Effects of Internet Use on Academic Achievement and

Transcription

Syracuse University
SURFACE
Child and Family Studies - Dissertations
David B. Falk College of Sport and Human
Dynamics
12-2011
E Effects of Internet Use on Academic
Achievement and Behavioral Adjustment among
South Korean Adolescents: Mediating and
Moderating Roles of Parental Factors
Soohyun Kim
Syracuse University
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Kim, Soohyun, "E Effects of Internet Use on Academic Achievement and Behavioral Adjustment among South Korean Adolescents:
Mediating and Moderating Roles of Parental Factors" (2011). Child and Family Studies - Dissertations. Paper 62.
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Abstract
The purpose of this study was to investigate the interrelationships among
adolescent Internet use, parent-adolescent relationships, and academic/ behavioral
adjustment in South Korean families. Despite the significant numbers of Korean
adolescents who use the Internet (98.7% of Korean children between the ages of 6 and
19 years use the Internet) for education, social, and recreational purposes, little is
known about how adolescent Internet use impacts family interactions and youth
outcomes. Most research studies on this subject have been descriptive and have
provided inconsistent findings. To examine the impact of adolescent Internet use on
youth outcomes in Korea, six hundred and nine adolescents (10th and 11th graders) and
their parents were recruited from five high schools in Seoul, Korea. Compared to the
general population in Korea, parents in this study were more educated and from higher
socio-economic status backgrounds. Findings indicated that Korean boys and girls
differed in the ways that they used the Internet. Girls were more likely to use the
Internet to watch online education classes and blog more frequently and longer than
boys, whereas boys were more likely to use the Internet for playing Internet games
than girls. Results indicated that Internet use for educational purposes was associated
with adolescent academic achievement. Social and recreational-Internet use of the
Internet was associated with lower academic achievement. The pathways did not vary
for boys and girls. Parent-child relationships (closeness and conflict) were found to be
vital to youth adjustment and played a significant role in the association between
adolescent Internet use and academic and behavioral outcomes. Future research
studies should investigate how Koreans cope with the influx of this rapidly developing
technology and its impact of family relationships. Additionally, parenting programs
should incorporate strategies about how the Internet can be used as an educational tool
to benefit adolescents.
THE EFFECTS OF INTERNET USE ON ACADEMIC ACHIEVEMENT AND
BEHAVIORAL ADJUSTMENT AMONG SOUTH KOREAN ADOLESCENTS:
MEDIATING AND MODERATING ROLES OF PARENTAL FACTORS
By
Soohyun Kim
B.F.A. Seoul National University, 1992
B.A. Ewah Womans University, 2000
M.A. Drexel University, 2003
DISSERTATION
Submitted in partial fulfillment of the requirement for the degree of Doctor of
Philosophy in Child and Family Studies in the David B. Falk College of Sport and
Human Dynamics
December 2011
Copyright 2011 Soohyun Kim
All Rights Reserved
v
Table of Contents
ABSTRAT
List of Tables ……………………………………………………………………… VIII
List of Figures …………………………………………………………………..
X
CHAPTER 1: INTRODUCTION …………………………………………………. 1
Internet Usage in South Korea ……………………………………………………. 2
Importance of the Study …………………………………………………………..
5
CHAPTER 2: LITERATURE REVIEW …………………………………………
12
Adolescent Internet Use …………………………………………………………. 12
Impact of Internet on Adolescents and Family Relationships ……………………
16
Effects of the Internet Usage on Academic Achievement ……………………….
24
Parent-Child Relationships and Adolescent Outcomes ………………………….
29
Parental Expectations and Adolescents’ Academic Achievement ……………….. 36
CHAPTER 3: THEORETICAL FRAMEWORKS AND PROPOSED CONCEPTUAL
MODELS
Uses and Gratifications Theory …………………………………………………
44
Observational Learning Theory …………………………………………………
46
Informational Processing Theory ……………………………………………….
47
Time Displacement Theory ……………………………………………………..
48
Human Ecology Theory ………………………………………………………..
49
Attachment Theory …………………………………………………………….
54
CHAPTER 4: CONCEPTUALIZATION
vi
Use of the Internet ………………………………………………………………
57
Educational Use of the Internet …………………………………………………
60
Social Use of the Internet ………………………………………………………
60
Recreational Use of the Internet ………………………………………………..
60
Parent-Adolescent Conflict …………………………………………………….
61
Parent-Adolescent Closeness …………………………………………………..
62
Parental Expectation ……………………………………………………………
62
Adolescent Behavioral Problems ………………………………………………
63
Academic Achievement ………………………………………………………..
63
CHPATER 5: RESEARCH QUESTIONS AND HYPOTHESES ……………..
64
CHAPTER 6: METHODOLOGY
Population ……………………………………………..……………….…………
70
Procedure …………………………………………………………………………. 72
Participants ……………………………………………………………………….. 74
Measurements ……………………………………………………………………. 76
Adolescent Internet Use ………………………………………………………. 76
Parent-Adolescent Relationships ………………………………………………
77
Parental Cultural Expectations …………………………………………………
80
Adolescent Outcomes ……………………………………………………….…. 81
CHAPTER 7: ANALYTIC STRATEGY ……………………………………..
CHAPTER 8: RESULTS
83
vii
Addressing Issues of Distribution and Missing Data …………………………
89
Demographic Characteristics of Participants …………………………………
90
Descriptive Analyses on the Nature of Adolescents’ Internet Use ……………
93
Factor Analysis and Reliability of Constructs ………………………………….. 99
Testing Hypotheses
Hypothesis 1 …………………………………………………………………. 112
Hypothesis 2 …………………………………………………………………. 116
Hypothesis 3 …………………………………………………………………. 123
Hypothesis 4 …………………………………………………………………. 141
CHAPTER 9: DISCUSSION ……………………………………………………
Findings from the Nature of Internet Use ………………………………………
147
148
Findings from the Direct Models ………………………………………………. 154
Findings from the Indirect Models …………………………………………….. 157
CHAPTER 10: THEORETICAL CONTRIBUTIONS,
LIMITATIONS, AND
FUTURE RESEARCH ……………………………………………………….. 165
References …………………………………………………….…………………
170
Appendices ………………………………………………………………………
241
viii
List of Tables
Table 1. Number and percentage of demographics by participants ………………
92
Table 2. Skewness and Kurtosis of demographic variables ………………………
93
Table 3a. Number and types of computers at home ………………………………
94
Table 3b. The nature of adolescent Internet use …………………………………..
95
Table 4a. Descriptive statistics on the number of times adolescents access the Internet
for various educational, social, and recreational activities during weekdays and
weekends …………………………………………………………………………. 96
Table 4b. Descriptive statistics on the intensity of adolescents’ Internet use for
educational, social, and recreational activities on weekdays and weekends
………………………………………………………………………..………….
