**3. Results**

The descriptive characteristics according to the content type of smartphone use are presented in Table 1. Results of chi-square analysis revealed that there were significant differences depending on age, sex, residential area, family economic status, sleep hours, and physical activity by content type of smartphone use. The "Study" group was more likely to be older, live in large cities, and have a higher family economic status. The "SNS" group had a higher prevalence of female respondents and a lower prevalence of physical activity. The "Game" group was more likely to be younger, boys, living in rural areas, sleeping less than 6 h, and less physically active. The "Entertainment" group had a higher prevalence of low family economic status compared to other groups (all *p* < 0.001).


**Table 1.** General characteristics of participants, according to content type of smartphone use.

SNS: Social-Networking Services.

The psychological characteristics of participants according to content type of smartphone use are presented in Table 2. The "SNS" group had a higher prevalence of high subjective stress level, current cigarette smoking, and current alcohol drinking. The "SNS" group also had significantly higher prevalence of depressive mood and suicidal ideation compared to other groups. The "Game" group had the lowest proportion of depressive mood and suicidal ideation among groups (all *p* < 0.001).

The average amount of time spent using a smartphone was greater in the "SNS" group (322.17 ± 228.90 min/day) than in other groups and lower in the "Study" group (176.97 ± 173.06 min/day). The proportion of adverse consequences of smartphone use, including conflicts with family, conflicts with friends, and poor academic performance due to smartphone use, were higher in the "SNS" group (59.2%, 27.6%, and 58.4% respectively), whereas the "Study" group had a lower prevalence of adverse consequences (41.8%, 20.1%, and 43.0% respectively) (Table 3).


**Table 2.** Psychological characteristics of participants, according to content type of smartphone use.

SNS: Social-Networking Services.

**Table 3.** Adverse consequences of smartphone use, according to content type of smartphone use.


SNS: Social-Networking Services.

Compared to the "Study" group, the "SNS" group was significantly more likely to report a depressive mood (AOR 1.36; 95% CI 1.24–1.49) and suicidal ideation (AOR 1.49; 95% CI 1.32–1.69). The "Entertainment" group also showed a positive association with suicidal ideation (AOR 1.20; 95% CI 1.06–1.35), and the "Game" group showed a negative association with depressive mood (AOR 0.77; 95% CI 0.69–0.85) (Table 4).

**Table 4.** Multivariable logistic regression analysis of content type of smartphone use, for depressive mood and suicidal ideation.


\* Adjustment for age, sex, region of residence, family economic status, sleep hours, and physical activity; SNS: Social-Network Services, OR: odds ratio.

The AORs for smartphone overuse (> 5 h per day) were 4.57 (95% CI, 4.20–4.98), 2.24 (95% CI, 2.05–2.45) and 2.60 (95% CI, 2.40–2.81) in the "SNS" group, "Game" group, and "Entertainment" group, respectively (Table 5).

**Table 5.** Multivariable logistic regression analysis of content type of smartphone use, for smartphone overuse (more than 5 h per day).


\* Adjustment for age, sex, region of residence, family economic status, sleep hours, and physical activity; SNS: Social-Networking Services, OR: odds ratio

#### **4. Discussion**

This study examined the association of psychological characteristics and addiction propensity with content type of smartphone use, within a relatively large convenience sample of adolescents in Korea. The results of this study revealed that depressive mood and suicidal ideation are significantly associated with higher SNS use, compared with smartphone use for games, study, and entertainment. Our results also suggested that the "SNS" group showed higher addiction propensity, including overuse and adverse consequences of smartphone use.

The results of this study expanded upon and shared similarities with previous findings on the relationship between mental health and SNS use. A prior systematic review by Frost et al. reported associations between SNS use (i.e., Facebook) and mental-health outcomes, such as alcohol use, addiction, anxiety, and depression [19]. Several studies have indicated that the prolonged use of SNS may be related to signs and symptoms of depression, and some authors have indicated that certain SNS activities might be associated with low self-esteem, especially in children and adolescents [20–23]. On the other hand, our results were contrary to a previous study that reported that the use of non-social smartphone features (i.e., news consumption, entertainment, and relaxation) were most related to depression and problematic smartphone use [24]. Furthermore, a prior study by our research group reported a potential protective effect from moderate use (1–2 h) of smartphones for social purposes (i.e., SNS and messaging) in regard to suicide attempts [1]. In these contexts, we should also consider the positive psychological effects of SNS use. In this study, we did not simply divide content type of smartphone use as social and non-social, but instead we compared detailed non-social uses: study, game, entertainment, and SNS. According to our results, content type of smartphone use should not be classified simply as social and non-social use but should also take into account the detailed characteristics of SNS use and various other tasks, including differences in the effects of mental health on adolescents.

