical studies have found that individuals high in zhongyong thinking demonstrate better social adaption, including mental health, social skill and academic achievement (1620). Young people will encounter more complicated social situations and more diverse peer types in university compared with their lives in basic educational system. University students come from different places across the country and thus their lifestyle, thinking style and value can remain divergent from one another. These differences may increase interpersonal conflicts and disrupt interpersonal relationships (21, 22). However, individuals high in zhongyong thinking may tolerant or accept these differences by reconsideration, find a balance between self needs and other needs and thus harmoniously manage the potential interpersonal tensions. Additionally, Chinese university students may have academic and career stress while zhongyong thinking can arm students with better coping skills and emotional regulation ability (20), which protect them from developing psychological issues when facing multiple stress sources.

Previous studies have shown that young people who have adaptive issues may treat the internet as a shelter, which increases the risk of they developing internet addiction (6, 11). As zhongyong thinking can help young people adapt better to campus life, individuals who score high on zhongyong thinking may have lower degree of internet addiction. Empirical evidence has also found a significantly negative correlation between zhongyong thinking and internet addiction among college students, which suggests that zhongyong thinking can be a protective factor for internet addiction (13, 14). Previous research has also found that zhongyong thinking can impact on internet addiction through the mediations of social interaction and negative emotions (13, 14). Although existing studies have partly explained why zhongyong thinking is associated with internet addiction, very few studies examine the topic in terms of cognitive characteristics.

According to the cognitive-behavioral model of pathological internet use, individual characteristics influence internet addiction through the mediating role of maladaptive cognition (23). Maladaptive cognition indicates the distorted perception that online world is better and happier than offline world and the online self is more excellent than the real self. However, individuals high in zhongyong thinking tend to adapt better to real-life situations than others (13, 14, 19, 20). Those well-adapted individuals have less maladaptive cognition, leading to a lower level of internet addiction (24). Therefore, maladaptive cognition may mediate the relationship between zhongyong thinking and internet addiction.

Although zhongyong thinking is beneficial for individual adaption, the effect may vary across different individual groups. We speculate that zhongyong thinking may play a more important role for individuals who have more negative emotions, compared to those who have less negative emotions. For example, prior evidence showed that the effect of zhongyong thinking improving task performance behavior presents larger for individuals who suffer more negative emotions (25). In addition, previous research has revealed that arts students experience more negative emotions than science students (26). Therefore, zhongyong thinking may be more helpful for arts students than for science students, as it restrains arts students' maladaptive cognition more strongly.

The present study, therefore, aim to construct a moderated mediation model to explore the relationships between zhongyong thinking and internet addiction. The first step is to examine whether maladaptive cognition mediates the indirect path between zhongyong thinking and internet addiction. The second step is to investigate whether subject moderates the indirect path between maladaptive cognition and internet addiction.

The relationship between zhongyong thinking and internet addiction

People high in zhongyong thinking usually exhibit competence in regulating their behavior, cognition and emotions. In behavioral terms, zhongyong thinking can contribute to developing innovative behavior, voice behavior, and employee performance (27). In cognitive terms, zhongyong thinking can increase creative thinking (28). In emotional terms, zhongyong thinking can increase emotional regulation and reduce negative emotions (13, 18, 20).

Young people who suffer from internet addiction cannot resists the temptation from the internet and spend excessive time on it, which result in damage to their study and life. Although the internet offers university students tremendous benefits including acquiring knowledge, expanding social circle and amending negative emotions, it brings about drawbacks including damaging physical health, consuming time and damaging real-life social interaction. Zhongyong thinking, nonetheless, emphasizes multiple perspective and holistic view, which may help young people realize both the advantages and disadvantages of the internet. In that case, they would plan their use of the internet more rational, leading to less probability of internet addiction.

Specifically, after considering both the advantages and disadvantages of the internet, young people high in zhongyong thinking may increase their time spent on instrumental matters (e.g., information collecting or online learning) and decrease time on hedonic matters (e.g., playing games or watch online videos). Compared to instrumental use, hedonic use can bring strong pleasure and flow experience, forming a negative reinforcement process on internet addiction. Numerous empirical studies have demonstrated that hedonic internet use can positively predict internet addiction, whereas instrumental use negatively predict it (2931). Therefore, zhongyong thinking may differently affect internet addiction regarding different types of internet use.

In addition, zhongyong thinking may prompt young people to control the total time they spent on the internet. Excessive internet use may trigger users' background craving of internet, which may increase the risk of internet addiction. Empirical studies have also shown that the time of internet use is positively associated with internet addiction (30, 31). Therefore, zhongyong thinking can influence internet addiction through time spent on the internet. This argument is empirically supported by previous studies (13, 14). Thereby, we proposed.

Hypothesis 1: Zhongyong thinking was negatively associated with internet addiction.

The mediation of maladaptive cognition

Although a few studies have examined the relationship between zhongyong thinking and internet addiction (13, 14), the mediating mechanisms have not been fully explored. According to the cognitive-behavioral model of pathological internet use, individual characteristics influence internet addiction through maladaptive cognition (23). Therefore, the study will examine the mediation of maladaptive cognition, a concept defined as the perception to consider the online world to be better than the real world (23).

