From early to late adolescence: Effect of problematic mobile phone use on depression of adolescents

Abstract

Problematic mobile phone use can predict depression in adolescents, but few studies have thoroughly explored its internal mechanism. This study surveyed 1,768 Chinese adolescents in three educational levels (upper grades of elementary, junior middle, and high school levels) using a questionnaire. Results showed that (1) problematic mobile phone use significantly positively predicted adolescents’ depression after controlling for gender and age, (2) parent–child relationship played a mediating role between problematic mobile phone use and adolescents’ depression, and (3) adolescents’ educational level moderated relationships between problematic mobile phone use and parent–child relationship as well as parent–child relationship and depression. The negative effect of problematic mobile phone use on the parent–child relationship and the impact of the parent–child relationship on depression are weakened as the educational level of adolescents increases. These findings indicated that problematic mobile phone use affects adolescents’ depression by reducing the quality of parent–child relationship, wherein the degree of influence reduces at high educational levels. Limitations and future directions of this study were also discussed.

Keywords

problematic mobile phone use depression parent–child relationship adolescents

Introduction

Smartphones have become an indispensable part of people’s daily lives and smartphones’ performance and functions are constantly expanding with the development of network and information technology. Mobile phone users have increased from 2.5 billion to 3.5 billion worldwide between 2016 and 2020 (Global Mobile Statistics, 2020). The scale of mobile Internet users in China has reached 986 million, of which 133 million are between the ages of 10 and 19 years old (China Internet Network Information Center [CNNIC], 2021). Adolescents have become one of the largest groups of mobile phone users. While enjoying the convenience and comfort brought by mobile phones, adolescents also fall into the “trap” of mobile phone use, including problematic mobile phone use. Problematic mobile phone use refers to the inability to regulate one’s own mobile phone use that negatively impacts one’s daily life (for review, Billieux, 2012). An empirical study showed that problematic mobile phone use causes not only deterioration in academic performance (Seo et al., 2016) but also emotional disorders, such as depression (Chen et al., 2016; Jun, 2016) and interpersonal problems (Chen et al., 2016). Thus, problematic mobile phone use has increasingly become an important unsolved problem in the psychological development of adolescents. Meanwhile, adolescence is a period of high incidence of emotional and affective disorders (Costello et al., 2005). For example, the incidence of depression in adolescents is 20% (for review, Thapar et al., 2012). Problematic mobile phone use is significantly related to adolescents’ depression (for review, Thomée, 2018). However, studies on underlying mechanisms of the relationship between problematic mobile phone use and depression in adolescents are limited.

Displacement hypothesis demonstrated that greater use of the Internet was associated with declines in their face-to-face communication with family members in the household, declines in their social circle size, and increases in their depression and loneliness (Kraut et al., 1998). An empirical study found that interpersonal relationships play a mediating role between problematic mobile phone use and depression (Chen et al., 2016). The parent–child relationship is an important part of adolescents’ interpersonal relationships. The role of the parent–child relationship between problematic mobile phone use and depression should be further explored. In addition, individuals are in constant developmental changes during their adolescence (Steinberg, 2005), and the rate of problematic mobile phone usage increases with the age of adolescents (Gilly et al., 2012). The relationship between problematic mobile phone use and depression of adolescents must be explored at different development stages. Therefore, a moderated mediation model is constructed in the present study to (a) clarify how (mediation of the parent–child relationship) and when (moderated of the educational level) problematic mobile phone use affects adolescents’ depression, (b) contribute to research on adolescent depression in the context of the Internet, and (c) provide important evidence for intervention and treatment of depression in adolescents.

Association between problematic mobile phone use and adolescents’ depression

Depression is a common negative emotion in adolescents and characterized by depressed mood, lack of interest and pleasure, lack of energy, and feelings of worthlessness (Major et al., 2000). A cross-sectional study of a large sample indicated that mobile phone dependence can positively predict depression in adolescents (Seo et al., 2016). A meta-analysis study showed that problematic mobile phone use is closely related to depression (Thomée, 2018). Systematic reviews have indicated that problematic mobile phone use is an important cause of increased depression among adolescents in recent years (for review, Elhai et al., 2017). Moreover, a large sample follow-up study revealed that problematic mobile phone use can predict depression in adolescents aged 20–24 one year later (Thomée et al., 2011). On the basis of these studies, the relationship between problematic mobile phone use and depression is mainly understood in the following aspects. First, mobile game, social network, and information addictions are all closely related to depression (Tamura et al., 2017; Wang et al., 2019). Problematic mobile phone use is a collection of game, social network, and information-seeking addictions that contribute to the possible occurrence of depression to a certain extent (Demirci et al., 2015). Second, problematic mobile phone use may be a way for adolescents to deal with negative events and emotions (Fumero et al., 2018; Kim et al., 2015). Third, although online social support can be obtained through mobile phone media, social support theory showed that communication through mobile phones may fail to generate offline social support needed in the physical and mental development of individuals (Cohen et al., 1985). Face-to-face interaction provides solid social support because it involves rich and multifaceted information exchange; this type of information exchange is usually absent in smartphone-based communication (Cerulo, 1997). Therefore, this kind of online social support obtained from social networking may fail to help individuals solve real-world problems and contribute to depression. Hence, we hypothesized that problematic mobile phone use can positively predict adolescent depression (H1).