96
Table 4c. The Frequencies for the Numbers of Functional Use of the Internet Use
(N=609) …….…………………………………………………………………… 98-99
Table 5a. Rotated Component Matrix – Frequency of adolescents’ Internet use … 101
Table 5b. Rotated Component Matrix – Intensity of adolescents Internet use …… 102
Table 6a. Rotated Component Matrix –mother-adolescent closeness ……………. 103
Table 6b. Rotated Component Matrix – father-adolescent closeness ……………
103
Table 7a. Rotated Component Matrix – Parent-adolescent conflict between mothers
and adolescents …………………………………………………………………… 105
Table 7b. Rotated Component Matrix – Parent-adolescent conflict between fathers and
adolescents …………………………………………………………………..…… 105
Table 8. Rotated Component Matrix – Parental cultural academic expectations ….106
Table 9a. Cronbach’s alphas of constructs …………………………..…………… 107
Table 9b. Skewness and Kurtosis of Independent Variables ……………………… 108
Table 10a. Rotated Component Matrix – Adolescent behavioral problems ……
109
Table 10b. Cronbach’s alphas of constructs ……………………………………… 111
Table 10c. Means and SD’s of Adolescents Behavioral Problems ………………
111
ix
Table 11. Descriptive Statistics for the Adolescent Academic Achievement ……
112
Table 12a. The Results of Yates’ Chi-Square Test - Gender Differences/Similarities in
the nature of Internet Use ………………………………………………………
114
Table 12b. Multivariate analysis of variance – Types of adolescent Internet us…. 116
Table 13a. Significance of indirect effects of links between the type of adolescent
Internet use and academic achievement through father-adolescent relationships … 125
Table 13b. Significance of indirect effects of links between the type of adolescent
Internet use and academic achievement through mother-adolescent relationships…127
Internet use and internalizing behaviors through father-adolescent relationships…. 131
Internet use and internalizing behaviors through mother-adolescent relationships…133
Internet use and externalizing behaviors through father-adolescent relationships….137
Internet use and externalizing behaviors through mother-adolescent relationships...139
x
List of Figures
Figure 1a. Direct effects between the types of adolescent Internet use and academic
achievement ………………………………………………………………………. 118
Figure 1b. Gender differences in the direct relationship between the types of
adolescent Internet use and academic achievement ……………………………….. 119
Figure 2a. Direct links between the types of adolescent Internet use and internalizing
problem behaviors ……………………………………………………………..…..120
Figure 2b. Gender differences on the direct relationship between the types of
adolescent Internet use and internalizing problem behaviors …………………….121
Figure 3a. Direct effect between the types of adolescent Internet use and externalizing
problem behaviors …………………………………………………………….….122
Figure 3b. Gender differences on the direct relationships between types of adolescent
Internet use and externalizing problem behaviors ………………………………..123
Figure 4a. Indirect effects linking the types of adolescent Internet use and academic
achievement through father-adolescent relationships ……………………………124
Figure 4b. Indirect effect of adolescent Internet use on academic achievement through
mother-adolescent relationships ………………………………………………… 126
Figure 4c. The indirect relationship between adolescent Internet use, father-adolescent
relationship, and academic achievement by youth gender ……………………… 128
Figure 4d. The indirect relationship among Internet use, mother-adolescent
relationship and academic achievement by youth gender ………………………… 129
Figure 5a. Indirect effect of Internet use through father-adolescent relationships on
internalizing behaviors …………………………………………………………130
Figure 5b. Indirect effect of types of Internet use on internalizing behaviors through
mother-adolescent relationships ……………………………………………………132
xi
Figure 5c. The indirect relationship between Internet use, mother-adolescent
relationship and internalizing behaviors by youth gender ……………………
134
Figure 6a. Indirect effects of Internet use on externalizing behaviors through fatheradolescent relationships …………………………………………………………
135
Figure 6b. Indirect effect of types of adolescent Internet use on externalizing
behaviors through mother-adolescent relationships ……………………………….138
Figure 6c. Link between Internet use, father-adolescent relationship and externalizing
behaviors by youth gender …………………………………………………………140
Figure 6d. Gender differences on the indirect relationship among Internet use, motheradolescent relationship and externalizing behaviors ……………………………….141
Figure 7a. Link between adolescent Internet use, father-adolescent relationships, and
academic achievement by fathers’ academic expectations ……………………….. 142
Figure 7b. Link between adolescent Internet use, mother-adolescent relationships, and
academic achievement by mothers’ academic expectations ……………………….143
Figure 8a. Different effects of parental expectation (PE) among Internet use, fatheradolescent relationships, and internalizing behaviors ……………………………..144
internalizing behaviors by mothers’ parental expectations …………………… …145
externalizing behaviors by fathers’ academic expectations ………………………..146
Figure 9b. Different effects of parental expectation (PE) among Internet use, motheradolescent relationships, and externalizing behaviors ……………………………..147
xii
ACKNOWLEDGEMENTS
I wish to thank those whose inspiration and support enabled me to complete this
dissertation. Throughout the dissertation process, my faculty advisor, Dr.
Krishnakumar, helped me to clarify my ideas and offered encouragement. I am also
grateful to my committee members: Dr. Narine, Dr. Ramadoss, Dr. Roopranine, Dr.
Jung, Dr. Kowk, and Dr. Krishnakumar. They motivated me, guided me, and provided
helpful comments on my dissertation.
I thank all of the study participants for their time and effort. Megan Lape, my friend,
generously read my dissertation and provided feedback.
My mother, Bonghee Kim, and old brother, Hyungoo Kim, gave unflagging support
and encouragement while I completed this dissertation. Throughout my life, my
parents have given me assistance, pray, and love.
1
Introduction
Increasing numbers of people worldwide are using the Internet (1,574,313,184
as of December 31, 2008). It has been recently reported that adolescents today spend a
significant amount of time on the Internet for multiple purposes (Ito, Horst, Bittanti,
Boyd, Herr-Stephenson, Lange, et al., 2008). Reports from the National Internet
Development Agency of Korea (2007) indicate that 98.7% of Korean children
between the ages of 6 and 19 years use the Internet. Studies have indicated that the use
of the Internet can be helpful to adolescents to complete schoolwork more effectively
and efficiently (Borzekowski & Robinson, 2005; Jackson, et al., 2006). However,
other investigators have suggested direct negative effects of Internet use on academic
outcomes (Choi, 2007; Sirgy, Lee, & Bae, 2006). Excessive Internet use has been
associated with problems with maintaining daily routines, school performance, and
family relationships (Rickert, 2001).
Much of the literature on the impact of adolescent Internet use has been
descriptive (Valkenburg & Peter, 2007), and investigations on the impact of adolescent
Internet use on family and youth outcomes have provided inconsistent findings (Lee &
Chae, 2007). Considering the current status of research area related the impact of
Internet use, the impacts of Internet use are called for. Therefore, the purpose of this
study is to contribute to the field of social science by investigating associations among
2
the prevalence of adolescent Internet use, parent-adolescent relationships, and
academic/ behavioral adjustment of adolescents in South Korean families.
In addition to the parent-adolescent relationship as mediators between
adolescent Internet use and academic achievement, the moderating role of a child’s
gender in explaining these relationships will also be examined. Adolescents’ use of the
Internet varies by gender (Lenhart, Madden, & Hitlin, 2005) and hence it is important
to test conceptual models linking adolescents’ Internet use, parent-adolescent
relationships, and academic outcomes by adolescent and parent gender.
