- Email: [email protected]
The exacerbating role of perceived social support and the “buffering” role of depression in the relation between sensation seeking and adolescent smartphone addiction
Personality and Individual Differences 130 (2018) 129–134
Contents lists available at ScienceDirect
Personality and Individual Differences journal homepage: www.elsevier.com/locate/paid
The exacerbating role of perceived social support and the “buffering” role of depression in the relation between sensation seeking and adolescent smartphone addiction
T
⁎
Pengcheng Wanga, Li Leia, , Xingchao Wanga, Jia Niea, Xiaoyuan Chua, Shuining Jinb a
Department of Psychology, The Center of Internet + Social Psychology, Renmin University of China, No. 59 Zhongguancun Street, Haidian District, Beijing 100872, China b School of Basic Medical Sciences & Nursing, Chengdu University, Shiling Town, Chengdu 610106, China
A R T I C LE I N FO
A B S T R A C T
Keywords: Adolescents Sensation seeking Perceived social support Depression Smartphone addiction
The present study examined the relation between sensation seeking and adolescent smartphone addiction, and tested both the moderating roles of perceived social support and depression on the relation between sensation seeking and smartphone addiction among Chinese adolescents. Six hundred and fifty-five adolescents completed measures regarding sensation seeking, smartphone addiction, perceived social support, and depression. The findings indicated that sensation seeking was positively significant associated with adolescent smartphone addiction. Contrary to the social support buffering hypothesis, the results indicated that perceived social support exacerbated the relation between sensation seeking and adolescent smartphone addiction. To be specific, for adolescents with a low level of perceived social support, the relation between sensation seeking and smartphone was positively significant, and for adolescents with a high level of perceived social support, the relation between sensation seeking and smartphone addiction was even stronger. Moreover, depression moderated the relation between sensation seeking and adolescent smartphone addiction. Specifically, for adolescents with a low level of depression, the relation between sensation seeking and smartphone addiction was positively significant, while for adolescents with a high level of depression, the relation between sensation seeking and smartphone addiction was not significant.
1. Introduction Smartphones have become an important part of many adolescents' daily lives in recent years. Smartphone addiction, as a relatively new form of behavioral addiction, is emerging as a big concern in the last decade (Bian & Leung, 2015; Lee & Lee, 2017). Smartphone addiction is a phenomenon characterized by withdrawal symptoms, tolerance, dependence, and social problems (Choi et al., 2015), it has received increasing academic attention because of its negative impacts on adolescent development. For example, previous studies indicate that smartphone addiction can negatively affect adolescents' sleep quality, emotional status, academic performance, peer relationship, and physical health (Kim, Kim, & Jee, 2015; Lemola, Perkinson-Gloor, Brand, Dewald-Kaufmann, & Grob, 2015; Lepp, Barkley, & Karpinski, 2014; Samaha & Hawi, 2016; Seo, Park, Kim, & Park, 2016; Thomee, Harenstam, & Hagberg, 2011; Wang et al., 2017). Given the adverse influences of smartphone addiction on adolescents, it is of both
theoretical and empirical importance to uncover the potential factors that can lead to adolescent smartphone addiction. Although some risk factors for adolescent smartphone addiction have been recognized (Bae, 2015; Bian & Leung, 2015; Gökçearslan, Mumcu, Haşlaman, & Çevik, 2016; Hong, Chiu, & Huang, 2012; Lee, Chang, Lin, & Cheng, 2014; Lee & Lee, 2017; Roberts, Pullig, & Manolis, 2015), however, little research has explored the relation between sensation seeking and smartphone addiction. Sensation seeking has long been documented as one of the most confirmed predictive personal traits of problem and addictive behaviors (Jonah, 1997; Zuckerman & Kuhlman, 2000). For example, previous research demonstrates that sensation seeking is positively related to alcohol abuse, smoking, casual sexual behaviors, and dangerous driving (Jonah, 1997; Zuckerman & Kuhlman, 2000). While some studies find that sensation seeking is positively related to Internet addiction, however, the relation between sensation seeking and Internet addiction has been less consistent (Lavin, Marvin, McLarney, Nola, & Scott, 1998; Lin & Tsai, 2001). One
⁎ Corresponding author at: Department of Psychology, The Center of Internet + Social Psychology, Renmin University of China, No. 59 Zhongguancun Street, Haidian District, Beijing 100872, China. E-mail address: [email protected] (L. Lei).
https://doi.org/10.1016/j.paid.2018.04.009 Received 12 January 2018; Received in revised form 29 March 2018; Accepted 6 April 2018 0191-8869/ © 2018 Elsevier Ltd. All rights reserved.
Personality and Individual Differences 130 (2018) 129–134
P. Wang et al.
possible reason is that there are certain key moderators causing the variation in the relation between sensation seeking and Internet addiction. Given that smartphones are based on the Internet, it is possible that the relation between sensation seeking and smartphone addiction would vary as a function of certain moderators. Confirming the relation between sensation seeking and smartphone addiction, and the moderators of this relation would be critical to advance our understanding of adolescent smartphone addiction and to enlighten effective prevention and intervention as well. In addition, adolescents have poorer impulsive control compared with adults and they use smartphones to manage their emotions and social status (Lopez-Fernandez, Honrubia-Serrano, Freixa-Blanxart, & Gibson, 2014), which makes them at the most risk of getting addicted to smartphones. However, the majority of the studies regarding smartphone addiction are focused on young adults such as college students, it is necessary and important to focus more on adolescent smartphone addiction (Lopez-Fernandez et al., 2014). To fill these gaps, the present study utilized a sample of Chinese adolescents to examine the effect of sensation seeking on adolescent smartphone addiction, and explored whether perceived social support and depression would moderate the relation between sensation seeking and adolescent smartphone addiction.
As the social support buffering hypothesis suggests (Cohen & Wills, 1985), perceived social support can buffer people from the impacts of some risk factors. Given that individuals with a high level of sensation seeking are more likely to seek varied, novel, complex, and intense sensations or experiences, even if they need to take physical, social, legal, and financial risks for the sake of such experience (Zuckerman, 1994). It is reasonable to regard sensation seeking as a risk factor in some cases. Therefore, it is theoretically possible that perceived social support could be a buffer in the relation between sensation seeking and adolescent smartphone addiction. Empirical research supports this notion. For example, a recent study found that family support moderated the relation between depression and Internet addiction (Wu, Li, Lau, Mo, & Lau, 2016). To our knowledge, no prior has examined the moderating effect of perceived social support in the relation between sensation seeking and adolescent smartphone addiction. Based on the social support buffering hypothesis and the empirical grounds reviewed above, we put forward the second hypothesis in the present study:
1.1. Sensation seeking and adolescent smartphone addiction
1.3. The moderating role of depression
Sensation seeking is a common characteristic among adolescents (Cauffman et al., 2010; Steinberg et al., 2008; Zuckerman, 1994). According to the sensation seeking theory, sensation seeking is “a trait by the seeking of varied, novel, complex, and intense sensations and experiences, and the willingness to take physical, social, legal, and financial risks for the sake of such experience” (Zuckerman, 1994). Sensation seeking is a biological trait, which is an important predictor of human behavior (Zuckerman, 1996; Zuckerman & Kuhlman, 2000). For individuals with a high level of sensation seeking, they have lower baseline arousal, which may drive them to participate in highly arousing experiences. Therefore, it is possible that sensation seeking can be related to smartphone addiction. Empirical research is in support of this notion. For example, some cross-sectional studies found that adolescents with a high level of sensation seeking are at more risk of getting addicted to the Internet (Li, Newman, Li, & Zhang, 2016; Lin & Tsai, 2001; Velezmoro, Lacefield, & Roberti, 2010), even after controlling for other predictive factors such as anxiety, depressive symptoms, and lack of assertiveness (Dalbudak et al., 2015). Besides, a longitudinal study found that sensation seeking was a powerful predictor of Internet addiction (Ko, Yen, Yen, Lin, & Yang, 2007). Moreover, a meta-analysis indicated that there was a moderate and positive relation between sensation seeking and Internet addiction (Wang, Chen, Yang, & Gao, 2013). To our knowledge, little research has directly explored the relation between sensation seeking and adolescent smartphone addiction before. Based on the literature reviewed above, we put up the first hypothesis in the present study:
The inconsistency of outcomes may also come from individual traits that moderate (i.e., exacerbate or buffer) the influence of sensation seeking on adolescent smartphone addiction, for instance, depression. Depression is regarded as a constellation of negative emotions and behaviors, including feelings of worthlessness and loneliness, worrying about doing bad things, crying, and feeling the need to be perfect (Petersen et al., 1993). According to the cognitive-behavioral model of pathological Internet use (Davis, 2001), people with negative mental status are more likely to get addicted to the Internet, given that smartphone is based on the Internet, it is theoretically possible that depression could predict smartphone addiction. Empirical research is in line with this notion. For example, a study found that depression was positively related to smartphone addiction among college students, even after controlling for some confounders such as demographics, personality traits, and academic variables (Boumosleh & Jaalouk, 2017). Moreover, depression may exacerbate the relation sensation seeking and adolescent smartphone addiction. According to the diathesis-stress framework, some personal traits such as depression can exacerbate the relation between some negative factors and their influences on people. Empirical research has supported this notion. For example, it is found that depression can moderate the relation between denial (a type of coping strategy) and Internet addiction (Chou et al., 2015). To our knowledge, no prior research has explored the direct relationship between sensation seeking and adolescent smartphone addiction, nor the moderating effect of depression on the relation between sensation seeking and adolescent smartphone addiction. Based on the literature reviewed above, we put up the third hypothesis in the present study:
Hypothesis 2. Perceived social support will moderate the relation sensation seeking and adolescent smartphone addiction. To be specific, the relation between sensation seeking and smartphone addiction will be stronger for adolescents with a low level of perceived social support.