Role of parent–child relationship between problematic mobile phone use and depression

According to ecological systems theory, family is an important microsystem for socialization and development of adolescents and the parent–child relationship is a key factor in the family system (Bronfenbrenner, 2005). The parent–child relationship is an interpersonal association between parents and children and an important variable in the family system that affects individual development and adaptation (Baldwin, 1948). Displacement hypothesis argues that addiction to mobile phones and other media may cause successive psychological and behavioral problems, reduce face-to-face interactions with others in real life, and lead to additional interpersonal problems (Kraut et al., 1998; Kuss & Griffiths, 2011). Previous studies showed that problematic mobile phone use can predict the decline of interpersonal relationships (Chen et al., 2016). As an important part of adolescent interpersonal relationships, the parent–child relationship may deteriorate due to adolescent problematic mobile phone use. A recent systematic review showed that excessive mobile phone use was associated with impaired parent–child relationships (Sahu et al., 2019). Data on 9,732 students demonstrated that the heavy use of social media is associated with negative parent–child relationships (Sampasa-Kanyinga et al., 2020). Previous studies showed that excessive mobile phone use may damage the quality of the parent–child relationship.

Meanwhile, high quality parent–child relationship is the key to maintaining the mental health of adolescents (Nickerson & Nagle, 2004). Attachment theory showed that satisfactory parent–child relationships can provide warmth and social support to children (Bowlby, 1982; Chng et al., 2015). An empirical study revealed that positive parent–child relationships help reduce the occurrence of depression among adolescents (Liu, 2003) and negative parent–child relationships (such as parent–child conflicts) can positively predict the occurrence of depression in adolescents (Piña-Watson & Castillo, 2015; Reinherz et al., 2003; Yang et al., 2017). Thus, excessive mobile phone use may contribute to depression among adolescents by weakening the quality of the parent–child relationship. Therefore, we hypothesized that the parent–child relationship mediates the relationship between problematic mobile phone use and adolescents’ depression (H2).

Moderated effect of educational level

Individuals experience multiple physical and psychosocial challenges during adolescence. Adolescents vary in physical, psychological, cognitive, and social developments at different developmental stages (Shaffer & Kipp, 2016). The adolescent period can be divided into three stages, namely, early (10–13 years old), middle (14–17 years old), and late (18–20 years old) adolescence (Smetana & Rote, 2019). For adolescents receiving secondary education, the development stages correspond to the educational stages. Problematic mobile phone usage varies among adolescents at different developmental stages. Specifically, the ratio of mobile phone use and mobile phone dependence among adolescents escalates with the increase of educational level (Gao et al., 2014). This finding may be due to the different maturation times of the adolescent brain and cognitive and behavioral systems, and a potential disconnection exists, especially in the limbic system that drives emotions and the prefrontal cortex that controls impulses (Steinberg, 2005). Notably, the individual’s sensory seeking behavior increases and reward orientation is strengthened in early adolescence, adjustment of deviant behaviors is difficult in middle adolescence, and maturity of the frontal cortex can promote their ability to regulate behaviors in late adolescence. The different sensory seeking intensities and behavioral adjustment abilities of adolescents at various stages may lead to differences in the degree of problematic mobile phone use. In addition, a longitudinal study showed that depression levels increase in middle adolescence and decrease in early and late adolescence (Ge et al., 2006). Furthermore, Costello et al. (2008) tracked the development trajectory of depression in 11,559 adolescents and revealed the following depression development trajectories in individuals from adolescence to early adulthood: (1) absence of depression (28.7%), (2) stable low depression (59.4%), (3) high level of depression in the early stage that gradually reduces (9.4%), and (4) depression that gradually increases in the late stage (2.4%). The development of adolescent depression exhibits evident stage characteristics.

Parent–child relationships change with the development of adolescents. Parent–child conflicts increase linearly from early adolescence to middle adolescence and then decline in late adolescence (De Goede et al., 2009; Herrenkohl et al., 2009). Another meta-analysis also showed that the frequency of parent–child conflicts decreases with age in all stages of adolescence while the intensity of conflict emotion increases from early adolescence to middle adolescence (Laursen et al., 1998). Long-term hostility in the family and conflict in the parent–child relationship is associated with poor psychosocial functions (Herrenkohl & Herrenkohl, 2007; Hoeve et al., 2007; Hofer et al., 2013), such as adolescent depression. Hence, we deduced that the relationship among problematic mobile phone use, parent–child relationship, and depression are possibly moderated by the educational level. We hypothesized that adolescents’ educational level moderates the relationship among problematic mobile phone use, parent–child relationship, and depression (H3).

Present study

The moderated mediation model shown in Figure 1 is constructed in this study to investigate (1) whether the parent–child relationship mediates the relationship between problematic mobile phone use and depression and (2) how adolescents’ educational level moderates the relationship between problematic mobile phone use and depression.

Method

Participants

A total of 1,846 students were selected from various schools in eastern China to complete questionnaires on problematic mobile phone use, parent–child relationship, and depression. A total of 1,768 valid questionnaires with an effective rate of 95.77% were obtained after eliminating questionnaires with false/missed and wrong answers. Participants in our study were 556 primary (age range: 10–14 years old, M = 11.21, SD = 0.79, and 287 male students, accounting for 51.8%), 644 junior middle (age range: 11–16 years old, M = 12.85, SD = 0.77, and 342 male students, accounting for 53.4%), and 568 senior high (age range: 14–18 years old, M = 15.75, SD = 0.74, and 306 male students, accounting for 54%) school students. The research team’s University Ethics Committee approved the study. Written informed consent were obtained from all participants before completing the survey.