Since it is well known for Koreans to possess high expectations and aspirations
for educational achievement (Chung, 1991), another goal of this study is to investigate
how the effects of parental expectation functions as a unique cultural variable among
the dynamics between Internet use and adolescent outcomes in Korean families.
Internet Usage in South Korea
Internet use among Asians has risen dramatically over the last decade (406.1%;
Internet World Stats, 2008). Based on current statistics, 34,820,000 of South Korean
households have access to the Internet, which is 70.7% of the population with an
astounding 82.9% growth in the period between 2000 and 2008 (Internet World Stats,
2008). The International Telecoms Union has reported that South Korea leads the
world in terms of the percentage of households with high-speed broadband access
3
(Cellular News, 2008). Based on a summary report from the National Internet
Development Agency of Korea (2007), the rate of internet usage for populations age
six years and over is 77.1%; consisting of 81.6% males, and 71.5% females. Korea
Communications Commission reported that nearly all high school and junior high
school graduates in South Korea are Internet users. Also, 99.4% of Internet users
access the Internet at least once a week, spending an average of 13.7 hours weekly on
the Internet (Korea Times, 2008, September 31).
South Korean youth use Internet-related technologies to play games, instant
message (IM), blog, download videos and music, social network socially and shop, all
of which assist them in constructing their own social communities (Jin & Chee, 2008).
For many South Korean youths, participating in online activities or communicating
through online communities is a part of mainstream everyday life (Huh, 2008). The
disparity in Internet access in South Korea in terms of educational settings and gender
have narrowed (Park, 2001); however, according to the international surveys by the
AMD Global Consumer Advisory Board (2003), Internet usage is still different
dependent on the age, education, income level, region, and gender of a user. The
national survey also showed that more men (74.4%) use the Internet than women
(62%). Internet usage stands at around 70% for urban inhabitants, while only 46.2% of
people who live in rural areas (CNET News, 2004, August 11) utilize the internet.
4
Over the past two decades, the South Korean government has strongly promoted
the establishment of a nationwide Internet network (National Internet Development
Agency of Korea, 2006), which contributed to Korea becoming one of the most wired
countries in the world and making the Korean Internet culture the barometer for other
countries to track. About 90% of Korean homes are connected to VDSL, which is very
high bitrate digital subscriber line. By 2005, Korea was the first country to complete
the conversion from dial-up to broadband and in 2006 it became the first country to
achieve over 50% broadband saturation consisting of he world’s cheapest and fastest
broadband service. Additionally in 2005, 96.8% of South Korean mobile phones had
internet access. Furthermore, 42% of the population maintain an individual blog site,
over half of the population have cell phones, and 25% of the total population
participates in multiplayer online gaming (Ahonen & O' Reilly, 2007). Also, Korea
was the first country in the world to provide high-speed Internet access for every
primary, junior, and high school (New York Times, 2006, April 2).
In South Korea, more adolescents and young adults use the Internet than any
other age group. Children under 18 years of age make up 25.1% (12,090) of the total
population in South Korea (Korean Statistical Information Service, 2004). By 2007,
98.7% of Korean children between the ages of 6 and 19 years of age used the Internet
(National Internet Development Agency of Korea, 2007). Based on a 2003 survey,
5
over 91% of those using the Internet, use it in their homes and almost half of them
have used it for more than 3 years. One third of them use it one to two hours a day,
another third use it thirty minutes to one hour a day, and 16% use the Internet for two
to three hours a day. Over 40% of them go online during the evening, which is
between 8 p.m. to 12 a.m., and another 40% use it from 12 p.m. to 4 p.m. The primary
reasons given for Internet use are for entertainment or recreation (59.3 %),
information seeking (55.5%), stress reduction (46.3%), and socialization (40.7%). The
breakdowns of activities on the Internet are: gaming (52.8%), searching for
information (34%), and socializing (64.9%), such as chatting, e-mailing, interacting
with web communities, and blogging. They use e-mails in order to keep in touch with
friends (50.6%), chat (31.2%), and send messages when they are uncomfortable
speaking face to face (31.2%). The world's fastest Internet connection with over 90%
Internet proliferation in Korean homes creates an ideal environment for playing online
games, which a lot of South Korean kids do.
Importance of the Study
The Internet seems to influence quality of life through individuals’ social,
consumer, leisure, economic, and community well-being (Cairncross, 1997; DiMaggio,
Hargitti, Neuman, & Robinson, 2001; Israel, 2000). The Internet’s influence stems
from the ease and convenience it provides to access many benefits in the context of
6
many life domains (e.g., social life, work life, leisure life, and education life). Some
authors have suggested that the Internet has positive effects on academic achievement
through the use of educational software, and the provision of useful information
(Borzekowski & Robinson, 2005; Jackson, von Eye, Biocca, Barbatsis, Zhao, &
Fitzgerald, 2006); others suggest that the Internet provides positive effects on
socialization as it stimulates the closeness of existing interpersonal relationships by
reducing restrictions of time and location (Lenhart, Madden, & Hitlin, 2005; Lenhart,
Rainie, & Lewis, 2001). Yet other studies suggest that the Internet can have direct
negative effects (Choi, 2007; Sirgy, Lee, & Bae, 2006), such as psychological
problems including social isolation, depression, loneliness, and difficulties with time
management as a result of excessive Internet use (Brenner, 1997; Kraut, Patterson,
Lundmark, Kiesler, Mukhopadhyay, & Scherlis, 1998; Young, & Rodgers, 1998).
Excessive use of the Internet may bring on Internet Addiction Disorder, which
includes problems with daily routines, school performance, and family relationships
(Rickert, 2001).
The importance of this study is follows: First, the Internet today is pervasive in
the lives of individuals, institutions, and societies especially in South Korea. The last
few decades have witnessed a dramatic increase in the use of the Internet and an
unprecedented proliferation of computer-based technology. Computer technologies
7
and the Internet bring social changes in modern society. Since computers have
become a common instrument of daily living for a vast proportion of our society, the
Internet has a significant influence on quality of life (Israel, 2000). Statistical research
tell us that Internet users in the world numbered 16 million in 1996, and increased to
500 million by 2001 (Castells, 2001). For example, almost nine out of 10 American
teens use the Internet, up from seven in 2000 (PEW Internet and American Life
Project, 2007a). However, as stated in above, South Korea is one of the fastest
growing countries in Internet use.
Second, adolescents are more involved in Internet activities than adults. Among
Korean teens, 99.6% of them use computers and 97.8% use the Internet (Dong-A Il
Bo, 2005, February 9). Teens spend less time online than do adults due to a variety of
reasons, such as school and after-school schedule, and sharing computers with others.
However, they are more involved in the communicative aspects of the Internet than
adults (Jupiter Communications, 2000a; Packel & Rainie, 2001). For example, the
PEW Internet and American Life Project (2007a, 2007b, 2007c) revealed that teens far
exceed adults in the intensity of using the Internet, such as instant messaging (74% of
teen users as opposed to 44% of adult users), chat-rooms (55% to 26%), and gaming
(66% to 34%; Lenhart, Rainie, & Lewis, 2001). Another survey reported that teens
8
spend more time on the Internet each week than they do watching television (Reuters,
2003).
