The Emotional Factors Influencing Mobile Phone Dependency of College Students and Gender Difference

Ⅰ. Introduction

The rapid advancement in technology has made many devices, and a mobile phone is one of them (Nishad and Rana, 2016). Mobile phone is a useful tool to provide a lot of functions and pleasures in everyday life. Almost 95 percent of Americans own cell phones and 77 percent own smartphones(Shoukat, 2019). According to the Gallup Report, the number of smartphone subscribers in Korea was 93 percent out of total population in the country(GallupReport, 2018). Almost every Korean college student has a mobile phone by 98.8 percent(Ha, 2015).

Mobile phones make out lives easier but on the other hands it binds us. Too much dependency makes us "Mobile addictive"(Shoukat, 2019). Mobile phone dependence means not only obsessing with using mobile phone without a clear purpose, but also giving difficulties in the relationship with people around(Kim, 2013; Kim and Im, 2016). Block (2008) expressed concerns about problematic use of mobile phones such as behavioral or technological addiction and the effects on social and personal characteristics. There are indications that younger people have an even higher likelihood of using short message service(SMS) function and other features, resulting in increased exposure to emotional and social problems(Bianchi & Phillips, 2005; Seo et al., 2016). Mobile phone dependency negatively predicted attention and positively predicted depression affected social relationship with friends and both Korean language arts and mathematics achievement(Seo et al., 2016). Mobile phone addiction not only represents physical effects but also psychological and academic effects. Sleep deficit, anxiety, stress and depression are related to mobile phone addiction (Shoukat, 2019). According to Hakoma and Hakoyama(2011), female college students have high level of attachment to mobile phone than male students, indicating that females tend to maintain social relationships through mobile phone usage. On the other hand, there are researches to argue that boys tend to use more mobile phone than girls for playing games, shopping, or watching movies(Bisen and Deshpande, 2016). Jun(2019) found that self-esteem is positively related with mobile phone dependency and peer-alienation is negatively related with it. Woo(2013) found that parenting abuse and neglect affected on children's mobile phone dependency. In the study of Hur et al.(2015), depression aggression, attention, social withdrawal, and self-identity were found as the significant predictors of mobile phone dependency in adolescent. Even though there are studies to find out the gender difference of mobile phone dependency, there is no study about gender difference of emotional factors affecting mobile phone dependency of college students.

In this context, even though mobile phone is used widely in every aspect of life, there is a need to educate students to have strong control in their mind not to be depended psychologically. From the education perspective, there should be intervention programs or strategies to make educational strategies for decreasing mobile phone dependency. There are few researches exploring the relationship between mobile phone dependency and positive emotions for decreasing mobile phone dependency.

The purpose of this study was to investigate the relationship between positive emotions, negative emotions, and mobile phone dependency of college students and to identify the influencing factors on mobile phone dependence and its difference by gender.

Ⅱ. Research Method

1. Subjects

This study used data from the Korea Children 's Youth Panel Survey(KCYPS) conducted by the Korea Youth Policy Institute. KCYPS was conducted in 2010 to identify the growth and developmental patterns of children and adolescents. 7,071 samples were sampled from 16 provinces including first year students, fourth grade students, and first year students of middle school in multi-level cluster sampling method. In this study, I selected 1st year college students in 2016 who were first year middle school students in 2010. Among the 2,351 samples extracted, the last 1,220 questionnaires were used for the final analysis, except for the missing questionnaires in the questionnaire response related to this study. The subjects weree 575 male students(47.1%) and 645 female students(52.9%). 375(30.7%) were 2-year junior college students and 845 (69.3%) were 4-year college students. 273 (22.4%) students were from the national and public universities, and 947 (77.6%) were from the private universities.