Measures

Problematic mobile phone use

The Mobile Phone Addiction Index (MPAI) (Leung, 2008) was used to measure the problematic mobile phone use of adolescents at different stages. The scale included 17 questions that cover four dimensions, namely, withdrawal, loss of control, inefficiency, and avoidance. Items were measured on a scale of 1 (strongly disagree) to 5 (strongly agree). A high score corresponds to a high tendency of problematic mobile phone use. The scale demonstrates satisfactory reliability and validity (Gao et al., 2020). The Cronbach’s alpha coefficient of the scale is 0.90 in this study.

Depression

The depression subscale in the Subjective Quality of Life Scale is a seven-item technique that demonstrates acceptable reliability and used to evaluate the degree of depression in adolescents at different stages (Cheng et al., 1998). Each item was measured on a four-point Likert scale ranging from 1 (none) to 4 (always). High scores indicate high levels of depression. The Cronbach’s alpha coefficient of the scale is 0.84 in this study.

Parent–child relationship

Parent-Adolescent Relationship Scale was developed by Kerr and Stattin in 2000 and then revised by Zhu et al. (2015) to assess feelings of adolescents on their relationship with their parents in the past six months. This 16-item scale, including mother–child and father–child relationships, demonstrates satisfactory reliability and validity. Each item was measured on a four-point Likert scale ranging from 1 (never) to 4 (always). A high total score indicates an increasingly positive parent–child relationship. The Cronbach’s alpha coefficient of the scale is 0.87 in this study.

Procedure and statistical analysis

Teachers administered the surveys to their class after receiving training. Standard instructions were provided to all participants before administering the survey to explain objectives of the study, confidentiality principle, answer method to questions, and other notable matters. The entire survey could be completed in 30 minutes. SPSS 24.0 was used to conduct descriptive statistical analysis, correlation analysis, and ANOVA test. The SPSS program PROCESS Macro was then used for moderated mediating effect analysis. This process is widely used in mediate, moderate, and moderated mediating models (Gao et al., 2020). Bootstrap method with bias correction was used to perform replay sampling 5,000 times. Interval estimation and significance test were also performed. The mediation effect is significant when the confidence interval does not contain zero.

Common method biases

Variables were measured using self-report questionnaires in this study, and a common method bias may exist. Harman’s single-factor test was used to ensure the accuracy of results. The results showed that eight factors demonstrate a characteristic root value of more than 1. The first largest factor indicated that the total variance of depression is 22.94%, which is less than the critical standard value of 40% (Zhou & Long, 2004). This finding indicated that evident common method biases are absent in the present study.

Results

Primary analysis

The results of correlation analysis (see Table 1) showed that problematic mobile phone use is significantly negatively correlated with parent–child relationship and significantly positively associated with adolescent depression. A significant negative correlation also exists between the parent–child relationship and adolescent depression.

Table 1.

Correlation analysis results.

Variables	M ± SD	1	2	3	4
1 Age	13.26 ± 1.99	–
2 Problematic mobile phone use	41.50 ± 14.27	0.39***	–
3 Parent-child relationship	48.42 ± 8.26	−0.11***	−0.31***	–
4 Depression	12.05 ± 4.28	0.19***	0.34***	−0.39***	–

***p < 0.001; **p < 0.01.

The results of one-way ANOVA (see Table 2) revealed that significant differences exist in problematic mobile phone use [F_(21,765) = 151.18, p < 0.001, η² = 0.15], depression [F_(21,765) = 44.54, p < 0.001, η² = 0.05], and parent–child relationship [F_(21,765) = 35.96, p < 0.001, η² = 0.04] among different educational levels. Multiple comparisons showed that scores of junior middle and senior high school students are significantly higher than those of primary school students in terms of problematic mobile phone use and depression while scores of senior high school students are significantly higher than those of junior middle school students. Primary school scores were higher than junior middle and senior high school scores while senior high school scores were higher than junior middle school scores in terms of the parent–child relationship. Notably, problematic mobile phone use and depression levels increase with the increase of the educational level and the parent–child relationship is the best in primary school, followed by senior high school and then junior middle school.

Table 2.

Results of one-way ANOVA.

	Primary school period (M ± SD)	Junior middle school period (M ± SD)	Senior high school period (M ± SD)	F
Problematic mobile phone use	34.76 ± 12.42	41.19 ± 14.28	48.44 ± 12.63	151.18***
Parent-child relationship	50.71 ± 8.42	46.79 ± 8.45	48.03 ± 7.36	35.96***
Depression	10.71 ± 4.14	12.40 ± 4.43	12.97 ± 3.91	44.54***

***p < 0.001; **p < 0.01.

Testing for moderated mediation

PROCESS (Hayes, 2012) was used in this study and two dummy variables were coded for the primary school period as the reference group. The moderated mediation effect test was conducted under the condition of controlling for gender and age. “HC3” in PROCESS was used to correct the mediation and moderation analysis because of the heteroscedasticity problem between the parent–child relationship and depression (Hayes, 2012).