There has been wide discussion on the potential causes for depressive mood resulting from increased time on SNS. The most commonly used mediator to explain the association between SNS use and depression is self-esteem. It is an important factor in developing and maintaining mental health and overall quality of life, and low self-esteem is associated with numerous mental illnesses, including depression and addiction [25,26]. Some authors have presented that individuals higher in narcissism and lower in self-esteem also showed more online activity, including self-promotional content such as SNS [27]. On the other hand, there is the that hypothesis feelings of depression can be predicted indirectly by SNS addiction [21]. Authors have indicated that SNS allows the user to get virtual community gratification and gain gratification from creating a self-image online. Based on the uses and gratifications theory, SNS use can lead to SNS addiction, as the functions available to the users allow them to gain instant gratification from using the service, which in turn could lead to excessive use.

Contrary to previous research that indicated a negative association between online-game use and adolescent mental health [28,29], the current study did not find that smartphone-game use was associated with depressive mood and suicidal ideation. The results might reflect the characteristics of categorization and reference group of study. The "Game" group of this study included those who enjoyed "gaming" more than other contents of the smartphone, but it does not mean that they had a "gaming addiction". Specifically, if a person performs gaming in a regular pattern, the person may relieve his/her stress. However, if a person overly performs gaming, he or she may have increased psychological problems, as shown in the literature. On the other hand, because of the statistically low number of "non-smartphone users", we used "Study" as a reference group. Studying does not mean the person cannot be addicted to it, and using "Study" as the reference can create some biases. For example, a person who is over-studying may have increased distress. Therefore, we cannot capture whether gaming is related to increased distress if studying is associated with high distress.

Furthermore, smartphone-game use predicted problematic smartphone use compared to the "Study" group, but showed a weak association compared to the "SNS" or "Entertainment" groups. Smartphone games are somewhat different from computer-based online games, allowing users to access them anywhere, anytime, but there is a limit to the use of tools for the games. There have been a number of studies on problematic game use, and recently, a WHO ICD-11 proposal for a new category named "Gaming Disorder" [30]. However, most of the studies so far have been limited to computer-based online games [31–33]. Furthermore, considering the recent trend that the use of entertainment, such as the use of YouTube, is particularly popular among adolescents and has become dominant in the media market worldwide [34,35], the results of the current study indicated the necessity for further studies about game and entertainment on the smartphone. Smartphones, which are relatively simple tools compared to conventional computers, may be better suited for simple functions, such as watching videos, than for more complex tasks, such as playing games, which may result in adolescents indulging in media instead.

The present study has a number of limitations that should be considered when interpreting the findings. First, due to the cross-sectional nature of national surveys, the present findings have limitations in explaining the causal inferences between content type of smartphone use and psychological characteristics. Further studies with sufficient time for investigation are needed to develop a clear understanding about the association of psychological characteristics and addiction propensity with content type of smartphone use. Second, the psychological characteristics and internet use were measured through the ad hoc questions rather than mental-health experts' assessment or validated scales, because the data were collected through the participants' self-reports, and therefore, some reporting bias could have occurred. Moreover, because the group was divided only for one main purpose of smartphone use, we could not distinguish those who performed two or more content types. Third, in our study, the addictive propensity was estimated only by time spent using a smartphone, not by the scales for smartphone addiction. In addition, most variables in the study, including conflicts with family/friends, and poor academic performance due to smartphone use, were surveyed on the basis of a self-reported questionnaire, which has inherent limitations regarding the validity of the data and the recall bias. However, in the previous study, excessive smartphone use was validated as the most powerful independent predictor of smartphone addiction [8], and we can use this to estimate the propensity to addiction. Fourth, our data lacked information regarding the familiarity or personological profile of the participants that might affect individuals with mood disorder and/or addiction. Despite the limitations of this cross-sectional survey, the present study has some strengths. We used a multilevel multinomial logistic modeling approach based on a nationally representative sample of Korean adolescents, who have the highest smartphone ownership rate in the world. Moreover, the response rate to the survey was very high. To the best of our knowledge, this study is the first to report on the association of psychological characteristics and addiction propensity with the content type of smartphone use in adolescents.