Hypothesis 1. Sensation seeking will predict adolescent smartphone addiction in general. To be specific, a high level of sensation seeking will predict a high level of adolescent smartphone addiction.
Hypothesis 3. Depression would positively predict adolescent smartphone addiction. Moreover, depression would moderate the relation between sensation seeking and adolescent smartphone addiction. To be specific, the relation between sensation seeking and smartphone addiction would be stronger for adolescents with a high level of depression.
1.2. The moderating role of perceived social support While these studies mentioned above are in support of the notion that sensation seeking could predict smartphone addiction, a few studies indicate that sensation seeking as an explanation for Internet addiction are inconsistent (Ko et al., 2007; Lavin et al., 1998; Li et al., 2016; Lin & Tsai, 2001; Velezmoro et al., 2010; Wan & Chiou, 2006; Wang et al., 2013). Therefore, it is possible that sensation seeking could predict smartphone addiction in general, but the effect would vary as a function of certain variables (e.g., perceived social support, depression).
1.4. The present study Taken together, the main purposes of the present study were as follows. First, this study explored whether sensation seeking would be positively associated with adolescent smartphone addiction. Second, 130
Personality and Individual Differences 130 (2018) 129–134
P. Wang et al.
this study examined whether perceived social support would moderate the relation between sensation seeking and adolescent smartphone addiction. Finally, the current study examined whether depression would moderate the relation between sensation seeking and adolescent smartphone addiction.
Table 1 Descriptive statistics and correlations of the main study variables.
2. Methods
Variables
M
SD
1
2
3
4
1. 2. 3. 4.
3.05 3.47 5.13 1.43
0.76 0.87 0.95 0.32
1 0.19⁎⁎⁎ −0.02 0.14⁎⁎⁎
1 0.00 0.26⁎⁎⁎
1 −0.33⁎⁎⁎
1
SS SA PSS Dep
Note: N=655. SS = sensation seeking, SA = smartphone PSS = perceived social support, and Dep = depression. ⁎⁎⁎ p < 0.001.
2.1. Participants A total of 655 middle school students (55% of the participants were males) participated in our survey. The participants were recruited from two middle schools in Hebei, China. The mean age of the participants was 16.80 years (SD = 0.74, range = 15–19 years). Students completed a survey designed to collect data regarding demographic variables, sensation seeking, smartphone addiction, perceived social support, depression, and some other measurements regarding adolescent development.
addiction,
2.3. Procedure The study was approved by the Institutional Review Board of the first's author's university. Informed consent was obtained from the middle school students and their parents before data collection. Students were invited to participate in the survey in anonymously in the classrooms. Well-trained postgraduate students conducted the survey. The authenticity, independence, and integral of all answers were emphasized to the participants. The participants received a gift as incentives. < 1% of the data were incomplete and the missing data were handled with mean imputation (Little & Rubin, 2002).
2.2. Measures 2.2.1. Sensation seeking Sensation seeking was measured by the Brief Sensation Seeking Scale (BSSS) (Hoyle, Stephenson, Palmgreen, Lorch, & Donohew, 2002), the scale consists of 8 items (e.g., “I would like to explore strange places”). The participants rated each item on a five-point scale from 1 = strongly disagree to 5 = strongly agree, with higher total scores indicating higher levels of sensation seeking. For the current study, the Cronbach α for the BSSS was 0.78.
3. Results 3.1. Preliminary analyses Means, standard deviations, and zero-order correlations for all study variables are presented in Table 1. As expected, adolescents with high levels of sensation seeking were more likely to get addicted to smartphones, and they were more likely to be depressed as well. Adolescents with high levels of perceived social support were less likely to be depressed. Besides, adolescents with high levels of depression were more likely to get addicted to smartphones.
2.2.2. Smartphone addiction Adolescent smartphone addiction was measured by the Smartphone Addiction Scale (SAS) (Kwon, Kim, Cho, & Yang, 2013). The scale consists of 10 items (e.g., “Missing planned work due to smartphone use”). The participants rated each item on a six-point scale ranging from 1 = strongly disagree to 6 = strongly agree, with higher scores indicating more addicted to smartphones. For the current study, the Cronbach α for the SAS was 0.85.
3.2. Test of the moderation model of perceived social support Hierarchical regression procedures were performed to examine the moderating effects of perceived social support on the relation between sensation seeking and smartphone addiction. All variables were standardized before the examination of the moderating effect. In the hierarchical regression model, the order of entry was as follows. At step 1, the predictor variable (sensation seeking) was entered into the regression. At step 2, the moderator variable (perceived social support) was entered into the regression equation. At step 3, the interaction of sensation seeking and perceived social support was added. As Table 2 shows, sensation seeking was positively associated with smartphone addiction, moreover, there was a significant interaction between sensation seeking and perceived social support, which suggests
2.2.3. Perceived social support Perceived social support was measured by the Multidimensional Scale of Perceived Social Support (MSPSS) (Zimet, Dahlem, Zimet, & Farley, 1988), which consists of 12 items. It measures perceived support from three sources including family (e.g., “I get emotional help and support I need from my family”), friends (e.g., “I can count on my friends when things go wrong”), and significant others (e.g., “There is a special person who is around me when am in need”). Each item was rated on a 7-point scale (1 = strongly disagree, 7 = strongly agree), with higher scores indicating greater perceived social support. In the present study, Cronbach's α for the MSPSS was 0.83.
Table 2 Hierarchical regression analysis predicting adolescent smartphone addiction from sensation seeking and perceived social support.
2.2.4. Depression Depression was measured by the Center for Epidemiological Studies Depression Scale (CES-D, Radloff, 1977), which consists of 20 items. It includes six components: feelings of guilt and worthlessness; depressed mood; feelings of helplessness and hopelessness; psychomotor retardation; loss of appetite; and sleep disturbance. Respondents indicate how often within the last week they experienced the symptoms on a 4point scale (1 = “rarely or none of the time”; 2 = “some or little of the time”; 3 = “occasionally or a moderate amount of time”; 4 = “most or all of the time”). The scores for the 20 items are added, with higher scores representing worse conditions on depression. In the present study, Cronbach's α for the CES-D was 0.89.
Variable
SS PSS SS × PSS Total R2
Smartphone addiction Step 1
Step 2
Step 3
β
β
β
0.19
0.04
⁎⁎⁎
0.19 0.00
⁎⁎⁎
0.04
Note: SS = sensation seeking, PSS = perceived social support. ⁎ p < 0.05. ⁎⁎⁎ p < 0.001. 131
0.20⁎⁎⁎ 0.00 0.08⁎ 0.05
Personality and Individual Differences 130 (2018) 129–134
P. Wang et al.
1 0.8
Low social support
1
High social support
0.8
High depression
0.6
0.4
Smartphone addiction
Smartphone addiction
0.6
Low depression
0.2 0 Low sensation seeking
High sensation seeking
-0.2 -0.4
0.4 0.2 0 Low sensation seeking -0.4
-0.6
-0.6
-0.8
-0.8
-1
-1
Fig. 1. Effects of sensation seeking and perceived social support on smartphone addiction.