Third, adolescents are more vulnerable than adults to the negative impacts of
the Internet world (Jonson-Reid, Williams, & Webster, 2001; Otto, Greenstein,
Johnson, & Friedman, 1992). Since they are immature, both physically and
psychologically, they may develop more serious complications than other age groups
regarding the negative impact of the Internet world (Christensen, Orzack, Babington,
& Patsdaughter, 2001; Oh, 2005). Teens may be trapped in their own cyber world,
suffer from psychological pains, and finally destroy their own personal and social
networks due to Internet addiction or excessive Internet use (Jonson-Reid, Williams,
& Webster, 2001; Otto, Greenstein, Johnson, & Friedman, 1992). Internet addiction or
excessive Internet use among adolescents varies across nations with prevalence rates
of 7.5% in Taiwan (Yen, Yen, Chen, Chen, & Ko, 2007) to 1.1% in North Cyprus
(Bayraktar & Gün, 2007) to 1.6% in South Korea (Kim, Ryu, Chon, Yeun, Choi, et al.,
2006). Other challenges associated with excessive usage of the Internet include
lowered concentration, lack of sleep, poor school attendance and performance, vision
problems and a wide range of behavioral problems (Block, 2008; Choi, 2007). In
addition, young adolescents are at high risk of being approached by online predators
since they are relatively new to online activities, actively seeking attention, isolated,
9
easily tricked by adults, and confused regarding their sexual identity (Wolak,
Finkelhor, Mitchell, & Ybarra, 2008). Although they become more interested in
sexuality (Ponton, & Judice, 2004), they are innocent about the sexual issues that get
youth into trouble online (Wolak, Finkelhor, Mitchell, & Ybarra, 2008). Between
2000 and 2005, youth Internet users experienced aggressive sexual solicitations at a
higher rate than adult users (Mitchell, Finkelhor, & Wolak, 2007). For example, the
N-JOV study found that 99% of victims of Internet-initiated sex crimes involved
adolescents between the ages of 13 to 17 years of age (Wolak, Finkelhor, & Mitchell,
2004). In addition, about one third (32.7%) of adolescent Internet users are exposed to
inappropriate sexual content (Korean Educational Development Institute, 2003).
In South Korea there is a growing fear that children and adolescents are
becoming addicted to the Internet: 14.4% of school children reported that they spend 4
hours or more online each day. They also reported that they had developed stiff wrists
and heard sounds from online games even when off line (PRI's The World, 2008). A
2005 government-led study found that half a million South Koreans are clinically
addicted to the Internet. Since the average Korean high school student spends about
twenty-three hours each week on gaming (Kim, 2007), up to 30% of South Korean
children under 18 are at risk of Internet addiction (Silverberg, 2007). According to the
government’s 2006 data, approximately 2.1% (210,000 children ages 6 to 19) are
10
estimated to be Internet addicts that are in need of treatment (Choi, 2007); about 80%
of them may need psychotropic medications, and about 22% may require
hospitalization (Ahn, 2007).
In order to deal with the consequences of the proliferation of the world’s fastest
Internet connection, South Korea has instituted numerous counseling and treatment
programs, along with holding the first International Symposium on Internet Addiction
(International Herald Tribune, 2008, August 4). South Korea has trained 1,043
counselors and enlisted over 190 hospitals and treatment centers to help with these
concerns (Ahn, 2007), and preventive measures have been introduced into primary
and secondary schools (Ju, 2007). Now the Korean government is working on new
rules to control the excessive use of the Internet, as well as the dissemination of false
information on the Web, under a new law entitled the Cyber Defamation Law
(International Herald Tribune, 2008, August 4).
Fourth, in as much as the Internet’s extensive trend is anticipated to continue, it
is necessary to consider the impact and influence of Internet use on families. Families,
as one of society’s primary socializing agents, may provide relatively unique insights
about how the Internet is used and understood. Although the lives of adolescents
outside of their families are increasing, the socializing effect of family is crucial
during adolescence because adolescents project themselves into the world through
11
family interactions (Tallman, Marotz-Baden, & Pindas, 1983). There is no doubt that
parents are the primary agents of socialization for adolescents (Grusec & Davidov,
2007). Although growing peer influence and achievement of independence increases
for adolescents, parental factors continue to have a significant influence on human
development (Campbell, 1969) and the vast majority of young adults continue to rely
on their parents for emotional support and advice (Maccoby & Martin, 1983; Merz,
Schuengel, & Schulze, 2008).
Finally, the dramatic increase in the use of the Internet has stimulated research
on its impact on our everyday lives. Scholars have studied the relationship of new
technologies on interpersonal communication and relationships (Baym, Zhang, & Lin,
2004; Cooper, & Sportolari, 1997; Joinson, 2001; Nie, 2001; Nie, Hillygus, & Erbring,
2002; Tidwell & Walther, 2002), psychological well-being, as well as mental health
(LaRose, Eastin, Gregg, 2001; Shaw & Gant, 2002), the impacts of video games
(Aarsand, 2007; Tüzün, Yilmaz-Soylu, Karakus, Inal, & Kizilkaya, 2009; Willoughby,
2008), and as new learning devices (Attewell, & Battle, 1999; Hedges,
Konstantopoulos, & Thoreson, 2000; Rompaey, Roe, & Struys, 2002; Shute, &
Miksad 1997). However, the existing literature on the impact of computer
technologies and the Internet within the context of family relationships is very limited
(Hughes & Hans, 2001; Lee & Chae, 2007; Mesch, 2006; Watt & White, 1999).
12
Considering the dominant presence of these technologies at home, a lack of study on
the role of Internet use on family relationships is surprising (Mesch, 2006).
Literature Review
Adolescent Internet Use
Recent statistics indicate that adolescents today spend a great deal of their time
on the Internet for communication, educational, and entertainment purposes (Lenhart,
Madden, & Hitlin, 2005; Korean Educational Development Institute, 2003; Packel &
Rainie, 2001). Not only do children gain knowledge and information on the Internet,
they also engage with their friends in social conversation and participate in cyber
communities (Ito, Horst, Bittanti, Boyd, Herr-Stephenson, Lange, et al., 2008). Hence,
adolescents’ socialization today occurs through interactions with people from both the
real and virtual worlds (McQuail, 2005). Since the Internet allows youngsters to
become more open to experimentation and social exploration (Ito et al., 2008), the
Internet can be considered an important tool in adolescent socialization (Krcmar &
Strizhakova, 2007).