First, Model 4 of Hayes (2012) SPSS Macro program was used to test the mediation effect of the parent–child relationship between problematic mobile phone use and depression in adolescents while controlling for gender and age. The results showed that problematic mobile phone use significantly positively predicts depression (β = 0.29, t = 12.02, p < 0.001), and the problematic mobile phone use significantly negatively predicts parent-child relationship (β = −0.29, t = −11.54, p < 0.001); when the problematic mobile phone use and the parent-child relationship to predict depression simultaneously, the parent-child relationship has a negative prediction function on depression (β = −0.31, t = −11.59, p < 0.001), and problematic mobile phone use had a significant positive prediction function on depression (β = 0.20, t = 8.23, p < 0.001) (see Table 3). The results showed that the parent–child relationship partially mediates effects of problematic mobile phone use on depression. The indirect effect of problematic mobile phone use on depression via the parent–child relationship was 0.09, 95% Bootstrap [0.07, 0.11], and the mediation effect accounts for 30.49% of the total effect.

Table 3.

Mediation model test of parent-child relationship.

	Model 1 (Criterion = Depression)		Model 2 (Criterion = Parent-child relationship)		Model 3 (Criterion = Depression)
	β	t	β	t	β	t
Gender	0.05	1.09	0	0.09	0.05	1.17
Age	0	−0.30	0	−0.05	0	−0.34
Problematic mobile phone use	0.29	12.02***	−0.29	−11.54***	0.20	8.23***
Parent-child relationship					−0.31	−11.59***
R²	0.08		0.08		0.17
F	48.89***		45.19***		77.00***

***p < 0.001; **p < 0.01. All the continuous variables in the model were put into the regression equation after standardized treatment. Gender 1 = male, 2= female.

Model 59 in the SPSS Macro compiled by Hayes (2012) was used to test the moderated mediation model under the condition of controlling for gender and age. The results showed that the interaction between problematic mobile phone use and educational level exerts a significant predictive effect on the parent–child relationship (β = 0.20, t = 3.24, p < 0.01). The interaction between parent–child relationship and educational level exerts a significant predictive effect on depression (β = 0.18, t = 2.70, p < 0.01). This finding indicated that educational level can moderate the predictive effect of problematic mobile phone use on the parent–child relationship and the predictive effect of the parent–child relationship on depression (see Table 4).

Table 4.

Moderated mediation model tests.

	Model 1 (Criterion = Parent-child relationship)		Model 2 (Criterion = Depression)
	β	t	β	t
Gender	−0.01	−0.14	0.06	1.31
Age	0.01	0.18	−0.03	−0.89
Problematic mobile phone use	−0.38	−9.06***	0.18	4.49***
Parent-child relationship			−0.43	−8.31***
Education level	−0.01	−0.11	0.04	0.54
Problematic mobile phone use × Education level	0.20	3.24**	−0.03	−0.43
Parent-child relationship × Education level			0.18	2.70**
R ²	0.09		0.18
F	22.77***		33.26***
Mediating effect in different education level	β	Boot SE	Boot LLCI	Boot ULCI
Primary school (1.00)	0.16	0.03	0.11	0.22
Junior middle school (2.00)	0.08	0.02	0.05	0.11
Senior high school (3.00)	0.04	0.01	0.02	0.07

***p < 0.001; **p < 0.01. All the continuous variables in the model were put into the regression equation after standardized treatment; Gender 1 = male, 2= female.

Simple slope analysis showed that the predictive effect of problematic mobile phone use on the parent–child relationship weakens from primary school level (β = −0.38, t = −9.06, p < 0.001), to junior middle school level (β = −0.31, t = −7.81, p < 0.001), and then to senior high school levels (β = −0.18, t = −3.80, p < 0.001) (see Figure 2). The effect of the parent–child relationship on depression weakens from primary school level (β = −0.43, t = −8.31, p < 0.001), to junior middle school level (β = −0.25, t = −5.89, p < 0.001), and then to senior high school level (β = −0.25, t = −5.73, p < 0.001) (see Figure 3). In addition, the mediation effect of the parent–child relationship on the relationship between problematic mobile phone use and depression also demonstrates a decreasing trend at the three education levels (see Table 4). Hence, the effect of problematic mobile phone use on depression weakens when the parent–child relationship deteriorates with the increase of the educational level.

Discussion

The potential mechanism between problematic mobile phone use and depression in Chinese adolescents were examined in this study. The results suggested that the parent–child relationship plays a mediating role between problematic mobile phone use and adolescents’ depression. Meanwhile, the educational level of adolescents can play a moderated role in the relationship between problematic mobile phone use and the parent–child relationship as well as the parent–child relationship and adolescents’ depression.

Differences in problematic mobile phone use

Significant differences exist in the problematic mobile phone use among students from different education levels. Problematic mobile phone use intensifies as the education level increases likely due to the following reasons. First, students in different education levels demonstrate various mobile phone ownerships. The Internet penetration rate of primary school students is 89.4%, while that of junior and senior high school students is 97.6% (CNNIC, 2020). Moreover, ownership of mobile phones in primary school students is unlikely. Second, the proportion of primary school students engaged in online social activities (online chatting, watching the news, and online shopping) is lower than that of other schools. The increase from primary school to junior middle school is 29.8% while that from junior middle school to senior high school is 9.9% in terms of usage of social networking sites; this finding demonstrated that the junior middle school level may be a critical period in the formation of online social attributes of adolescents that can lead to increasingly problematic mobile phone use (CNNIC, 2020).