High sensation seeking
-0.2
Fig. 2. Effects of sensation seeking and depression on smartphone addiction.
4. Discussion that perceived social support moderated the relation between sensation seeking and adolescent smartphone addiction. For descriptive purposes, we plotted the regression of smartphone addiction on sensation seeking at high and low levels of perceived social support (see Fig. 1). Simple slope tests showed that for adolescents with a low level of perceived social support, high level of sensation seeking was associated with high level of smartphone addiction, bsimple = 0.12, p < 0.05. Surprisingly, for adolescents with a high level of perceived social support, the effect of sensation seeking on smartphone addiction was even stronger, bsimple = 0.28, p < 0.001. Therefore, Hypothesis 1 was partially supported.
Little research has explored the relationship between sensation seeking and adolescent smartphone, and the moderating mechanisms underlying this relationship are largely unknown. The present study examined whether sensation seeking would predict adolescent smartphone addiction and whether this relation was moderated by perceived social support or depression. The results indicated that sensation seeking could lead to adolescent smartphone addiction. Moreover, this relation was moderated by perceived social support and depression, separately. However, contrary to our hypothesis, the results showed that perceived social support exacerbated, instead of buffered, the relation between sensation seeking and adolescent smartphone. Meanwhile, depression buffered the relation between sensation seeking and adolescent smartphone addiction statistically. The following sections will discuss each of the study hypotheses.
3.3. Test of the moderation model of depression The same procedures were performed to examine the moderating effect of depression on the relation between sensation seeking and smartphone addiction. The results indicated that depression moderated the influence of sensation seeking on smartphone addiction. (See Table 3.) For descriptive purposes, we plotted the regression of smartphone addiction on sensation seeking at high and low levels of depression (see Fig. 2). Simple tests showed that for adolescents with a low level of depression, high level of sensation seeking was associated with high level of smartphone addiction, bsimple = 0.27, p < 0.001. However, for adolescents with a high level of depression, the relation between sensation seeking and smartphone addiction was no longer significant, bsimple = 0.08, p > 0.05. Therefore, Hypothesis 2 was partially supported.
4.1. Sensation seeking as a protective factor of adolescent smartphone addiction Although some prior studies have explored the relationship between sensation seeking and Internet addiction (Li et al., 2016; Lin & Tsai, 2001; Velezmoro et al., 2010), little research has ever explored the relation between sensation seeking and adolescent smartphone addiction. The present study is the first to document the predictive role of sensation seeking on adolescent smartphone addiction. This finding goes beyond the previous studies by uncovering that sensation seeking, as a personality trait (Zuckerman, 1994), could lead to adolescent smartphone addiction. This could advance our understanding of what kind of people are more likely to get addicted to information technologies products such as smartphones, which is important and necessary for inspiring detections, interventions, and preventions aimed at reducing people's overusing of these products. 4.1 The moderating role of perceived social support. As expected, the results showed that perceived social support could indeed moderate the relation between sensation seeking and smartphone addiction. However, the results reveal that, contrary to our assumption, perceived social exacerbated, instead of buffering the relation between sensation seeking and adolescent smartphone addiction. To be specific, the relation between sensation seeking and smartphone addiction was stronger among adolescents with a high level of perceived social support compared with adolescents with a low level of perceived social support. This finding was not in line with the social support buffering hypotheses and previous empirical evidence (Cohen & Wills, 1985; Jaffee, 2017), which suggest that social support could buffer individuals from the negative influences of some risk factors. Therefore, it is important to analyze why this finding makes sense.
Table 3 Hierarchical regression analysis predicting adolescent smartphone addiction from sensation seeking and depression. Variable
SS Dep SS × Dep Total R2
Smartphone addiction Step 1
Step 2
Step 3
β
β
β
⁎⁎⁎
⁎⁎⁎
0.19
0.16 0.24⁎⁎⁎
0.04
0.09
0.17⁎⁎⁎ 0.26⁎⁎⁎ −0.09⁎⁎ 0.10
Note: SS = sensation seeking, Dep = depression. ⁎⁎ p < 0.01. ⁎⁎⁎ p < 0.001. 132
Personality and Individual Differences 130 (2018) 129–134
P. Wang et al.
5. Conclusion
Given that the basic purpose of mobile phone use is to allow people to communicate with each other (Choi et al., 2015; Townsend, 2000), and for adolescents with a high level of perceived social support, they are more likely to regard others as warm and reliable. Therefore, when they want to seek some novel experiences or just want to do something, it is more likely that they will use the smartphone to discuss or share the activities with their friends, families, and intimate others, which can lead to their overuse, dependency, or even addiction to smartphones. For adolescents with a low level of perceived social support, because they may not regard being with other as encouraging, when they want to do something, it is less likely that they would act alone instead of doing it with the others. This finding challenges the view that social support invariably buffers people from the impacts of adverse factors, and it also inspires future researchers to distinguish the moderating effect of social support in different domains.
In summary, the present study reveals that sensation seeking is a risk factor in adolescent smartphone addiction. Moderating analyses indicate that the perceived social support exacerbates the relation between sensation seeking and smartphone addiction, with the relation being stronger for adolescents with a high level of perceived social support. Moreover, depression can “buffer” the relation between sensation seeking and adolescent smartphone addiction. To be specific, for adolescents with a low level of depression, the relation between sensation seeking and smartphone addiction is positively significant. While for adolescents with a high level of depression, the relation between sensation and smartphone is no longer significant. Conflict of interest The authors report no conflicts of interest.
4.2. The moderating role of depression
Acknowledgement
The third aim of the current study was to examine the moderating role of depression in the relation between sensation seeking and adolescent smartphone addiction. The result indicated that depression did moderate the relation between sensation seeking and adolescent, however, contrary to our hypothesis, the result showed that depression buffered the relation between sensation seeking and adolescent smartphone addiction, statistically. To be specific, for adolescents with a high level of depression, the relation between sensation seeking and adolescent smartphone was not significant. Meanwhile, for adolescents with a low level of depression, the relation between sensation seeking and smartphone addiction was positively significant. One explanation is that, depression is a robust predictor of adolescent smartphone addiction, as previous studies demonstrate that depression is most related to Internet addiction (Carli et al., 2013) and depression could predict Internet addiction even after controlling for a variety of confounding factors (Boumosleh & Jaalouk, 2017). Therefore, for adolescents with a high level of depression, they are likely to get addicted to smartp014nes regardless of whether they have a high or low level of sensation seeking. Overall, the present study found that sensation seeking as a personal trait, could predict adolescent smartphone addiction in general. Surprisingly and reasonably, the present study indicated that perceived social support could exacerbate the relation between sensation seeking and adolescent smartphone addiction, and depression can “buffer” the relation between sensation seeking and adolescent smartphone addiction. All these findings can help deepen our understanding of the relation between individual characteristics and technologies overuse such as smartphone addiction, which can lay the groundwork for future research or practices that aimed at detecting and reducing technologies overuses in the digital era.
