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INTRODUCTION
South Korea has a fairly high smartphone penetration rate. In 27 countries worldwide, the average percentage of smartphone users is about 76%, whereas, in Korea, smartphone users comprise 95% [1]. The proportion of Korean teenagers who own a smartphone continues to increase, reaching 89.7% in 2019 and 94.4% in 2020 [2]. As smartphone use becomes more ubiquitous, the risk of overdependence is also increasing annually. Across the risk groups by age, the ratio of the teenage group is the highest, compared to other age groups [2,3]. The smartphone overdependence ratio in school-aged children is about 30%, which is higher than that in preschool children (27%) and adults (22%) [3].
During the late school age, the frontal lobe has not yet developed [4]. This issue may make children highly impulsive children are highly impulsive and lack control and are at high risk of dependence on technology like a smartphone or the internet [3]. Children's excessive use of smartphones causes various health issues. When a child spends a lot of time using a smartphone, it can cause neck and spine flexion [5]. and visual impairment [6]. Additionally, the risk of obesity, sleep disorders, and poor physical activity increases [7,8]. Technology like internet and smartphone addiction also affects brain development, causing children to become distracted and have a shorter attention span, increasing the likelihood of attention deficit hyperactivity disorder [8,9]. Furthermore, children who constantly use smartphones are at an increased risk for depression, anxiety disorder, and suicidal ideation [9]. To preserve children’s health into adolescence and adulthood, it is necessary to identify the factors that influence smartphone dependence in children, as they are more prone to overuse.
Several studies identify factors related to smartphone dependence [10-13]. Factors such as impulsivity and lack of self-control were found to be internal individual factors highly correlated with smartphone dependence [11,12]. Recently, grit has gained attention as an internal individual factor related to technology dependence [14]. Grit refers to the ability to manage impulsivity and self-control in connection with addiction, as well as the ability to maintain perseverance and passion in the long term to achieve goals [15]. Grit is a variable that allows for a better understanding of an individual's internal characteristics associated with dependence and addiction. Grit is an acquired ability that can be learned through practice and experience [16], so it can serve as a protective factor against addiction. However, few studies have examined grit as a factor in children's dependence. Therefore, the present study selected grit as an internal factor of smartphone dependence.
The family is an external factor that has a significant influence on children's behavior. Children who lack support at home or have poor familial relationship become preoccupied and dependent on the relationship they create online and are more susceptible to harmful behaviors and addiction [13,17]. Among family-related factors, family strengths are qualities that emphasize the well-being of the family and can be used as an index to identify family functions such as familial relationship, emotional support, and communication [18]. Therefore, this study selected family strengths as an external factor in children's smartphone dependence.
Several studies to identify factors of smartphone dependence have been conducted on young adolescents attending middle or high school [10,11,13]. Studies on children aimed at identifying both internal and external factors of smartphone dependence are rare. Therefore, this study aimed to investigate grit as an internal factor and family strength as an external factor that would be significant factors associated with smartphone dependence among late school-aged children. This study’s findings are expected to provide a basis for interventions to help children avoid smartphone overdependence.
METHODS
2. Study participants
This study was conducted using a convenience sampling method. The participants consisted of late school-aged children from two schools in U and Y city, South Gyeongsang province. The inclusion criteria were as follows: children in grades 5 and 6 (10 to 11 years old), children who are currently using a smartphone and could answer the provided questionnaire in Korean. The exclusion criteria were as follows: children who received treatment or psychological counseling for smartphone addiction or internet game addiction. The children voluntarily consented to participate in the study, and their guardians also gave written consent to the children's participation.
It is recommended that the number of samples required for multiple regression analysis be at least 40 per predictor [19]. We predicted five predictors and dropout odds of 20% and calculated that the estimated sample size was 200. We distributed 240 copies and collected all of them, of which 22 were excluded as not all of the questions were answered. Therefore, the responses of 218 questionnaires were analyzed.
