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Mobile phone addiction and interpersonal problems among Chinese young adults: the mediating roles of social anxiety and loneliness

BMC Psychology volume 13, Article number: 372 (2025) Cite this article

Abstract

Mobile phone addiction leads to difficulties that arise in relationships with others; however, the psychological mechanisms that underpin this relationship are not well understood. The present study examined a multiple mediation model with both social anxiety and loneliness as mediators in the relationship between mobile phone addiction and interpersonal problems among young adults. A sample of 758 Chinese college students reported items on the survey, including demographics, the Mobile Phone Addiction Tendency Scale, UCLA Loneliness Scale, Interaction Anxiousness Scale, and Interpersonal Comprehensive Diagnostic Scale. Results showed that mobile phone addiction was positively associated with interpersonal problems. Loneliness and social anxiety served as both independent and sequential mediators in this relationship. Moreover, these two types of mental states play equally important mediating roles. These results suggested that young adults with mobile phone addiction tended to have more interpersonal problems, not only due to their higher loneliness but also their higher social anxiety. In other words, both loneliness and social anxiety were factors that increase the risk of interpersonal problems.

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Introduction

With the development of digital devices, mobile phones are omnipresent and have brought great convenience to social life. According to the 55th Statistical Report on Internet Development in China, as of December 2024, mobile phone internet users in China reached 1.108 billion, representing 99.73% of all internet users [1]. However, the accessibility and convenience of mobile phones have greatly increased the risk of excessive use and even potential addiction, particularly among young adults [2–3].

This phenomenon has been defined as mobile phone addiction, which generally refers to an addictive behavior caused by the improper and excessive use of mobile phones, leading to significant impairments in physical, psychological, and social functioning for individuals [4–5]. A recent cross-temporal meta-analysis revealed that mobile phone addiction among college students has steadily increased over the past decade, with contributing factors such as anxiety, depression, and loneliness strongly correlating with excessive mobile phone use [6]. The study found that the national internet penetration rate and the national GDP index are key predictors of mobile phone addiction among Chinese college students. Furthermore, factors such as parenting style and individual virtues have been identified as significant determinants in the development of mobile phone addiction [7]. Additionally, the severity of mobile phone addiction is clearly demonstrated in multiple studies. For example, recent research showed that mobile phone addiction was significantly associated with various adverse psychological, physical, and sleep problems, including social anxiety, depression, loneliness, palpitations, and poor sleep quality [8–9]. Notably, excessive mobile phone use, particularly beyond four hours per day, exacerbates these issues. Even more concerning, excessive mobile phone use could impair cognitive functions, leading to significant disruptions in users’ daily lives [10]. All of these negative consequences can substantially interfere with daily functioning.

Given the negative impacts of mobile phone addiction, a growing body of research has shown that mental states such as loneliness [11] and social anxiety [12], and environmental factors such as interpersonal problems [13], are closely linked to mobile phone addiction. Addictive use of mobile phones and its impact on psychological disorders has received more attention in the fields of human health and psychology; relatively less evidence has been provided regarding how psychological problems influence environmental factors such as interpersonal problems [14]. Loneliness and social anxiety are both associated with interpersonal problems, representing two aspects of negative mental states experienced during social interactions [15–16]. Moreover, several studies have shown that individuals with high levels of loneliness or social anxiety typically struggle with face-to-face communication and experience greater interpersonal problems [17–18]. Consequently, both negative mental states seem to play an important role in the relationship between mobile phone addiction and interpersonal problems. However, there have been few investigations simultaneously exploring and comparing the roles of the two negative mental states, loneliness and social anxiety, in the relationship between mobile phone addiction and interpersonal problems. In other words, why do some young adults with mobile phone addiction tend to experience high levels of interpersonal problems? The mechanisms remain unclear. Therefore, the present study intended to simultaneously test the mediating roles of loneliness and social anxiety in the relationship between mobile phone addiction and interpersonal problems.

Mobile phone addiction and interpersonal problems

Interpersonal problems refer to difficulties that arise in relationships with others and can often be observed in technology addicts [19]. In recent years, researchers have become increasingly interested in revealing how mobile phone addiction could contribute to interpersonal problems [20–21]. For example, an early survey of 10,191 Chinese young adults revealed that individuals who reported high-intensity mobile phone use were at a greater risk of experiencing difficulties in their interpersonal relationships [22]. Another important study conducted by Chen et al. (2016) surveyed 1089 young adults in China to investigate the correlation between mobile phone addiction and interpersonal problems [23]. They found that the level of mobile phone addiction was positively correlated with interpersonal problems. Furthermore, a recent survey conducted among young adults found that problematic social media use was strongly related to perceived inter-parental conflict [13]. According to displacement theory [24], excessive media use, especially for activities such as television viewing or internet browsing, can lead to a decrease in the time individuals spend engaging in face-to-face interactions with family, friends, or other social groups. This displacement of social interaction may produce many more interpersonal problems. Therefore, based on the displacement theory and literature reviewed above, our first hypothesis predicted that mobile phone addiction may increase interpersonal problems among young adults.