The present study was supported by the Key Research Institute in Humanities and Social Sciences of the Ministry of Education (Academy of Psychology and Behavior, Tianjin Normal University) (14JJD190005), the Key Project of Social Science Fund of Beijing, China (15SHA005), the Outstanding Innovative Talents Cultivation Funded Programs 2017 of Renmin University of China. References Bae, S. M. (2015). 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. School Psychology International, 36(5), 513–531. Bian, M., & Leung, L. (2015). Linking loneliness, shyness, smartphone addiction symptoms, and patterns of smartphone use to social capital. Social Science Computer Review, 33(1), 61–79. Boumosleh, J. M., & Jaalouk, D. (2017). Depression, anxiety, and smartphone addiction in university students - A cross-sectional study. PLoS One, 12(8), e0182239. Carli, V., Durkee, T., Wasserman, D., Hadlaczky, G., Despalins, R., Kramarz, E., et al. (2013). The association between pathological internet use and comorbid psychopathology: A systematic review. Psychopathology, 46(1), 1–13. Cauffman, E., Shulman, E. P., Steinberg, L., Claus, E., Banich, M. T., Graham, S., et al. (2010). Age differences in affective decision making as indexed by performance on the Iowa Gambling Task. Developmental Psychology, 46, 193–207. Choi, S. W., Kim, D. J., Choi, J. S., Ahn, H., Choi, E. J., Song, W. Y., ... Youn, H. (2015). Comparison of risk and protective factors associated with smartphone addiction and internet addiction. Journal of Behavioral Addictions, 4(4), 308–314. Chou, W.-P., Ko, C.-H., Kaufman, E. A., Crowell, S. E., Hsiao, R. C., Wang, P.-W., ... Yen, C.-F. (2015). Association of stress coping strategies with internet addiction in college students: The moderating effect of depression. Comprehensive Psychiatry, 62, 27–33. Cohen, S., & Wills, T. A. (1985). Stress, social support, and the buffering hypothesis. Psychological Bulletin, 98(2), 310–357. Dalbudak, E., Evren, C., Aldemir, S., Taymur, I., Evren, B., & Topcu, M. (2015). The impact of sensation seeking on the relationship between attention-deficit/hyperactivity symptoms and severity of internet addiction risk. Psychiatry Research, 228(1), 156–161. Davis, R. A. (2001). A cognitive-behavioral model of pathological internet use. Computers in Human Behavior, 17(2), 187–195. Gökçearslan, Ş., Mumcu, F. K., Haşlaman, T., & Çevik, Y. D. (2016). Modelling smartphone addiction: The role of smartphone usage, self-regulation, general self-efficacy and cyberloafing in university students. Computers in Human Behavior, 63, 639–649. Hong, F. Y., Chiu, S. I., & Huang, D. H. (2012). A model of the relationship between psychological characteristics, smartphone addiction and use of mobile phones by Taiwanese female university students. Computers in Human Behavior, 28(6), 2152–2159. Hoyle, R. H., Stephenson, M. T., Palmgreen, P., Lorch, E. P., & Donohew, R. L. (2002). Reliability and validity of a brief measure of sensation seeking. Personality and Individual Differences, 32(3), 401–414. Jaffee, S. R. (2017). Child maltreatment and risk for psychopathology in childhood and adulthood. Annual Review of Clinical Psychology, 13(1), 525–551. Jonah, B. A. (1997). Sensation seeking and risky driving: A review and synthesis of the literature. Accident Analysis & Prevention, 29(5), 651–665. Kim, S. E., Kim, J. W., & Jee, Y. S. (2015). Relationship between smartphone addiction and physical activity in Chinese international students in Korea. Journal of Behavioral Addictions, 4(3), 200–205. Ko, C., Yen, J., Yen, C., Lin, H., & Yang, M. (2007). Factors predictive for incidence and remission of internet addiction in young adolescents: A prospective study.
4.3. Limitations and future directions Several limitations should be considered when interpreting the findings of the present study. First, this study was cross-sectional designed, so no causality can be inferred. Future research could apply the longitudinal or experimental designs to determine the causal hypothesis in the current study. Second, the measures were based on self-report, further studies should make efforts to collect data from multiple informants (e.g., peers, parents, or teachers) to confirm our findings. Third, it is important and necessary to explore whether the exacerbating effect of perceived social support in the relation between sensation seeking and smartphone addiction would exist in other technologies or products that allow for individual communication, for example, social networking sites. Fourth, the present study was conducted among middle school students, thus, these results should not be generalized in other samples. Further studies can benefit from examining these findings in other groups such as young adults. 133
Personality and Individual Differences 130 (2018) 129–134
P. Wang et al.
Seo, D. G., Park, Y., Kim, M. K., & Park, J. (2016). Mobile phone dependency and its impacts on adolescents' social and academic behaviors. Computers in Human Behavior, 63, 282–292. Steinberg, L., Albert, D., Cauffman, E., Banich, M., Graham, S., & Woolard, J. (2008). Age differences in sensation seeking and impulsivity as indexed by behavior and selfreport: Evidence for a dual systems model. Developmental Psychology, 44, 1764–1778. Thomee, S., Harenstam, A., & Hagberg, M. (2011). Mobile phone use and stress, sleep disturbances, and symptoms of depression among young adults - A prospective cohort study. BMC Public Health, 11(66), 1–11. Townsend, A. M. (2000). Life in the real-time city: Mobile telephones and urban metabolism. Journal of Urban Technology, 7, 85–104. Velezmoro, R., Lacefield, K., & Roberti, J. W. (2010). Perceived stress, sensation seeking, and college students' abuse of the internet. Computers in Human Behavior, 26(6), 1526–1530. Wan, C.-S., & Chiou, W.-B. (2006). Psychological motives and online games addiction: A test of flow theory and humanistic needs theory for Taiwanese adolescents. Cyberpsychology & Behavior, 9(3), 317–324. Wang, J., Chen, J., Yang, L., & Gao, S. (2013). Meta-analysis of the relationship between sensation seeking and internet addiction. Advances in Psychological Science, 21, 1720–1730. Wang, P., Zhao, M., Wang, X., Xie, X., Wang, Y., & Lei, L. (2017). Peer relationship and adolescent smartphone addiction: The mediating role of self-esteem and the moderating role of the need to belong. Journal of Behavioral Addictions, 6(4), 708–717. Wu, A. M. S., Li, J., Lau, J. T. F., Mo, P. K. H., & Lau, M. M. C. (2016). Potential impact of internet addiction and protective psychosocial factors onto depression among Hong Kong Chinese adolescents – Direct, mediation and moderation effects. Comprehensive Psychiatry, 70, 41–52. Zimet, G. D., Dahlem, N. W., Zimet, S. G., & Farley, G. K. (1988). The multidimensional scale of perceived social support. Journal of Personality Assessment, 52(1), 30–41. Zuckerman, M. (1994). Behavioral expressions and biosocial bases of sensation seeking. New York: Cambridge Press. Zuckerman, M. (1996). The psychobiological model for impulsive unsocialized sensation seeking: A comparative approach. Neuropsychobiology, 34, 125–129. Zuckerman, M., & Kuhlman, D. M. (2000). Personality and risk-taking: Common biosocial factors. Journal of Personality, 68(6), 999–1029.
Cyberpsychology & Behavior, 10, 545–551. Kwon, M., Kim, D., Cho, H., & Yang, S. (2013). The smartphone addiction scale: Development and validation of a short version for adolescents. PLoS One, 8(12), e83558. Lavin, M., Marvin, K., McLarney, A., Nola, V., & Scott, L. (1998). Sensation seeking and collegiate vulnerability to internet dependence. CyberPsychology and Behavior, 2, 425–430. Lee, C., & Lee, S. J. (2017). Prevalence and predictors of smartphone addiction proneness among Korean adolescents. Children and Youth Services Review, 77, 10–17. Lee, Y. K., Chang, C. T., Lin, Y., & Cheng, Z. H. (2014). The dark side of smartphone usage: Psychological traits, compulsive behavior and technostress. Computers in Human Behavior, 31, 373–383. Lemola, S., Perkinson-Gloor, N., Brand, S., Dewald-Kaufmann, J. F., & Grob, A. (2015). Adolescents' electronic media use at night, sleep disturbance, and depressive symptoms in the smartphone age. Journal of Youth and Adolescence, 44, 405–418. Lepp, A., Barkley, J. E., & Karpinski, A. C. (2014). The relationship between cell phone use, academic performance, anxiety, and satisfaction with life in college students. Computers in Human Behavior, 31, 343–350. Li, X., Newman, J., Li, D., & Zhang, H. (2016). Temperament and adolescent problematic internet use. Computers in Human Behavior, 60, 342–350. Lin, S. J., & Tsai, C. C. (2001). Sensation seeking and internet dependence of Taiwanese high school adolescents. Computers in Human Behavior, 18, 411–426. Little, R. J., & Rubin, D. B. (2002). Statistical analysis with missing data (2nd ed.). New Jersey: Wiley. Lopez-Fernandez, O., Honrubia-Serrano, L., Freixa-Blanxart, M., & Gibson, W. (2014). Prevalence of problematic mobile phone use in British adolescents. CyberPsychology, Behavior, and Social Networking, 17(2), 91–98. Petersen, A. C., Compas, B. E., Brooks-Gunn, J., Stemmler, M., Ey, S., & Grant, K. E. (1993). Depression in adolescence. American Psychologist, 48(2), 155–168. Radloff, L. S. (1977). The CES-D scale. Applied Psychological Measurement, 1(3), 385–401. Roberts, J. A., Pullig, C., & Manolis, C. (2015). I need my smartphone: A hierarchical model of personality and cell-phone addiction. Personality and Individual Differences, 79, 13–19. Samaha, M., & Hawi, N. S. (2016). Relationships among smartphone addiction, stress, academic performance, and satisfaction with life. Computers in Human Behavior, 57, 321–325.