In the 1990’s, the Internet was primarily used for entertainment and information
gathering (Valkenburg, & Soeters, 2001), but the function of the Internet for
adolescents has changed considerably. The majority of adolescents today use the
Internet intensely to communicate with existing friends (Gross, 2004) and to make
13
new friends (Wolak, Mitchell, & Finkelhor, 2002) and in addition to their traditional
face-to-face communications (Grinter & Eldridge, 2003; Grinter & Palen, 2002;
Lenhart, Madden, & Hitlin, 2005; Lenhart, Rainie, & Lewis, 2001). Adolescents also
favor instant messaging, text messaging, and social networking websites such as
Facebook and MySpace as modes of communication (Lenhart, Madden, & Hitlin,
2005). Some adolescents prefer digital communication over more traditional ways
such as face to face interaction and telephone calls (Madden & Rainie, 2003),
particularly because these are more convenient, less expensive, and faster to use than
traditional technologies (Bryant, Sanders-Jackson, & Smallwood, 2006; Jin, & Chee,
2008; Lenhart, Madden, & Hitlin, 2005). E-mail and text messaging allow for rapid,
asynchronous communication with others, while instant messaging allows for
synchronous communication among many people at once. Adolescents use instant
messaging more frequently than adults among online populations in both the U.S. and
the U.K. (Lenhart, Rainie, & Lewis, 2001; Livingston & Bober, 2005) and 65% of
total teens population and 75% of teenage online population in the U.S. use instant
messaging regularly (Lenhart, Madden, & Hitlin, 2005).
Some gender differences (although inconsistent) on adolescents’ daily use of
Internet have been reported (Haythronthwaite & Wellman, 2002; Jackson, et al., 2006;
Lenhart, Madden, & Hitlin, 2005). Numerous previous studies have documented that
14
overall, boys use the Internet more frequently, for longer and for a wider variety of
uses than girls do (Gross, 2004; Haythronthwaite & Wellman, 2002; Morahan-Martin,
1998; Subrahmanyam, Greenfield, Kraut, & Gross, 2001). They tend to spend more
time alone online than girls engaged in gaming (Jupiter Communications, 2000b;
Subrahmanyam, et al., 2001; Kraut, Scherlls, Mukhopadhyay, Manning, & Kiesler,
1996).
Girls also report using text messaging more frequently than boys (Jennings &
Wartella, 2004; Lenhart, Madden, & Hitlin, 2005), and are more likely to be involved
in other online social interactions, such as using e-mail, than are boys (Subrahmanyam,
et al., 2001). How email is used also differs by gender. For example, girls tend to use
e-mail to exchange small talk and engage in relationship-building communications
and boys tend to use e-mail for instrumental communication (Subrahmanyam, et al.,
2001). Gender differences in adolescent Internet use have also been reported across
countries. For instance, males have been found to have a greater amount of frequency
and motivation of Internet use with Romanian and Dutch children (Durndell & Haag,
2002; Valkenburg & Soeters, 2001), American college students (Schumacher &
Morahan-Martin, 2001), English secondary school students (Madell & Muncer, 2004),
Israeli school students (Nachmias, Mioduster, & Shelma, 2000), North Cyprus
adolescents (Bayraktar & Gun, 2007), Greek adolescent students (Siomos, Dafouli,
15
Braimiotis, Mouzas, & Angelopoulos, 2008), and Hong Kong adolescents (Ho, & Lee,
2001), as well as Korean adult users (Rhee & Kim, 2004). However, there is no
gender difference in how long adolescents using the Internet, with most of the
participants having been online for more than two years (Gross, 2004).
Despite great concerns over isolation and depression, teens report an optimistic
picture about the social use of the Internet (Lenhart, Rainie, & Lewis, 2001). For
example, Bryant and colleagues (2006) found that online communication technologies
encourage communication with existing friends and families. In addition, some
researchers demonstrated that Internet use is positively related to time spent with
existing friends and family members (Kraut, Kiesler, Boneva, Cummings, Helgeson,
& Crawford, 2002), to the closeness of existing friendships (Valkenburg & Peter,
2007b), and to the well being of adolescents (Kraut et al., 2002; Morgan & Cotton,
2003, Shaw, & Grant, 2002). The Internet Life Report study reported that e-mail and
the Internet have enhanced users’ relationships with their family and friends (PEW
Internet and American Life Project, 2000). Nie, Hillygus, and Erbring (2002) also
provided primary evidence that Internet use does not negatively impact household
time together. A UCLA study found that the Internet provided opportunities for social
gathering and engagement (UCLA Center for Communication Policy, 2003). Between
Internet non-users and Internet users, the amount of weekly time spent sleeping,
16
exercising, participating in clubs/organizations, socializing with friends, and
socializing with household members were similar (UCLA Center for Communication
Policy, 2003). Authors of the PEW study argue that Internet use may create a social
community because Internet users reported more social resources and connections
than non-users. Those who have been online for three years become even more
interpersonally engaged and gain more social support than new users (PEW Internet
and American Life Project, 2000).
Impact of Internet on Adolescents and Family Relationships
There has been continuing debates about the impact of the Internet on family
relationships and human development. Some studies on Internet use have raised
concerns that excessive use of the Internet might bring social isolation, loneliness,
depression, and deterioration of psychological well-being (Brenner, 1997; Lee, Han,
Yang, Daniels, Na, Kee, et al., 2008; National Public Radio, 2000; Nie, 2001; Nie,
Hillygus, & Erbring, 2002; Spada, Langston, Nikcevic, & Moneta, 2008; Van den
Eijnden, Meerkerk, Vermulst, Spijkerman, & Engels, 2008). Other studies indicated
that the Internet leads to substantially greater communication and enhances human
connectivity and sociability (PEW Internet and American Life Project, 2000; UCLA
Center for Communication Policy, 2003). The Internet can also provide opportunities
for family collaboration and communication between parents and children (Kiesler,
17
Zdaniuk, Lundmark, & Kraut, 2000; Orleans & Laney, 2000) and increases their
access to useful information regarding parenting, education, and family health
(Hughes & Hans, 2001). Moderate use of the Internet may also have pro-social effects
on young people by helping them sustain friendships (Subrahmanyam, et al., 2001).
However, the inconsistent findings of some studies do not allow any firm conclusions
to be drawn about the impact of Internet usage on family relationships.
The effects of Internet use on youngsters can also be seen to vary as a function
of the motivation and type of Internet usage (McKenna & Bargh, 2000). For example,
the social use of Internet has been found to be related to depression, while non-social
use of the Internet such as information seeking and entertainment, have not been
found to be related to adolescent depression (Bessière, Kiesler, Kraut, & Boneva,
2008). Therefore, researchers such as Gross (2004), disagree with the early research
assumptions about the negative effects of adolescent Internet use, as Gross reports that
most teenage Internet users are more likely to communicate with existing friends than
with strangers. Supportive relationships with friends can positively contribute to
adolescents’ sense of well-being, self-esteem, connectedness, and ability to cope with
stress (Eisenberg, Sallquist, French, Purwono, Suryanti, & Pidada, 2009; Hartup &
Stevens, 1997). In a national survey, nearly 50% of teenagers reported that the Internet
18
has improved their relationships with their existing friends (Lenhart, Rainie, & Lewis,
2001).
Unfortunately, studies on the association between adolescents’ Internet use and
family relationships are limited. Only some positive association between poor family
relationships and excessive/ problematic use of the Internet or Internet addiction has
been supported by empirical findings. Youths who experience high levels of conflict
with their parents are at risk for some negative outcomes in Internet use. For example,
participants who reported poor emotional bonds with caregivers were more likely to
view pornography online (Ybarra & Mitchell, 2005). Ybarra and Mitchell (2004a)
also found that youths who exhibit offensive behaviors in Cyber space(s) are also
more likely to report poor emotional bonds with their parents than other Internet users.