The mediating role of loneliness

Loneliness is defined as the aversive state of feeling in which one is unhappy because there is a discrepancy between one’s existing and desired social relationships [25–26]. Several studies have found that this increase in loneliness among young adults is potentially related to mobile phone addiction, such as their screen time and social media use [27]. For example, Shen and Wang (2019) found that there is a positive association between mobile phone addiction and loneliness [28]. A longitudinal study also indicated that loneliness is an important predictor of mobile phone addiction [29]. Although there is continued debate in the literature regarding the causal direction of this relationship between mobile phone addiction and loneliness [30], a recent theoretical model posits that the link between loneliness and mobile phone overuse is bidirectional and dynamic [31]. Mobile phones provide more chances for social bonding; however, they can also foster an environment that promotes social comparisons, leading to heightened feelings of social isolation and loneliness, which can then produce many more interpersonal problems, particularly among young adults with mobile phone addiction [25]. Furthermore, empirical studies suggest that loneliness is strongly related to interpersonal problems among young adults [32]. Therefore, loneliness may play a role in the association that mobile phone addiction shares with interpersonal problems. Consequently, our second hypothesis predicted that mobile phone addiction may be indirectly associated with interpersonal problems through loneliness among young adults.

The mediating role of social anxiety

Social anxiety, an important mental state, can be described as an excessive and unreasonable fear of interpersonal interactions and embarrassment in public performance [33]. According to social cognitive theory [34], the interaction between an individual’s behaviors and mental states is mutually influential. Not only are the behaviors of individuals responsive to their mental states (e.g., social anxiety affects mobile phone addiction), but these behaviors (e.g., excessive mobile phone use) can also have an impact on their mental states (e.g., social anxiety) [23]. Indeed, empirical studies suggest that individuals with high levels of mobile phone addiction are more likely to experience social anxiety. For example, one study conducted among junior high school students in China found that mobile phone addiction has a significant positive effect on social anxiety [35]. A similar result was found among Chinese college students [36]. A recent three-level meta-analysis also showed a significant positive correlation between mobile phone addiction and social anxiety [37]. Furthermore, previous studies have indicated that individuals with high levels of social anxiety often experience feelings of inadequacy in social situations, which might lead to interpersonal problems [38–39]. Therefore, social anxiety is another risk variable for interpersonal problems among young adults; this factor may affect the relationship between mobile phone addiction and interpersonal problems. Thus, our third hypothesis predicted that mobile phone addiction may be indirectly associated with interpersonal problems through social anxiety among young adults.

The sequential mediation model

On one hand, given the findings from theories and empirical studies, loneliness and social anxiety have been identified as potential mediators and may serve as mediators in a parallel way. On the other hand, they may also mediate the relationship in a sequential manner. A growing body of empirical studies has shown that loneliness is closely associated with social anxiety [15]. Individuals experiencing loneliness are more inclined to perceive themselves as unlikable and unaccepted [40]. Individuals with this perception are even less willing to engage in social interactions, which in turn contribute to the rise in their social anxiety [41]. The social neuroscience model posits that when individuals experience feelings of loneliness, their brains enter a self-protective mode. This protective mode results in corresponding behaviors and brain responses, leading individuals to become more anxious [42]. Furthermore, considering the relationships between mobile phone addiction and loneliness, as well as social anxiety and interpersonal problems, it can be inferred that loneliness and social anxiety may play sequential mediating roles in the relationship between mobile phone addiction and interpersonal problems. Therefore, based on the above hypotheses, our fourth hypothesis predicted that loneliness and social anxiety may sequentially mediate the relationship between mobile phone addiction and interpersonal problems among young adults.

Materials and methods

Participants and procedure

The convenience sample used in this study was drawn from universities located in Zhengzhou, Henan Province, China (one of the most economically developed cities in central China). The data were collected between April 9, 2024, and April 18, 2024 through Wenjuanxing (https://www.wjx.cn/), which is an online platform widely used for large-scale surveys in China. College students were informed by their teachers in class that they were welcome to participate in a questionnaire survey. All participants were told that their participation was voluntary, and they had the right to withdraw from the study at any time without consequence. A total of 999 young adults (455 males and 544 females) agreed to participate in the survey. All respondents owned and identified themselves as mobile phone users. Among the 999 participants, 758 valid questionnaires (298 males and 460 females) were obtained. The remaining 241 participants (24.12%) were excluded due to missing data or incorrect answers to control questions. The age range of the participants was 17 to 24 years, with a mean age of 20.77 (SD = 1.47). The sample included 176 freshmen (23.2%), 140 sophomores (18.5%), 266 juniors (35.1%), and 176 seniors (23.2%). Demographic data were collected on age, gender, and grade. The study protocol, including questionnaires, was reviewed by the Ethics Committee of Zhengzhou Normal University.

In addition, Monte Carlo power analysis for mediation models was used to calculate the statistical power of the multiple mediation model [43].The correlation matrix (see Table 1) of study’s variables was input into the application, and the results showed that the sample size of this study (N = 758) had sufficient power above the conventional value of 0.80 [44] for the mediation analyses. Specifically, the statistical power for all three mediational pathways were greater than 0.95.

Instruments

Mobile phone addiction tendency scale (MPATS)

The 16-item Mobile Phone Addiction Tendency Scale was developed by Xiong et al. [5] based on Young’s [45] Internet Addiction Scale, which was used to assess the tendency of mobile phone addiction. As a self-report questionnaire, the 16 items captured four dimensions of mobile phone addiction, including withdrawal symptoms, salience, social comfort, and mood changes. All items were answered on a five-point Likert scale, ranging from 1 (totally disagree) to 5 (totally agree). The sum of the 16 item scores could range from 16 to 80 and the higher the score, the higher tendency of mobile phone addiction. Sample items included: “My friends often say that I rely too much on my phone” and “I feel lonely if I don’t have my phone.” The scale displayed excellent reliability and validity among Chinese young adults in previous research [23, 39, 46], and the Cronbach’s alpha was 0.94 in the current study.