<Table 1>

General characteristics of the subjects

2. Research Instruments

1) Positive emotions: Self-esteem, Ego-resilience, Self-identity, Life satisfaction

As positive emotions in this study, 4 variables were chosen from the section of social-emotional development in KCYPS database. Self-esteem was used by Rogenberg(1965) with 10 items. Ego-resilience is composed of 14 items by Block & Kreman(1996) and revised by Sun-kyung Yoo and Haw-won Shim(2002). Self-identity consists of 8 items. Life satisfaction is 3 items by Shin-young Kim et al.(2006). All four scales consisted of a 4-point Likert scale(not at all=1, no =2, yes=3, and very much=4). The reversed items were reversely coded, so the higher the sum of the items, the higher the variables. Cronbach's alpha for self-esteem, ego-resilience, self-identity, and life satisfaction are .843, .826, .722, and .781, respectively.

2) Negative emotions: Attention deficit, Aggression, Depression, Social Withdrawal

As negative emotions in this study, 4 variables were chosen from the section of social-emotional development in KCYPS database. Attention deficit and Aggression were extracted from the scale by Bong-whan Jo & Kyung-hee Im(2003) and each variable has 7 and 6 itmes respectively. Depression consists of 9 items from Simple Mental Diagnostic Test by Kwang-il Kim et al.(1984). Social withdrawal is 5 items by Sun-hee Kim and Kyung-yeon Kim(1998). All four scales consisted of a 4-point Likert scale(not at all=1, no =2, yes=3, and very much=4). The reversed items were reversely coded, so the higher the sum of the items, the higher the variables. Cronbach's alpha for attention deficit, aggression, depression and social withdrawal are .797, .807, .829 and .894, respectively.

3) Mobile phone dependency

Mobile phone dependency is a dependent variable of this study, utilized the 7th survey data in 2016. It is composed of 7 items made with 4-point Likert scale (not at all=1, no =2, yes=3, and very much=4) by Siyoung Lee et al.(2002).

The larger the sum of the items, the higher the mobile phone dependency. The reliability of the instrument(Cronbach's alpha) was .845. The items in this study were as shown in <Table 2>.

<Table 2>

Items of mobile phone dependency

Ⅲ. Research Results

1. Descriptive Statistics of Main Variables

Mobile phone dependency was high as 2.46 out of 4 points. The mean of positive emotion (M=2.83) was higher than that of negative emotion (M=1.96). In positive emotions, self-esteem of 2.95 was highest, followed by life satisfaction of 2.85, ego-resilience of 2.84, and self-identity of 2.67. In negative emotions, social depression of 2.20 was highest, follwed by attention deficit of 2.05, depression of 1.81, and aggression of 1.78 (<Table 3>).

<Table 3>

Descriptive statistics of variables

2. Difference in Mobile Phone Dependency by Gender

As a result of analyzing the differences of mobile phone dependency according to the students' gender, there was a significant difference in gender (<Table 4>). The dependence of female students (M = 2.60) on mobile phone was higher than male students (M = 2.31).

<Table 4>

Gender difference in mobile phone dependency

3. Correlation between Main Variables

Mobile phone dependency showed a significant positive correlation with attention deficit, depression, aggression, and social withdrawal, and negatively correlated with self-esteem, ego-resilience, self-identity, and life satisfaction (p<0.01). Among them, the correlation with self-identity was the highest (r = -.31.3), and the correlation with life satisfaction was the lowest (r = -.163) (<Table 5>).

<Table 5>

Correlation among variables

4. Factors Affecting College Students' Mobile Dependency and Gender Difference

In order to examine the effect of positive emotions (Self-esteem, Ego-resilience, Self-identity, Life satisfaction) and negative emotions (Attention deficit, Aggression, Depression, Social withdrawal) on mobile phone dependency, stepwise multiple regression analysis was performed(<Table 6>). First, the level of explanations of self-identity, aggression and depression was 13.3% (r2=0.133), and this regression model was statistically significant (F=132.071, p<0.001). In order to grasp the relative influence, the standardization coefficients were found to be self-identity (-0.231), aggression (0.135), and depression (0.098). It can be seen that the higher the level of aggression and depression, and the lower the degree of self-identity, the more influence on mobile phone dependency. Tolerance and VIF statistics were checked to identify multicollinearity problems. As a result, the Tolerance value was less than 1.0, the VIF value was less than 10, and the Durbin-Watson value was 1.876, which was close to 2, so that it did not have the problem of multicollinearity.

