The relationships between perceived parenting style,learning motivation,friendship satisfaction,and the addictive use of smartphones with elementary school students of South Korea: Using multivariate latent growth modeling

Abstract

We examined how perceived parenting style, friendship satisfaction, and academic motivation influence the addictive use of smartphones longitudinally. We utilized the panel data (from 2010–2012) of Korean children and youth panel survey of the National Youth Policy Institute. Data were collected from 2,376 individuals in the first year (boys: 1,241, girls: 1,135), 2264 individuals in the second year (boys: 1,180, girls: 1,084), and 2,218 individuals in the third year (boys: 1,167, girls: 1,051). Results of the multivariate latent growth modeling indicated that higher democratic parenting (warmth, supervisory, and rational explanation) was related to lower addictive use of smartphones. And, the more perceived democratic parenting was high, the more academic motivation and friendship satisfaction were high. Also, friendship satisfaction and academic motivation negatively influenced the addictive use of smartphones; the more friendship satisfaction and academic motivation increased rapidly over time, the more the addictive use of smartphones decreased over time. These results imply that affective and supervisory parenting can positively impact peer relationship and learning motivation, and the satisfaction of peer relationship and academic motivation can be protective factors for the addictive use of smartphones.

Keywords

Academic motivation latent growth modeling perceived parenting styles satisfaction of friendship smartphone addiction

Smartphone use by adolescents and adults is common in South Korea; recently, the proportion of elementary school students using a smartphone has rapidly increased. Excessive use of smartphones can lead to a host of physical symptoms, including eye fatigue, neck pain, and sleep disturbance (Suler, 1996; Thomée, Harenstam, & Hagberg, 2011). Moreover, excessive use of smartphones can negatively influence daily life, including learning achievement and social functioning (Suler, 2004). Currently, the definition of smartphone addiction is unclear. Therefore, this study uses the term ‘the addictive use of smartphones’ rather than ‘smartphone addiction’. The addictive use of smartphones is defined as the psychological dependence on smartphones, as well as dysfunction in daily life resulting from the excessive use of smartphones (Shaffer, 1999).

Given that smartphone use in primary school students has recently emerged, it seems prudent for researchers to examine their smartphone use in order to offer precautions that will prevent damage from the excessive use of smartphones. During the primary school years, children need their parents’ care and guidance more compared to during the middle and high school years (Rubin, Root, & Bowker, 2010). Also, elementary school students are greatly influenced by friends (Salvy, de la Haye, Bowker, & Hermans, 2012) and academic stress increases rapidly as students advance in schooling. Thus, researchers should consider together the parents, peers, and school variables to enhance our understanding of the addictive use of smartphones for primary school students.

Harry Stack Sullivan’s (1953) Interpersonal Theory proposed that parent-child relationship, parenting style in childhood impacts the interpersonal relationship of adolescents. In particular, he emphasized that the self-image (‘good me’, ‘bad me’, ‘not me’), which stems from parent-child relationship or parenting style, is later reflected in peer relationships of adolescents. This theory emphasized that children and adolescents who have a difficulty in interpersonal relationships are likely to present maladaptive or problem behaviors. Numerous studies have demonstrated that parent-child relationships and parenting style have great effects on interpersonal relationships during the adolescent period (Bell, Cornwell, & Bell, 1988; Feldman & Wentzel, 1990). Also, Suler (1996) verified that almost all addictive behaviors (e.g. excessive substance use, internet addiction, cell-phone addiction) can be influenced by interpersonal problems during childhood. Numerous studies suggested that people who have interpersonal difficulties prefer online communication in order to escape the discomfort of face-to-face contact (Peter, Valkenburg, & Schouten, 2005).

Many studies have reported that parental warmth and supervision are negatively related to children’s problem behaviors (Larid, Pettit, Bates, & Dodge, 2003). Maccoby and Martin (1983) also argued that parental warmth and supervision are core attitudes that influence children’s psychological, emotional, and behavioral development. Additionally, Lee and Lee (2012) reported that perceived parenting style significantly influenced the addictive use of smartphones. A longitudinal study that followed 138 youths over seven years suggested that mother-child relationship was a significant predictor of preference for online communication (Szwedo, Mikami, & Allen, 2011). Parents who engage in behaviors marked by warmth are intimately connected to their children and respond sensitively to their children’s needs. These parental attitudes have been shown to decrease children’s problem behaviors and aid in children’s adaptation (Chung & Lee, 2006).