Adolescents who do not have open communication about their Internet use with their
parents are more likely to be involved in risky Internet behaviors, such as having a
face-to-face meeting with a stranger who they encountered online (Liau, Khoo, & Ang,
2005). Other research found that paternal alienation and adolescents’ insecurity and
mistrust with their fathers contribute significantly to problematic Internet use among
Chinese adolescents. Adolescents’ security and trust in their relationships with their
fathers is negatively related to the negative outcomes of Internet use (Lei & Wu,
2007). Lei and Wu (2007) argued that adolescents who experience a negative
19
relationship with their fathers are more likely to use the Internet excessively to seek
emotional support. In the study of pathological Internet use in South Korea, high
school students with pathological Internet use showed more problems in family
relations than the non- pathological Internet use group (Cho, Kim, Kim, Lee, & Kim,
2008).
The negative effects of Internet use on family communication and closeness can
be explained by the nature of virtual relationships and the displacement hypothesis,
which argues that high frequency of Internet use might be related to the decrease of
family time (Jackson, von Eye, Barbatis, Biocca, Zhao, & Fitzgerald, 2003; Nie,
Simpser, Stepanikova, & Zheung, 2004). The displacement hypothesis argues that
computer-mediated communication hinders adolescents’ well being because it
displaces valuable time that could be spent with existing friends (Kraut et al., 1998;
Nie, 2001; Nie, Hillygus, & Erbring, 2002). According to the displacement hypothesis,
individuals have a limited amount time (Huston, Wright, Marquis, & Green, 1999;
Larson & Verma, 1999). If individuals increase the time they spend on a particular
activity, they may make sacrifices in other areas (Neuman, 1991). Therefore, time
spent on online activities may cut other activities such as reading and social
interaction, which are essential to normal development (Kraut et al., 1998; Morgan &
Cotton, 2003; Nie, 2001; Nie, Hillygus, & Erbring, 2002; Weiser, 2001).
20
Online relationships are characterized by some researchers as being of lesser
depth, more superficial, and weaker than typically found in face to face relationships
(Chan & Cheng, 2004; Kraut et al., 1998; Nie, Hillygus, & Erbring, 2002). Scholars
argue that there is a cyberspace that exists apart from everyday life, which is inferior
to real space (Haythronthwaite & Wellman, 2002; Miller & Slater, 2000). Kraut et al.
(1998) also described Internet social relationships as poor and weak and face-to-face
relationships as strong. Therefore, weak and superficial ties of virtual contact on the
Interne may bring experience of loneliness and depression (Ybarra, Alexander, &
Mitchell, 2005). In addition, online communications with strangers and acquaintances
typically provide less social support than offline relationships with family and friends
(Wellman, Salaff, Dimitrova, Garton, Gulia, & Haythornthwaite, 1996). For example,
HomeNet study participants reported that they felt less close to those they
communicated with online compared to those they communicated with face-to-face
(Parks & Roberts, 1998). Chan and Cheng (2004) found that computer-mediated
communication and relationships are less beneficial than traditional off-line
relationships, at least in the early stages. Among teens and adults in the HomeNet
project, greater use of the Internet during the first year of access is associated with
small but significant declines in social involvement as measured by communication
within the family, size of social networks, and feelings of loneliness (Kraut et al.,
21
1996). It may be assumable that having greater online bonds with strangers than close
family- and peer- ties may be problematic.
The Internet Life Report study (National Public Radio, 2000) found that 58% of
Americans spend less time with friends and family due to Internet usage and half of
Americans believe that computers have given people less free time. The Internet and
Society study (Nie & Erbring, 2002) also found that as the number of hours of Internet
use has increased, the time for social activities declined, such as spending time with
friends and family, staying outside of their home for social gathering, and talking to
friends and family members on the telephone. Nie (2001) found a steady decrease in
social interactions with family and friends as individuals engaged in longer Internet
usage sessions. However, other studies have found no significant relationship between
physical social interactions and the length of time individuals spend in Internet use
(Gross, 2004; Kraut et al., 2002; Jackson, et al., 2003; Mesch, 2001, 2003; Sanders,
Field, Diego, & Kaplan, 2000; Wastlund, Norlander, & Archer, 2001).
Length of time may not be as important as the type of Internet use. Research has
demonstrated that the impact of Internet communication on adolescents’ social
relationships is dependent on the way communication is used and the type of activities
in which the individual engages (Lee & Chae, 2007; Subrahmanyam, Kraut,
Greenfield, & Gross, 2000). Some researchers argue that people use the Internet to
22
strengthen their traditional face to face relationships (Kraut, et al., 1998; McKenna &
Bargh, 2000). For example, much of the time adolescents spend alone with computers
is actually used to keep up existing friendships (Gross, 2004; Subrahmanyam, et al.,
2000; Valkenburg & Peter, 2007a) and most online interactions are between people
who also talk on the telephone or meet face-to-face (Miller & Slater, 2000; PEW
Project on the Internet and American Life, 2000; UCLA Center for Communication
Policy, 2003).
Many parents are concerned about the potential harmful effects of Internet use
(Subrahmanyam, et al., 2000). Surveys of parental attitudes about teen Internet use
indicate that parents are insecure about their teens’ Internet use. The majority of
parents (75%) are concerned about the disclosure of personal information and
exposure to sexually explicit images (Clemente, Espinosa, & Vidal, 2008; Turow,
1999), and 57% of parents are concerned about online contact between their children
and strangers (The PEW Internet and American Life Project, 2007a). A study
conducted in Singapore, conducted by Liau, Khoo, and Ang (2005), found that 78% of
parents indicated that their major concern was that their children would be exposed to
pornographic and violent material while using the Internet. In fact, 60% of adolescents
indicated that they have received messages from strangers (PEW Internet and
American Life Project, 2001).
23
Parents, despite these concerns, are willing to purchase home computers and
Internet subscriptions so that their children can have access to educational
opportunities and are prepared for the information age (Buckingham, Scanlon, &
Sefton-Green, 2001; Linvingston, 2003). However, they are disappointed when they
find that their children’s primary online activities include gaming, downloading lyrics
of popular songs and pictures of rock stars, etc., and the potential harmful effects of
Internet use (Subrahmanyam, Kraut, Greenfield, & Gross, 2000). Consequently, there
has been a decrease since 2004 in the number of parents who believe that the Internet
is beneficial for their children (PEW Internet and American Life Project, 2007a).
In part these intergenerational conflicts on Internet usage may be explained by
differences between parental expectation of Internet usage and actual Internet use by
adolescents (Kiesler, Zdaniuk, Lundmark, & Kraut, 2000; Lenhart, Raine, & Lewis,
2001; Turow, 2001). The majority of parents expect their children to use the Internet
for educational purposes (Lenhart, Raine, & Lewis, 2001), while teens prefer to use
the Internet for socializing and entertainment (Lenhart, Madden, & Hitlin, 2005).