<Table 6>

Factors affecting the increase of mobile phone dependency of college students by multiple regression analysis

In the case of male students, the level of explanations of depression and self-identity was 7.93% (r2=0.079), and this regression model was statistically significant (F=25.676, p<0.001). The standardization coefficients of depression(.166) and self-identity(-.166) were the same in impacting on the mobile phone dependency and depression was the first factor in the regression model. In the case of female students, the level of explanations of self-identity and aggression was 15.3% (r2=0.153), and this regression model was statistically significant (F=93.005, p<0.001). The standardization coefficients of self-identity(-.316) and aggression(.176) were calculated and self-identity was the first factor in the regression model.

Ⅳ. Discussion and Conclusions

The purpose of this study was to investigate the negative or positive emotional factors affecting mobile phone dependency of college students in South Korea based on the data of 1,220 students in the 7th year of KCYPS and its difference by gender. Self-identity, depression, and aggression affected the students' mobile phone dependency. The high level of self-identity and the lower level of depression and aggression showed low level of mobile phone dependency. In the male students, the depression was the first factor impacting on mobile phone dependency while in the female students, self-identity was important and secondly, aggression impacted on the mobile phone dependency.

As expected, mobile phone dependency showed a significant positive correlation with negative emotional factors (attention deficit, depression, aggression, and social withdrawal), and negatively correlated with positive emotional factors (self-esteem, ego-resilience, self-identity, and life satisfaction). This results give a lesson that in order to decrease mobile phone dependency of college students, positive emotional conditions are supporting their control in using mobile phone and their decision when to use or how to use it.

Out of positive or negative emotional factors, self-identity give highest effect on mobile phone dependency, followed by aggression and depression. The relationship of depression with mobile phone dependency has been studied in many studies (Seo et al., 2016; Kim, 2013; Kim & Im, 2014; Nishad & Rana, 2016; Shoukat, 2019).

In the case of male students, depression was the first factor in the regresssion model while self-identity was for female students. The self-identity was the common factor both in male and female students. Without self-identity, depression was an important factor in explaining male students' mobile phone dependency but aggression was an important factor in the case of female students. Therefore, it can be explained that in the case of male student, depression and loneliness make them depend on the mobile phone while aggression emotion of female students makes them depend on the mobile phone. In the case of women, more social media are used to maintain social relations and text messages are used as channels of social relations than men. The first factor was self-identity to female students. So using mobile phone is related to playing the self and making the self through mobile phone to female students while avoiding depression and loneliness is related to using mobile phone to male students. Self-identity is a positive emotion while depression is a negative emotion.

This result is consistent with the result of gender difference of mobile phone dependency by ANOVA as shown in Table 2. The girls' mobile dependency was higher than boys, which is consistent with the results of Hakoma and Hakoyama (2011), which argues that female students tend to maintain social relationship more than male students. Many researches revealed that female students have higher mobile dependency than boys (Kim, 2013; Kim and Im, 2014). In the study of Seo et al. (2016), mobile phone dependency of female students affected social relationship with friends but it was not the case of male students. This means that female students tend to have social relationship through mobile phone and mobile phone has a meaning as a channel to maintain social relationship for female students. As Bianchi and Phillips (2005) point out, younger female students use short message(SEM) service. In Korea, KakaoTalk is a popular SEM application to communicate with people in a easy way.

In this context, there is an implication for educational intervention for college students. Self-identity is considered to be a stable and coherent concept of oneself. According to the Webster dictionary, it is the quality that makes a person different from others (http://www.merriam-webster.com). In other words, students who know who they are, who they should be, and in which they are different from others, could have a power to control when or how to use mobile phones. Therefore, long-term strategy to make our students use mobile phone without depending much on it, should be related to education in their developmental stage of self-identity such as child-bearing of parents. In addition, the short-term intervention program in colleges for students should be provided to explore who they are or how to have strong self-identify. As college students prepare their careers, the educational programs or counseling programs to decrease mobile phone dependency could be related to career guidance programs.

