The Relationship between Children's School Adaptation, Academic Achievement, Happiness, and Problematic Smartphone Usage: A Multiple Informant Moderated Mediating Model.

The school environment is a primary realm of life for school-aged children and thus their adaptation to school and academic performance may affect their degree of happiness. The age of smartphone users has declined, and problematic smartphone usage has widely expanded such that young children are also affected by such devices. This study assessed adaptation to school, academic achievement, problematic smartphone usage, and general happiness in a panel data sample of 695 Korean 10-year-old children and their teachers and mothers, and a moderated mediation model of these variables was tested. Results revealed that school adaptation affected general happiness of children through academic performance, and problematic smartphone usage demonstrated significant moderating effects on the relationship between school adaptation and academic achievement. Specifically, in children with a high level of adaptation to school life, the difference in problematic smartphone usage did not affect academic performance. However, lower level of adaptation led to greater differences in academic performance depending on problematic smartphone usage, and children with high problematic smartphone usage showed poorer academic performance. This study is meaningful because variables related to adaptation of 10-year-old children were collected from multiple informants. In addition, this study focused on general happiness, a positive factor, as the outcome variable to test the effects of variables related to school and problematic smartphone usage. Limitations include that a causal relationship cannot be examined, and qualitative differences in smartphone usage were not measured. Supplementary Information: The online version contains supplementary material available at 10.1007/s11482-022-10080-w. © The International Society for Quality-of-Life Studies (ISQOLS) and Springer Nature B.V. 2022.

Introduction

Happiness is a state of satisfaction with life while experiencing positive emotions or a state where one feels meaning in life and achieves self-growth, and it encompasses subjective well-being and satisfaction with life (Deci & Ryan, 2008; Diener, 2009; Seligman, 2011). It is closely related to quality of life and mental health status, and a higher sense of happiness leads to greater positive emotions and physical and emotional health (Heizomi et al., 2015). In the past, individual adaptation was evaluated based on existence of problems, but recently, with increasing interest in the effects of positive factors, happiness has been suggested as an important empirical and clinical variable (D’raven et al., 2015).

Following the enactment of the UN Convention on the Rights of the Child in 1989, interest in happiness of children has increased significantly (Ninomiya et al., 2021). In particular, children’s happiness is a variable that is closely related to not only the current state, but also positive future growth (Park, 2004). However, a number of previous studies mainly focused on negative factors such as attention deficit, emotion dysregulation, and behavioral problems of children (Huebner et al., 2014). Therefore, it would be necessary to conduct studies focusing on positive factors, especially those related to happiness.

School-aged children spend a significant amount of time at school and gain various experiences to become independent individuals (Galindo & Sheldon, 2012). In previous studies conducted in various cultures, school is one of the main areas of life for children, and variables related to school adaptation affect the overall life of children (Allen et al., 2018; Gómez-Baya et al., 2021; López-Pérez et al., 2016). School adaptation is a central task because children establish key social relationships at school, develop overall adaptability, and experience interactions with different systems as well as the wider world (Santrock, 2011). School adaptation encompasses prosocial behaviors, maintaining positive relationships with peers and teachers, and developing positive interpersonal qualities (Kiuru et al., 2007, 2009; Rodríguez-Fernández et al., 2016). Children with a high level of adaptation to school show higher satisfaction with school life, and this is closely related to their overall life satisfaction (Huebner & Gilman, 2006). As shown in a previous study conducted in Korea, adaptation to school is closely related to overall happiness of children (Lee & Yoo, 2015).

One of the variables related to school adaptation is academic achievement. It is an important yardstick as it serves as an indicator of how well children have adapted to school and subsequently contributes to overall achievement and career decisions (Rana & Mahmood, 2010). In particular, previous findings demonstrate a strong relationship between academic achievement and emotional state. For example, in a study of elementary school students, high academic achievement predicted higher positive emotions and lower negative emotions (Lv et al., 2016). Furthermore, higher academic achievement was a predictor of higher satisfaction with life (Diseth et al., 2012). However, only a limited number of studies have directly examined the effects of academic achievement on overall happiness in children.

As modern technology advance, the use of smartphones has become an essential part of daily life, and it is not difficult to find even very young children using smartphones (OECD, 2017). In particular, diverse smartphone applications with high utility are continuously being developed, and high mobility and accessibility have further contributed to the rapid increase in smartphone usage (Chaudhury & Tripathy, 2018; Van Deursen et al., 2015). Additionally, the current COVID-19 pandemic has led to closure of schools, leaving children with more free time, which has been associated with increased use of the internet and smartphones (Billieux, 2012). According to a study conducted in Korea, the degree of children’s dependence on smartphones has increased during the pandemic period up to 47.5% (Ju, 2021). Therefore, it is necessary to closely observe and apply the findings of studies on the effects of smartphone usage on children.