Mediating role of the parent–child relationship

The parent–child relationship is an important factor that affects adolescent development and adaptation. Exploring the mediating role of this relationship in the relationship between problematic mobile phone use and depression helps reveal which factors of problematic mobile phone use may exert adverse effects on an individual’s mental health. The results of this study showed that problematic mobile phone use can influence adolescent depression through the mediating effect of the parent–child relationship. This result verified our H2 and supported the previous findings of Chen et al. (2016). Parent–child relationship problems caused by problematic mobile phone use of adolescents may further induce the occurrence of depression. This mechanism may be explained as follows. First, problematic mobile phone use negatively affects the parent–child relationship. Adolescents with problematic mobile phone use tend to communicate with others by calling or texting rather than performing face-to-face communication because this can help make them feel comfortable (Kamibeppu & Sugiura, 2005). However, this behavior may weaken the effectiveness of information exchange and emotional communication between parents and children and thus damage the parent–child relationship. The problematic mobile phone use of adolescents is often accompanied by game and social addictions and adolescents tend to shift the focus of interpersonal relationship establishment and maintenance from their parents to peers; these behaviors may decrease face-to-face communication and deteriorate the quality of the parent–child relationship (Kraut et al., 1998; Kuss & Griffiths, 2011). Meanwhile, the improper control of adolescent behavior of parents often causes parent–child conflicts and thus result in the deterioration of the parent–child relationship quality. Second, the parent–child relationship can negatively predict adolescents’ depression. Adolescents demonstrate low levels of depression when they perceive a positive relationship with their parents (Piña-Watson & Castillo, 2015). Attachment theory states that a positive parent–child relationship may provide warmth and support to children, and these factors are important in maintaining adolescent mental health and may effectively prevent depression among adolescents (Bowlby, 1982).

Moderating role of educational level

Educational level can moderate the first and second halves of the “problematic mobile phone use/parent–child relationship/depression” mediation chain. Specifically, the impact of problematic mobile phone use on the parent–child relationship is significant in primary school, and this negative impact gradually weakens in middle and high school levels. This finding may be due to the weak self-control ability of children in primary school (Steinberg, 2005), and parents tend to supervise their children’s external behaviors, such as mobile phone use. Parental restriction of children’s external social development can easily cause conflicts between parents and children. Moreover, children in primary school experience more frequent contact with their parents in space and time than older children. Thus, problematic mobile phone use can easily intensify conflicts between parents and children. Although problematic mobile phone use will also cause the decline in the quality of the parent–child relationship in junior middle school, these students are better at self-management than primary school students, parental supervision of their children is relatively lax, and the time for parent–child contact is reduced. These behaviors may effectively alleviate the negative impact of problematic mobile phone use on the parent–child relationship. The adolescents in this study and a part of Chinese adolescents will live in school during senior high school, and the space distance between adolescents and their parents will be widened further as the contact time decreases. Therefore, the impact of problematic mobile phone use on the parent–child relationship is further reduced at this stage. A high level of education generally indicates minimal impact of problematic mobile phone use on the parent–child relationship.

The predictive effect of the parent–child relationship on adolescent depression is most significant in primary school, and this effect gradually weakens in junior middle and senior high school levels. Family is a crucial source of social support for individuals in lower grades, and conflicts between parents and children fail to provide warmth and support to adolescents. This lack of warmth and support may cause additional mental health problems. Interpersonal relationships of adolescents in the upper grades gradually shifts from the parent–child relationship in the early stage to peer relationships (Zhong et al., 2014). A positive peer relationship that helps adolescents obtain social support (Mota & Matos, 2013; Pascuzzo et al., 2013) may effectively alleviate the impact of parent–child conflict on adolescent depression. Thus, the predictive effect of parent–child relationships on depression weakens from early adolescence to middle adolescence.

Implications in theory and practice

A moderated mediating effect model is constructed in this study to reveal how (mediating effect of the parent–child relationship) and when (moderating effect of the educational level) problematic mobile phone use affects adolescent depression. The results showed that the parent–child relationship plays an important role in the influence of problematic mobile phone use on adolescent depression and the effect of the parent–child relationship weakens with the increase of adolescent educational level. This study can provide empirical support and a theoretical reference for mitigating the influence of problematic mobile phone use and maintaining the physical and mental health of adolescents in the mobile Internet era.

Mobile phone use demonstrates both favorable and unfavorable consequences. An optimal method for maximizing positive impacts and minimizing negative impacts is necessary to regulate mobile phone usage. First, schools and school administrators can increase the number of campus public telephones, use specially designed student mobile phones (e.g., the mobile phone provides parent backstage control function, automatic shielding of bad information function, time management function), and sign an agreement between families and schools to reduce the problematic mobile phone use of students (Gao et al., 2014). Second, teachers and school administrators must focus on promoting the cultivation of adolescents’ network literacy to improve their ability in managing mobile phone use. Third, school staff should fully consider the complex diversity at different education levels rather than treat these levels as a homogeneous entity when developing effective intervention and guidance measures in the various growth stages of adolescence. Fourth, problematic mobile phone use damages the parent–child relationship and thus affects the mental health of adolescents. Therefore, parents should consciously encourage their children to practice face-to-face communication and reduce online communication via mobile phones while providing a warm and supportive growth environment to enhance the important role of the parent–child relationship. Finally, the parent–child relationship plays an important role in early adolescence. Apart from strengthening the parent–child relationship, parents and teachers should actively promote the positive effect of peer and teacher–student relationships on adolescents during middle and late adolescence stages.

Limitations

This study presents the following limitations. First, causality cannot be inferred in the present study due to its cross-section design. Future investigations should use longitudinal designs or experiments to explore the causal relationship between problematic mobile phone use and depression as well as problematic mobile phone use and the parent–child relationship. Second, other important factors, such as parenting style and family economic status of adolescents themselves, may exist between problematic mobile phone use and depression. Such factors must be further explored. Third, many mobile phone activities, such as video gaming and social networking, and their effects on adolescent depression should be explored and compared in future investigations. Fourth, the education level may be correlated with other factors, such as children’s developmental stage. Future investigations should use pure and adjustable variables as the moderating variable. Finally, this study based on a sample from a specific city and cultural context rather than diverse locations. The degree to which the findings would generalize to other populations nationally and internationally is unknown, and warrants further investigation.