UCLA loneliness scale

The 20-item UCLA Loneliness Scale was developed by [26]. All items were answered on a four-point Likert scale ranging from 1 (never) to 4 (often). The sum of the 20 item scores could range from 20 to 80, with higher scores representing greater levels of loneliness. Sample items included: “Do you often feel a lack of companions?” and “Do you often feel ignored by others?” The scale was widely used among Chinese young adults and demonstrated good reliability and validity [47]. The study sample produced a Cronbach’s alpha of 0.89.

Interaction anxiousness scale (IAS)

The 15-item Interaction Anxiousness Scale was developed by Leary [48] and was used to measure participants’ level of social anxiety. In this scale, participants are asked to assess the extent to which they had experienced the listed symptoms using a five-point Likert scale (1 = not at all consistent to 5 = extremely consistent), in which the 3rd, 6th, 10th, and 15th questions are reverse scored. The sum of 15-item scores could vary from 15 to 75, with higher scores indicating greater levels of social anxiety. Sample items included: “Social gatherings often make me feel anxious and uncomfortable” and “I feel nervous when calling someone I’m not very familiar with.” The IAS has demonstrated good validity and reliability among Chinese college students in previous research [47, 49]. In this study, Cronbach’s alpha for the scale was 0.86.

Interpersonal comprehensive diagnostic scale (ICDS)

The Interpersonal Comprehensive Diagnostic Scale was compiled by Zheng [50]. This scale consists of 28 items with four dimensions, including conversation, making friends, dealing with people and heterosexual interactions. Each of the 28-items on the ICDS is rated on a five-point Likert scale (1 = not at all consistent to 5 = extremely consistent), with higher scores indicating greater levels of interpersonal problems. Sample items included: “I feel rejected and ignored by others” and “I find it difficult to get al.ong with others.” The scale was verified with fairly good validity and reliability among Chinese university students [32, 51, 52]. The Cronbach’s alpha for the scale in our study was 0.95.

Data analysis

Data analysis was conducted using SPSS 21.0 and the PROCESS macro (http://www.afhayes.com) suggested by Hayes [53]. We first used this software to conduct descriptive statistics (M ± SD) and correlational analyses on the main variables. All the research variables were first standardized to minimize multi-collinearity before the correlational analyses and mediational analysis [54]. We then used Model 6 of PROCESS macro in SPSS to further examine and compare the mediating roles of social anxiety and loneliness in the relations between mobile phone addiction and interpersonal problems. This PROCESS macro is specifically developed for testing complex models, including the sequential mediation model with the bias-corrected percentile bootstrap method and has been widely used by scholars [54–55]. To examine the significance of the indirect effects, 5000 bootstrap samples were used to obtain 95% bias-corrected bootstrap confidence intervals. If zero was not contained in the 95% confidence interval, an indirect effect was deemed significant [53]. Moreover, considering that previous research indicated that gender and age were more likely to impact negative mental states (e.g., anxiety) [56, 57], we controlled for these two demographic factors in the statistical analyses.

Results

Preliminary analyses

Descriptive statistics and correlation matrix for all variables are summarized in Table 1. According to the correlation analysis, all the main variables showed significantly positive correlations with each other. Specifically, mobile phone addiction was positively correlated with loneliness (r = 0.38, p<0.01) and social anxiety (r = 0.58, p<0.01), indicating that mobile phone addiction is a risk factor for both social anxiety and loneliness. In addition, both loneliness and social anxiety were positively correlated with interpersonal problems (r = 0.63, p<0.01; r = 0.67, p<0.01), suggesting that young adults with social anxiety and loneliness tend to have more interpersonal problems. These results supported Hypothesis 1 and provided a preliminary basis for Hypothesis 2 to Hypothesis 4.

Table 1 Descriptive statistics and correlations for the variables (N = 758)
Full size table

Testing the sequential mediation model

We ran the PROCESS (Model 6), using gender and age as covariates, to test the sequential mediation model. As presented in Table 2, the results of regression analysis showed that mobile phone addiction was positively related to interpersonal problems (β = 0.69, p<0.001). When interpersonal problems were regressed onto all predictors, the direct effect between mobile phone addiction and interpersonal problems remained significant (β = 0.36, p<0.001). In addition, mobile phone addiction was positively associated with loneliness and social anxiety (β = 0.38, p<0.001; β = 0.48, p<0.001). Loneliness was positively correlated with social anxiety (β = 0.23, p<0.001) and interpersonal problems (β = 0.36, p<0.001). Social anxiety was positively associated with interpersonal problems (β = 0.33, p<0.001). These results were in line with the correlation analysis, providing further support for Hypothesis 2 to Hypothesis 4.