Firstly, zhongyong thinking may decrease maladaptive cognition. On the one hand, young people high in zhongyong thinking are usually well-adaptive in offline world, which makes online world not as attractive as to those who are not so accomplishing in real life. Given their tendency to think from multiple and holistic perspectives and pay much attention to interpersonal harmony, they tend to maintain amiable social atmosphere around acquaintances and often have better interpersonal skills. As a situational factor, social interaction greatly impacts on cognition (32). In a similar vein, how successful individuals' social life in reality and on the internet determine the emergence and persistence of maladaption cognition (33). University life is usually more complicated than individual earlier life regarding the difference in young people' s values, lifestyles, ways of thinking and habits (21, 22). Such heterogeneous situations require young people to have more interpersonal skills and wisdom in dealing with potential interpersonal conflicts. Zhongyong thinking, indeed, is practical in these situations.

On the other hand, young people low in zhongyong thinking, whose social performance in real life is unsatisfactory, may have a chance to achieve social prestige in the online world. Unlike the real world, the online world has the ability to filter out people who are different from the self, rendering possible interactions within people who are highly homogeneous (4). Such similarity in the social environment increases interpersonal attraction and satisfaction (34), drawing these young people into the shelter of the internet. With regard to empirical evidence, researchers have found a negative association between zhongyong thinking and psychopathology, such as anxiety and depression (16, 18), which increase maladaptive cognition (23).

In addition, maladaptive cognition has a positive effect on internet addiction. The core features of maladaptive cognition are the overestimation of the virtual world and the devaluation of the real world (23). Individuals with a high level of maladaptive cognition think the virtual world good and comfortable, while the real world is bad and unbearable. Therefore, they will form positive outcome expectations about their online experience and then invest a lot of time and energy into the internet (23). Furthermore, the internet can provide individuals with a lot of content stimulation and various forms of activities which reinforces the use of the internet (23). However, the over-satisfaction in the virtual world may erode the agency and desire for living in the real world. Investing too much time and energy on the internet may leave individuals insufficient resources to fulfill their real-life roles, thereby harming their social, academic and living functions (23). Repeated satisfaction in the virtual world and frustration in the real world may further reinforce maladaptive cognition. Gradually, individuals may lose control of themselves online and their real life will be worsened, which will eventually develop into internet addiction. Masses of empirical studies across culture and age have found a positive association between maladaptive cognition and internet addiction (3537). Accordingly, we proposed.

Hypothesis 2: Maladaptive cognition plays a mediating role in the relationship between zhongyong thinking and internet addiction. Zhongyong thinking is positively correlated with maladaptive cognition while maladaptive cognition is negatively correlated with internet addiction.

Moderation of subject

Considering that subject is a prominent identity for university students, we assume that subject may be a moderator on the relationship between zhongyong thinking and maladaptive cognition. Some evidence in previous literature indicates that science students score higher than arts students on the openness dimension in the personality scale (38), which supports our assumption. Openness motivates young people to broaden their horizons by seeking out novel knowledge and experience which often challenge their current opinions. As a result, they are inclined to accept difference and have less prejudice and discrimination and more likely to form positive belief about people from outgroups (3941). Therefore, university students high in openness are more likely to accept different values and lifestyles, resulting in less interpersonal conflicts with people who hold different opinions. To sum up, openness plays a similar role as zhongyong thinking in coping potential interpersonal conflicts. Although zhongyong thinking reduces maladaptive cognition through decreasing interpersonal conflicts, the effect is weaker among people high in openness.

As openness has been adequate in helping science students to manage their social life, the effect of zhongyong thinking on science students' maladaptive cognition may not be as stronger. In contrast, arts student whose openness trait is less than science students, are more likely to be involved in interpersonal troubles. Therefore, zhongyong thinking can be more effective for arts students in terms of restraining maladaptive cognition.

Based on the above argument, we propose hypothesis H3.

Subject moderates the relationship between zhongyong thinking and maladaptive cognition. Zhongyong thinking style has a greater impact on maladaptive cognition for arts students than for science students.

The present study

The purpose of this study was threefold. First, we examined whether zhongyong thinking predicts adolescent internet addiction by proposing Hypothesis 1.

Hypothesis 1: Zhongyong thinking was negatively associated with internet addiction.

Subsequently, we tested a mediator model to examine how zhongyong thinking is correlated to internet addiction by proposing Hypothesis 2.

Hypothesis 2: Maladaptive cognition plays a mediating role in the relationship between zhongyong thinking and internet addiction. Zhongyong thinking is positively correlated with maladaptive cognition while maladaptive cognition is negatively correlated with internet addiction.

Finally, we examined whether subject moderated the relationship between zhongyong thinking and maladaptive cognition, by advancing Hypotheses 3.

Hypothesis 3: Subject moderates the relationship between zhongyong thinking and maladaptive cognition. Zhongyong thinking style has a greater impact on maladaptive cognition for arts students than for science students.

Please see the hypothetical model in Figure 1.

FIGURE 1
www.frontiersin.org

Figure 1. The hypothetical model.

Materials and methods

Participants

A convenience sample was taken and 1,575 college subject were selected from five universities in Henan province, one university in Jiangsu, one university in Shandong and one university in Anhui. Five participants refused to submit their answers. A total of 1,518 valid questionnaires was obtained after deleting the 5 withdrawers' answers along with 52 regular and incomplete answers. The invalid answers were deleted according to the order as follows: 34 regular answers and 23 incomplete answers, including 1 from gender, 1 from age, 1 from subject, 11 from zhongyong thinking, 6 from maladaptive cognition and 3 from internet addiction. Subject were aged 15–26 years (M = 19.77; SD = 1.45), of whom 776 were male and 742 were female; 403 were arts students and 1,115 were science students; 710 were freshmen, 413 were sophomores, 292 were juniors, and 103 were seniors.

