With urbanization, the Internet has become increasingly convenient, cheap, and rife with addictive content (Ko et al., 2022). Moreover, as Internet use has increased rapidly worldwide, Internet addiction has become a serious public health problem for all groups (Hassan et al., 2020). Internet addiction is an impulse control disorder in which excessive Internet use results in the neglect of real-life relationships, work, and normal daily life (Young, 1998, 2004, 2007).

Internet addiction has been found to be in co-morbidity with other psychological symptoms and psychiatric disorders (Otsuka et al., 2020), Internet addiction has been found to be associated with depression (Lau et al., 2018) and anxiety symptoms (Cai et al., 2021), insomnia (Goel et al., 2021), academic failure (Kuo et al., 2018), interpersonal withdrawal (Kato et al., 2020), and aggressive behavior (Zhao et al., 2022). Internet addiction and poor mental health status each increased the risk of onset of the other (Otsuka et al., 2020).

Currently, there is a high detection rate of internet addiction among college students (Al Shawi et al., 2021), and the impact of Internet addiction is particularly significant for college students (Shen et al., 2020), as they are still undergoing psychosocial development. Baturay and Toker, (2019) reported that Internet addiction decreases college students’ self-esteem, self-confidence, social self-efficacy, academic self-efficacy and triggers loneliness.

Compared with other maladaptive problems, Internet addiction is strongly correlated with anxiety and depression (Li et al., 2019; Andrade et al., 2020). Emotional problems, of which depression and anxiety are the most common (Tsai et al., 2020), and the comorbidity rate is high (Zeng et al., 2019), can mediate other psychological and behavioral problems (Warren et al., 2021); moreover, difficulty in emotional regulation can predict subsequent Internet addiction (Effatpanah et al., 2020). Among college students, emotional problems are more common, particularly depression and anxiety (Ramón-Arbués et al., 2020).

The influence of depression and anxiety on Internet addiction has been demonstrated in many previous studies (Christ et al., 2020; Sayed et al., 2022). Evren et al. (2019) found that the severity of Internet addiction relates to the levels of depression and anxiety. Depression is also more common among Internet addicts and over-users (Kim et al., 2016; Tan et al., 2016), and depressive symptoms have the highest predictive ability for Internet addiction (Przepiorka et al., 2019; Diotaiuti et al., 2022a). Furthermore, Karaer and Akdemir (2019) found that greater anxiety is an important predictor of Internet addiction, and Internet addiction is related to an increase in anxiety (Shen et al., 2020; Gao et al., 2021). Morita et al. (2022) conducted a three-year longitudinal study and found a two-way relationship between Internet addiction and depressive symptoms.

Internet addiction differs by sex (Liang et al., 2016). Men are more prone to Internet addiction than women (Chi et al., 2020). Researchers have identified that men showed higher levels of Internet addiction, this is related to men being more dependent, more impulsive and more interdependent (Diotaiuti et al., 2022b). A follow-up survey of 1,715 adolescents showed that depressive symptoms had a more significant predictive effect on Internet addiction among male adolescents, indicating that depression can lead to Internet addiction. Conversely, among female adolescents, Internet addiction can significantly predict subsequent depression, indicating that Internet addiction can lead to depression (Yi and Li, 2021).

Some studies have found that women with Internet addiction are more likely to have depressive symptoms (Li et al., 2019), whereas men with Internet addiction are more likely to have anxiety symptoms (Shan et al., 2021). These results show that the relationship between Internet addiction and depression varies by sex.

Many previous studies have investigated Internet addiction, but the main focus has been the bivariate study of Internet addiction and other factors rather than the relationship between depression, anxiety, and Internet addiction. Moreover, previous studies on the relationship between depression, anxiety, and Internet addiction were mostly cross-sectional; longitudinal studies have been relatively few, and there has been a lack of research on the long-term mechanism of depression, anxiety, and Internet addiction. Furthermore, to date, few studies have focused on sex-related differences in depression, anxiety, and Internet addiction. Therefore, this study adopted a longitudinal approach to explore the mutual influence and dynamic relationship between depression, anxiety, and Internet addiction in college students. In this exploration, this study aimed to clarify the relationship between Internet addiction, depression, and anxiety as well as clarify the mechanisms of Internet addiction itself.

Therefore, the purpose of this study is to explore the mutual influence and dynamic relationship between depression, anxiety, and Internet addiction in college students. Based on the findings of our literature review, we arrived at the following hypotheses: Hypothesis 1. There was a sex difference in Internet addiction. Hypothesis 2. Depression, and anxiety were positively associated with Internet addiction. Hypothesis 3. Depression and anxiety significantly predicted subsequent Internet addiction. Hypothesis 4. Internet addiction significantly predicted subsequent depression and anxiety.

In recent years, Internet addiction among college students has been widely studied. Researchers have proposed a close relationship between Internet addiction and college students’ emotional problems. The descriptive statistics show the high detection rate of internet addiction among college students. This is related to that they are the main group of network users (Nagaur, 2020). Because most students live in the dormitory of the school, they are far away from their families, relatives and friends, so they spend more time on online entertainment and communication (Baturay and Toker, 2019). Moreover, they also need to complete most learning tasks through the network.