Table 2 Testing the sequential mediation model using PROCESS (N = 758)
Full size table

Based on the principle for testing mediational significance, Table 2; Fig. 1 showed that loneliness and social anxiety partially mediated the relationship between mobile phone addiction and interpersonal problems. The total effect of mobile phone addiction on interpersonal problems (effect = 0.69, t = 25.91) could be decomposed into the direct effect (effect = 0.36, t = 14.48), and three indirect effects. To be specific, firstly, the pathway of “mobile phone addiction → loneliness → interpersonal problems” was significant (indirect effect = 0.14, 95% CI: 0.10 to 0.17). Secondly, the pathway of “mobile phone addiction → social anxiety → interpersonal problems” was significant (indirect effect = 0.16, 95% CI: 0.13 to 0.19). Thirdly, the sequential pathway of “mobile phone addiction → loneliness → social anxiety → interpersonal problems” was significant (indirect effect = 0.03, 95% CI: 0.02 to 0.04). Thus, loneliness and social anxiety sequentially mediated the link between mobile phone addiction and interpersonal problems. Furthermore, there were significant differences among these three pathways: the first pathway and the third pathway (effect difference = 0.11, 95% CI: 0.08 to 0.14), and the second pathway and the third pathway (effect difference = 0.13, 95% CI: 0.10 to 0.17). However, the difference between the first pathway and the second pathway was not significant (effect difference = 0.02, 95% CI: -0.08 to 0.03). Additionally, the ratio of the total indirect effects to the total effect reached 47.07%, highlighting the importance of both loneliness and social anxiety as mediators in transmitting the impact of mobile phone addiction to interpersonal problems. Overall, these results supported Hypothesis 2 to 4.

Fig. 1
figure 1

The sequential mediation model. Path values refer to path coefficients. ***p<0.001

Full size image

Discussion

Although some researchers have examined the impact of mobile phone addiction on loneliness and social anxiety [35], research has rarely explored the further impact of psychological problems on developmental social problems [14] and has seldom simultaneously examined different mediating roles in the association between mobile phone addiction and interpersonal problems. By testing a sequential mediation model, we examined the mediating roles of loneliness and social anxiety between mobile phone addiction and interpersonal problems. It is important to note that the cross-sectional design employed in this study does not confirm causality between the variables in the proposed model. However, the results obtained still enhance comprehension of the association between mobile phone addiction and interpersonal problems, and offer a comprehensive approach to addressing and intervening in interpersonal problems among young adults.

Relationship between mobile phone addiction and interpersonal problems

Mobile phone addiction showed a positive correlation with interpersonal problems, consistent with displacement theory [24], which indicated that individuals experiencing mobile phone addiction may neglect real-world social interactions, leading to potential conflicts within relationships. This finding supports the first hypothesis and is consistent with results from previous research [58]. Addiction to mobile phones may prompt individuals to overlook group norms within their social context, thereby resulting in weakening social relations in reality [59]. More specifically, when attempting to maintain a connection with others, individuals may separate themselves from the reality due to excessive use of their mobile phones. Consequently, they may neglect the social norms of their group context, which weakens interpersonal relationships and produces interpersonal problems. These findings also align with the displacement hypothesis regarding mobile phone use, which suggests that individuals tend to spend more time in online environments than offline, leading to a deterioration of their existing relationships [24]. According to the flow theory [60], individuals addicted to mobile phones unintentionally focus on the information within the device, leading to a loss of self-awareness and time perception. This intense focus often comes at the expense of sleep quality. This phenomenon has been supported by empirical research, which suggests that the severity of mobile phone addiction negatively correlates with sleep quality [61]. Sleep loss, beyond influencing personal health, can subsequently provoke difficulties in interpersonal communication, giving rise to interpersonal relationship issues [62]. These phenomena, however, require further research, such as investigating how sleep quality may act as a mediator between mobile phone addiction and interpersonal problems.

Mediating roles of loneliness and social anxiety

This study found that loneliness and social anxiety separately significantly mediated the relationship between mobile phone addiction and interpersonal relationships, which supported our second and third hypotheses. Consistent with previous studies, the results showed that mobile phone addiction was positively related to negative mental states, such as loneliness [28] and social anxiety [23], which, in turn, were positively associated with interpersonal problems [32, 38]. This highlights the importance of loneliness and social anxiety in the mechanism for explaining why mobile phone addiction is positively related to interpersonal problems. According to cognitive-behavioral model, when establishing interpersonal relationships, individuals with high levels of loneliness cognitively exhibit high defensive motivation and low approach motivation [63]. They have a tendency to overestimate the risks within their interactions, making it difficult for them to establish healthy interpersonal relationships. Consequently, they are more likely to experience interpersonal problems. Therefore, when addressing interpersonal issues arising from mobile phone use among young adults, greater attention should be given to the loneliness caused by mobile phone addiction. Furthermore, social anxiety serves as one of the underlying diatheses that precipitate cognitive distortions related to self-perception, such as self-doubt and negative self-appraisal [64]. This implies that social anxiety may hinder individuals from cultivating healthy relationships. More interestingly, the mediating effects of loneliness and social anxiety did not show significant differences, suggesting that loneliness and social anxiety had a parallel effect in the relationship between mobile phone addiction and interpersonal problems. This suggests that when dealing with interpersonal problems caused by mobile phone addiction, we should not only concentrate on alleviating loneliness but also recognize the significant impact of social anxiety on individuals.

