Network structure of mobile phone addiction and anxiety symptoms among rural Chinese adolescents

In recent decades, the use of mobile phone has brought great convenience to people’s life, and the number of mobile phone user are constantly increasing. As of August 2022, the size of China’s mobile Internet users has reached 10.47 billion People, where children and adolescents aged 10 ~ 19 account for 13.5% of the total Internet population [1]. Teenagers are one of main groups of mobile phone users, which are also the most vulnerable victims to the mobile phone addiction [2]. According to relevant surveys, the prevalence of problematic smartphone use among adolescents rose from 6.3% [3] in 2011 to 16% [4] in 2016, which suggests mobile phone addiction among adolescents need urgent attention.

Mobile phone addiction is considered to be an important cause of various psychological and behavioral adjustment problems, especially in adolescents [5]. In recent years, there have been an increasing number of studies on mobile phone addiction among rural adolescents [6, 7]. Interestingly, one representative study found that although there are fewer Internet resources in rural areas, the rate of Internet addiction among rural teenagers is significantly higher than that in urban areas [8]. Several studies have also confirmed that rural areas are a significant predictor of mobile phone addiction [9‐11]. However, some problems caused by mobile phone addiction, such as poor academic performance and irrational procrastination, will lead to great academic distress for adolescents [12]. Also, excessive use of mobile phones is more likely to cause headaches, anxiety, lack of concentration and poor sleep quality [13].

Among the many problems caused by mobile phone addiction, the emergence of anxiety symptoms is particularly noteworthy. A cross-sectional study in China found that the prevalence of anxiety among adolescents increased significantly from 2016 to 2020 [14], which brought about the interference of sleep, relaxation and enjoyment of life [15]. It is worth noting that there seem to be a bidirectional relationship between mobile phone addiction and anxiety symptoms [16]. Since mobile phones can alleviate negative emotions, anxious individuals become increasingly dependent on them, eventually leading to addiction [17, 18]. In turn, excessive mobile phone dependence makes addicts feel scared and anxious whenever they are away from their phones [16, 19]. The cognitive-behavioral model argues that an individual’s cognition and emotions could be affected by behavioral problems [20], which indicated those who have mobile phone addiction are more likely to experience high levels of tension and anxiety [21]. Gender differences in psychological distress have also been the focus of relevant research [22]. On the one hand, due to biological differences between men and women, such as hormones and cortisol levels, this may be reflected in emotions and behavior [23]. Women may suffer greater sadness and anxiety than males do, however, since they are more sensitive to stress and pain [24]. Therefore, there is also a need for research on gender differences.

At present, the investigation of mobile phone addiction and anxiety symptoms of rural adolescents is obviously insufficient. Previous studies mostly discussed mobile phone addiction and anxiety as two independent individuals [25], without adequately analyzing their internal mechanisms and relationships. However, we wish to focus on the network structure (i.e., the web of relationships between symptoms) and its effect on the network state (i.e., the activation of symptoms). The network analysis approach fits our needs exactly, allowing us to consider mental health as an emergent property of the interaction of multiple symptoms [26, 27], and the symptom network composed of the various symptoms of the disorder provides rich visual information that allows us to understand the co-morbidity between different mental disorders [28]. Therefore, this study was the first to use network analysis to explore the association between mobile phone addiction and anxiety symptoms, determine that intervention can alleviate the most central (most influential) symptoms of anxiety and mobile phone addiction in rural adolescents, and investigate the relationship between central symptoms and sleep quality.

Of the 1920 adolescents included in the network, the mean age was 16.28 (Standard Deviation (SD) = 1.70)) years; 837 (43.59%) of them were male; the mean GAD total score was 4.40 (SD = 4.90) and a mean MPA total score was 38.34 (SD = 15.21). The demographic characteristics of the participants are shown in Table 1. The scores for each item on mobile phone addiction and anxiety symptoms are listed in Supplementary Table 1.

This is a network analysis study on mobile phone addiction and anxiety symptoms among rural Chinese adolescents. In this study, we aimed to examine the relationship between mobile phone addiction and anxiety symptoms through network analysis to determine the central symptoms of this network model and the prediction of highly central nodes on sleep quality. The results of the analysis showed that nodes’ Failure to cut down the time (MPA6), Anxiety if not used for some time (MPA10), and Alleviate loneliness (MPA14) were the most influential symptoms in the mobile phone addiction-anxiety network. The bridge symptoms connecting mobile phone addiction and anxiety symptoms are nodes Irritability (GAD6), Feeling afraid (GAD7), Nervousness (GAD1), and Anxiety if not used for some time (MPA10). In addition, high-strength nodes in the mobile phone addiction-anxiety symptom network were not predictive of sleep quality in rural adolescents.