Many researchers have also reported that parental warmth and supervision influence friendship satisfaction (Putallaz & Heflin, 1990). Parental affective attitudes can also build feelings of trust in children, as well as provide children with emotional stability. Through parent-child relationships, children imitate and learn behaviors that teach them how to interact with their peers and other individuals outside of the family (Maccoby, 1992). Indeed, Mayseless, Sharabany, and Sagi (1997) reported that a higher levels of parental affective attitudes were related to a higher level of satisfaction in children’s peer relationships. Recently, a similar longitudinal study showed that authoritative (emotional warmth and reasoned communication) parenting style decreased peer problems (Yamagata et al., 2013), and another study found that harsh and reactive parenting style at 17 months predicted peer victimization at three to six years (Barker, Arseneault, Brendgen, Fontaine, & Maughan, 2008).

The relation between friendship satisfaction and the addictive use of smartphones has been primarily found in adolescents (Ezoe & Toda, 2013; Hertlein & Webster, 2008). However, a few studies have been conducted on elementary school students. As children get older, the influence of friends gradually increases. Children who experience conflicts with friends are likely to experience maladaptive psychological outcomes, including loneliness. Therefore, they may attempt to find alternative activities to compensate for poor interpersonal relationships. In these situations, smartphone could be an attractive way to interact with others without face-to-face contact (Lee & Lee, 2012; Park, Kim, & Hong, 2012).

Smartphone use by children and adolescents is an important way to interact with friends; some studies have reported that having a large number of friends and high interaction frequency are related to more addictive use of smartphones (Campbell & Russo, 2003; Jin, 2007). However, other studies have reported that lower friendship satisfaction is associated with higher addictive use of smartphones (Lee & Lee, 2012). These contradictory results may be due to inaccurate measurements of friendship quality. That is, researchers must not jump to a conclusion that having a lot of friends and high interaction results in high friendship satisfaction. It is possible that friendship satisfaction is low despite having a lot of friends and interaction. Thus, researchers should estimate the quality of friendship satisfaction rather than the number of friends or the interaction frequency which do not ensure friendship satisfaction.

Problem Behavior Theory (Jessor, 1991; Jessor, Donovan, & Costa, 1991) is a psychosocial theory which has been applied to explain various problem behaviors. This theory is composed of three systems: The perceived environment system, the personality system, and the behavior system. Perceived environment system includes social models, controls, and support. These variables can be differentiated on the basis of the conceptual closeness with problem behaviors and the directness of their relations to problem behaviors. That is, distal variables (e.g. parenting style, parent support) are more remote in the causal relationship chain, whereas proximal variables (e.g. peer models for cigarette use) directly influence a particular problem behavior.

Personality system includes values, beliefs, and attitudes toward self, others, and the world. This system consists of motivational structure (e.g. academic motivation), personal belief structure (e.g. alienation, self-esteem), and personal control structure (e.g. destructiveness, tolerance). Behavior system is composed to both problem behaviors (e.g. problem drinking, excessive internet use) and conventional behaviors (e.g. church attendance, academic achievement). This theory supposed that the balance of controls and incitement (instigation) across the three systems determines problem behavior proneness in children and adolescents. In this study, we attempted to extend the Problem Behavior Theory (PBT) to the addictive use of smartphone.

Many studies have reported that parenting style has an impact on academic motivation and activities (Ginsburg & Bronstein, 1993; Kim & Jung, 2012; Leung & Lee, 2013). Academic motivation is an internal trait resulting in the need to prepare for and achieve learning; students with high academic motivation concentrate and participate actively in their studies. Steinberg, Elmen, and Mounts (1989) argued that parents who nurture their children affectionately and supervise them properly can improve children’s academic motivation and academic achievement.

Previous studies suggest that authoritarian parenting (highly restrictive, directive, and punitive) increases academic motivation in Asian countries. Authoritative parenting (emotional warmth and reasoned communication) was also linked to higher academic motivation in the United States (Stenberg, Lamborn, Dornbush, & Darling, 1992). Recently, Watabe and Hibbard (2014) identified the relationship between parenting style and academic motivation in the United States and Japan, and the results were quite interesting. Authoritative parenting had a positive influence on American children’s academic motivation but did not predict Japanese children’s academic motivation. Cheung and McBride-Chang’s (2008) study also examined whether mother’s parenting attitude (concern, affective) increased Hong Kong Chinese children’s academic motivation and achievement.