The sequential mediation model

The results showed that loneliness and social anxiety work together through a sequential mediation in the relationship between mobile phone addiction and interpersonal problems. Firstly, the results validate the perspective of social cognitive theory [34]. There exists a reciprocal association between individuals’ behaviors and their mental states; that is, individuals’ mental states not only react to their behaviors but their mental states can also affect their behaviors. Mobile phone addiction can prompt individuals to experience feelings of loneliness and social anxiety, and these changes in mental states might subsequently impact their interpersonal environment (such as inappropriate social behaviors), leading to interpersonal problems. Secondly, these findings align with prior research indicating that loneliness is a significant predictor of social anxiety [15–16, 65]. Lonely individuals lack a positive self-perception in interpersonal relationships [40], which, in turn, leads to an increase in social anxiety [41]. As stated earlier, the findings are also consistent with the social neuroscience model. Loneliness may trigger a series of self-protective responses such as heightened sensitivity to social threat signals, which lead individuals to become more anxious and result in greater social withdrawal [42]. Moreover, social anxiety could potentially lead to an attention bias [66]. Perceiving social anxiety can decrease one’s willingness to engage with social stimuli, making it more challenging for them to derive pleasure from interpersonal interactions, subsequently leading to interpersonal difficulties. Finally, the study found that the effect size of the sequential mediation pathway was significantly lower than the independent mediating effects of loneliness and social anxiety. This indicates that mobile phone addiction primarily induces the two negative mental states, which in turn directly affect interpersonal problems.

Limitations

This study simultaneously examined the mediating roles of two important negative mental states between mobile phone addiction and interpersonal problems. The results demonstrated that loneliness and social anxiety served as both independent and sequential mediators in this relationship between mobile phone addiction and interpersonal problems. Nevertheless, this study had several limitations. First, even though this study was based on the theoretical foundation and empirical studies, as stated earlier, it was not possible to infer causality due to the cross-sectional nature of the data. Future research could adopt a longitudinal design to track the development of mobile phone addiction and explore whether changes in mobile phone addiction are correlated with changes in social anxiety, loneliness, and interpersonal relationships. Additionally, participants could be categorized into an addiction group and a non-addiction group, with assessments of their loneliness and social anxiety. Experimental research could then be conducted to examine the performance of both groups in interpersonal relationship tasks. Such studies would provide stronger evidence for the causal mechanisms linking mobile phone addiction to psychological and interpersonal problems. Second, response bias may exist in the analyses based on self-reported data. Future studies should collect data from multiple methods and informants. Third, we found that the indirect paths only explained 47.07% of the variance between mobile phone addiction and interpersonal problems, implying that other important explanatory factors remain to be explored, such as self-esteem, emotional regulation, and social support. Future studies should explore these additional pathways. Fourth, the study used a convenience sample consisting of college students from a relatively developed area in China, which may limit the generalizability of the findings to other age groups or cultural contexts. Future research should aim to include more diverse samples. Finally, the study did not differentiate among various types of mobile phone usage (e.g., social media, gaming, educational use), which may have different effects on loneliness, social anxiety, and interpersonal problems. Thus, future studies should explore the impact of differentiating among various types of mobile phone usage on psychological problems. For example, longitudinal studies could examine whether certain types of mobile phone usage, such as social media, have a stronger impact on psychological and interpersonal problems compared to other forms of phone use, such as gaming.

Practical implications

Despite these limitations, the findings in the current study have important practical implications, particularly for educators, psychologists, and policymakers. There is growing evidence that mobile phone addiction among young adults has become a matter of concern due to its high occurrence rate [2] and is significantly associated with various adverse psychological problems [8]. Specifically, the results of the present study suggest that attention should not only be given to the external interpersonal issues caused by mobile phone addiction but also to the internal psychological problems, particularly loneliness and social anxiety. In practice, college administrators and educators should organize various activities to alleviate loneliness and reduce social anxiety among students affected by mobile phone addiction, such as individual counseling and group therapy. These initiatives can help improve the interpersonal issues that arise from mobile phone addiction. Just as importantly, psychologists should prioritize developing targeted interventions to help individuals better manage underlying psychological problems while also addressing excessive use of mobile phones. Finally, policymakers should establish guidelines requiring app developers to implement restrictions that prevent excessive mobile phone use, particularly among college students. For example, automatic notifications on mobile phones that remind users to take breaks after extended usage may significantly reduce excessive phone use and encourage healthier usage habits [67].

Conclusion

In summary, the present study examined multiple mediation models to explore how mobile phone addiction is associated with interpersonal problems among Chinese young adults. The results revealed that (1) mobile phone addiction is positively associated with interpersonal problems. (2) Loneliness and social anxiety served as both independent and sequential mediators in this relationship. Moreover, these two types of mental states play equally important mediating roles. These findings improve the current understanding of how mobile phone addiction impacts interpersonal problems.

Data availability

The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.

References

  1. China Internet Information Center:The 55th China Internet Development Statistical Report. https://www.cnnic.net.cn/ (2024). Accessed 10 Feb 2025.

  2. Ka Chun N, Wu LH, Lam HY, Lam LK, Nip PY, Cho Man N, et al. The relationships between mobile phone use and depressive symptoms, bodily pain, and daytime sleepiness in Hong Kong secondary school students. Addict Behav. 2020;101:105975.

    Article  Google Scholar 

  3. Yang X, Hu H, Zhao C, Xu H, Tu X, Zhang G. A longitudinal study of changes in smart phone addiction and depressive symptoms and potential risk factors among Chinese college students. BMC Psychiatry. 2021;21(1):252.

    Article  PubMed  PubMed Central  Google Scholar 

  4. Lapierre MA, Zhao P, Custer BE. Short-Term longitudinal relationships between smartphone use/dependency and psychological Well-Being among late adolescents. J Adolesc Health. 2019;65(5):607–12.

    Article  PubMed  Google Scholar 

  5. Xiong J, Zhou Z, Chen W, You Z, Zhai Z. Development of the mobile phone addiction tendency scale for college students. Chin Mental Health J. 2012;26(3):222–5.