134
Contents lists available at ScienceDirect
Personality and Individual Differences journal homepage: www.elsevier.com/locate/paid
The exacerbating role of perceived social support and the “buffering” role of depression in the relation between sensation seeking and adolescent smartphone addiction
T
⁎
Pengcheng Wanga, Li Leia, , Xingchao Wanga, Jia Niea, Xiaoyuan Chua, Shuining Jinb a
Department of Psychology, The Center of Internet + Social Psychology, Renmin University of China, No. 59 Zhongguancun Street, Haidian District, Beijing 100872, China b School of Basic Medical Sciences & Nursing, Chengdu University, Shiling Town, Chengdu 610106, China
A R T I C LE I N FO
A B S T R A C T
Keywords: Adolescents Sensation seeking Perceived social support Depression Smartphone addiction
The present study examined the relation between sensation seeking and adolescent smartphone addiction, and tested both the moderating roles of perceived social support and depression on the relation between sensation seeking and smartphone addiction among Chinese adolescents. Six hundred and fifty-five adolescents completed measures regarding sensation seeking, smartphone addiction, perceived social support, and depression. The findings indicated that sensation seeking was positively significant associated with adolescent smartphone addiction. Contrary to the social support buffering hypothesis, the results indicated that perceived social support exacerbated the relation between sensation seeking and adolescent smartphone addiction. To be specific, for adolescents with a low level of perceived social support, the relation between sensation seeking and smartphone was positively significant, and for adolescents with a high level of perceived social support, the relation between sensation seeking and smartphone addiction was even stronger. Moreover, depression moderated the relation between sensation seeking and adolescent smartphone addiction. Specifically, for adolescents with a low level of depression, the relation between sensation seeking and smartphone addiction was positively significant, while for adolescents with a high level of depression, the relation between sensation seeking and smartphone addiction was not significant.
1. Introduction Smartphones have become an important part of many adolescents' daily lives in recent years. Smartphone addiction, as a relatively new form of behavioral addiction, is emerging as a big concern in the last decade (Bian & Leung, 2015; Lee & Lee, 2017). Smartphone addiction is a phenomenon characterized by withdrawal symptoms, tolerance, dependence, and social problems (Choi et al., 2015), it has received increasing academic attention because of its negative impacts on adolescent development. For example, previous studies indicate that smartphone addiction can negatively affect adolescents' sleep quality, emotional status, academic performance, peer relationship, and physical health (Kim, Kim, & Jee, 2015; Lemola, Perkinson-Gloor, Brand, Dewald-Kaufmann, & Grob, 2015; Lepp, Barkley, & Karpinski, 2014; Samaha & Hawi, 2016; Seo, Park, Kim, & Park, 2016; Thomee, Harenstam, & Hagberg, 2011; Wang et al., 2017). Given the adverse influences of smartphone addiction on adolescents, it is of both
theoretical and empirical importance to uncover the potential factors that can lead to adolescent smartphone addiction. Although some risk factors for adolescent smartphone addiction have been recognized (Bae, 2015; Bian & Leung, 2015; Gökçearslan, Mumcu, Haşlaman, & Çevik, 2016; Hong, Chiu, & Huang, 2012; Lee, Chang, Lin, & Cheng, 2014; Lee & Lee, 2017; Roberts, Pullig, & Manolis, 2015), however, little research has explored the relation between sensation seeking and smartphone addiction. Sensation seeking has long been documented as one of the most confirmed predictive personal traits of problem and addictive behaviors (Jonah, 1997; Zuckerman & Kuhlman, 2000). For example, previous research demonstrates that sensation seeking is positively related to alcohol abuse, smoking, casual sexual behaviors, and dangerous driving (Jonah, 1997; Zuckerman & Kuhlman, 2000). While some studies find that sensation seeking is positively related to Internet addiction, however, the relation between sensation seeking and Internet addiction has been less consistent (Lavin, Marvin, McLarney, Nola, & Scott, 1998; Lin & Tsai, 2001). One
⁎ Corresponding author at: Department of Psychology, The Center of Internet + Social Psychology, Renmin University of China, No. 59 Zhongguancun Street, Haidian District, Beijing 100872, China. E-mail address: [email protected] (L. Lei).
https://doi.org/10.1016/j.paid.2018.04.009 Received 12 January 2018; Received in revised form 29 March 2018; Accepted 6 April 2018 0191-8869/ © 2018 Elsevier Ltd. All rights reserved.
Personality and Individual Differences 130 (2018) 129–134
P. Wang et al.
possible reason is that there are certain key moderators causing the variation in the relation between sensation seeking and Internet addiction. Given that smartphones are based on the Internet, it is possible that the relation between sensation seeking and smartphone addiction would vary as a function of certain moderators. Confirming the relation between sensation seeking and smartphone addiction, and the moderators of this relation would be critical to advance our understanding of adolescent smartphone addiction and to enlighten effective prevention and intervention as well. In addition, adolescents have poorer impulsive control compared with adults and they use smartphones to manage their emotions and social status (Lopez-Fernandez, Honrubia-Serrano, Freixa-Blanxart, & Gibson, 2014), which makes them at the most risk of getting addicted to smartphones. However, the majority of the studies regarding smartphone addiction are focused on young adults such as college students, it is necessary and important to focus more on adolescent smartphone addiction (Lopez-Fernandez et al., 2014). To fill these gaps, the present study utilized a sample of Chinese adolescents to examine the effect of sensation seeking on adolescent smartphone addiction, and explored whether perceived social support and depression would moderate the relation between sensation seeking and adolescent smartphone addiction.
As the social support buffering hypothesis suggests (Cohen & Wills, 1985), perceived social support can buffer people from the impacts of some risk factors. Given that individuals with a high level of sensation seeking are more likely to seek varied, novel, complex, and intense sensations or experiences, even if they need to take physical, social, legal, and financial risks for the sake of such experience (Zuckerman, 1994). It is reasonable to regard sensation seeking as a risk factor in some cases. Therefore, it is theoretically possible that perceived social support could be a buffer in the relation between sensation seeking and adolescent smartphone addiction. Empirical research supports this notion. For example, a recent study found that family support moderated the relation between depression and Internet addiction (Wu, Li, Lau, Mo, & Lau, 2016). To our knowledge, no prior has examined the moderating effect of perceived social support in the relation between sensation seeking and adolescent smartphone addiction. Based on the social support buffering hypothesis and the empirical grounds reviewed above, we put forward the second hypothesis in the present study:
1.1. Sensation seeking and adolescent smartphone addiction
1.3. The moderating role of depression
Sensation seeking is a common characteristic among adolescents (Cauffman et al., 2010; Steinberg et al., 2008; Zuckerman, 1994). According to the sensation seeking theory, sensation seeking is “a trait by the seeking of varied, novel, complex, and intense sensations and experiences, and the willingness to take physical, social, legal, and financial risks for the sake of such experience” (Zuckerman, 1994). Sensation seeking is a biological trait, which is an important predictor of human behavior (Zuckerman, 1996; Zuckerman & Kuhlman, 2000). For individuals with a high level of sensation seeking, they have lower baseline arousal, which may drive them to participate in highly arousing experiences. Therefore, it is possible that sensation seeking can be related to smartphone addiction. Empirical research is in support of this notion. For example, some cross-sectional studies found that adolescents with a high level of sensation seeking are at more risk of getting addicted to the Internet (Li, Newman, Li, & Zhang, 2016; Lin & Tsai, 2001; Velezmoro, Lacefield, & Roberti, 2010), even after controlling for other predictive factors such as anxiety, depressive symptoms, and lack of assertiveness (Dalbudak et al., 2015). Besides, a longitudinal study found that sensation seeking was a powerful predictor of Internet addiction (Ko, Yen, Yen, Lin, & Yang, 2007). Moreover, a meta-analysis indicated that there was a moderate and positive relation between sensation seeking and Internet addiction (Wang, Chen, Yang, & Gao, 2013). To our knowledge, little research has directly explored the relation between sensation seeking and adolescent smartphone addiction before. Based on the literature reviewed above, we put up the first hypothesis in the present study:
The inconsistency of outcomes may also come from individual traits that moderate (i.e., exacerbate or buffer) the influence of sensation seeking on adolescent smartphone addiction, for instance, depression. Depression is regarded as a constellation of negative emotions and behaviors, including feelings of worthlessness and loneliness, worrying about doing bad things, crying, and feeling the need to be perfect (Petersen et al., 1993). According to the cognitive-behavioral model of pathological Internet use (Davis, 2001), people with negative mental status are more likely to get addicted to the Internet, given that smartphone is based on the Internet, it is theoretically possible that depression could predict smartphone addiction. Empirical research is in line with this notion. For example, a study found that depression was positively related to smartphone addiction among college students, even after controlling for some confounders such as demographics, personality traits, and academic variables (Boumosleh & Jaalouk, 2017). Moreover, depression may exacerbate the relation sensation seeking and adolescent smartphone addiction. According to the diathesis-stress framework, some personal traits such as depression can exacerbate the relation between some negative factors and their influences on people. Empirical research has supported this notion. For example, it is found that depression can moderate the relation between denial (a type of coping strategy) and Internet addiction (Chou et al., 2015). To our knowledge, no prior research has explored the direct relationship between sensation seeking and adolescent smartphone addiction, nor the moderating effect of depression on the relation between sensation seeking and adolescent smartphone addiction. Based on the literature reviewed above, we put up the third hypothesis in the present study:
Hypothesis 2. Perceived social support will moderate the relation sensation seeking and adolescent smartphone addiction. To be specific, the relation between sensation seeking and smartphone addiction will be stronger for adolescents with a low level of perceived social support.