Most studies have focused on the negative effects of smartphones on children, and most of the problems occur with uncontrolled and dysregulated use, called “problematic smartphone usage” (Billieux et al., 2015; Horwood & Anglim, 2018). Problematic smartphone usage negatively impacts daily life functions and further imposes negative consequences on physical and mental health as well as interpersonal relationships (Horwood & Anglim, 2019; Sohn et al., 2019; Tao et al., 2017). Problematic smartphone usage is also sometimes considered a form of behavioral addiction, similar to game and internet addiction (Cha & Seo, 2018; Van Deursen et al., 2015). Problematic smartphone usage is deeply related to school life of children. In particular, it was found to be negatively associated with academic achievement (Lepp et al., 2014; Li et al., 2015). Various students responded that they overuse smartphone even at school, and smartphone usage distracts them from studying, suggesting that using smartphones excessively is an interfering factor that may prevent students from focusing on academic work (Lin et al., 2014; Tindell & Bohlander, 2012).

The relationship among these variables can be explained through the self-determination theory (SDT; Ryan & Deci 2000). According to SDT, individuals have basic psychological needs such as autonomy, relatedness and competence, and satisfaction of these needs lead to personal development. High level of adaptation to school life and high academic achievement may help to satisfy these three needs and contribute to the sense of happiness in children (DeHaan & Ryan, 2014; Neubauer et al., 2018). More specifically, individuals inherently have the proactive tendency to assimilate to the social environment, and innately possesses desire for learning or achievement (Niemiec & Ryan, 2009). Even though the outcomes may be affected by external factors such as others’ support and control, one can experience autonomy and competence during this process, and achieve facilitated well-being or happiness (Neubauer et al., 2018). As previously discussed, school adaptation, academic achievement, problematic smartphone usage, and general happiness are essential factors contributing to children’s adaptation to daily life. However, only a limited number of studies have assessed how these factors affect one another and how they contribute to children’s adjustment. Additionally, while many related studies have been conducted on adolescents (e.g., Fischer-Grote et al., 2019), there is a lack of research on younger age groups.

In studies related to children, one of the main concerns is the method of measurement. Specifically, the reliability and validity of data can be enhanced when variables are measured through difference sources of information (Stuart & Jose, 2012). This is because children vary according to the contexts, and integrating multi-informant reports may be able to reflect more realistic aspects of children (De Los Reyes & Langer, 2018). However, most of the previous studies only rely on self-report of children or adolescents or parental report (e.g., Heizomi et al., 2015; Shah et al., 2019). Therefore, data need to be collected from multiple informants such as children themselves as well as adults such as parents and teachers.

Thus, this study examined the following hypotheses, and the research model is presented in Fig. 1.

Fig. 1

Proposed theoretical moderated-mediation model

Hypothesis 1

Children’s school adaptation is a positive predictor of their general happiness.

Hypothesis 2

Children’s academic achievement mediates the relationship between school adaptation and general happiness.

Hypothesis 3

The interaction between school adaptation and problematic smartphone usage mediates the effect of academic achievement on children’s general happiness.

Method

Participants

This study used data from the 11th Panel Study of Korea Children (PSKC) conducted by the Korean Institute of Child Care and Education. PSKC is an annual nation-wide and longitudinal survey which has been conducted on a representative sample of Korean children born between April and July of 2008 and their teachers as well as parents (Bahk et al., 2015). Participants who were recruited from 30 hospitals across the country were interviewed face to face with trained interviewers. After the in-person interview, an interview has been administered by phone annually. Data was collected from multiple informants including parents, teachers, and children to evaluate variables that had effects on children’s growth and development. The present study utilized the most recently publicly opened dataset collected in 2018. In this dataset, data representing 695 children (695 children, their mothers and teachers) with complete datasets across the main variables of interest in this study were analyzed. Mean age (standard deviation) of the children was 10.32 (0.09) (female: 10.33 (0.09), male: 10.31 (09)). The gender and regional distribution of participants are presented in Table 1.