Conclusions

This work extends a previous study by examining the underlying mechanism between problematic mobile phone use and adolescents’ depression. Problematic mobile phone use can increase depression in adolescents by weakening the parent–child relationship. Moreover, the moderating effect of educational level is explored in this study. The impact of problematic mobile phone use on the parent–child relationship and that of the parent–child relationship on depression gradually weakened with the increase of the educational level.

Footnotes

Ethical statement

Shenzhen University Ethics Committee provided approval for the study. All participants were offered the possibility of contact with the authors in case they had questions or concerns regarding the study.

Declaration of conflicting interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was supported by the National Social Science Fund of China (Grant Number 16BSH089), Research Program Funds of the Collaborative Innovation Center of Assessment Toward Basic Education Quality at Beijing Normal University (KJ02252019-0801), Fundamental Research Funds of Central China Normal University (CCNU20ZT016).

ORCID iDs

Fanchang Kong

Jianjun Deng

Author biographies

Fanchang Kong is an Associate Professor and Deputy Director of the Institute of Developmental Psychology, Central China Normal University. Research fields include adolescent sociality and personality development; Internet use and adolescent development; self and health.

Guofeng Liu, a master degree student in Development Psychology at Central China Normal University, with a focus on adolescent cyber psychology and behavior.

Qiufeng Gao is an Assistant Professor in the Department of Sociology at Shenzhen University. She has expertise in adolescent mobile phone addiction, bullying and parent-child relationship, with a particular interest in parents’ involvement in children’s education.

Jianjun Deng is a Psychological Counseling Teacher, Faculty of Education, Shenzhen University. He has expertise in psychology counseling and youth education, with a particular interested in teenage cell phone addiction.

References

Baldwin

A. L.

(1948). Socialization and the parent-child relationship. Child Development, 19, 127–136. http://dx.doi.org/10.2307/1125710

Billieux

(2012). Problematic use of the mobile phone: A literature review and a pathways model. Current Psychiatry Reviews, 8, 299–307. http://dx.doi.org/10.2174/157340012803520522

Bowlby, J. (1982). Attachment and loss: Vol. 1. Attachment (2nd ed.). New York: Basic Books.

Bronfenbrenner, U. (2005). Making human beings human: Bioecological perspectives on human development. Thousand Oaks: Sage.

Cerulo

K. A.

(1997). Reframing sociological concepts for a brave new (virtual?) world. Sociological Inquiry, 67, 48–58. https://doi.org/10.1111/j.1475-682X.1997.tb00428.x

Chen

Yan

Tang

Yang

Xie

(2016). Mobile phone addition levels and negative emotions among Chinese young adults: The mediating role of interpersonal problems. Computers in Human Behavior, 55, 856–866. https://doi.org/10.1016/j.chb.2015.10.030

Cheng

Z. H.

Gao

B. L.

Peng

Lei

L. F.

(1998). Preparation and reliability and validity analysis of children's subjective quality of life questionnaire. Chinese Journal of Clinical Psychology, 6, 11–16. https://doi.org/https://doi.org/10.16128/j.cnki.1005-3611.1998.01.003

China Internet Network Information Center. (2020). Nation research report on internet use by minors. http://www.cnnic.net.cn/

China Internet Network Information Center. (2021). 47th Statistical report on internet development in China. http://www.cnnic.net.cn/

10.

Chng

G. S.

Liau

A. K.

Khoo

(2015). Moderating eﬀects of the family environment for parental mediation and pathological internet use in youths. Cyberpsychology, Behavior and Social Networking, 18, 30–36. https://doi.org/10.1089/cyber.2014.0368

11.

Cohen, S., Mermelstein, R., Kamarck, T., & Hoberman, H. M. (1985). Measuring the functional components of social support. In Sarason, I. G., Sarason, B. R. (Eds.), Social support: Theory, research and applications (pp. 73–94). Martinus Niijhoff. https://doi.org/10.1007/978-94-009-5115-0_5

12.

Costello

Egger

Angold

(2005). 10-year research update review: The epidemiology of child and adolescent psychiatric disorders: I. Methods and public health burden. Journal of the American Academy of Child and Adolescent Psychiatry, 44, 972–986. https://doi.org/10.1097/01.chi.0000172552.41596.6f

13.

Costello

D. M.

Swendsen

Rose

J. S.

Dierker

L. C.

(2008). Risk and protective factors associated with trajectories of depressed mood from adolescence to early adulthood. Journal of Consulting and Clinical Psychology, 76, 173–183. https://doi.org/10.1037/0022-006X.76.2.173

14.

De Goede

I. A.

Branje

S. T.

Delsing

M. H.

Meeus

W. J.

(2009). Linkages over time between adolescents’ relationships with parents and friends. Journal of Youth and Adolescence, 38, 1304–1315. https://doi.org/10.1007/s10964-009-9403-2

15.

Demirci

Akgönül

Akpinar

(2015). Relationship of smartphone use severity with sleep quality, depression, and anxiety in university students. Journal of Behavioral Addictions, 4, 85–92. https://doi.org/10.1556/2006.4.2015.010

16.