The most significant symptoms in the mobile phone addiction-anxiety symptom network are concentrated in the nodes of mobile phone addiction, such as node Failure to cut down the time. This may be related to weaker self-control. Numerous studies examined the relationship between self-control and mobile phone addiction, and mobile phone addiction and found that mobile phone addiction has a high correlation with self-control [48‐50]. These suggest that the lower the self-control, the greater the likelihood of mobile phone addiction [51, 52]. The more serious the mobile phone addiction is, the more the interpersonal problems of the individual, and then the individual’s anxiety will be induced [53]. Moreover, the features of the phone itself and the Internet access it provides can alleviate anxiety [54], so the more anxious individuals will be unable to resist the temptation of the phone because it is like a pacifier for them, and they need it more for psychological comfort.

Node Anxiety if not used for some time is also one of the central symptoms of the mobile phone addiction-anxiety symptom network, which is consistent with the findings of Elhai et al. [16]. Many studies on the association between problematic mobile phone use and mental health symptoms suggest that high levels of anxiety are positively associated with habitual smartphone-checking behaviors, which may lead to increased addiction to mobile phone use [49, 55]. Social networks are considered a way to meet the demands of relationships [56]. Some research suggests that people who have a strong desire to participate in what others are doing will be prone to a fear of being excluded from social networks [57, 58], and this anxious thought can lead phone users to stay connected to social networks by using their phones frequently to alleviate anxiety and satisfy their need to feel a sense of social belonging [49]. Conversely, anxiety can arise if one leaves the phone behind.

In addition, Alleviate loneliness (i.e. relieving loneliness by chatting with others on mobile phones) is also an influential symptom of the mobile phone addiction-anxiety symptom network, which is consistent with the findings of Yue et al. [59]. Loneliness is a subjective state, usually understood as a negative emotional reaction caused by the difference between a person’s satisfactory interpersonal communication level and the actual interpersonal communication level [60], and a lot studies have proved that loneliness is related to mobile phone addiction. Enez Darcin et al. point out that people who often feel lonely are more likely to rely on the Internet [61]. Other studies have also shown that loneliness significantly predicts mobile phone use patterns and the severity of mobile phone addiction [62]. Through the ‘compensatory Internet use mode’, Kardefelt-Winther puts forward the reason why loneliness leads to mobile phone addiction, that is, people will use mobile phones to escape real-life problems and alleviate negative emotions (including loneliness) [63]. Moreover, lonely people also experience more anxiety [64, 65]. In contrast, most rural adolescents, whose parents work outside the home, live with their grandparents. They are more likely to be neglected and to feel negative emotions such as loneliness [66]. Therefore, they may use mobile phones frequently to relieve their anxiety and to satisfy their psychological need to interact with or be included by others. The Chinese government has also done a lot to address the current situation of rural youths, such as creating a mental health service system for adolescents, but it is still important to continuously focus on the state of rural adolescents’ lives, studies and friendships to alleviate their negative emotions.

In our network, the most influential bridge symptoms were nodes Irritability and Feeling afraid, indicating that those nodes were most closely associated with mobile phone addiction. Some studies have shown that during COVID-19, adolescents become more irritable and may increase their mobile phone use to vent their emotions [67]. And adolescents who feel fearful may be more introverted, anxious or lonely and want to escape from the real world more, so they spend more time on their phones [68‐70]. So this would explain why feeling scared would be a bridging symptom between mobile phone addiction and anxiety.

Our study found that mobile phone addiction and anxiety symptom networks were not predictive of sleep, which is not quite in line with previous research findings [71]. The reason for this may be due to the fact that this study investigated mainly middle school students, who are under more academic pressure and students generally have shorter sleep times, and the difference in sleep duration was not significant. However, sleep is particularly important for middle school students’ health and still needs to be given attention.

Our study has some limitations. First, the use of self-report questionnaires to measure mobile phone addiction and anxiety symptoms, rather than by systematic diagnosis, may result in some bias. Second, because the data were collected in a cross-sectional study design, it was not possible to determine causality. Future longitudinal studies are needed to explore the causal relationship between mobile phone addiction and anxiety symptoms over time. Third, we did not investigate issues such as the content of adolescents’ mobile phone use and parental supervision methods, and we failed to exclude the influence of other psychological problems when investigating anxiety symptoms, which should be covered more rigorously in the questionnaire in subsequent studies. Fourth, our data were collected after the onset of the COVID-19 epidemic and were not compared with pre-epidemic data. Therefore, there may be limitations in generalizing to non-epidemic periods.

In conclusion, the most influential symptoms in the network analysis of mobile phone addiction and anxiety symptoms are mainly concentrated in the part of mobile phone addiction. This allows our research to provide some basis for preventive measures that focusing on diverse factors in mobile phone addiction. And now, due to the outbreak of COVID-19, the learning mode of online teaching has increased the time spent using mobile phones, which makes it more necessary for us to monitor the impact of smartphones on the mental health of rural adolescents. Therefore, we may be able to reduce adolescents’ symptoms of mobile phone addiction and anxiety through timely educational monitoring and targeted psychological intervention.