Table 1

Gender and regional distribution of participants (N = 695)

		N	%ile	Total
Gender	Female	339	48.8	695
	Male	356	51.2
Region	Seoul	65	9.4	695
	Gyeonggi / Incheon	186	26.8
	Chungcheong/Gandwon	118	17.0
	Daegu/Gyeongbuk	99	14.2
	Busan/Gyeongnam	124	17.8
	Gwangju/Jeolla	103	14.8

Measures

School adaptation

School adaptation was measured using the School Adjustment Inventory (Chi & Jung, 2006). SAI consists of 35 items related to school life, behavior during class, and relationship with friends and teachers (e.g., “I follow the rules,” “I help my teachers”). SAI is completed by the teachers and is evaluated on a 5-point Likert scale. Higher score indicates a higher level of adaptation to school, and internal consistency in Chi & Jung (2006) and the current study were 0.98, and 0.96, respectively.

Academic achievement

The Academic Performance Scale (Rhee et al., 2009) was used to measure the children’s academic achievement. The scale is completed by teachers and measures children’s achievement in subjects such as language, mathematics, science, and social studies on a 5-point Likert scale. The scale consists of 15 items such as “How good is 000’s reading ability compared to classmates” and “How well does 000 count compared to classmates.” Higher score indicates higher academic performance, and internal consistency in both Rhee et al., (2009) and the current study were 0.97.

General happiness

To evaluate general happiness of the participants, six items measuring general happiness from the Millennium Cohort Study were used (Connelly & Platt, 2014). A total of four pictures of facial expressions are provided, and the participants are asked to indicate the facial expression to answer the questions (e.g., “How do you feel when you think of your friends?”, “How do you feel when you think of your family?”). Higher score indicates a higher level of happiness in all areas of daily life. The internal consistency in a previous study was .72 (Sung & Ki, 2021), and .77 in the current study.

Problematic smartphone usage

To assess problematic smartphone usage, mothers were asked to complete the Internet Addiction Diagnostic Scale based on children’s problematic smartphone usage (Kim et al., 2002). The 15-item scale was evaluated on a 4-point Likert scale. The term “internet” in the original scale was replaced with “smartphone” to assess problematic smartphone usage. Items such as “I often fight with my family over problems with smartphone usage” and “I use my smartphone in one place without moving for more than four hours a day” were included, and a higher score indicates problematic smartphone usage. Internal consistency of the scale in Kim et al.’s (2002) study was 0.91, and 1.00 in the current data.

Data Analysis

For data analysis, SPSS 25.0 and PROCESS macro were used. First, to examine internal consistency of measures, Cronbach’s α values were calculated. Second, descriptive and correlation analyses between variables were conducted. Third, to test the proposed theoretical model (Fig. 1), PROCESS macro for SPSS (Hayes, 2017) was conducted using 10,000 bootstrapping to examine the moderated mediating model (model 7). PROCESS calculates ordinary least squares which are regression-based (Hayes, 2017). It was considered to be significant if 95% confidence intervals (CI) did not include 0.

Results

Descriptive statistics and correlation of main variables

All study variables showed statistically significant correlations. School adaptation was associated with lower problematic smartphone usage (γ = − 0.16, p < .001), higher academic achievement (γ = 0.55, p < .001) and general happiness (γ = 0.24, p < .001). Problematic smartphone usage also demonstrated correlation with lower academic achievement (γ = − 0.18, p < .001) and lower general happiness (γ = − 0.16, p < .001). In addition, academic achievement was positively correlated with general happiness (γ = 0.21, p < .001). Table 2 presents the means, standard deviation and Pearson correlations of the main variables.

Table 2

Descriptive statistics and correlations among main variables (N = 695)

	M(SD)	School adaptation	Problematic smartphone usage	Academic achievement	General happiness
School adaptation	4.28(0.82)	1
Problematic smartphone usage	26.58(6.46)	− 0.16***	1
Academic achievement	4.21(0.98)	0.55***	− 0.18***	1
General happiness	3.22(0.46)	0.24***	− 0.16***	0.21***	1

***p < .001

The moderated mediation analysis

To test the hypotheses, moderated mediation analysis using PROCESS macro with the bootstrapping method was conducted (Hayes, 2017). Results of analyses are presented in Table 3. First, the interaction effect between school adaption and problematic smartphone usage in their relationship to academic achievement was significant, F(1, 691) = 11.039, b = 0.005, SE = 0.002, R = 0.32, ΔR = 0.011, 95% CI [0.002, 0.009]. The interaction effect between school adaptation and problematic smartphone usage was probed at recentered values (± 1 SD from the mean) of problematic smartphone usage to understand the nature of the interaction through simple slope analysis. The association between school adaptation and academic achievement was significant at -1 SD, b = 0.164, SE = 0.014, 95% CI [0.135, 0.192], the mean, b = 0.191, SE = 0.011, 95% CI [0.168, 0.213], and + 1 SD of problematic smartphone usage, b = 0.228, SE = 0.016, 95% CI [0.198, 0.259]. This pattern of results indicates that the relationship between school adaptation and academic achievement is moderated by problematic smartphone usage, such that at lower levels of school adaptation, different levels of academic achievement were found, depending on the degree of problematic smartphone usage. More interestingly, for children with higher level of school adaptation, problematic smartphone usage did not demonstrate a significant effect on academic achievement (Fig. 2).