Measures

Zhongyong thinking

Zhongyong thinking was measured by the Chinese version of the Zhongyong thinking Style Scale (15). This scale consists of 13-items rated on a five-point scale (1 = “strongly disagree,” 7 = “strongly agree”). Examples of items were as follows “I am used to think about things in multiperspectives,” “I seek a compromise between my opinions and others,” “When making decisions, I tend to consider the overall atmosphere and try to maintain harmony.” The scale has shown acceptable reliability and validity (16, 18, 20, 25). In this study, the Cronbach's alpha of the total scale was α = 0.94.

Maladaptive cognition

Maladaptive cognition was measured by a maladaptive cognition scale in Chinese (23, 42). This scale consists of 4 items, for example, “I am worthless offline, but online I am someone.” Participants evaluated the items on a 5-point Likert scale ranging from 1 = Never to 5 = Always. The scale has been commonly used among Chinese participants and has good reliability and validity (33, 42, 43). In this study, the Cronbach's alpha of the total scale was α = 0.92.

Internet addiction

Internet addiction was measured by the Chinese version of the internet addiction scale (44), which includes 8 items. A 5-point Likert scale was adopted (1 = not at all true to 6 = completely true). The scale has been demonstrated to has good reliability and validity on Chinese samples (13, 14). In this study, the Cronbach's alpha of the total scale was α = 0.89.

Statistical analyses

First, before the test, we employed several approaches toreduce common method bias, including participant anonymity, rearrangement, and reverse expression of items. In addition, we employed Harman's single factor test to determine whether common method bias exists in this study. The results showed a multiple-factor structure, and that the largest loading factor only accounted for 33.23% of the total variance, far less than the 40.00% threshold, suggesting no significant common method bias in this study (45).

Second, descriptive analysis was performed to examine the participants' characteristics regarding the studied variables, and Pearson correlation analysis was performed to examine the correlations between variables.

Third, the present study used PROCESS version 3 to test the mediating and moderated model (46). Given that PROCESS Marco does not provide standardized regression coefficients, we calculated z-scores before data analyses. We generated 5,000 bootstrapped samples to approximate the confidence interval (CI) of the indirect effect based on the original sample (n = 1,518). A 95% bias-corrected accelerated CI without zero indicates statistical significance. In addition, the age and gender of the participants were controlled in the analyses.

Results

Examination of the measurement model

We assessed the discriminant and convergent validity of the measurement model following previous research (47). We evaluated the convergent validity for all latent measures using satisfactory standardized factor loadings. All factor loadings ranged from 0.56 to 0.90, reaching the criterion of 0.40 or above (48). We included three criteria for the evaluation of convergent validity: Cronbach's alpha value, composite reliability (CR), and the average variance extracted (AVE). As demonstrated in Appendix, the alpha values for all variables ranged from 0.89 to 0.94, reaching the criterion of 0.70 or above (49). The CR values ranged from 0.89 to 0.94, agreeing with Hair et al. (47) criterion of 0.70 or above (47). Finally, the AVE values of all variables ranged from 0.51 to 0.74, reaching the criterion of 0.36 or above (50). Therefore, all of the results satisfied the criteria for convergent validity. Additionally, we evaluated divergent validity using the AVE–SV comparison (49). As demonstrated in Appendix, all of the square roots of the AVE were higher than the correlation among the constructs, satisfying the criteria for divergent validity (49).

Preliminary analyses

Table 1 presents the Pearson correlations, means, and standard deviations of all variables. As Table 1 indicates, zhongyong thinking was negatively correlated with maladaptive cognition and internet addiction. Maladaptive cognition was positively correlated with internet addiction.

TABLE 1
www.frontiersin.org

Table 1. Correlation coefficients, means, and standard deviations of variables.

Testing a moderated mediation model

The analysis of mediated effects with moderation is performed in two steps, first testing the simple mediated model and then the mediated model with moderation.

As a first step, the simple mediation model is tested first. Among the mediated models with adjustment, the simple mediated model is the benchmark model, so it is tested first (46). We used Model 4 of PROCESS (46) to examine the possible association between zhongyong thinking and internet addiction as well as the possible mediating effect of maladaptive cognition. The results of the mediation analysis are presented in Table 2 and Figure 2. After controlling for age, gender, we first found that Zhongyong thinking negatively predicted internet addiction B = −0.06, p < 0.05, maladaptive cognition positively predicted internet addiction, B = 0.45, p < 0.001 (Equation 1). Second, zhongyong thinking negatively predicted maladaptive cognition, B = −0.19, p < 0.001 (Equation 2). Finally, the bias-corrected bootstrapping mediation test indicated that the process by which zhongyong thinking predicted internet addiction through smaladaptive cognition was significant, indirect effect = −0.08, SE = 0.01, 95% CI = [−0.11, −0.06]. The results of the mediation analysis support H1 and H2.

TABLE 2
www.frontiersin.org

Table 2. Mediation of maladaptive cognition.