Especially, in South Korea, students in higher elementary school grades spend more time in school. In this situation, academic motivation as well as the quality of peer relationships can influence the psychological, emotional, and behavioral problems of children. Also, lower academic motivation can be associated with poorer academic performance and school adjustment (Jacobsen & Forste, 2011; Sanchez-Martinez & Otero, 2009). Also, Suler (1996) insisted that students who are uninterested in studying and do not put value on it are likely to overuse internet, game, and cell phones because they experience difficulties in obtaining a sense of control and positive self-concept in reality. Studies have also reported that there are differences in academic motivation and learning activities between those who are addicted to smartphones and those who are not (Lee & Myung, 2007).

Based on the Problem Behavior Theory (Jessor et al., 1991), children and adolescents who are not properly supervised or monitored by parents and whose academic motivation is low can be vulnerable to behavioral addictions, such as internet and smartphone overuse, as well as problem behaviors including alcohol, cigarette, and substance use (Andrews & Duncan, 1997).

Many previous studies (Jang, 2011) have compared addictive use of smartphones and control groups on family variables (e.g. perceived parenting style, parent-child communication), school variables (e.g. academic motivation, academic achievement, school adaptation), and peer variables (e.g. friendship satisfaction, interaction frequency). Moreover, existing studies have insufficiently examined the relationship among variables (parenting style, peer relationship, school adaptation, and addictive use of smartphones) because most studies have implemented cross-sectional designs.

The purpose of this study is to identify the relationships among perceived parenting style, friendship satisfaction, academic motivation, and the addictive use of smartphone for elementary school students based on the Interpersonal Theory and the Problem Behavior Theory which suppose causal chain by lapse of time to explain maladaptive behaviors. Thus, this study used the latent growth modeling, which is a useful method to examine the causality between variables in the longitudinal view.

We hypothesized the following. H1: Perceived parenting style (warmth, rational explanation, and supervisory parenting) will decrease the addictive use of smartphones in the longitudinal study (Hong, Chiu, & Huang, 2012). H2: Perceived parenting style (warmth, rational explanation, and supervisory parenting) will positively influence friendship satisfaction in the longitudinal study (Durbin, Darling, Steinberg, & Brown, 1993). H3: Friendship satisfaction will negatively impact the addictive use of smartphones in the longitudinal study (Lee & Myung, 2007). H4: Perceived parenting style (warmth, rational explanation, and supervisory parenting) will positively influence academic motivation in the longitudinal study (Turner, Chandler, & Heffer, 2009). H5: Academic motivation will negatively impact the addictive use of smartphones in the longitudinal study (Lee & Myung, 2007). H6: Friendship satisfaction and academic motivation play a mediation role in relationships between parenting style and addictive use of smartphones in the longitudinal study. The hypothetical model suggested by this study is presented in Figure 1.

Figure 1.

Multivariate latent growth model of addictive use of cellular phone.

Method

Participants

Cohort sequential Panel data (from 2010–2012) from Korea and a youth panel survey of the National Youth Policy Institute that conduct basic and policy researches related with adolescents were used. These data were sampled using stratified multi-stage cluster sampling for fourth grade primary school students of 95 schools from 16 national cities and provinces (27 clusters) in South Korea from 2010–2012. A total of 2376 individuals participated in the study in the first year (boys: 1241, girls: 1135), 2264 in the second year (boys: 1180, girls: 1084), and 2218 in the third year (boys: 1167, girls: 1051). Students who live in Seoul and six metropolitans (Pusan, Daegu, Incheon, Gwangju, Daejeon, and Ulsan) made up 42.7% of the total sample. An average annual income in the family was about 45.9 million won. The percentage distribution of the annual income is as listed: 3.3% for less than 10 million, 8.6% for more than 10 million to less than 20 million, 17.8% for more than 20 million to less than 30 million, 22.1% for more than 30 million to less than 40 million, 20.3% for more than 40 million to less than 50 million, 11.9% for more than 50 million to less than 60 million, 5.7% for more than 60 million to less than 70 million, 4.7% for more than 70 million to less than 80 million, 1.6% for more than 80 million to less than 90 million, 2.8% for more than 90 million to less than 100 million, and 1.3% for more than 100 million. The frequency of purpose of children’s smartphone use was measured using a four-point Likert scale (don’t use any = 1; hardly used = 2; occasionally use = 3; frequently use = 4). Means and standard deviations of the frequency of each purpose of smartphone use are as follows: Talking to family members on the phone (M = 3.73, SD = 0.52); texting with family members (M = 3.28, SD = 0.80); talking to friends on the phone (M = 3.14, SD = 0.81); texting with friends (M = 3.14, SD = 0.89); playing games (M = 2.37, SD = 0.93); taking pictures (M = 2.73, SD = 0.90); watching moving graphics (M = 2.03, SD = 0.95); listening to music (M = 2.46, SD = 1.12).