    Google Scholar 

  6. Lyu C, Cao Z, Jiao Z. Changes in Chinese college students’ mobile phone addiction over recent decade: the perspective of cross-temporal meta-analysis. Heliyon. 2024;10(11):e32327.

    Article  PubMed  PubMed Central  Google Scholar 

  7. Lian L, You X, Huang J, Yang R. Who overuses smartphones?? Roles of virtues and parenting style in smartphones? addiction among Chinese college students. Comput Hum Behav. 2016;65:92–9.

    Article  Google Scholar 

  8. Mei S, Hu Y, Wu X, Cao R, Kong Y, Zhang L, et al. Health risks of mobile phone addiction among college students in China. Int J Mental Health Addict. 2022;21(4):2650–65.

    Article  Google Scholar 

  9. Chen G, Lyu C. The relationship between smartphone addiction and procrastination among students: A systematic review and meta-analysis. Pers Indiv Differ. 2024;224.

  10. Ren F, Li Y, Zhang J. Perceived parental control and Chinese middle school adolescents’ creativity: the mediating role of autonomous motivation. Psychol Aesthet Creativity Arts. 2017;11(1):34–42.

    Article  Google Scholar 

  11. Ma S, Huang Y, Ma Y. Childhood maltreatment and mobile phone addiction among Chinese adolescents: loneliness as a mediator and Self-Control as a moderator. Front Psychol. 2020;11:813.

    Article  PubMed  PubMed Central  Google Scholar 

  12. Annoni AM, Petrocchi S, Camerini AL, Marciano L. The relationship between social anxiety, smartphone use, dispositional trust, and problematic smartphone use: A moderated mediation model. Int J Environ Res Public Health. 2021;18(5).

  13. Wang M, Xu Q, He N. Perceived interparental conflict and problematic social media use among Chinese adolescents: the mediating roles of self-esteem and maladaptive cognition toward social network sites. Addict Behav. 2021;112:106601.

    Article  PubMed  Google Scholar 

  14. Seo DG, Park Y, Kim MK, Park J. Mobile phone dependency and its impacts on adolescents’ social and academic behaviors. Comput Hum Behav. 2016;63:282–92.

    Article  Google Scholar 

  15. Chen X, Li Z, Wang J. Impact of loneliness and social anxiety on depression of vulnerable children: the intermediary role of self-esteem. J Psychol Sciency. 2021;44(1):199–204.

    Google Scholar 

  16. Maes M, Nelemans SA, Danneel S, Fernández-Castilla B, Van den Noortgate W, Goossens L, et al. Loneliness and social anxiety across childhood and adolescence: multilevel meta-analyses of cross-sectional and longitudinal associations. Dev Psychol. 2019;55(7):1548–65.

    Article  PubMed  Google Scholar 

  17. Epkins CC, Heckler DR. Integrating etiological models of social anxiety and depression in youth: evidence for a cumulative interpersonal risk model. Clin Child Fam Psychol Rev. 2011;14(4):329–76.

    Article  PubMed  Google Scholar 

  18. Li J, Zhan D, Zhou Y, Gao X. Loneliness and problematic mobile phone use among adolescents during the COVID-19 pandemic: the roles of escape motivation and self-control. Addict Behav. 2021;118:106857.

    Article  PubMed  PubMed Central  Google Scholar 

  19. Horowitz LM, Rosenberg SE, Baer BA, Ureno G, Villasenor VS, INVENTORY OF INTERPERSONAL PROBLEMS - PSYCHOMETRIC PROPERTIES AND CLINICAL-APPLICATIONS. J Consult Clin Psychol. 1988;56(6):885–92.

    Article  PubMed  Google Scholar 

  20. Chen R, Liu J, Cao X, Duan S, Wen S, Zhang S, et al. The relationship between mobile phone use and suicide-related behaviors among adolescents: the mediating role of depression and interpersonal problems. J Affect Disord. 2020;269:101–7.

    Article  PubMed  Google Scholar 

  21. Park TY, Kim S, Lee J. Family therapy for an Internet-addicted young adult with interpersonal problems. J Family Therapy. 2014;36(4):394–419.

    Article  Google Scholar 

  22. Yen CF, Tang TC, Yen JY, Lin HC, Huang CF, Liu SC, et al. Symptoms of problematic cellular phone use, functional impairment and its association with depression among adolescents in Southern Taiwan. J Adolesc. 2009;32(4):863–73.

    Article  PubMed  Google Scholar 

  23. Chen L, Yan Z, Tang W, Yang F, Xie X, He J. Mobile phone addiction levels and negative emotions among Chinese young adults: the mediating role of interpersonal problems. Comput Hum Behav. 2016;55:856–66.

    Article  Google Scholar 

  24. Kraut R, Patterson M, Lundmark V, Kiesler S, Mukophadhyay T, Scherlis W. Internet paradox: A social technology that reduces social involvement and psychological well-being? Am Psychol. 1998;53(9):1017.

    Article  PubMed  Google Scholar 

  25. O’Day EB, Heimberg RG. Social media use, social anxiety, and loneliness: A systematic review. Computers Hum Behav Rep. 2021;3.

  26. Russell DW. UCLA loneliness scale (Version 3): reliability, validity, and factor structure. J Pers Assess. 1996;66(1):20–40.