FIGURE 2
www.frontiersin.org

Figure 2. The Integrated Model. The values in parentheses are the total effect of Zhongyong thinking on Internet addiction. Path values are the path coefficients, *p < 0.05, ***p < 0.001.

In the second step, the test has a moderating mediating role. Since the moderating variable regulates the first half of the mediating effect, mode 7 is chosen for testing. The results of the moderation analysis can be found in Table 3. Regression analyses indicated that zhongyong thinking negatively predicted maladaptive cognition (B = −0.19, p < 0.001) and subject was not a significant predictor of maladaptive cognition (B = −0.04, p > 0. 05), while the interaction between zhongyong thinking and subject was not a significant predictor of maladaptive cognition (B = 0.05, p > 0. 05), with a 95% confidence interval of [−0.08, 0.19] and contain 0. The results indicate that subject has no moderating effect on the relationship between maladaptive cognition and zhongyong thinking, and hypothesis H3 was not tested.

TABLE 3
www.frontiersin.org

Table 3. Tests for mediating effects with moderation.

Discussion

The relationship between zhongyong thinking and internet addiction

This study found a negative relationship between zhongyong thinking and internet addiction, which is consistent with the results in previous studies (13, 14). The present results suggest that zhongyong thinking as a traditional Chinese wisdom can still play an important role in regulating young people's behavior in the digital age.

Although this study sampled from Chinese population, the results can communicate to a larger audience as internet addiction has long been a social and educational problem in other Asian countries deeply influenced by Confucius culture (17, 27, 51), such as Japan, Korea and Malaysia (6, 8). Empirical studies have demonstrated that zhongyong thinking has a significantly positive impact on mental health of young people from East Asia (17), suggesting that the present findings may adapt to these countries.

Moreover, this study may provide a better knowledge of intervening internet addiction in western society. Although zhongyong thinking as a concept does not exist in western culture, social mindfulness share many similarities with zhongyong thinking regarding theoretical overtones and functioning mechanism (52). For example, the two concepts both focus on social value, underlining the attention on other people's need. Zhongyong thinking can increase social support, decrease interpersonal conflicts and increase prosocial behavior within a group (13, 14, 53). Similarly, social mindfulness also can help individuals achieve social applaud and trust, which subsequently increases individual prosocial behavior (52, 54). Given these similarities, we speculate that social mindfulness may influence internet addiction.

The mediation of maladaptive cognition

This present study found that maladaptive cognitive mediated the relationship between zhongyong thinking and internet addiction. Young people high in zhongyong thinking may be more easily to integrate into the social environment of a complex campus and have better social experience in everyday life. In comparison, individuals low in zhongyong thinking are likely to experience frustration in a diverse campus and become overly dependent on the internet to provide social need satisfaction, ultimately increasing the risk of maladaptive cognition and internet addiction.

We introduced a theoretical perspective to explain why zhongyong thinking decreases the risk of internet addiction and illustrate its mediating mechanism. From the perspective of cognitive-behavioral model of pathological internet use, distal individual characteristics can influence internet addiction through proximal factors, for example, maladaptive cognition (23). This model provides us a way of understanding the functioning mechanism underlying the relationship between zhongyong thinking and internet addiction, which has barely been investigated in previous research. Past research examining the mediation of the relationship between zhongyong thinking and addiction has mostly focused on distal factors such as social support, peer conflict and loneliness (13, 14) while proximal factors were hardly discussed. As a proximal factor, maladaptive cognition is more closely linked to internet addiction in terms of etiology compared with previously studied variables. Examining proximal factors can deepen our understanding regarding how zhongyong thinking affects internet addiction and offer suggestions for relevant interventions.

Intervention practitioners often choose to consider a mediating factor instead of directly intervening the dependent variable. With respect to internet addiction, interventions for maladaptive cognition has advantages over social support, peer conflict, and loneliness. Additionally, maladaptive cognition has been demonstrated to be effective in intervening internet addiction and existing maladaptive cognitive intervention programs for internet addiction are systematic and mature and conducive to widespread application (55). Moreover, the effect of interventions for maladaptive cognition was more individually based, whereas the effect of interventions for social interaction and loneliness also counts on the social environment.

The cognitive-behavioral model of pathological internet use emphasizes the importance of maladaptive cognition and the mediating role in the relationship between individual characteristics and internet addiction. Although copious previous studies have demonstrated the model, most of them focus on individual characteristics of cultural universality, for example, personality and social anxiety (37, 56, 57), and only one study have noticed individual characteristics of cultural particularity (58). The present study expanded the cultural scope of the model by investigating zhongyong thinking, a characteristic of traditional Chinese culture, influencing Internet addiction through maladaptive cognition. Future research could further examine whether there are other culturally distinctive factors which influences internet addiction and maladaptive cognition, further enhancing the cultural depth of the cognitive-behavioral model of pathological internet use.

Moderation of subject

The results of moderation analysis indicated that subject can not significantly moderate the relationship between zhongyong thinking and maladaptive cognition, which failed to demonstrate our Hypothesis 3. For both arts students and science students, zhongyong thinking can reduce their maladaptive cognition. Our previous assumption was that the effect might be significantly weaker for science students than for arts students because empirical research found that science students scored higher on openness scale and had less interpersonal conflicts, which protected them from developing maladaptive cognition.