Procedure

A professional research company surveyed fourth grade elementary school students from 2010–2012. Students reported their perceived parenting style, the level of academic motivation, the level of friendship satisfaction, and the addictive use of smartphone. Ninety-five (95.29%) percent of the total students who were involved in the first year participated in the second year. Also, ninety-seven (97.97%) percent of total participants who were involved in the second year participated in third year. The survey of this study was conducted by a professional research company. Informed consent was given by all participants, and IRB acknowledged the appropriateness of this survey.

Measures

Perceived parenting attitude scale

Ten items were used to measure perceived parenting style. This scale was developed by Huh (2000) and consists of three items relevant to supervision, four items relevant to warmth, and three items relevant to rational explanation. Items are rated on a four-point Likert scale and higher scores reflect more affection, rational supervision and rational explanation. To identify the validity of the three-factor structure (affection, supervision, and rational explanation), we conducted confirmatory factor analysis by AMOS 20.0 Program. Model indexes were as follows: Chi-square = 148.768; Goodness of fit index (GFI) = 0.988; Turker-Lewis index (TLI) = 0.978; Comparative fit index (CFI) = 0.985; Root mean square error of approximation (RMSEA) = 0.041. Standardized regression weight of total items ranged from 0.514–0.762, and squared multiple correlation ranged from 0.395–0.576. The Cronbach’s alpha for the current sample was 0.854.

Academic motivation scale

A five-item survey developed by Min (1991) was used to assess academic motivation towards school. Items include, ‘The class is interesting’, and ‘I ask other people something that I do not understand’. Items are rated on a four-point Likert scale, with higher scores indicating higher academic motivation. To identify the validity of one factor structure, we conducted confirmatory factor analysis by AMOS 20.0 Program. Model indexes were as follows: Chi-square = 15.938; GFI = 0.999; TLI = 0.996; CFI = 0.998; RMSEA = 0.018. Standardized regression weight of total items ranged from 0.482–0.724, and squared multiple correlation ranged from 0.310–0.524. The Cronbach’s alpha for the current sample was 0.831 in the first year, 0.751 in second the year, and 0.716 in the third year.

Friendship satisfaction scale

Friendship satisfaction quality was assessed with the revised version of the School Life Adaptation Scale developed by Min (1991). Items included, ‘My friends and I are very well suited’, and ‘I apologize first to friends when I fight with them’. Items are rated on a four-point Likert scale and higher scores reflect higher friendship satisfaction. We conducted confirmatory factor analysis by AMOS 20.0 Program to verify the validity of one factor structure. Model indexes were as follows: Chi-square = 8.062; GFI = 0.999; TLI = 0.992; CFI = 0.997; RMSEA = 0.021. Standardized regression weight of total items ranged from 0.519–0.635, and squared multiple correlation ranged from 0.269–0.403. The Cronbach’s alpha for the current sample was 0.765 in the first year, 0.790 in the second year, and 0.815 in the third year.

Addictive use of smartphones scale

An inventory developed by Lee, Kim, and Na (2002) was used, and it consists of seven items rated on a four-point Likert scale. Examples of the items are as follows: ‘I spend more and more time using smartphone’, ‘If I don’t have a smartphone when I go out, I get nervous’, ‘I can’t live without a smartphone’. Higher scores are related to higher addictive use of smartphones. We conducted confirmatory factor analysis by AMOS 20.0 Program to verify the validity of one factor structure. Model indexes were exceptional (chi-square = 16.654; GFI = 0.998; IFI = 0.998; TLI = 0.993; CFI = 0.998; RMSEA = 0.027). Standardized regression weight of total items range from 0.474–0.826, and squared multiple correlation ranged from 0.325–0.682. The Cronbach’s alpha for the current sample was 0.828 in the first year, 0.881 in the second year, and 0.890 in the third year.