Hypothesis 1. Sensation seeking will predict adolescent smartphone addiction in general. To be specific, a high level of sensation seeking will predict a high level of adolescent smartphone addiction.
Hypothesis 3. Depression would positively predict adolescent smartphone addiction. Moreover, depression would moderate the relation between sensation seeking and adolescent smartphone addiction. To be specific, the relation between sensation seeking and smartphone addiction would be stronger for adolescents with a high level of depression.
1.2. The moderating role of perceived social support While these studies mentioned above are in support of the notion that sensation seeking could predict smartphone addiction, a few studies indicate that sensation seeking as an explanation for Internet addiction are inconsistent (Ko et al., 2007; Lavin et al., 1998; Li et al., 2016; Lin & Tsai, 2001; Velezmoro et al., 2010; Wan & Chiou, 2006; Wang et al., 2013). Therefore, it is possible that sensation seeking could predict smartphone addiction in general, but the effect would vary as a function of certain variables (e.g., perceived social support, depression).
1.4. The present study Taken together, the main purposes of the present study were as follows. First, this study explored whether sensation seeking would be positively associated with adolescent smartphone addiction. Second, 130
Personality and Individual Differences 130 (2018) 129–134
P. Wang et al.
this study examined whether perceived social support would moderate the relation between sensation seeking and adolescent smartphone addiction. Finally, the current study examined whether depression would moderate the relation between sensation seeking and adolescent smartphone addiction.
Table 1 Descriptive statistics and correlations of the main study variables.
2. Methods
Variables
M
SD
1
2
3
4
1. 2. 3. 4.
3.05 3.47 5.13 1.43
0.76 0.87 0.95 0.32
1 0.19⁎⁎⁎ −0.02 0.14⁎⁎⁎
1 0.00 0.26⁎⁎⁎
1 −0.33⁎⁎⁎
1
SS SA PSS Dep
Note: N=655. SS = sensation seeking, SA = smartphone PSS = perceived social support, and Dep = depression. ⁎⁎⁎ p < 0.001.
2.1. Participants A total of 655 middle school students (55% of the participants were males) participated in our survey. The participants were recruited from two middle schools in Hebei, China. The mean age of the participants was 16.80 years (SD = 0.74, range = 15–19 years). Students completed a survey designed to collect data regarding demographic variables, sensation seeking, smartphone addiction, perceived social support, depression, and some other measurements regarding adolescent development.
addiction,
2.3. Procedure The study was approved by the Institutional Review Board of the first's author's university. Informed consent was obtained from the middle school students and their parents before data collection. Students were invited to participate in the survey in anonymously in the classrooms. Well-trained postgraduate students conducted the survey. The authenticity, independence, and integral of all answers were emphasized to the participants. The participants received a gift as incentives. < 1% of the data were incomplete and the missing data were handled with mean imputation (Little & Rubin, 2002).
2.2. Measures 2.2.1. Sensation seeking Sensation seeking was measured by the Brief Sensation Seeking Scale (BSSS) (Hoyle, Stephenson, Palmgreen, Lorch, & Donohew, 2002), the scale consists of 8 items (e.g., “I would like to explore strange places”). The participants rated each item on a five-point scale from 1 = strongly disagree to 5 = strongly agree, with higher total scores indicating higher levels of sensation seeking. For the current study, the Cronbach α for the BSSS was 0.78.
3. Results 3.1. Preliminary analyses Means, standard deviations, and zero-order correlations for all study variables are presented in Table 1. As expected, adolescents with high levels of sensation seeking were more likely to get addicted to smartphones, and they were more likely to be depressed as well. Adolescents with high levels of perceived social support were less likely to be depressed. Besides, adolescents with high levels of depression were more likely to get addicted to smartphones.
2.2.2. Smartphone addiction Adolescent smartphone addiction was measured by the Smartphone Addiction Scale (SAS) (Kwon, Kim, Cho, & Yang, 2013). The scale consists of 10 items (e.g., “Missing planned work due to smartphone use”). The participants rated each item on a six-point scale ranging from 1 = strongly disagree to 6 = strongly agree, with higher scores indicating more addicted to smartphones. For the current study, the Cronbach α for the SAS was 0.85.
3.2. Test of the moderation model of perceived social support Hierarchical regression procedures were performed to examine the moderating effects of perceived social support on the relation between sensation seeking and smartphone addiction. All variables were standardized before the examination of the moderating effect. In the hierarchical regression model, the order of entry was as follows. At step 1, the predictor variable (sensation seeking) was entered into the regression. At step 2, the moderator variable (perceived social support) was entered into the regression equation. At step 3, the interaction of sensation seeking and perceived social support was added. As Table 2 shows, sensation seeking was positively associated with smartphone addiction, moreover, there was a significant interaction between sensation seeking and perceived social support, which suggests
2.2.3. Perceived social support Perceived social support was measured by the Multidimensional Scale of Perceived Social Support (MSPSS) (Zimet, Dahlem, Zimet, & Farley, 1988), which consists of 12 items. It measures perceived support from three sources including family (e.g., “I get emotional help and support I need from my family”), friends (e.g., “I can count on my friends when things go wrong”), and significant others (e.g., “There is a special person who is around me when am in need”). Each item was rated on a 7-point scale (1 = strongly disagree, 7 = strongly agree), with higher scores indicating greater perceived social support. In the present study, Cronbach's α for the MSPSS was 0.83.
Table 2 Hierarchical regression analysis predicting adolescent smartphone addiction from sensation seeking and perceived social support.
2.2.4. Depression Depression was measured by the Center for Epidemiological Studies Depression Scale (CES-D, Radloff, 1977), which consists of 20 items. It includes six components: feelings of guilt and worthlessness; depressed mood; feelings of helplessness and hopelessness; psychomotor retardation; loss of appetite; and sleep disturbance. Respondents indicate how often within the last week they experienced the symptoms on a 4point scale (1 = “rarely or none of the time”; 2 = “some or little of the time”; 3 = “occasionally or a moderate amount of time”; 4 = “most or all of the time”). The scores for the 20 items are added, with higher scores representing worse conditions on depression. In the present study, Cronbach's α for the CES-D was 0.89.
Variable
SS PSS SS × PSS Total R2
Smartphone addiction Step 1
Step 2
Step 3
β
β
β
0.19
0.04
⁎⁎⁎
0.19 0.00
⁎⁎⁎
0.04
Note: SS = sensation seeking, PSS = perceived social support. ⁎ p < 0.05. ⁎⁎⁎ p < 0.001. 131
0.20⁎⁎⁎ 0.00 0.08⁎ 0.05
Personality and Individual Differences 130 (2018) 129–134
P. Wang et al.
1 0.8
Low social support
1
High social support
0.8
High depression
0.6
0.4
Smartphone addiction
Smartphone addiction
0.6
Low depression
0.2 0 Low sensation seeking
High sensation seeking
-0.2 -0.4
0.4 0.2 0 Low sensation seeking -0.4
-0.6
-0.6
-0.8
-0.8
-1
-1
Fig. 1. Effects of sensation seeking and perceived social support on smartphone addiction.