Table 3

Regression results for testing moderated mediation with Academic achievement as the mediator (N = 695)

Variables	b	SE	t	LLCI	ULCI	R 2
Outcome variable: Academic achievement						0.32
School adaptation	0.19	0.01	16.82	0.17	0.22
Problematic smartphone usage	− 0.12	0.00	-2.67	− 0.02	− 0.00
School adaptation X Problematic smartphone usage	0.01	0.00	3.32	0.00	0.01
Outcome variable: General happiness						0.07
School adaptation	0.03	0.01	4.00	0.02	0.05
Academic achievement	0.05	0.02	2.61	0.01	0.10

Fig. 2

Simple slope of the relation between school adaptation and academic achievement at problematic smartphone usage

Results of logistic regression showed that academic achievement, b = 0.054, SE = 0.021, 95% CI [0.014, 0.096] and school adaptation, b = 0.03, SE = 0.008, 95% CI [0.016, 0.046] were significant predictors of general happiness. Finally, the indirect effect of school adaptation on general happiness through academic achievement was examined, with problematic smartphone usage moderating the indirect effect. The index of moderated mediation was significant, F(2, 692) = 24.410, b = 0.031, SE = 0.02, R = 0.066, 95% CI [0.001, 0.024]. Therefore, the indirect effect of school adaptation on general happiness via academic achievement was significant with the moderation of problematic smartphone usage at the mean level, b = 0.011, SE = 0.005, 95% CI [0.001, 0.019], at + 1 SD level, b = 0.013, SE = 0.006, 95% CI [0.001, 0.024], and − 1 SD level, b = 0.009, SE = 0.004, 95% CI [0.001, 0.017].

Discussion

The purpose of the current study was to examine the moderated mediation model with school adaptation, academic achievement, general happiness, and problematic smartphone usage. Data from a sample of nationwide 10-year-old children, their mothers, and teachers were analyzed. The following conclusions were drawn by examining the study model.

First, we observed that school adaptation and academic achievement are significant predictors of general happiness. These results are in agreement with previous studies that found school adaptation and academic performance to be important in children’s well-being (i.e., Allen et al., 2018; Gómez-Baya et al., 2021). It further highlights that school environment is a main realm of functioning for children and adaptation to school plays an essential role in well-being. Moreover, these findings suggest that helping children gain more positive experiences and achieve a higher level of adaptation to school life is important for their overall happiness.

Second, academic achievement was a significant mediating factor in the relationship between school adaptation and general happiness. A higher level of adaptation to school was associated with better academic performance, which led to greater overall happiness. It is not surprising that students who adapt well to school where education is the primary purpose, are more likely to evidence better academic achievement and subsequently experience more positive emotions as well as a sense of well-being (Yang et al., 2019). In particular, in East Asian cultures that prioritize academic performance, the positive relationship between school adaptation and high academic achievement may be stronger, and academic achievement is highly likely to affect overall happiness of children (Leung et al., 2021).

Third, in the moderated mediation model in the current study, the interaction between problematic smartphone usage and school adaptation had significant effects on academic achievement. More specifically, children with moderate or low level of school adaptation were more significantly affected by the degree of problematic smartphone usage. In other words, the more they reported to problematically use smartphones, their grades were lower. However, the level of problematic smartphone usage did not seem to have significant effects on academic achievement in children with a higher level of school adaptation. This finding indicates that children with a low level of school adaptation may be more vulnerable to the negative effects of smartphones. Previous studies revealed the effects of smartphones are commonly negative (e.g., Sohn et al., 2019). However, the findings of the current study demonstrate that the extent of such negative effects may depend on adaptation level of children.

Academic achievement of children with high school adaptation was reported to be highest compared to children exhibiting mean or low school adaptation regardless of how much they use smartphones problematically. This implies that even with problematic smartphone usage, children with good school adaptation may hold protective factors that may buffer its negative impact. In a similar vein, previous studies have demonstrated that protective factors can neutralize or minimize the negative effect of problematic smartphone usage (e.g., Kiss et al., 2020). In other words, children with a high level of school adaptation may have access to factors that buffer the adverse effects of problematic smartphone usage. This may include a high level of self-regulation ability (Coyne et al., 2019), resilience (Hou et al., 2017; Kim et al., 2014) or other kinds of external regulatory systems (Chang et al., 2019) that affect problematic smartphone usage as well as school adaptation.