Statistical analysis

We utilized Multivariate Latent Growth Modeling (LGM) by AMOS 20.0 program (SPSS, Inc. 2011) to identify the relationships among perceived parenting style, friendship satisfaction, academic motivation and the addictive use of smartphones longitudinally. This study used full information maximum likelihood (FIML), and we used the chi-square value, CFI (Comparative Fit Index), TLI (Tucker-Lewis Index) and RMSEA (Root Mean Square Error of Approximation) to evaluate the fit of model. Finally, we conducted the bootstrap test to identify the direct, indirect, and total effects.

Results

Type of smartphone use

Means, Standard Deviations and correlations of variables

The Means and Standard Deviations of perceived parenting style, academic motivation, friendship satisfaction and the addictive use of smartphones, as well as the correlations between the variables are presented in Tables 1 and 2.

Table 1.

Mean and standard deviation of variables.

Variable		First year		Second year		Third year
Variable		M	SD	M	SD	M	SD
Perceived parenting style	Supervision	10.08	1.90
	Warmth	9.92	1.96
	Rational	9.47	2.05
Learning motivation		15.17	2.48	14.90	2.57	14.63	2.51
Friendship satisfaction		15.40	2.30	15.48	2.30	15.57	2.14
Addictive use of cellular phone		11.38	3.25	12.52	4.05	14.36	4.52

Table 2.

Correlation between variables.

	A	b	c	d	e	f	g	h	i	j	k
a
b	0.50^***
c	0.39^***	0.61^***
d	0.38^***	0.45^***	0.34^***
e	0.27^***	0.31^***	0.23^***	0.48^***
f	0.21^***	0.28^***	0.20^***	0.37^***	0.44^***
g	0.38^***	0.40^***	0.30^***	0.60^***	0.40^***	0.35^***
h	0.30^***	0.28^***	0.19^***	0.39^***	0.57^***	0.34^***	0.50^***
i	0.24^***	0.26^***	0.20^***	0.31^***	0.35^***	0.53^***	0.42^***	0.48^***
j	−0.16^***	−0.12^***	−0.08^**	−0.23^**	−0.17^***	−0.14^***	−0.25^***	−0.22^***	−0.20^***
k	−0.06^*	−0.06^**	−0.03	−0.05^*	−0.10^***	−0.08^**	−0.10^**	−0.18^***	−0.19^***	0.36^***
l	−0.02	−0.02	−0.00	0.02	−0.03	−0.08^**	−0.05^*	−0.11^***	−0.22^***	0.28^***	0.43^***

p < 0.05; ^**p < 0.01; ^***p < 0.001.

a = supervision; b = warmth; c = rational; d = friendship satisfaction at first year; e = friendship satisfaction at second year; f = friendship satisfaction at third year; g = learning motivation at first year; h = learning motivation at second year; i = learning motivation at third year; j = addictive use of cellular phone at first year; k = addictive use of cellular phone at second year; l = addictive use of cellular phone at third year.

Change model of each variable over time

Before conducting the multivariate latent growth modeling, we conducted latent growth modeling to identify change in academic motivation, friendship satisfaction, and addictive use of smartphones over time. First, we assumed a no-change model and a change model for each variable. Second, we identified which model demonstrated the best fit to our data. The no-change model has the slope that does not increase or decrease linearly over time, whereas the change model increases or decreases linearly over time. The fit of the no-change model, the change model of each variable, and the variation of the intercept and slope of each variable are presented in Tables 3 and 4.

Table 3.

The fit for no change model and linear change model of each variables.

Variable	Model	χ²(df)	TLI	CFI	RMSEA
Learning motivation	No change model	118.130	0.937	0.916	0.110
Learning motivation	Linear change model	0.031(1)	1.000	1.000	0.000
Friendship satisfaction	No change model	52.084(4)	0.968	0.958	0.071
Friendship satisfaction	Linear change model	0.022(1)	1.000	1.000	0.000
Addictive use of cellular phone	No change model	930.922(4)	0.066	0.000	0.312
Addictive use of cellular phone	Linear change model	19.852(1)	0.913	0.971	0.089

Table 4.

Results of line change model for each variables.