High sensation seeking
-0.2
Fig. 2. Effects of sensation seeking and depression on smartphone addiction.
4. Discussion that perceived social support moderated the relation between sensation seeking and adolescent smartphone addiction. For descriptive purposes, we plotted the regression of smartphone addiction on sensation seeking at high and low levels of perceived social support (see Fig. 1). Simple slope tests showed that for adolescents with a low level of perceived social support, high level of sensation seeking was associated with high level of smartphone addiction, bsimple = 0.12, p < 0.05. Surprisingly, for adolescents with a high level of perceived social support, the effect of sensation seeking on smartphone addiction was even stronger, bsimple = 0.28, p < 0.001. Therefore, Hypothesis 1 was partially supported.
Little research has explored the relationship between sensation seeking and adolescent smartphone, and the moderating mechanisms underlying this relationship are largely unknown. The present study examined whether sensation seeking would predict adolescent smartphone addiction and whether this relation was moderated by perceived social support or depression. The results indicated that sensation seeking could lead to adolescent smartphone addiction. Moreover, this relation was moderated by perceived social support and depression, separately. However, contrary to our hypothesis, the results showed that perceived social support exacerbated, instead of buffered, the relation between sensation seeking and adolescent smartphone. Meanwhile, depression buffered the relation between sensation seeking and adolescent smartphone addiction statistically. The following sections will discuss each of the study hypotheses.
3.3. Test of the moderation model of depression The same procedures were performed to examine the moderating effect of depression on the relation between sensation seeking and smartphone addiction. The results indicated that depression moderated the influence of sensation seeking on smartphone addiction. (See Table 3.) For descriptive purposes, we plotted the regression of smartphone addiction on sensation seeking at high and low levels of depression (see Fig. 2). Simple tests showed that for adolescents with a low level of depression, high level of sensation seeking was associated with high level of smartphone addiction, bsimple = 0.27, p < 0.001. However, for adolescents with a high level of depression, the relation between sensation seeking and smartphone addiction was no longer significant, bsimple = 0.08, p > 0.05. Therefore, Hypothesis 2 was partially supported.
4.1. Sensation seeking as a protective factor of adolescent smartphone addiction Although some prior studies have explored the relationship between sensation seeking and Internet addiction (Li et al., 2016; Lin & Tsai, 2001; Velezmoro et al., 2010), little research has ever explored the relation between sensation seeking and adolescent smartphone addiction. The present study is the first to document the predictive role of sensation seeking on adolescent smartphone addiction. This finding goes beyond the previous studies by uncovering that sensation seeking, as a personality trait (Zuckerman, 1994), could lead to adolescent smartphone addiction. This could advance our understanding of what kind of people are more likely to get addicted to information technologies products such as smartphones, which is important and necessary for inspiring detections, interventions, and preventions aimed at reducing people's overusing of these products. 4.1 The moderating role of perceived social support. As expected, the results showed that perceived social support could indeed moderate the relation between sensation seeking and smartphone addiction. However, the results reveal that, contrary to our assumption, perceived social exacerbated, instead of buffering the relation between sensation seeking and adolescent smartphone addiction. To be specific, the relation between sensation seeking and smartphone addiction was stronger among adolescents with a high level of perceived social support compared with adolescents with a low level of perceived social support. This finding was not in line with the social support buffering hypotheses and previous empirical evidence (Cohen & Wills, 1985; Jaffee, 2017), which suggest that social support could buffer individuals from the negative influences of some risk factors. Therefore, it is important to analyze why this finding makes sense.
Table 3 Hierarchical regression analysis predicting adolescent smartphone addiction from sensation seeking and depression. Variable
SS Dep SS × Dep Total R2
Smartphone addiction Step 1
Step 2
Step 3
β
β
β
⁎⁎⁎
⁎⁎⁎
0.19
0.16 0.24⁎⁎⁎
0.04
0.09
0.17⁎⁎⁎ 0.26⁎⁎⁎ −0.09⁎⁎ 0.10
Note: SS = sensation seeking, Dep = depression. ⁎⁎ p < 0.01. ⁎⁎⁎ p < 0.001. 132
Personality and Individual Differences 130 (2018) 129–134
P. Wang et al.
5. Conclusion
Given that the basic purpose of mobile phone use is to allow people to communicate with each other (Choi et al., 2015; Townsend, 2000), and for adolescents with a high level of perceived social support, they are more likely to regard others as warm and reliable. Therefore, when they want to seek some novel experiences or just want to do something, it is more likely that they will use the smartphone to discuss or share the activities with their friends, families, and intimate others, which can lead to their overuse, dependency, or even addiction to smartphones. For adolescents with a low level of perceived social support, because they may not regard being with other as encouraging, when they want to do something, it is less likely that they would act alone instead of doing it with the others. This finding challenges the view that social support invariably buffers people from the impacts of adverse factors, and it also inspires future researchers to distinguish the moderating effect of social support in different domains.
In summary, the present study reveals that sensation seeking is a risk factor in adolescent smartphone addiction. Moderating analyses indicate that the perceived social support exacerbates the relation between sensation seeking and smartphone addiction, with the relation being stronger for adolescents with a high level of perceived social support. Moreover, depression can “buffer” the relation between sensation seeking and adolescent smartphone addiction. To be specific, for adolescents with a low level of depression, the relation between sensation seeking and smartphone addiction is positively significant. While for adolescents with a high level of depression, the relation between sensation and smartphone is no longer significant. Conflict of interest The authors report no conflicts of interest.
4.2. The moderating role of depression
Acknowledgement
The third aim of the current study was to examine the moderating role of depression in the relation between sensation seeking and adolescent smartphone addiction. The result indicated that depression did moderate the relation between sensation seeking and adolescent, however, contrary to our hypothesis, the result showed that depression buffered the relation between sensation seeking and adolescent smartphone addiction, statistically. To be specific, for adolescents with a high level of depression, the relation between sensation seeking and adolescent smartphone was not significant. Meanwhile, for adolescents with a low level of depression, the relation between sensation seeking and smartphone addiction was positively significant. One explanation is that, depression is a robust predictor of adolescent smartphone addiction, as previous studies demonstrate that depression is most related to Internet addiction (Carli et al., 2013) and depression could predict Internet addiction even after controlling for a variety of confounding factors (Boumosleh & Jaalouk, 2017). Therefore, for adolescents with a high level of depression, they are likely to get addicted to smartp014nes regardless of whether they have a high or low level of sensation seeking. Overall, the present study found that sensation seeking as a personal trait, could predict adolescent smartphone addiction in general. Surprisingly and reasonably, the present study indicated that perceived social support could exacerbate the relation between sensation seeking and adolescent smartphone addiction, and depression can “buffer” the relation between sensation seeking and adolescent smartphone addiction. All these findings can help deepen our understanding of the relation between individual characteristics and technologies overuse such as smartphone addiction, which can lay the groundwork for future research or practices that aimed at detecting and reducing technologies overuses in the digital era.