Acknowledgments

Funding for this paper was provided by Namseoul University.

References

• Bianchi, A, and Phillips, JG, (2005), Psychological predictors of problem mobile phone use, Cyber Psychology & Behavior, 8, p39-51. [https://doi.org/10.1089/cpb.2005.8.39]
• Bisen, S, and Deshpande, Y, (2016), An analytical study of smart phone addiction among engineering students: a gender difference, The International Journal of Indian Psychology, 4(1), p70-83.
• Block, J, and Kremen, AM, (1996), IQ and ego-resiliency: Conceptual and empirical connections and separateness, Journal of Personality and Social Psychology, 70, p349-361. [https://doi.org/10.1037/0022-3514.70.2.349]
• Block, JJ, (2008), Issues for DSM-V: internet addiction, American Journal Psychiatry, 165, p306-307. [https://doi.org/10.1176/appi.ajp.2007.07101556]
• Cho, BH, and Im, KH, (2003), A study on the development and validation of self-report type rating scale for children's emotional and behavioral problems, Korean Psychological Counseling and Psychotherapy, 15(4), p729-746.
• GallupReport, (2018), Gallup Korea Daily Opinion, http://www.gallup.co.kr/gallupdb/reportContent.asp?seqNo=943 on February 14.
• Ha, HS, (2015), Media usage behavior of college students, KISTI STAT Report.
• Hakoma, M., and Hakoyama, S, (2011), The impact of cell phone use on social networking and development among college students, American Association of Behavioral and Social Sciences Journal, 15, p120.
• Hur, JY, Sim, YB, Cho, EK, and Chun, JW, (2015), Influence of mental health on mobile phone dependency in adolescent, Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology, 4(4), p261-269.
• Jun, SK, (2019), The mediating effect of self-esteem between college students' peer alienation and mobile phone dependency, Humantities Dilman, forthcoming.
• Kim, BN, (2013), The mediating effect of depression on the relationship between self-control of college students and smartphone addiction, Korean Family Welfare, 30, p49-81.
• Kim, EY, and Im, SI, (2014), The recognition of the youth about the symptoms of smartphone overuse, Youth Research, 21(6), p255-279.
• Kim, GI, Kim, JH, and Won, HT, (1984), Practical guideline for psychiatric diagnostic test, Seoul, Central Aptitude Test.
• Kim, SH, and Kim, KY, (1998), Developing behavior problem scale for children and adolescents, Journal of Korean Home Management, 27(4), p348-357.
• Kim, SY, et al., (2006), Survey of youth development indicators I, Seoul, Korea Youth Development Institute.
• Lee, SY, Kim, HS, Na, EY, Lee, SY, Kim, SN, and Bae, JH, (2002), A study on the usage and influence of youth mobile phone, Samsung Life Insurance Foundation Social Mental Health Institute.
• Nishad, P, and Rana, A.S, (2016), Impact of mobile phone addiction among college going students: a literature review, Advance Research Journal of Social Science, 7(1), p111-115.
• Rosenberg, Morris, Society and the Adolescent Self-Image, Princeton University Press, (1965), Print. [https://doi.org/10.1515/9781400876136]
• Seo, DG, Park, Y, Kim, MK, and Park, J, (2016), Mobile phone dependency and its impacts on adolescents' social and academic behaviors, Computers in Human Behavior, 63, p282-292. [https://doi.org/10.1016/j.chb.2016.05.026]
• Shoukat, S, (2019), Cell phone addiction and psychological and physiological health in adolescents, EXCLI Journal, 18, p47-50.
• Yoo, SK, and Shim, HW, (2002), Exploring the psychological protection elements of adolescents with adaptive flexibility, Educational Psychology Research, 16(4), p189-206.