Variable	Mean		Variation
Variable	Intercept	Change rate	Intercept	Change rate
Learning motivation	15.175^***	−0.272^***	3.656^***	0.495^***
Friendship satisfaction	15.398^***	0.087^***	3.289^***	0.477^***
Addictive use of cellular phone	11.310^***	1.469^***	4.551^***	2.190^***

p < 0.05; ^**p < 0.01; ^***p < 0.001.

Results indicated that the academic motivation variable demonstrated a better fit in the change model compared to the no-change model. In addition, friendship satisfaction and the addictive use of smartphones better fit the change model. Estimation of the change model for academic motivation indicated that the intercept was significant and positive; however, the slope was significant and negative. These results indicated that academic motivation decreases linearly over time. The variation of the intercept and slope for academic motivation was also significant, thereby indicating that the intercept and slope for academic motivation was different between the subjects. In addition, the intercepts and slopes for friendship satisfaction and the addictive use of smartphones were also significant and positive. Thus, it appears that friendship satisfaction and the addictive use of smartphones increased linearly over time. The variation of the intercepts and slopes of the two variables was also significant. Thus, the intercepts and slopes of friendship satisfaction and the addictive use of smartphones were different between the subjects.

Relationships between variables

We concluded that the model of our study can be proposed as an explanatory model of addictive use of smartphone because fit indexes of the multivariate latent growth model were very good (Chi-squares = 151.382; TLI = 0.976; CFI = 0.986; RMSEA = 0.035).

The results of the analysis are as follows. First, perceived parenting style (affective, rational, and supervising parenting) positively influenced the intercept of friendship satisfaction and negatively impacted the change rate of friendship satisfaction. Thus, it appears that higher democratic parenting style was related to higher friendship satisfaction in the first year, and higher democratic parenting was associated with slow rate of increase of friendship satisfaction over time. Second, higher democratic parenting style positively influenced the intercept of academic motivation and negatively affected the change rate of academic motivation. Thus, higher democratic parenting style was related to higher academic motivation in the first year, and higher democratic parenting was associated with slow rate of increase of academic motivation over time. Third, higher democratic parenting style negatively impacted the intercept and change rate of the addictive use of smartphones. Thus, higher democratic parenting was associated with a lower intercept of the addictive use of smartphones; further, higher democratic parenting was associated with slow rate of decrease in the addictive use of smartphones over time. Fourth, higher academic motivation in the first year was related to less addictive use of smartphones in the first year; moreover, the rate of change for academic motivation was negatively related to the change rate of the addictive use of smartphones. This result indicates that the more academic motivation increase rapidly over time, the more the addictive use of smartphones decline rapidly over time. Fifth, higher friendship satisfaction in the first year was related to lower addictive use of smartphones in the first year; moreover, the change rate of friendship satisfaction negatively influenced the change rate of the addictive use of smartphones. Therefore, it appears that the more friendship satisfaction increase rapidly over time, the more the addictive use of smartphones decrease rapidly over time. The fit of the multivariate latent growth model and the path coefficients of each path are presented in Tables 5 and 6.

Table 5.

The fit of multivariate latent growth model.

	χ²(df)	TLI	CFI	RMSEA
Latent growth model	151.382(38)	0.976	0.986	0.035

χ² = Chi-Squares; df = degree of freedom; TLI = Tucker-Lewis Index; CFI = Comparative Fit Index; RMSEA = root mean square error of approximation.

Table 6.

Path coefficients of multivariate latent growth model for addictive use of cellular phone.

Path	Unstandard coefficient	Standard error	Standard coefficient	t
PPS → intercept of FS	1.091	0.053	0.680	20.646^***
PPS → change rate of FS	−.266	0.026	−0.476	−10.037^***
PPS → intercept of LM	1.034	0.054	0.625	19.170^***
PPS → change rate of LM	−0.200	0.027	−0.407	−7.334^***
PPS → intercept of AU	−0.311	0.106	−0.162	−2.943^**
PPS → change rate of AU	−0.597	0.172	−0.451	−3.479^***
Intercept of LM → intercept of AU	−0.428	0.087	−0.369	−4.934^***
Intercept of LM → change rate of AU	−0.063	0.121	−0.078	−0.517
Change rate of LM → change rate of AU	−1.856	.519	−0.690	−3.574^***
Intercept of FS → intercept of AU	−0.192	0.099	−0.161	−1.936^*
Intercept of FS → change rate of AU	0.241	0.125	0.292	1.934^*
Change rate of FS → change rate of AU	−0.620	0.271	−0.261	−2.283^*

p < 0.05; ^**p < 0.01; ^***p < 0.001.