However, science students' lower scores on extroversion and received social support (38, 59) may play a confounding role in our hypothetical moderation model, leading zhongyong thinking an important factor to reduce maladaptive cognition both for science students and arts students. Individuals low on extroversion rarely start a social conversation and they are less likely to reveal themselves during social interaction (60, 61). These traits reduce their odds of obtaining social support (59). Therefore, in light of extroversion, science students may be more difficult than arts students to receive social support. Zhongyong thinking, however, bears the features of taking others' needs into consideration and emphasizing the harmony of relationship. With these traits, science students will be more likely to receive social support (13), which subsequenty reduces their maladaptive cognition (62).

Limitations and implications

The first limitation lies on the fact that we merely studied young people from mainland China, rendering it impossible to generalize the results to a more general population. As zhongyong thinking also exists or even prevails in other east Asian countries (17, 27, 51), future studies can test the results among young people from these places. The second limitation is the homologous data, which may cause shared variance among the researched variables and exaggerated the effects between variables. Therefore, researchers can collect data from multiple sources of participants, for example, parents and peers in the future. The third limitation is the cross-sectional design of the current study, which renders it impossible to draw casual conclusions. Longitudinal studies can be conducted to illustrate the directions between variables in this research.

More practical implications could be drawn from this study. First, the result that zhongyong thinking can be effective in reducing internet addiction suggests that practitioners intervene in internet addiction by strengthening zhongyong thinking among college students. Although there are many interventions and programs for internet addiction to date (55), hardly any of them involves Chinese cultural elements. According to an intervention study, mental health and suicide intervention programs based on zhongyong thinking have shown to be effective. Compared to general group counseling, group counseling based on zhongyong thinking can be more effective in reducing depression among college students (16). Dialectical behavior therapy in relation to zhongyong thinking has also been demonstrated to be effective in alleviating participants' psychological symptoms (63).

Data availability statement

The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.

Ethics statement

The studies involving human participants were reviewed and approved by the Research Ethics Committee of School of Educational Science, Xinyang Normal University. Written informed consent to participate in this study was provided by the participants' legal guardian/next of kin.

Author contributions

HW, WC, and HX designed the work. HW, HX, and LL provided the method. HW, WC, and HX collected the data and analyzed the data results and drafted the manuscript. WC and LL revised the manuscript. All authors contributed to the article and approved the submitted version.

Conflict of interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Publisher's note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

References

1. Gergely F. Internet addiction. Life. (2022) 12:861. doi: 10.3390/life12060861

PubMed Abstract | CrossRef Full Text | Google Scholar

2. Han L, Sun R, Gao F, Zhou Y, Jou M. The effect of negative energy news on social trust and helping behavior. Comput Hum Behav. (2019) 92:128–38. doi: 10.1016/j.chb.2018.11.012

CrossRef Full Text | Google Scholar

3. Han L, Xiao M, Jou M, Hu L, Sun R, Zhou Z, et al. The long-term effect of media violence exposure on aggression of youngsters. Comput Hum Behav. (2020) 106:106257. doi: 10.1016/j.chb.2020.106257

CrossRef Full Text | Google Scholar

4. Gosling SD, Mason W. Internet research in psychology. Annu Rev Psychol. (2015) 66:877–902. doi: 10.1146/annurev-psych-010814-015321

PubMed Abstract | CrossRef Full Text | Google Scholar

5. Petry NM, Zajac K, Ginley MK. Behavioral addictions as mental disorders: to be or not to be? Annu Rev Clin Psychol. (2018) 14:399–423. doi: 10.1146/annurev-clinpsy-032816-045120

PubMed Abstract | CrossRef Full Text | Google Scholar

6. Kuss DJ, Kristensen AM, Lopez-Fernandez O. Internet addictions outside of Europe: a systematic literature review. Comput Hum Behav. (2021) 115:106621. doi: 10.1016/j.chb.2020.106621

PubMed Abstract | CrossRef Full Text | Google Scholar

7. Acikgoz A, Acikgoz B, Acikgoz O. The effect of internet addiction and smartphone addiction on sleep quality among Turkish adolescents. PeerJ. (2022) 10:12876. doi: 10.7717/peerj.12876

PubMed Abstract | CrossRef Full Text | Google Scholar

8. Lai CM, Mak KK, Watanabe H, Jeong J, Kim D, Bahar N, et al. The mediating role of Internet addiction in depression, social anxiety, and psychosocial well-being among adolescents in six Asian countries: a structural equation modelling approach. Public Health. (2015) 129:1224–36. doi: 10.1016/j.puhe.2015.07.031

PubMed Abstract | CrossRef Full Text | Google Scholar

9. Li G, Hou G, Yang D, Jian H, Wang W. Relationship between anxiety, depression, sex, obesity, and internet addiction in Chinese adolescents: a short-term longitudinal study. Addict Behav. (2019) 90:421–7. doi: 10.1016/j.addbeh.2018.12.009

PubMed Abstract | CrossRef Full Text | Google Scholar

10. Tian Y, Qin N, Cao S, Gao F. Reciprocal associations between shyness, self-esteem, loneliness, depression and Internet addiction in Chinese adolescents. Addict Res Theory. (2021) 29:98–110. doi: 10.1080/16066359.2020.1755657

CrossRef Full Text | Google Scholar

11. Lozano-Blasco R, Robres AQ, Sanchez AS. Internet addiction in young adults: a meta-analysis and systematic review. Comput Hum Behav. (2022) 130:107201. doi: 10.1016/j.chb.2022.107201