Therefore, when parental expectations and adolescents’ use of the Internet contradict,
intergenerational conflicts can increase (Mesch, 2003).
24
Effects of the Internet Usage on Academic Achievement
Over the last couple of decades, personal computers have spread rapidly into
American homes, provoking thoughts that those who do not have access to home
computers may become disadvantaged. According to the National survey, over 70%
of households having children aged three to seven possesses a home computer (U.S.
Census Bureau, 2005). However, large disparities in computer ownership by race and
family income remain. Many government and non-governmental organizations are
trying to bridge this digital divide across nations and between households. The U.S.
Congress has made it a national priority to provide all American children with access
to computers at school. Congress enacted the Goals 2000, i.e., Educate America Act
(PL 103-227) and the Improving America’s Schools Act (PL 103-382), and created
several programs to help elementary and secondary schools acquire and use
technology to improve the delivery of educational services (Coley, Cradler, & Engel,
1996). As a result of this endeavor, the percentage regarding access to computers and
the Internet in American public elementary and secondary schools has increased from
35% in 1994 to 95% in 1999. Finally, all public schools have had Internet access since
2003 (National Center for Education Statistics, 2005).
Many scholars consider home computers a tool that reinforces or supplements
school learning, and are concerned that a lack of access to a home computer may be
25
related to lower educational achievement. Most parents also believe that computers
are an important educational resource that allows their children to discover fascinating
and useful things, and that children without access are disadvantaged compared to
those with access (Clemente, Espinosa, & Vidal, 2008; Turow, 1999). As a result, a
growing number of parents are providing their children with access to computers at
home. Among households with children-aged two to seventeen, home computer
ownership jumped from 48% in 1996 to 70% in 2000, while connections to the
Internet catapulted from 15% to 52% over the same 5-year period in the U.S.
(Woodward & Gridina, 2000).
Given the increased prevalence of access to computers and the Internet in
homes and schools, the potential value of a personal computer in child development
has been debated consistently among parents, educators, and researchers for decades.
Students’ computer use can be conceptualized in two ways: (a) home computer use for
socializing, entertainment, and educational purpose, and (b) school computer use
primarily with computer-based instruction and as a learning assistance tool. Despite
positive expectations about computer technology, a positive relationship between the
use of computer technology and academic outcomes has only partially been supported
through inconsistent research findings (Angrist & Lavy, 2002; Blanton, Moorman,
Hayes, & Warner, 1997; Campuzano, Dynarski, Agodini, Rall, & Pendleton, 2009;
26
Dynarski, Agodini, Heaviside, Novak, Carey, Campuzano, et al., 2007; Goolsbee &
Guryan, 2006; Li, Atkins, & Stanton, 2006; Rouse & Krueger, 2004). Some studies
have revealed positive correlations (Attewell & Battle, 1999; Attewell, Suazo-Garcia,
& Battle, 2003; Borzekowski & Robinson, 2005; Judge, 2005; Beltran, Das, & Fairlie,
2006; Jackson et al., 2006), such as between computer use and children’s fine motor
skills (Christensen, 2004; Ziajka, 1983), word/letter recognition (Cuffaro, 1984;
Mioduser, Tur-Kaspa, & Leitner, 2000), concept learning (Howard-Jones, & Martin,
2002; Sung, Chang, & Lee, 2008), number recognition (Cuffaro, 1984), counting
skills and pre-mathematical knowledge (Clements, 2002; Hess, & McGarvey, 1987),
reading readiness (Hess, & McGarvey, 1987), cognitive development (Howell, Scott,
&Diamond, 1987; Sung, Chang, & Lee, 2008; Shute & Miksad, 1997), visual spatial
skills (Subrahmanyam, et al., 2000) and self-esteem (Ellison, Steinfield, & Lampe,
2007; Haugland, 1992; Vogelwiesche, Grob, & Winkler, 2006). However, other
studies have found no significant evidence of computer technology use and positive
school outcomes (Malamud & Pop-Eleches. 2008; Shapley, Sheehan, Maloney, &
Caranikas-Walker, 2008). A recent study based on a survey given to one million
children by Vigdor and colleagues (Clotfelter, Ladd, & Vigdor, 2008) has revealed
that high speed internet availability is associated with less educational use of
computers and lower math and reading test scores.
27
Children and teens frequently use home computers and the Internet for their
homework and run educational programs (Kraut, et al., 1996; National Center for
Education Statistics, 2003; PEW Internet and American Life Project, 2001; UCLS
Center for Communication Policy, 2003). Home computer use has been linked to
improvements in literacy (Attewell & Battle, 1999; Weinberger, 1996; PEW Internet
and American Life Project, 2007c), language (Næ vdal, 2007), mathematics (Attewell
& Battle, 1999) and general academic performance (Attewell, 2001; Rocheleau, 1995).
Early computer exposure among young children before school years is also associated
with the development of preschool concepts and cognition (Li & Atkins, 2004). It was
found that children who had access to a computer had shown better performance in
school readiness and cognitive tests.
These positive effects are not, however, always the result of computer and
Internet use. Internet use can be a source of non-productive activities according to the
displacement hypothesis. Students with home computers are more likely to live in
families with higher incomes and education, which are highly correlated with better
academic performance (Li & Atkins, 2004). It has been found that children from a
higher socio-economic status obtain more benefits from home computers than children
from lower socio-economic statuses (Giacquinta, Bauer, & Levin, 1993). On the
contrary, having a home computer among low-income Romanian families has
28
negative consequences on children’s school performance and behaviors, because
children in households that own a home computer spend large amounts of time in
front of the computer and show negative behavioral outcomes (Malamud & PopEleches, 2008). Other research shows similar results. Giacquinta and colleagues
(1993) examined home computing among seventy middle class families for three year,
that children use home computers almost exclusively for playing games and that
academic use of computers is almost absent.
This might be explained in terms of the contribution of parental support;
findings from the Romanian study suggest that parental monitoring and supervision
are important mediating factors (Malamud & Pop-Eleches, 2008). Giacquinta et al.,
(1993) interpreted that children’s lack of educational use of the Internet is highly
dependent on parental support and guidance. In other words, greater educational usage
of computers by children might be the result of parental involvement, such as through
the purchase of educational software, monitoring of computer use, and managing of
the children’s computer time. Therefore, one may speculate that more affluent and
more highly educated parents are better able to provide supportive learning
environments and are more likely to have high expectation of their children’s
educational achievement (Attewell & Battle, 1999).
29
Parent-Child Relationship and Adolescent Outcomes
The parent-child relationship is vital to the development and adjustment of the
child. The younger the child the more they are dependent upon their parents; the
relationship with parents is very important to the children’s survival. Although there is
some doubt, a large body of evidence indicates that parents still play an important role
in the development and adjustment of their adolescent children (Hair, Moore, Garrett,
Ling, & Cleveland, 2008; Steinberg, 2008). For example, good quality relationships
with parents have been found to predict lower levels of adolescent delinquent behavior
(Hair, et al., 2008) and adolescent depression (Aseltine, Gore, & Colten, 1998). Also,
positive relationships between parents and children show buffering effects of marital
conflict or family disruption on antisocial behaviors of children (Conger, Ge, Elder,
Lorenz, & Simons, 1994) and can protect adolescents from the negative effects of
abusive parenting styles (Moore, Guzman, Hair, Lippman, & Garrett, 2004).