PPS = perceived parenting style; LM = learning motivation; FS = friendship satisfaction; AU = addictive use of cellular phone.

Discussion

The purpose of this study was to identify the relationships among perceived parenting style, friendship satisfaction, academic motivation, and addictive use of smartphones longitudinally in elementary school students.

Before identifying the relations between the variables, we evaluated how each variable changed over time. The results indicated that friendship satisfaction and the addictive use of smartphones increased linearly over time. Thus, it appears that as children move to a higher grade, friendship satisfaction increases gradually. This is likely because the importance of friendship grows and the interaction between friends increases gradually. As students move to a higher grade, the frequency of smartphone use increased rapidly and psychological dependence on smartphones also grew over time (Park & Park, 2014). However, academic motivation decreased linearly over time. These results indicate that as children move to a higher grade, the stress of learning achievement is also growing, which results in decreases in academic motivation.

Results also revealed that higher authoritative parenting style (affective, supervisory, rational) was associated with lower addictive use of smartphones. This is consistent with previous studies that contend that the parent-child relationship is a powerful predictor of the addictive use of smartphones (Jang, 2011; Lee & Lee, 2012). Parents’ affective and rational attitudes are likely to positively influence children’s self-identification, and children who grow in these environments and share emotional intimacy with others are less likely to feel alienated and suffer from maladaptive psychological outcomes. Moreover, the more children maintain emotional closeness with others and retain emotional stability, the less likely they are to use media (smartphone, internet) excessively to compensate for a lack of interaction with other people. In addition, parents’ proper supervision can impact children’s general well-being, which can provide children with appropriate guidelines for behavior and help regulate children’s smartphone use (Kim & Kim, 2004).

Perceived parenting style also influenced the friendship satisfaction and academic motivation (Jang, Yoon, & Hwang, 2010). Notably, greater parental affection and supervision was associated with greater friendship satisfaction and academic motivation. Parents’ rational and accepting attitudes can help children view others as trustworthy, which can improve social skills and interpersonal interactions. Furthermore, affective and supervisory parenting may encourage children’s autonomy and can motivate spontaneous academic motivation. Meanwhile, the more this parenting style was high, the more the rate of increase of friendship satisfaction and academic motivation decreased over time. This result implies that the effects of parenting style on friendship satisfaction and academic motivation declined considerably over time.

Higher friendship satisfaction was related to a lower addictive use of smartphones. Furthermore, the more friendship satisfaction increased rapidly over time, the more addictive use of smartphones decreased rapidly over time. These results suggest that friendship satisfaction is a powerful predictor of addictive use of smartphones over time. A study of Yoon and Kwon (2011) indicated that addictive users of smartphones were prone to compensate for a strong need for interpersonal interaction. While they had a lot of friends and frequent interactions with other people, their friendship satisfaction was lower, which indicates that children who do not interact intimately with friends are more likely to rely on superficial interactions by using smartphones or the internet (Lee, Tam, & Chie, 2014).

These results are in line with the Interpersonal Theory of Sullivan (1953) who asserted that parent-child relationship or parenting style significantly impacts peer relationship quality, and someone who has difficulties in interpersonal relationship are likely to present problem behaviors such as internet or smartphone overuse as well as alcohol or cigarette overuse (Liu & Kuo, 2007).

The higher academic motivation was associated with the lower addictive use of smartphones (Junco & Cotton, 2011). Furthermore, the more academic motivation increased rapidly over time, the more the addictive use of smartphones decreased rapidly over time. Academic stress of South Korean children and adolescents is an especially important factor that influence their life satisfaction. Lower academic motivation is related to lower school performance, which negatively impacts children’s general adaptation to school (Vansteenkiste, Zhou, Lens, & Soenens, 2005) and can influence problem behaviors, such as the addictive use of internet or smartphone and delinquent behaviors.