PubMed Abstract | CrossRef Full Text | Google Scholar

12. Zewde EA, Tolossa T, Tiruneh SA, Azanaw MM, Yitbarek GY, Admasu FT, et al. Internet addiction and its associated factors among African high school and university students: Systematic review and meta-analysis. Front Psychol. (2022) 13:847274. doi: 10.3389/fpsyg.2022.847274

PubMed Abstract | CrossRef Full Text | Google Scholar

13. Ding Q, Zhang Y, Wei H, Hu W. Zhongyong thinking style and internet addiction of college students: serial mediating effect of social support and loneliness. Stud Psychol Behav. (2019) 17:553–60. doi: 10.3969/j.issn.1672-0628.2019.04.015

CrossRef Full Text | Google Scholar

14. Wei H, Li Q, Zhou ZK, Ding Q, Xiong J. Zhongyong thinking style and Internet addiction of college students: the role of peer conflict and gender. Psychol Develop Edu. (2021) 37:66874. doi: 10.16187/j.cnki.issn1001-4918.2021.05.07

CrossRef Full Text | Google Scholar

15. Wu JH, Lin YZ. Development of a Zhong-yong thinking style scale. Indig Psychol Res Chin Soc. (2005) 24:247–300. doi: 10.6254/2005.24.247

CrossRef Full Text | Google Scholar

16. Yang X, Zhang P, Zhao J, Zhao J, Wang J, Chen Y, et al. Confucian culture still matters the benefits of zhongyong thinking (Doctrine of the Mean) for mental health. J Cross-Cult Psychol. (2016) 47:1097–113. doi: 10.1177/0022022116658260

CrossRef Full Text | Google Scholar

17. Fang L, Kwon S, Moon M. The effects of athletes' zhongyong attitude on psychological well-being : a study by country of Korea and China. Kor J Sports Sci. (2022) 31:403–15. doi: 10.35159/kjss.2022.10.31.5.403

CrossRef Full Text | Google Scholar

18. Hou Y, Xiao R, Yang X, Chen Y, Zhang X. Parenting style and emotional distress among Chinese college students: a potential mediating role of the zhongyong thinking style. Front Psychol. (2020) 11:1774. doi: 10.3389/fpsyg.2020.01774

PubMed Abstract | CrossRef Full Text | Google Scholar

19. Lan X, Ma C, Ma Y. A person-centered investigation of adolescent psychosocial and academic adjustment: the role of peer attachment and Zhong-Yong thinking. Child Indic Res. (2021) 14:1479–500. doi: 10.1007/s12187-021-09807-2

CrossRef Full Text | Google Scholar

20. Zhou S, Li X. Zhongyong thinking style and resilience capacity in chinese undergraduates: the chain mediating role of cognitive reappraisal and positive affect. Front Psychol. (2022) 13:814039. doi: 10.3389/fpsyg.2022.814039

PubMed Abstract | CrossRef Full Text | Google Scholar

21. van Osch YM, Breugelmans SM. Perceived intergroup difference as an organizing principle of intercultural attitudes and acculturation attitudes. J Cross-Cult Psychol. (2012) 43:801–21. doi: 10.1177/0022022111407688

CrossRef Full Text | Google Scholar

22. Wetherell G, Benson OS, Reyna C, Brandt MJ. Perceived value congruence and attitudes toward international relations and foreign policies. Basic Appl Soc Psych. (2015) 37:3–18. doi: 10.1080/01973533.2014.973108

CrossRef Full Text | Google Scholar

23. Davis RA. A cognitive–behavioral model of pathological Internet use. Comput Hum Behav. (2001) 17:187–95. doi: 10.1016/S0747-5632(00)00041-8

CrossRef Full Text | Google Scholar

24. Wang L, Li M, Xu Y, Yu C. Predicting adolescent internet gaming addiction from perceived discrimination, deviant peer affiliation and maladaptive cognitions in the chinese population: a 2-year longitudinal study. Int J Environ Res Public Health. (2022) 19:3505. doi: 10.3390/ijerph19063505

PubMed Abstract | CrossRef Full Text | Google Scholar

25. Sun X, Yan M, Chu X. Passive mood and work behavior: the cross-level mediating effect of zhong-yong thinking style. Acta Psychol Sin. (2014) 46:1704–18. doi: 10.3724/SP.J.1041.2014.01704

CrossRef Full Text | Google Scholar

26. Montgomery K. Your future with madness: the relationship between mental illness and career goals. North Texas J Undergraduate Res. (2019) 1:1–7. doi: 10.12794/journals.ntjur.v1i1.76

CrossRef Full Text | Google Scholar

27. Ning B, Omar R, Ye Y. Zhong-Yong thinking and employees' behaviour at the workplace: setting a research agenda. Asian J Bus Res. (2020) 10:154–72. doi: 10.14707/ajbr.200095

CrossRef Full Text | Google Scholar

28. Zhou Z, Zhang H, Li M, Sun C, Luo H. The effects of zhongyong thinking priming on creative problem-solving. J Creat Behav. (2021) 55:145–53. doi: 10.1002/jocb.441

PubMed Abstract | CrossRef Full Text | Google Scholar

29. Lei L, Yang Y, Liu M. The relationship between adolescents' neuroticism, internet service preference? and internet addiction. Acta Psychol Sin. (2006) 38:375–81.