The results hold implications across various levels. To apply the results of studies in practice, some researchers have suggested interpreting the results at multiple levels (Serpa & Ferreira, 2018; Valsiner & Rosa, 2007). At the micro-level, because it was found that children’s general happiness is associated with school adaptation and academic achievement under the moderation effect of problematic smartphone usage, teachers and mothers can try to provide more specific guidelines and instructions to children concerning school performance and general happiness, as well as monitor their smartphone usage (i.e., Gentile et al., 2012). At the mezzo level, school authorities may implement preventive interventions concerning students’ problematic smartphone usage, especially for students with a lower degree of school adaptation. Kim & Lee (2020) reported that teachers’ participation in preventive programs had an effect on students’ school adaptation, and thus teachers’ active role in such programs is warranted. At the macro level, the government should pay closer attention at the policy level targeting school-aged children who have difficulties in adapting to school. In particular, if they are using smartphones problematically, it is more likely to lead to academic problems which are also associated with psychological maladjustment.

Smartphone usage may become problematic, but smartphones also hold benefits such as more efficient search capacity and provision of study aids (Singh & Samah, 2018; Woodcock et al., 2012). Therefore, it is not realistic to forbid children to use smartphone unconditionally. Indeed, because schools were closed during the COVID-19 pandemic period, many students spent more time at home during the daytime, which resulted in increased screen time even for the elementary school students (Wang et al., 2020). Moreover, many classes have been conducted online in this period of COVID-19, and exposure to smartphone-based educational contents has increased, naturally leading to increased exposure to smartphone and other devices (Limone & Toto, 2021). More children were reported to be engaged in problematic smartphone usage than before COVID-19 in Korea (Choi et al., 2021). This phenomenon seems critical given that early-onset of behavioral addiction problems including problematic smartphone usage may follow a chronic course (Roh et al., 2018). Therefore, it is a strength of this study that relatively younger children were assessed, unlike in previous studies that mainly focused on late childhood or adolescents (e.g., Fischer-Grote, 2019).

Another strength of the present study is that data were collected from multiple informants, thereby enhancing reliability and validity of the measured data (Stuart & Jose, 2012). A large proportion of studies focusing on younger children primarily depend on parental report measures (e.g., Shah et al., 2019). However, measures were collected not only from multiple informants but across different environments. Specifically, it has more significance that data in this study was collected from the informant who could report the variable best. That is, general happiness was measured from children, problematic smartphone usage from mothers, and school-related variables from teachers.

However, the current study has some limitations, and the recommendations for future studies can be suggested. First, our findings do not indicate causal relationships between the variables. Previous studies have reported that school adaptation and academic achievement predict mental health, well-being, and happiness of children (Lv et al., 2016; Verkuyten & Thijs, 2002). However, other studies have also demonstrated that emotional stability, subjective well-being, and experience of positive emotions expand cognitive abilities of children to affect their academic performance (Whitley et al., 2012). Therefore, longitudinal studies are needed to evaluate the causal relationship and the directions of effects between the variables.

Second,, only the extent of problematic smartphone usage was measured in the present study. Differences in how much time children spend using a smartphone, how children spend their time after school, or how their parents monitor children’s behaviors can have significant roles to buffer the effect of the problematic smartphone usage (Delany & Cheung, 2020; Thulin et al., 2020). For example, in a previous study, the length of smartphone usage time positively correlated with smartphone addiction (Ellis et al., 2019). Moreover, afterschool activities, such as physical exercise, music and art education were found to moderate the effect of problematic smartphone usage on adolescents’ adaptation, in addition to fostering better self-regulatory ability, a significant protective factor in behavioral problems (Guilmette et al., 2019; Seo et al., 2021; Williams, 2018). Thus, such variables must be considered in future research models.

Third, the extent of monitoring parents provide may have a significant role in the effect of problematic smartphone usage (Shin & Li, 2017). In the traditional vein of related research, parental style has been considered as an important factor in children’s behavioral problems (Ruiz-Hernández et al., 2019). However, parental monitoring was ineffective in reducing problematic behaviors related to using online devices in other studies (Chang et al., 2019; Hefner, Knop, Schmitt, & Votherderer, 2019). Therefore, the effect of parental monitoring should be included in future studies to verify its role more precisely.

Below is the link to the electronic supplementary material.

Supplementary Material 1