Elhai

J. D.

Levine

J. C.

Dvorak

R. D.

Hall

B. J.

(2017). Problematic smartphone use: A conceptual overview and systematic review of relations with anxiety and depression psychopathology. Journal of Affective Disorders, 207, 251–259. https://doi.org/10.1016/j.jad.2016.08.030

17.

Fumero

Marrero

R. J.

Voltes

Penate

(2018). Personal and social factors involved in internet addiction among adolescents: A meta-analysis. Computers in Human Behavior, 86, 387–400. https://doi.org/10.1016/j.chb.2018.05.005

18.

Gao

Sun

Jia

Xiang

(2020). Parent-child relationship and smartphone use disorder among Chinese adolescents: The mediating role of quality of life and the moderating role of educational level. Addictive Behaviors, 101, 106065. https://doi.org/10.1016/j.addbeh.2019.106065

19.

Gao

Yan

Zhao

Pan

(2014). To ban or not to ban: Differences in mobile phone policies at elementary, middle, and high schools. Computers in Human Behavior, 38, 25–32. https://doi.org/10.1016/j.chb.2014.05.011

20.

Natsuaki

M. N.

Conger

R. D.

(2006). Trajectories of depressive symptoms and stressful life events among male and female adolescents in divorced and nondivorced families. Development and Psychopathology, 18, 253–273. https://doi.org/10.1017/S0954579406060147

21.

Gilly

M. C.

Celsi

M. W.

Schau

H. J.

(2012). It don't come easy: Overcoming obstacles to technology use within a resistant consumer group. Journal of Consumer Affairs, 46, 62–89. https://doi.org/10.1111/j.1745-6606.2011.01218.x

22.

Global Mobile Statistics. (2020). Number of smartphone users from 2016 to 2021. https://www.statista.com/statistics/330695/number-of-smartphone-users-worldwide/

23.

Hayes, A. F. (2012). PROCESS: A versatile computational tool for observed variable mediation, moderation, and conditional process modeling. University of Kansas, KS.

24.

Herrenkohl

T. I.

Herrenkohl

R. C.

(2007). Examining the overlap and prediction of multiple forms of child maltreatment, stressors, and socioeconomic status: A longitudinal analysis of youth outcomes. Journal of Family Violence, 22, 553–562. http://dx.doi.org/10.1007/s10896-007-9107-x

25.

Herrenkohl

T. I.

Kosterman

Hawkins

Mason

(2009). Effects of growth in family conflict in adolescence on adult depressive symptoms: Mediating and moderating effects of stress and school bonding. The Journal of Adolescent Health: Official Publication of the Society for Adolescent Medicine, 44, 146–152. http://dx.doi.org/10.1016/j.jadohealth.2008.07.005

26.

Hoeve

Smeenk

W. H.

Loeber

Stouthamer-Loeber

Van der Laan

P. H.

Gerris

J. R.

Dubas

J. S.

(2007). Long term effects of parenting and family characteristics on delinquency of male young adults. European Journal of Criminology, 4, 161–194. https://doi.org/10.1177/1477370807074854

27.

Hofer

Eisenberg

Spinrad

T. L.

Morris

A. S.

Gershoff

Valiente

, … Eggum

N. D.

(2013). Mother-adolescent conflict: Stability, change, and relations with externalizing and internalizing behavior problems. Social Development (Oxford, England), 22, 259–279. https://doi.org/10.1111/sode.12012

28.

Jun

(2016). The reciprocal longitudinal relationships between mobile phone addiction and depressive symptoms among Korean adolescents. Computers in Human Behavior, 58, 179–186. https://doi.org/10.1016/j.chb.2015.12.061

29.

Kamibeppu

Sugiura

(2005). Impact of the mobile phone on junior high-school students’ friendships in the Tokyo metropolitan area. Cyberpsychology & Behavior: The Impact of the Internet, Multimedia and Virtual Reality on Behavior and Society, 8, 121–130. https://doi.org/10.1089/cpb.2005.8.121

30.

Kerr

Stattin

(2000). What parents know, how they know it, and several forms of adolescent adjustment: Further support for a reinterpretation of monitoring. Developmental Psychology, 36, 366–380. https://doi.org/10.1037/0012-1649.36.3.366

31.

Kim

J. H.

Seo

David

(2015). Alleviating depression only to become problematic mobile phone users: Can face-to-face communication be the antidote? Computers in Human Behavior, 51, 440–447. https://doi.org/10.1016/j.chb.2015.05.030

32.

Kraut

Patterson

Lundmark

Kiesler

Mukophadhyay

Scherlis

(1998). Internet paradox. A social technology that reduces social involvement and psychological well-being? American Psychologist, 53, 1017–1031. http://dx.doi.org/10.1037/0003-066X.53.9.1017

33.

Kuss

D. J.

Griffiths

M. D.

(2011). Online social networking and addiction—A review of the psychological literature. International Journal of Environmental Research and Public Health, 8, 3528–3552. https://doi.org/10.3390/ijerph8093528

34.

Laursen

Coy

K. C.

Collins

(1998). Reconsidering changes in parent-child conflict across adolescence: A meta-analysis. Child Development, 69, 817–832. https://doi.org/10.1111/j.1467-8624.1998.tb06245.x

35.

Leung

(2008). Linking psychological attributes to addiction and improper use of the mobile phone among adolescents in Hong Kong. Journal of Children and Media, 2, 93–113. https://doi.org/10.1080/17482790802078565

36.