Google Scholar

30. Khang H, Kim JK, Kim Y. Self-traits and motivations as antecedents of digital media flow and addiction: The Internet, mobile phones, and video games. Comput Hum Behav. (2013) 29:2416–24. doi: 10.1016/j.chb.2013.05.027

CrossRef Full Text | Google Scholar

31. Zhang JT, Chen C, Wang LJ, Liu L, Liu FE, Zhao FC, et al. The relationship between time spent online and internet addiction among chinese college freshmen: A mediated moderation model. Acta Psychol Sin. (2014) 46:1521–33. doi: 10.3724/sp.j.1041.2014.01521

CrossRef Full Text | Google Scholar

32. Beck AT, Haigh EA. Advances in cognitive theory and therapy: The generic cognitive model. Annu Rev Clin Psychol. (2014) 10:1–24. doi: 10.1146/annurev-clinpsy-032813-153734

PubMed Abstract | CrossRef Full Text | Google Scholar

33. Wei H, Wu N, Wang T, Zhou Z, Cui N, Xu L, et al. Be loyal but not addicted: Effect of online game social migration on game loyalty and addiction. J Consum Behav. (2017) 16:343–51. doi: 10.1002/cb.1637

CrossRef Full Text | Google Scholar

34. Montoya RM, Horton RS, Kirchner J. Is actual similarity necessary for attraction? A meta-analysis of actual and perceived similarity. J Soc Pers Relatsh. (2008) 25:889–922. doi: 10.1177/0265407508096700

CrossRef Full Text | Google Scholar

35. Forrest CJ, King DL, Delfabbro PH. Maladaptive cognitions predict changes in problematic gaming in highly-engaged adults: a 12-month longitudinal study. Addict Behav. (2017) 65:125–30. doi: 10.1016/j.addbeh.2016.10.013

PubMed Abstract | CrossRef Full Text | Google Scholar

36. Liu RD, Hong W, Ding Y, Oei TP, Zhen R, Jiang S, et al. Psychological distress and problematic mobile phone use among adolescents: the mediating role of maladaptive cognitions and the moderating role of effortful control. Front Psychol. (2019) 10:1589. doi: 10.3389/fpsyg.2019.01589

PubMed Abstract | CrossRef Full Text | Google Scholar

37. Zhou N, Geng X, Du H, Wu L, Xu J, Ma S, et al. Personality and problematic internet use among Chinese college students: the mediating role of maladaptive cognitions over internet use. Cyberpsychol Behav Soc Network. (2018) 21:719–26. doi: 10.1089/cyber.2018.0279

PubMed Abstract | CrossRef Full Text | Google Scholar

38. Coenen J, Borghans L, Diris R. Personality traits, preferences and educational choices: a focus on STEM. J Econ Psychol. (2021) 84:102361. doi: 10.1016/j.joep.2021.102361

CrossRef Full Text | Google Scholar

39. Albrecht A, Dilchert S, Deller J, Paulus FM. Openness in cross-cultural work settings: a multicountry study of expatriates. J Pers Assess. (2014) 96:64–75. doi: 10.1080/00223891.2013.821074

PubMed Abstract | CrossRef Full Text | Google Scholar

40. Brandt MJ, Chambers JR, Crawford JT, Wetherell G, Reyna C. Bounded openness: the effect of openness to experience on intolerance is moderated by target group conventionality. J Pers Soc Psychol. (2015) 109:549–68. doi: 10.1037/pspp0000055

PubMed Abstract | CrossRef Full Text | Google Scholar

41. Ng DX, Lin PK, Marsh NV, Chan KQ, Ramsay JE. Associations between openness facets, prejudice, and tolerance: a scoping review with meta-analysis. Front Psychol. (2021) 12:707652. doi: 10.3389/fpsyg.2021.707652

PubMed Abstract | CrossRef Full Text | Google Scholar

42. Ding Q, Tang Y, Wei H, Zhang Y, Zhou Z. The relationship between relative deprivation and online gaming addiction in college students: a moderated mediation model. Acta Psychol Sin. (2018) 50:104150. doi: 10.3724/sp.j.1041.2018.01041

CrossRef Full Text | Google Scholar

43. Shen X, Xie X, Wu S. Do adolescents addict to internet games after being phubbed by parents? The roles of maladaptive cognition and self-esteem. Curr Psychol. (2022) 1–13. doi: 10.1007/s12144-022-03255-z

CrossRef Full Text | Google Scholar

44. Young KS, Abreu N, De CN. Internet Addiction: A Handbook and Guide to Evaluation and Treatment. New York, NY: John Wiley and Sons (2010).

Google Scholar

45. Podsakoff PM, MacKenzie SB, Podsakoff NP. Sources of method bias in social science research and recommendations on how to control it. Annu Rev Psychol. (2012) 63:539–69. doi: 10.1146/annurev-psych-120710-100452

PubMed Abstract | CrossRef Full Text | Google Scholar

46. Hayes AF. Introduction to Mediation, Moderation, and Conditional Process Analysis: A Regression-Based Approach. New York, NY: Guilford publications (2013).

Google Scholar

47. Hair JF, Black WC, Babin BJ, Anderson RE. Multivariate Data Analysis (ed. 7th). Essex: Pearson Education Limited (2014).