The correlation analysis of this study show that depression, anxiety, and Internet addiction are positively correlated, which is consistent with previous studies (Mak et al., 2018; Geng et al., 2021). These results indicate an internal relationship among the three, providing further support for their longitudinal relationship.

Gender differences can be found in many addictive behaviors and their related factors, including Internet addiction. The present study show that men are more prone to Internet addiction than women. This difference might be owing to the different ways men and women use the Internet: men may focus more on online games, whereas women may focus more on online shopping, novel reading, and interpersonal communication (Liang et al., 2016). Both men and women can experience Internet addiction, but there are differences in their manner and purpose of Internet use as well as the content of their subsequent addictions, and the way men surf the Internet contains more addictive content. In previous research by this research group, it was also found that more of men’ online behaviors may be concentrated in online games, and more of women’s online behaviors may be concentrated in online shopping, novel reading, and interpersonal communication (detailed data can be obtained from the author).

This study used a half a year longitudinal design to gain insights into the role of gender in the association between depression, anxiety and Internet addiction. We found that the causal relationship between Internet addiction and anxiety varies by sex. Moreover, the causal relationship between Internet addiction and depression also varies by sex.

For male college students, Internet addiction can significantly predict the occurrence of later depression, but depression does not significantly predict Internet addiction. These results support the Internet addiction leads to depression in males. Some evidence suggests the gender differences in depression that women are more likely to have depressive symptoms than men (Lin et al., 2021). Several theorists have suggested that gendered processes of socialization affect how some boys and men express depression (Swetlitz.2021). In contrast, in this study, for males, Internet addiction is a risk factor for depression (Diotaiuti et al., 2022a). According to the previous studies, excessive Internet use has a negative influence on real-world social interactions, including reducing the scale of social circle (Mak et al., 2018). Some studies have found that Internet addicted men have less social contact in the offline world, which usually leads to depression (Paudel et al., 2021). Moreover, anxiety significantly predicts Internet addiction among male college students, this is consistent with previous follow-up research results (Tsai et al., 2020). This suggests that anxiety is a risk factor for Internet addiction among male college students (Shan et al., 2021). This is consistent with our research hypothesis.

For female college students, Internet addiction does not significantly predict the occurrence of later anxiety, and anxiety does not significantly predict the occurrence of later Internet addiction also. This is inconsistent with previous conclusions (Kim et al., 2021). Moreover, there was no causal relationship between depression and Internet addiction, contrary to the results of a previous study (Yi and Li, 2021). Depression was not a significant predictor of Internet addiction, and Internet addiction was not a predictor of depression. This is inconsistent with our research hypothesis.

The cross-lagged analysis indicated that anxiety was a predictor of depression among both men and women, but depression did not significantly predict anxiety; there was no two-way predictive relationship between anxiety and depression. According to the cross-lagged analysis, college students’ depression could predict anxiety in the overall group, indicating that individuals with high depression levels are more likely to face anxiety problems. Additionally, college students’ anxiety could predict depression, indicating that individuals with high anxiety levels are also more likely to experience subsequent depression. Depression and anxiety have a two-way predictive relationship. The results for the overall group show that anxiety can predict Internet addiction, which in turn could significantly predict depression, aligning with existing research (Hsueh et al., 2019; Gao et al., 2021). When college students experience great psychological pressure and develop anxiety about their studies and lives, they will often use the Internet to escape pain, vent about their anxiety, and obtain temporary psychological satisfaction (Javaeed et al., 2019). Internet use for short periods of time may temporarily relieve individuals’ anxiety, but long-term dependence on the Internet can cause more feelings of social disconnection and aggravate depression when facing real life (Swetlitz, 2021).

Although this study has some achievements, some limitations must still be addressed. First, the sample was from a single university in Southwest China, which limits the universality of the results. Second, the span of the three time points was short; future research should use more time points over a longer period to gain detailed understanding of the interaction of variables over time. Third, this study only investigated the degree of Internet addiction and did not analyze the differences in Internet addiction behaviors, such as gaming and shopping. In the future, we will conduct a thorough analysis of different Internet addiction behaviors.

This study achieved some expected results through system tracking and cross-lagged analysis. The results indicate that to develop Internet addiction interventions, attention should be paid to anxious individuals’ frequency and duration of Internet use. Corresponding policies should be formulated to guide the use of diversified ways to alleviate anxiety. The results also suggest that prevention and intervention strategies for Internet addiction should be designed for different sexes. Special attention should be paid to men, and targeted strategies and methods should be provided to alleviate anxiety when intervening in Internet addiction.

A cross-lagged study was used to analyze the relationships among depression, anxiety, and Internet addiction at three time points. The results showed that anxiety was a predictor of Internet addiction, and that Internet addiction could significantly predict depression. The results also showed that the relationship between Internet addiction and anxiety varies by sex. Male anxiety had a significant predictive effect on Internet addiction.

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

Written informed consent was obtained from the individual(s) for the publication of any potentially identifiable images or data included in this article.

XX, HC, and ZC designed the study and drafted the manuscript. XX and HC analyzed the data and discussed the results. XX and ZC revised the manuscript. All authors contributed to the article and approved the submitted version.

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.

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