3. Data collection
This study was approved by the Institutional Review Board of K University (KSU-19-11-009). The data were collected for the month of December 2019 (just before the novel coronavirus [COVID-19] pandemic). Prior to data collection, we communicated with the elementary school administrators and head teachers in charge of grades 5 and 6, and a recruitment notice was posted on the bulletin board in the 5th and 6th-grade classrooms. The students who wanted to participate in the study told the researcher or homeroom teacher. We met the study participants in the classroom and explained the purpose, methods, procedures, potential risks and benefits, and then a letter containing information about the study was sent to their guardians. They read the letter, filled out the informed consent and sent it to us by mail. After we confirmed informed consent from both study participants and their guardians, the homeroom teacher distributed self-report questionnaires to the participating students, who filled it out in the classroom and submitted it to their teacher, and the teacher passed us the questionnaires.
4. Measures
1) Smartphone dependence
Smartphone dependence was evaluated using the short version of smartphone addiction scale [20] that is recognized as a valid and reliable tool for the dependence of smartphone use. This tool consisted of 10 items which can be scored in a 6 point scale, which ranges from 1 point (“not at all”) to 6 points (“always”). The scores of each response are added together for a total score. A higher total score indicates a greater intensity of smartphone dependence. Cronbach's α was 0.91 at the time of its development [20] and 0.85 in the present study.
2) Grit
Grit was evaluated using the original grit scale (Grit-O) originally developed by Duckworth et al. [15]. Lee and Sohn [21] has translated the Grit-O into Korean and presented Cronbach’s a of 0.79. The tool consisted of 12 items. Responses were based on a five-point scale ranging from 1 point (“not at all”) to 5 points (“always”). The total score is calculated as a sum of item scores. A higher total score indicates higher grit level. Cronbach's α was 0.66 in the present study.
3) Family strengths
Family strengths was evaluated using the scale for measuring family strengths for Korean developed by Eo and Yoo [18]. The tool consisted of 34 items. Responses were based on a 5-point scale ranging from 1 point (“not at all”) to 5 points (“always”). The total score is calculated as a sum of item scores. A higher total score indicates greater family strength. Cronbach's α was 0.94 at the time of its development [18] and 0.96 in this study.
In addition to the items regarding smartphone dependence, grit and family strengths, we collected data on general characteristics: gender, smartphone usage duration (year), average smartphone usage hours per day (<2 hours or ≥2 hours) and the main purpose of using a smartphone (gaming, social networking, listening to music, watching videos, searching information or phone call, and text messaging).
5. Data analysis
The data were analyzed using SPSS version 25 software (IBM Corp., Armonk, NY, USA). The data were first analyzed using descriptive statistics with frequencies, and percentages and means and standard deviations were calculated for the participants smartphone dependence and other variables. The differences in smartphone dependence according to the general characteristics were analyzed using the independent t-test or one-way analysis of variance. The correlations among the variables were performed using Pearson’s correlation analysis. Multiple regression analysis was done to identify the factors associated with smartphone dependence. Categorical variables are converted to dummy variables, and the variables of general characteristics that showed significant associations with smartphone dependence in previous studies [10,13] were entered as control variables. In the model, there was no multicollinearity, with the variance inflation factor of 1.069-5.047. There was no auto-correlation, as shown by a Durbin-Watson statistic of 1.985. A P-value of less than 0.05 was considered statistically significant.
RESULTS
Of 218 respondents, 55% were female. As for smartphone usage duration, 47.3% of participants were more than 3 years. 57.3% of the participants used a smartphone for less than 2 hours a day. The main purpose of using a smartphone was to watch a video (37.2%), followed by social networking (26.6%) and games (22.5%) (Table 1). The mean scores for smartphone dependence by general characteristics are presented in Table 2. We found significant differences in smartphone dependence based on the smartphone usage hours per a day (t=-4.38, P<0.001) and the main purpose of usage (F=3.24, P=0.008). The overall smartphone dependence of the participants was 2.47 (±0.93) out of 6. The participants’ grit was 3.30 (±0.49) and family strengths was 3.99 (±0.68) out of 5. A significant negative correlation was observed between the participants’ smartphone dependence and grit (r=-0.56, P<0.001). The participants’ family strengths was also significantly and negatively correlated to the smartphone dependence (r=-0.32, P<0.001) (Table 3).
Table 4 shows the multiple regression statistics of factors influencing the smartphone dependence. In the model, the explanatory power was 38% (F=17.620, P<0.001) and smartphone usage time ≥2 hours per a day (β=0.198, P<0.001), gaming (β=0.215, P=0.046) or social networking (β=0.304, P=0.007) of the main purpose of smartphone usage and grit were significant factors associated with the levels of smartphone dependence.