Liu

Y. L.

(2003). Parent-child interaction and children's depression: The relationships between parent-child interaction and children's depressive symptoms in Taiwan. Journal of Adolescence, 26, 447–457. https://doi.org/10.1016/S0140-1971(03)00029-0

37.

Major, B., Cozzarelli, C., Horowitz, M. J., Colyer, P. J., Fuchs, L. S., Shapiro, E. S., Stoiber, K. C., Malt, U. F., Teo, T., Winter, D. G., & Nelson, E. L. (2000). Encyclopedia of psychology: 8 Volume set. New York and Washington: Oxford University Press and the American Psychological Association.

38.

Mota

C. P.

Matos

P. M.

(2013). Peer attachment, coping, and self-esteem in institutionalized adolescents: The mediating role of social skills. European Journal of Psychology of Education, 28, 87–100. https://doi.org/10.1007/s10212-012-0103-z

39.

Nickerson

A. B.

Nagle

R. J.

(2004). The influence of parent and peer attachments on life satisfaction in middle childhood and early adolescence. Social Indicators Research, 66, 35–60. http://dx.doi.org/10.1023/B:SOCI.0000007496.42095.2c

40.

Pascuzzo

Cyr

Moss

(2013). Longitudinal association between adolescent attachment, adult romantic attachment, and emotion regulation strategies. Attachment & Human Development, 15, 83–103. https://doi.org/10.1080/14616734.2013.745713

41.

Piña-Watson

Castillo

L. G.

(2015). The role of the perceived parent-child relationship on Latina adolescent depression. Child and Adolescent Social Work Journal, 32, 309–315. http://dx.doi.org/10.1007/s10560-014-0374-0

42.

Reinherz

H. Z.

Paradis

A. D.

Giaconia

R. M.

Stashwick

C. K.

Fitzmaurice

(2003). Childhood and adolescent predictors of major depression in the transition to adulthood. The American Journal of Psychiatry, 160, 2141–2147. https://doi.org/10.1176/appi.ajp.160.12.2141

43.

Sahu

Gandhi

Sharma

M. K.

(2019). Mobile phone addiction among children and adolescents. Journal of Addictions Nursing, 30, 261–268. https://doi.org/10.1097/JAN.0000000000000309

44.

Sampasa-Kanyinga

Goldfield

G. S.

Kingsbury

Clayborne

Colman

(2020). Social media use and parent–child relationship: A cross‐sectional study of adolescents. Journal of Community Psychology, 48, 793–803. https://doi.org/10.1002/jcop.22293

45.

Seo

D. G.

Park

Kim

M. K.

Park

(2016). Mobile phone dependency and its impacts on adolescents' social and academic behaviors. Computers in Human Behavior, 63, 282–292. https://doi.org/10.1016/j.chb.2016.05.026

46.

Shaffer

D. R.

Kipp

(2016). Developmental psychology: Childhood and adolescence (9th ed.). China Light Industry Press.

47.

Smetana

J. G.

Rote

W. M.

(2019). Adolescent-Parent relationships: Progress, process, and prospects. Annual Review of Developmental Psychology, 1, 41–68. https://doi.org/10.1146/annurev-devpsych-121318-084903

48.

Steinberg

(2005). Cognitive and affective development in adolescence. Trends in Cognitive Sciences, 9, 69–74. https://doi.org/10.1016/j.tics.2004.12.005

49.

Tamura

Nishida

Tsuji

Sakakibara

(2017). Association between excessive use of mobile phone and insomnia and depression among Japanese adolescents. International Journal of Environmental Research and Public Health, 14, 701. https://doi.org/10.3390/ijerph14070701

50.

Thapar

Collishaw

Pine

D. S.

Thapar

A. K.

(2012). Depression in adolescence. The Lancet, 379, 1056–1067. https://doi.org/10.1016/S0140-6736(11)60871-4

51.

Thomée

(2018). Mobile phone use and mental health. A review of the research that takes a psychological perspective on exposure. International Journal of Environmental Research and Public Health, 15, 2692. https://doi.org/10.3390/ijerph15122692

52.

Thomée

Härenstam

Hagberg

(2011). Mobile phone use and stress, sleep disturbances, and symptoms of depression among young adults—A prospective cohort study. BMC Public Health, 11, 66–11. https://doi.org/10.1186/1471-2458-11-66

53.

Wang

H. Z.

Sheng

J. R.

Wang

J. L.

(2019). The association between mobile game addiction and depression, social anxiety, and loneliness. Frontiers in Public Health, 7, 247. https://doi.org/10.3389/fpubh.2019.00247

54.

Yang

Y. Q.

Chen

L. Q.

Zhang

W. X.

(2017). The influence of maternal depression on adolescent depression: The mediating role of parent-child relationship and the negative emotional regulatory role of adolescents. Psychological Development and Education, 33, 368–377. https://doi.org/10.16187/j.cnki.issn1001-4918.2017.03.15

55.

Zhong

Liu

J. H.

Chen

(2014). Adolescent peer attachment: A developmental perspective. Advances in Psychological Science, 22, 1149–1158. https://doi.org/10.3724/SP.J.1042.2014.01149

56.

Zhou

Long

L. R.

(2004). Statistical test and control method of common method deviation. Advances in Psychological Science, 12, 942–942.

57.

Zhu

Zhang

Bao

(2015). Early adolescent internet game addiction in context: How parents, school, and peers impact youth. Computers in Human Behavior, 50, 159–168. https://doi.org/10.1016/j.chb.2015.03.079