The present study was supported by the Key Research Institute in Humanities and Social Sciences of the Ministry of Education (Academy of Psychology and Behavior, Tianjin Normal University) (14JJD190005), the Key Project of Social Science Fund of Beijing, China (15SHA005), the Outstanding Innovative Talents Cultivation Funded Programs 2017 of Renmin University of China. References Bae, S. M. (2015). 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. School Psychology International, 36(5), 513–531. Bian, M., & Leung, L. (2015). Linking loneliness, shyness, smartphone addiction symptoms, and patterns of smartphone use to social capital. Social Science Computer Review, 33(1), 61–79. Boumosleh, J. M., & Jaalouk, D. (2017). Depression, anxiety, and smartphone addiction in university students - A cross-sectional study. PLoS One, 12(8), e0182239. Carli, V., Durkee, T., Wasserman, D., Hadlaczky, G., Despalins, R., Kramarz, E., et al. (2013). The association between pathological internet use and comorbid psychopathology: A systematic review. Psychopathology, 46(1), 1–13. Cauffman, E., Shulman, E. P., Steinberg, L., Claus, E., Banich, M. T., Graham, S., et al. (2010). Age differences in affective decision making as indexed by performance on the Iowa Gambling Task. Developmental Psychology, 46, 193–207. Choi, S. W., Kim, D. J., Choi, J. S., Ahn, H., Choi, E. J., Song, W. Y., ... Youn, H. (2015). Comparison of risk and protective factors associated with smartphone addiction and internet addiction. Journal of Behavioral Addictions, 4(4), 308–314. Chou, W.-P., Ko, C.-H., Kaufman, E. A., Crowell, S. E., Hsiao, R. C., Wang, P.-W., ... Yen, C.-F. (2015). Association of stress coping strategies with internet addiction in college students: The moderating effect of depression. Comprehensive Psychiatry, 62, 27–33. Cohen, S., & Wills, T. A. (1985). Stress, social support, and the buffering hypothesis. Psychological Bulletin, 98(2), 310–357. Dalbudak, E., Evren, C., Aldemir, S., Taymur, I., Evren, B., & Topcu, M. (2015). The impact of sensation seeking on the relationship between attention-deficit/hyperactivity symptoms and severity of internet addiction risk. Psychiatry Research, 228(1), 156–161. Davis, R. A. (2001). A cognitive-behavioral model of pathological internet use. Computers in Human Behavior, 17(2), 187–195. Gökçearslan, Ş., Mumcu, F. K., Haşlaman, T., & Çevik, Y. D. (2016). Modelling smartphone addiction: The role of smartphone usage, self-regulation, general self-efficacy and cyberloafing in university students. Computers in Human Behavior, 63, 639–649. Hong, F. Y., Chiu, S. I., & Huang, D. H. (2012). A model of the relationship between psychological characteristics, smartphone addiction and use of mobile phones by Taiwanese female university students. Computers in Human Behavior, 28(6), 2152–2159. Hoyle, R. H., Stephenson, M. T., Palmgreen, P., Lorch, E. P., & Donohew, R. L. (2002). Reliability and validity of a brief measure of sensation seeking. Personality and Individual Differences, 32(3), 401–414. Jaffee, S. R. (2017). Child maltreatment and risk for psychopathology in childhood and adulthood. Annual Review of Clinical Psychology, 13(1), 525–551. Jonah, B. A. (1997). Sensation seeking and risky driving: A review and synthesis of the literature. Accident Analysis & Prevention, 29(5), 651–665. Kim, S. E., Kim, J. W., & Jee, Y. S. (2015). Relationship between smartphone addiction and physical activity in Chinese international students in Korea. Journal of Behavioral Addictions, 4(3), 200–205. Ko, C., Yen, J., Yen, C., Lin, H., & Yang, M. (2007). Factors predictive for incidence and remission of internet addiction in young adolescents: A prospective study.
4.3. Limitations and future directions Several limitations should be considered when interpreting the findings of the present study. First, this study was cross-sectional designed, so no causality can be inferred. Future research could apply the longitudinal or experimental designs to determine the causal hypothesis in the current study. Second, the measures were based on self-report, further studies should make efforts to collect data from multiple informants (e.g., peers, parents, or teachers) to confirm our findings. Third, it is important and necessary to explore whether the exacerbating effect of perceived social support in the relation between sensation seeking and smartphone addiction would exist in other technologies or products that allow for individual communication, for example, social networking sites. Fourth, the present study was conducted among middle school students, thus, these results should not be generalized in other samples. Further studies can benefit from examining these findings in other groups such as young adults. 133
Personality and Individual Differences 130 (2018) 129–134
P. Wang et al.
Seo, D. G., Park, Y., Kim, M. K., & Park, J. (2016). Mobile phone dependency and its impacts on adolescents' social and academic behaviors. Computers in Human Behavior, 63, 282–292. Steinberg, L., Albert, D., Cauffman, E., Banich, M., Graham, S., & Woolard, J. (2008). Age differences in sensation seeking and impulsivity as indexed by behavior and selfreport: Evidence for a dual systems model. Developmental Psychology, 44, 1764–1778. Thomee, S., Harenstam, A., & Hagberg, M. (2011). Mobile phone use and stress, sleep disturbances, and symptoms of depression among young adults - A prospective cohort study. BMC Public Health, 11(66), 1–11. Townsend, A. M. (2000). Life in the real-time city: Mobile telephones and urban metabolism. Journal of Urban Technology, 7, 85–104. Velezmoro, R., Lacefield, K., & Roberti, J. W. (2010). Perceived stress, sensation seeking, and college students' abuse of the internet. Computers in Human Behavior, 26(6), 1526–1530. Wan, C.-S., & Chiou, W.-B. (2006). Psychological motives and online games addiction: A test of flow theory and humanistic needs theory for Taiwanese adolescents. Cyberpsychology & Behavior, 9(3), 317–324. Wang, J., Chen, J., Yang, L., & Gao, S. (2013). Meta-analysis of the relationship between sensation seeking and internet addiction. Advances in Psychological Science, 21, 1720–1730. Wang, P., Zhao, M., Wang, X., Xie, X., Wang, Y., & Lei, L. (2017). Peer relationship and adolescent smartphone addiction: The mediating role of self-esteem and the moderating role of the need to belong. Journal of Behavioral Addictions, 6(4), 708–717. Wu, A. M. S., Li, J., Lau, J. T. F., Mo, P. K. H., & Lau, M. M. C. (2016). Potential impact of internet addiction and protective psychosocial factors onto depression among Hong Kong Chinese adolescents – Direct, mediation and moderation effects. Comprehensive Psychiatry, 70, 41–52. Zimet, G. D., Dahlem, N. W., Zimet, S. G., & Farley, G. K. (1988). The multidimensional scale of perceived social support. Journal of Personality Assessment, 52(1), 30–41. Zuckerman, M. (1994). Behavioral expressions and biosocial bases of sensation seeking. New York: Cambridge Press. Zuckerman, M. (1996). The psychobiological model for impulsive unsocialized sensation seeking: A comparative approach. Neuropsychobiology, 34, 125–129. Zuckerman, M., & Kuhlman, D. M. (2000). Personality and risk-taking: Common biosocial factors. Journal of Personality, 68(6), 999–1029.
Cyberpsychology & Behavior, 10, 545–551. Kwon, M., Kim, D., Cho, H., & Yang, S. (2013). The smartphone addiction scale: Development and validation of a short version for adolescents. PLoS One, 8(12), e83558. Lavin, M., Marvin, K., McLarney, A., Nola, V., & Scott, L. (1998). Sensation seeking and collegiate vulnerability to internet dependence. CyberPsychology and Behavior, 2, 425–430. Lee, C., & Lee, S. J. (2017). Prevalence and predictors of smartphone addiction proneness among Korean adolescents. Children and Youth Services Review, 77, 10–17. Lee, Y. K., Chang, C. T., Lin, Y., & Cheng, Z. H. (2014). The dark side of smartphone usage: Psychological traits, compulsive behavior and technostress. Computers in Human Behavior, 31, 373–383. Lemola, S., Perkinson-Gloor, N., Brand, S., Dewald-Kaufmann, J. F., & Grob, A. (2015). Adolescents' electronic media use at night, sleep disturbance, and depressive symptoms in the smartphone age. Journal of Youth and Adolescence, 44, 405–418. Lepp, A., Barkley, J. E., & Karpinski, A. C. (2014). The relationship between cell phone use, academic performance, anxiety, and satisfaction with life in college students. Computers in Human Behavior, 31, 343–350. Li, X., Newman, J., Li, D., & Zhang, H. (2016). Temperament and adolescent problematic internet use. Computers in Human Behavior, 60, 342–350. Lin, S. J., & Tsai, C. C. (2001). Sensation seeking and internet dependence of Taiwanese high school adolescents. Computers in Human Behavior, 18, 411–426. Little, R. J., & Rubin, D. B. (2002). Statistical analysis with missing data (2nd ed.). New Jersey: Wiley. Lopez-Fernandez, O., Honrubia-Serrano, L., Freixa-Blanxart, M., & Gibson, W. (2014). Prevalence of problematic mobile phone use in British adolescents. CyberPsychology, Behavior, and Social Networking, 17(2), 91–98. Petersen, A. C., Compas, B. E., Brooks-Gunn, J., Stemmler, M., Ey, S., & Grant, K. E. (1993). Depression in adolescence. American Psychologist, 48(2), 155–168. Radloff, L. S. (1977). The CES-D scale. Applied Psychological Measurement, 1(3), 385–401. Roberts, J. A., Pullig, C., & Manolis, C. (2015). I need my smartphone: A hierarchical model of personality and cell-phone addiction. Personality and Individual Differences, 79, 13–19. Samaha, M., & Hawi, N. S. (2016). Relationships among smartphone addiction, stress, academic performance, and satisfaction with life. Computers in Human Behavior, 57, 321–325.
134