    Article  PubMed  Google Scholar 

  27. Twenge JM, Joiner TE, Rogers ML, Martin GN. Increases in depressive symptoms, suicide-Related outcomes, and suicide rates among U.S. Adolescents after 2010 and links to increased new media screen time. Clin Psychol Sci. 2017;6(1):3–17.

    Article  Google Scholar 

  28. Shen X, Wang J-L. Loneliness and excessive smartphone use among Chinese college students: moderated mediation effect of perceived stressed and motivation. Comput Hum Behav. 2019;95:31–6.

    Article  Google Scholar 

  29. Kim J-H. Longitudinal associations among psychological issues and problematic use of smartphones. J Media Psychol. 2019;31(3):117–27.

    Article  Google Scholar 

  30. Song H, Zmyslinski-Seelig A, Kim J, Drent A, Victor A, Omori K, et al. Does Facebook make you lonely? A meta analysis. Comput Hum Behav. 2014;36:446–52.

    Article  Google Scholar 

  31. Nowland R, Necka EA, Cacioppo JT. Loneliness and social internet use: pathways to reconnection in a digital world?? Perspect Psychol Sci. 2018;13(1):70–87.

    Article  PubMed  Google Scholar 

  32. Li X, Jiang Y, Zhang B. The influence of loneliness on problematic mobile social networks usage for adolescents: the role of interpersonal distress and positive self presentation. J Psychol Sciency. 2018;41(5):1117–23.

    Google Scholar 

  33. Association AP. Diagnostic and statistical manual of mental disorders. 5th ed. Arlington, VA: American Psychiatric Association; 2013.

    Book  Google Scholar 

  34. Bandura. Social foundations of thought and action: A social cognitive theory. Englewood Cliffs, NJ: Prentice Hall; 1986.

    Google Scholar 

  35. Wang JL, Sheng JR, Wang HZ. The association between mobile game addiction and depression, social anxiety, and loneliness. Front Public Health. 2019;7:247.

    Article  PubMed  PubMed Central  Google Scholar 

  36. Li Z, Wang T, Liang Y, Wang M. The relationship between mobile phone addiction and subjective well-being in college students: the mediating effect of social anxiety. Stud Psychol Behav. 2017;15(4):562–8.

    Google Scholar 

  37. Ran G, Li J, Zhang Q, Niu X. The association between social anxiety and mobile phone addiction: A three-level meta-analysis. Comput Hum Behav. 2022;130.

  38. Kim S-S, Bae S-M. Social anxiety and social networking service addiction proneness in university students: the mediating effects of experiential avoidance and interpersonal problems. Psychiatry Invest. 2022;19(6):462–9.

    Article  Google Scholar 

  39. You Z, Zhang Y, Zhang L, Xu Y, Chen X. How does self-esteem affect mobile phone addiction? The mediating role of social anxiety and interpersonal sensitivity. Psychiatry Res. 2019;271:526–31.

    Article  PubMed  Google Scholar 

  40. Zhu M, Zhu C, Gao X, Luo J. Lonely individuals do not show interpersonal self-positivity bias: evidence from N400. Front Psychol. 2018;9:325217.

    Article  Google Scholar 

  41. Knowles ML, Lucas GM, Baumeister RF, Gardner WL. Choking under social pressure: social monitoring among the lonely. Pers Soc Psychol Bull. 2015;41(6):805–21.

    Article  PubMed  Google Scholar 

  42. Cacioppo S, Capitanio JP, Cacioppo JT. Toward a neurology of loneliness. Psychol Bull. 2014;140(6):1464.

    Article  PubMed  PubMed Central  Google Scholar 

  43. Schoemann AM, Boulton AJ, Short SD. Determining power and sample size for simple and complex mediation models. Social Psychol Personality Sci. 2017;8(4):379–86.

    Article  Google Scholar 

  44. Vendemia MA, DeAndrea DC. The effects of viewing thin, sexualized selfies on Instagram: investigating the role of image source and awareness of photo editing practices. Body Image. 2018;27:118–27.

    Article  PubMed  Google Scholar 

  45. Young KS. Internet addiction: the emergence of a new clinical disorder. CyberPsychology Behav. 1998;1(3):237–44.

    Article  Google Scholar 

  46. Li M, Jiang X, Ren Y. Mediator effects of positive emotions on social support and depression among adolescents suffering from mobile phone addiction. Psychiatria Danubina. 2017;29(2):207–13.

    Article  PubMed  Google Scholar 

  47. Li Y, Bi C. The influence of Self-Focus on social anxiety: the regulating effect of self-distance and mindfulness. J Psychol Sciency. 2020;43(1):239–46.

    Google Scholar 

  48. Leary MR. Social anxiousness: the construct and its measurement. J Pers Assess. 1983;47(1):66–75.

    Article  PubMed  Google Scholar 

  49. Ye S, Cheng H, Zhai Z, Liu H. Relationship between social anxiety and internet addiction in Chinese college students controlling for the effects of physical exercise, demographic, and academic variables. Front Psychol. 2021;12:698748.

    Article  PubMed  PubMed Central  Google Scholar 

  50. Zheng RC. Psychological health diagnosis of college students. Jinan: Shandong Education; 1999.

    Google Scholar 

  51. Mou L, Lei W, Chen J, Zhang R, Liu K, Liang X. Mediating effect of interpersonal relations on negative emotions and dysmenorrhea in female adolescents. Gen Psychiatr. 2019;32(1):e100008.

    Article  PubMed  PubMed Central  Google Scholar 

  52. Zhang X, Zhao P. The study on the relations among perfectionism & coping style & interpersonal relationship of university students. Asian Social Sci. 2010;6(1):145–51.