Google Scholar

48. Brown TA. Confirmatory Factor Analysis for Applied Research. New York, NY: Guilford Publications (2015).

Google Scholar

49. Fornell C, Larcker DF. Evaluating structural equation models with unobservable variables and measurement error. J Mark Res. (1981) 18:39–50. doi: 10.1177/002224378101800313

CrossRef Full Text | Google Scholar

50. Chin WW. Commentary: Issues and opinion on structural equation modeling. Manag Inform Sys Quart. (1998) 3:7–16.

Google Scholar

51. Kim S, Baek M. A Religious approach to the “zhongyong”: With a focus on western translators and korean confucians. J Korean Relig. (2015) 6:27–60. doi: 10.1353/jkr.2015.0015

CrossRef Full Text | Google Scholar

52. Van Doesum NJ, Van Lange DA, Van Lange PA. Social mindfulness: skill and will to navigate the social world. J Pers Soc Psychol. (2013) 105:86–103. doi: 10.1037/a0032540

PubMed Abstract | CrossRef Full Text | Google Scholar

53. Ning B, Omar R, Ye Y, Ting H, Ning M. The role of Zhong-Yong thinking in business and management research: a review and future research. Agenda. (2021) 27:150–79. doi: 10.1080/13602381.2021.1857956

CrossRef Full Text | Google Scholar

54. Van Doesum NJ, Murphy RO, Gallucci M, Aharonov-Majar E, Athenstaedt U, Au WT, et al. Social mindfulness and prosociality vary across the globe. Proc Nat Acad Sci. (2021) 118:e2023846118. doi: 10.1073/pnas.2023846118

PubMed Abstract | CrossRef Full Text | Google Scholar

55. Young KS, Abreu, De CN. Internet addiction: A Handbook and Guide to Evaluation and Treatment. John Wiley and Sons (2010).

Google Scholar

56. Mai Y, Hu J, Yan Z, Zhen S, Wang S, Zhang W, et al. Structure and function of maladaptive cognitions in Pathological Internet Use among Chinese adolescents. Comput Hum Behav. (2012) 28:2376–86. doi: 10.1016/j.chb.2012.07.009

CrossRef Full Text | Google Scholar

57. Zhang H, Li D, Xian L. Temperament and problematic internet use in adolescents: a moderated mediation model of maladaptive cognition and parenting styles. J Child Fam Stud. (2015) 24:1886–97. doi: 10.1007/s10826-014-9990-8

CrossRef Full Text | Google Scholar

58. Wei H, Duan H, Ding Q, Zhou Z. Filial piety comes first? The relationship between filial piety belief and internet addiction of college students. Psychol Develop Edu. (2019) 35:407. doi: 10.16187/j.cnki.issn1001-4918.2019.01.05

CrossRef Full Text | Google Scholar

59. Olawa BD, Idemudia ES. The extraversion-neuroticism and geriatric depression relations: do social engagements and social supports have roles to play? Heliyon. (2020) 6:e5719. doi: 10.1016/j.heliyon.2020.e05719

PubMed Abstract | CrossRef Full Text | Google Scholar

60. Rammstedt B, John OP. Measuring personality in one minute or less: a 10-item short version of the big five inventory in English and German. J Res Pers. (2007) 41:203–12. doi: 10.1016/j.jrp.2006.02.001

CrossRef Full Text | Google Scholar

61. Woodcock A, Graziano WG, Branch SE, Habashi MM, Ngambeki I, Evangelou D, et al. Person and thing orientations: psychological correlates and predictive utility. Soc Psychol Personal Sci. (2013) 4:117–24. doi: 10.1177/1948550612444320

CrossRef Full Text | Google Scholar

62. Zhou HL, Jiang HB, Zhang B, Liang HY. Social anxiety, maladaptive cognition, mobile phone addiction, and perceived social support: A moderated mediation model. J Psychol Afr. (2021) 31:248–53. doi: 10.1080/14330237.2021.1927354

CrossRef Full Text | Google Scholar

63. Yang X, Liu D, Wang Y, Chen Y, Chen W, Yang C, et al. Effectiveness of Zhong-Yong thinking based dialectical behavior therapy group skills training versus supportive group therapy for lowering suicidal risks in Chinese young adults: a randomized controlled trial with a 6-month follow-up. Brain Behav. (2020) 10:1–14. doi: 10.1002/brb3.1621

PubMed Abstract | CrossRef Full Text | Google Scholar

Appendix

TABLE A1
www.frontiersin.org

Table A1. Validity and reliability of latent variable constructs.

TABLE A2
www.frontiersin.org

Table A2. The item of each variable.

Keywords: maladaptive cognition, internet addiction, cognitive behavioral model of pathological internet use, subject, zhongyong thinking

Citation: Wei H, Xu H, Chen W and Lu L (2023) Zhongyong thinking (doctrine of the mean) and internet addiction: The mediation of maladaptive cognition and the moderation of subject. Front. Public Health 10:1045830. doi: 10.3389/fpubh.2022.1045830

Received: 27 September 2022; Accepted: 28 December 2022;
Published: 26 January 2023.

Edited by:

Gergely Feher, University of Pécs, Hungary

Reviewed by:

Yibo Wu, Peking University, China
Hui Li, Shanghai Normal University, China

Copyright © 2023 Wei, Xu, Chen and Lu. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Wu Chen, yes 415785283@qq.com

Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.