DISCUSSION
This study was conducted to investigate grit as an internal factor and family strength as an external factor on the smartphone dependence of late school-aged children.
Grit exerts the most significant influence on smartphone dependence in children in this study, which means that the lower grit, the higher the smartphone dependence. This is in line with previous studies that have shown that grit has a significant factor on addictions [14,22]. This is because the grit is the ability to sustain effort over a long period to achieve a goal [15]; hence, a person with a high level of grit will continue to strive to reduce or avoid smartphone use, even if there are obstacles. People with a high level of grit self-regulate and control themselves to achieve their goals [15]. In other words, children with a high level of grit are better at managing and controlling smartphone use, so they are more resistant to overdependence. Given that grit is an acquired ability [16] and that childhood is a period when parental control begins to wane and inhibitory control, such as self-control and regulation, begins to improve [4], strengthening grit during childhood will help children avoid overdependence and achieve desired growth and development. Grit is also an important quality that contributes to the overall development and successful adaptation [16,21]. Therefore it is necessary to enhance the grit of late school-age children through educational interventions that have been found to be effective in promoting grit.
Children whose main purpose of smartphone usage is gaming or social networking have a higher level of dependence than children who use smartphone mainly for calling and messaging. Previous studies reported that engagement with social media or games may be a strong factor of dependence [10,13]. The reasons child smartphone users engage strongly with social media platforms or games may be to form friendships, have fun, and relieve stress [10]. Social media platforms and games allow them to build relationship better than is possible for them in real life, while also bringing them joy. These benefits give children a sense of belonging and help them relieve negative emotions such as depression and anxiety. This acts as a reward, further encouraging overdependence [10,13]. Therefore, offline activities from which rewards can be derived and that encourage physical activity and peer interaction are needed to meet children's needs.
Time spent on a smartphone was also found to be a factor of smartphone dependence. Previous studies have demonstrated that the longer the usage time, the higher the risk of technology addiction [13,23]. However, restricting usage, that is, forcibly limiting time spent on smartphones, is known to be ineffective against overdependence [24,25]. Therefore, as an alternative strategy, it is important to direct children toward spending more time on offline activities, rather than forcing them to refrain from using smartphones. Additionally, as previously mentioned, it is vital that children develop the ability to self-regulate and exercise self-control through mechanisms such as grit. Moreover, improving media literacy, which is the ability to exercise judgment and control concerning media use, will be more effective in relieving children's maladjustment problems caused by smartphone use [26].
In this study, the external factor, family strengths, was not significant. This may be attributable to the fact that although modern society incorporates many different types of families, the tools used in this study were developed based on a traditional nuclear family [18], so it may not reflect the behavior of different kinds of families. Future research that encompasses a range of family types is needed to measure family strengths more accurately. Furthermore, since the overall explanatory power of the model was rather low, external factors affecting smartphone dependence should be expanded. It is necessary to explore environmental factors surrounding children that affect smartphone dependence, such as parents' smartphone use time and patterns, relationships with friends. The present study showed that dependence is not associated with gender. Gender is known to be a major predictor of smartphone dependence, but some studies have proven otherwise [13]. According to previous studies, girls mainly use their phones for social media, while boys tend to play online games [13,17]. In other words, there are gendered differences in the purposes of smartphone use, which seem to cause differences in smartphone dependence. Additional research is needed to collect more evidence.
1. Limitations and suggestions
This study has some limitations. First, convenient sampling was used to select subjects from two regions. Care should therefore be exercised in generalizing the findings. Secondly, family strengths constituted the sole external factor. Since children are strongly influenced by their peers as well as by their families, external factors need to be expanded to include peers. Third, Cronbach's α of grit was measured as low. Grit scale was developed for adults and translated into Korean for high school students. Therefore, it should be used for children through the process of refinement of tools. Nevertheless, this study has significance as follows. Due to the COVID-19 pandemic, smartphone use has become more common, and more activities are happening online. Given that the research data were collected just prior to the outbreak of the COVID-19 pandemic, the findings of this study can be used to compare children's degree of dependence pre- and post-pandemic. The research is also significant in that the study focused on childhood, during which there is a high chance of becoming heavily smartphone dependent. Finally, the study has demonstrated that grit, an acquired ability, is one of the major factors preventing smartphone dependence.
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