    Google Scholar 

  53. Hayes AF. Introduction to mediation, moderation, and conditional process analysis: a regression-based approach. New York: Guilford Press; 2013.

    Google Scholar 

  54. Wang M, Wang J, Deng X, Chen W. Why are empathic children more liked by peers? The mediating roles of prosocial and aggressive behaviors. Pers Indiv Differ. 2019;144:19–23.

    Article  Google Scholar 

  55. Guo L, Tian L, Scott Huebner E. Family dysfunction and anxiety in adolescents: A moderated mediation model of self-esteem and perceived school stress. J Sch Psychol. 2018;69:16–27.

    Article  PubMed  Google Scholar 

  56. Lee J, Allen J. Gender differences in healthy and unhealthy food consumption and its relationship with depression in young adulthood. Community Ment Health J. 2021;57(5):898–909.

    Article  PubMed  Google Scholar 

  57. Li Y, Li J, Yang Z, Zhang J, Dong L, Wang F, et al. Gender differences in anxiety, depression, and nursing needs among isolated coronavirus disease 2019 patients. Front Psychol. 2021;12:615909.

    Article  PubMed  PubMed Central  Google Scholar 

  58. He L, Yang S, Meng Y. Correlational research on mobile phone addiction and the interpersonal relationship distress of Chinese college students. Ethics Progress. 2023;14(1):126–43.

    Article  Google Scholar 

  59. Hong F-Y, Lin C-C, Lin T-J, Huang D-H. The relationship among the social norms of college students, and their interpersonal relationships, smartphone use, and smartphone addiction. Behav Inform Technol. 2021;40(4):415–26.

    Article  Google Scholar 

  60. Csikszentmihalyi M, Csikzentmihaly M, Flow. The psychology of optimal experience. Harper & Row New York; 1990.

  61. Moretta T, Franceschini C, Musetti A. Loneliness and problematic social networking sites use in young adults with poor vs. good sleep quality: the moderating role of gender. Addict Behav. 2023;142:107687.

    Article  PubMed  Google Scholar 

  62. Mi Y, Lei X. Sleep loss and lack of social interaction: a summary interview. Brain-Apparatus Communication: J Bacomics. 2023;2(1):2163593.

    Article  Google Scholar 

  63. Bai j, Zhao Y, Jian Y, Deng Q. The influence of loneliness on the interpersonal goal-pursuit: the role of likelihood of goal attainment. Stud Psychol Behav. 2022;20(4):464–71.

    Google Scholar 

  64. Zhang Y, Ding Q, Wang Z. Why parental phubbing is at risk for adolescent mobile phone addiction: A serial mediating model. Child Youth Serv Rev. 2021;121:105873.

    Article  Google Scholar 

  65. Li W, Wang J, Zu J, Li C. An analysis of cross-lagged on the relationship between social anxiety, self-control and loneliness of primary school students. Psychol Dev Educ. 2024;40(5):687–94.

    Google Scholar 

  66. Chu X, Long J, Lei L. The relationship between social interaction anxiety and undergraduates’ problematizing excessive online gaming: the mediating role of self-compensation motivation and moderating role of extroversion. J Psychol Sciency. 2020;43(4):943–9.

    Google Scholar 

  67. Clayton M, Helms B, Simpson C. Active prompting to decrease cell phone use and increase seat belt use while driving. J Appl Behav Anal. 2006;39(3):341–9.

    Article  PubMed  PubMed Central  Google Scholar 

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Acknowledgements

We would like to express our sincere gratitude to the respondents for their time in completing the survey.

Funding

This research was funded by Program for Science and Technology Development of Henan Province (grant numbers 242102321087; 232103810101); Program for international science and technology cooperation of Henan province (grant numbers 241111520300); Planning projects of philosophy and Social Sciences of Henan Province (grant numbers 2023CJY078).

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Authors and Affiliations

  1. International Joint Laboratory of Behavior and Cognitive Science, Zhengzhou Normal University, Zhengzhou, Henan, China

    Kaibin Zhao, Yu Liu, Yiming Shi, Dandan Bi, Ruijun Chen & Zheng Jin

  2. Music College, Hansei University, Gunpo-si, Gyeonggi-do, South Korea

    Chu Zhang

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  1. Kaibin Zhao
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Contributions

Kaibin Zhao and Chu Zhang contributed to the design of the study. The topic selection, data collection and processing, thesis writing and revision of this study were done by Kaibin Zhao, Yu Liu, Yiming Shi and Chu Zhang; Dandan Bi and Ruijun Chen was involved in the revision of the thesis; the development of the research plan and the revision of the thesis were done by Kaibin Zhao and Zheng Jin. All authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.

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Correspondence to Kaibin Zhao or Yiming Shi.

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Informed consent was obtained from all human participants involved in the study. The study was conducted in accordance with the Declaration of Helsinki, and approved by the Ethics Committee of Zhengzhou Normal University (Approval Number: ZZNU-2024-017).

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Not applicable.

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The authors declare no competing interests.

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Zhao, K., Liu, Y., Shi, Y. et al. Mobile phone addiction and interpersonal problems among Chinese young adults: the mediating roles of social anxiety and loneliness. BMC Psychol 13, 372 (2025). https://doiorg.publicaciones.saludcastillayleon.es/10.1186/s40359-025-02686-0

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BMC Psychology

ISSN: 2050-7283

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