Based on the Problem Behavior Theory, problem behaviors of children and adolescents are caused by combination and interaction of perceived environment variables (e.g. family and peer relationship), personality variables (e.g. self-esteem, academic motivation), and behavior variables (problem and conventional behaviors, such as delinquency, academic achievement) (Karaman, 2013). Jessor and colleagues (1991) insisted that protective behaviors are necessary to reduce problem behaviors, and protective factors influence risk factors as well as problem behaviors. Also, Jessor et al. (2003) suggested that supports of parents and friends and conventional activities can become protective factors and thus decrease the probability of problem behaviors. Addictive use of smart phones could also be explained by applying the PBT theory. Children who did get appropriate parental supervisory and affection, experience friendship satisfaction (perceived environment variables) and have high level of academic motivation (personality variable) are unlikely to present problem behaviors (addictive use of smartphone, internet addiction, conduct problem etc).

Finally, we conducted the bootstrap test and results indicated that the indirect effects (mediating effects) of academic motivation and friendship satisfaction on the relationship between perceived parenting style and addictive use of smartphones were significant. Thus, perceived parenting style indirectly influenced the addictive use of smartphones via academic motivation and friendship satisfaction (p < 0.05), as well as directly impacting the addictive use of smartphones (p < 0.05). Our results can help explain how perceived parenting style impacts the addictive use of smartphones. That is, democratic parenting can decrease the addictive use of smartphones because democratic parenting increases friendship satisfaction and academic motivation, which, in turn, decreases the addictive use of smartphones.

Korean society is experiencing excessive educational enthusiasm. Many primary school students are participate in a variety of private education/tuition and have very little free time due to the pressure of studying. In this situation, smartphones have become an important part of daily life of Korean children. Interestingly, Korean parents give children the first smartphone as a gift for getting good grades in mid-terms or final exams during elementary school. Parents also check their children’s attendance at academies by calling and texting. If parents overly control their children, teenagers are likely to compensate for their autonomy unhealthily (e.g. by overusing smartphones). In addition, many Koreans are careful when expressing their opinions to others. The culture of Korean society is likely to accelerate the development of online communication network such as internet, smartphone, and social network system such as Facebook, where anonymity is guaranteed.

Considering the results of our study, the Interpersonal Theory, the model of Leung and Lee (2013), and cultural features of Korean society all together, children who negatively perceive their parenting style and have a peer-relationship problem and a low level of academic motivation can excessively use smartphones to compensate for their need for interpersonal interaction and low level of self-esteem. In particular, friendship satisfaction and academic motivation seem more important to the addictive use of smartphones over time.

The clinical implications for results are outlined as follows. First, as the use of smartphones increases among elementary school students, there is a need to prevent damage caused by the excessive use of smartphones. Based on the results of this study and the results of previous studies, it seems that perceived parenting style is an important antecedent variable of the addictive use of smartphones. Especially, parental warmth and the proper supervision of children may be important factors in preventing the addictive use of smartphones. In addition, school psychologists can consider a means to promote effective parenting behavior and friendship from this study. Professionals should educate parents regarding how to talk to their children about the use of smartphones, smartphone usage rules, and how to find useful information from smartphones and so on.

It is likely that friendship satisfaction is a core component in predicting and preventing the addictive use of smartphones. Thus, it is important that parents are concerned with their children’s friendships and encourage their children to maintain emotional intimacy with their friends. In addition, it seems important that teachers sensitively identify the conflicts among children and appropriately intervene. Also, parents should educate and explain to their children the joys of learning to increase academic motivation. Moreover, teachers should also develop various methods that can improve academic motivation.

The limitations of this study and suggestions for future studies are as follows. First, it is important to note that the results of the current study are only generalizable to elementary-aged children. Second, this study is an early attempt to evaluate an explanatory model for the addictive use of smartphones in elementary school students. Thus, we expect that our study will be a resource for future studies, as well as interventions for the addictive use of smartphones. And, replication studies are required to verify the validity of the model of this study. Third, this study only used self-reported scales to evaluate addictive use of smartphone. In future studies, researchers should consider parent or teacher reports or observation.

Footnotes

Note

This study utilized the panel data (from 2010–2012) for elementary school of Korean children and a youth panel survey of the National Youth Policy Institute.

Author's biography

Sung Man Bae, is an Assistant Professor of the Department of Counseling Psychology at the Cyber University of Korea in Seoul, South Korea. He worked as a Clinical Psychologist and a Clinical Psychology Professor (supervisor) at Ilsanpaik Hospital of the Inje University from 2007–2014. His interest includes causes and treatments of post-traumatic stress disorder and behavior addictions, such as internet, game, smartphone, and SNS addiction.

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