An association between the quality of intergenerational relationships and
adolescents’ educational and life outcomes has been well established using various
methodologies (Barber, 1996; Burt, McGue, Krueger, & Iacono, 2005; Kerr & Stattin,
2000; Petti, Laird, Dodge, Bates, & Criss, 2001). For example, longitudinal research
findings indicate that there are significant association between the quality of parent
adolescent and adolescents’ externalizing problems (Fanti, Henrich, Brookmeyer, &
30
Kuperminc, 2008); and a reciprocal relationship was also reported to exist between the
quality of the parent-adolescent relationship and adolescents’ internalizing problems
(Buist, Dekovic, Meeus, & Van Aken, 2004; Fanti, et al., 2008; Sameroff &
MacKenzie, 2003). Cross-sectional research also indicates that a close link exists
between the quality of adolescents’ relationships with their parents and adolescents’
emotional and behavioral problems (Garber, Robinson, & Valentiner, 1997).
Furthermore, some studies found that parent-adolescent closeness is positively
related to adolescents’ academic achievement. Intergenerational closeness may lead to
shared expectations of adolescents’ psychological, behavioral, social expectations and
values, as well as a shared responsibility for practicing and correcting undesirable
behaviors (Amato & Gilbreth, 1999; Englund, Egeland, & Collins, 2008). These
multidimensional social ties may become an important pathway for information and
resources that could directly enhance adolescents’ academic progress (Rosenbaum &
Rochford, 2008). Other researchers (Brewster & Bowen, 2004; Catterall, 1998;
Jimersn, Egeland, Sroufe, & Carlson, 2000) have indicated that parental instrumental
and emotional support, hostility and rejection, and intergenerational communications
are prominent determinants of educational success or failure. In other words, the
quality of parent-adolescent relationships is an important predictor of adolescents’
psychosocial adjustment (Amato & Rivera, 1999), school adaptation, coping strategies,
31
socio-emotional competence, and social interaction among peers (Lieberman, Doyle,
& Markiewicz, 1999).
Family cohesion also was found to be the core predictor of children’s academic
success (Forkel & Silbereisen, 2001; Rosenbaum & Rochford, 2008; Windle, 1992). It
has also been found that adolescents’ perception of the cohesiveness of
intergenerational relationships is significantly related to young adolescents’ well being
(Sun & Hui, 2007; Wentzel & Feldman, 1993). Therefore, how the adolescent
assesses and interprets the nature of their parent adolescent relationship may have a
strong direct and indirect impact on their own behavior and adaptation (Feldman,
Wentzel, & Gehring, 1989). For example, Hindin (2005) found that adolescent boys
attained more education if they reported being close to their mothers. Another study
reveals an important relationship between family cohesion and children’s internalizing
and attention problems (Lucia & Breslau, 2006). Conversely, the lack of parental
support was significantly contributing to adolescents’ depression, anxiety, low selfesteem, hopelessness and subsequent suicidal ideation (Simon & Murphy, 1985).
Adolescents’ depressive symptoms and suicidal ideations are commonly predicted by
the lack of closeness to parents and negative life events (Kandel, Raveis, & Davies,
1991).
32
In addition, a significant relationship between family conflict and lower
psychological distress was found among Latino groups (Rivera, Guarnaccia,
Mulvaney-Day, Lin, Torres, & Alegria, 2008). Meneese and colleagues (1992) found
that when girls experience more family conflict, they develop a sense of hopelessness
and when boys perceived a low level of family cohesion, they develop poor coping
strategies, a sense of hopelessness and depression. In conclusion, intergenerational
conflict is one of the most significant predictors of adolescents’ psychological
maladjustment (Lee, Wong, Chow, & McBride-Chang, 2006), along with
intergenerational closeness/ cohesion.
Adolescence is a period during which autonomy and independence develop, and
parent-child conflict increases (Paikoff & Brooks-Gunn, 1991). The onset of puberty
is often associated with increased conflict, decreased cohesiveness, and emotional
distance from parents (Steinberg, 1987). Parent-child conflict is defined as a state of
resistance or opposition between parents and children (Shantz & Hartup, 1992)
characterized by frequent disagreements, fights, arguments, and anger. The level of
conflict varies depending on prior family relationships, family structure, and
individual parent and child characteristics (Montemayor, 1986; Small, Eastern, &
Cornelius, 1988). The consequences of parent-and-adolescent conflict are seen as a
33
normal aspect of development or a healthy facilitator of psychological growth (Shantz
& Hartup, 1992).
Parent-adolescent conflict is also considered a risk factor for developing
emotional and behavioral problems (Marmorstein & Iacono, 2004), well-being
(Dekovic, 1999), and troubles in parent-adolescent relationships (Shantz & Hartup,
1992). For example, parent-adolescent conflict has been found by multiple researchers
to be related to adolescents’ internal and external behaviors (Adams, Gullotta, &
Clancy, 1985; Bradford, Vaughn, & Barber, 2008; Patterson, 1982; Stevens,
Vollebergh, Pels, & Crijnen, 2005a, b), depression (Dumka, Roosa, & Jackson, 1997;
Marmorstein & Iacono, 2004), and adolescents’ well being (Dekovic, 1999). Adams
and colleagues (1985) also found that intergenerational conflict is positively related to
adolescent delinquency and running away from home.
Parent-child conflict is also related to a child’s school achievement as well. For
example, parent-child conflict along with depression and discrimination influence
adolescents’ self-esteem and school achievement among Spanish-speaking
adolescents (Portes & Zady, 2002). Adams and Laursen (2007) also found negative
relations between intergenerational conflict and school grades, and positive
relationships between delinquency and withdrawal for adolescents and their parents.
34
Parenting styles are also one aspect of intergenerational relationships and have
received notable attention. Parenting styles typically include parental control and
warmth (Radziszewska, Richardson, Dent, & Flay, 1996). Therefore, parenting style
as an aspect of parent-child relationships has been identified as the key factor for
understanding adolescent cognitive, academic, and behavioral development (Hindin,
2005). Baumrind (1991) developed four types of parenting styles: authoritarian,
authoritative, permissive, and rejecting-neglectful. In particular, an authoritative
parenting style has been found to be beneficial to adolescents for psychosocial
adjustment and well-being (Steinberg, 2008). For example, an authoritative parenting
style is predictive of academic achievement among white adolescents (Dornbusch,
Ritter, Leiderman, Roberts, & Fraleigh, 1987). Rimm and Lowe (1988) found that
parents of high-achieving gifted students are more consistently using an authoritative
approach than parents of low-achieving gifted students. Many studies show that
adolescents from authoritative homes show good school achievement, less depressive
and anxious symptoms, high self-esteem and self-reliance, and less antisocial
behaviors such as drug use and delinquency (Lamborn, Mounts, Steinburg, &
Dornbusch, 1991; Steinburg, Lamborn, Darling, Mounts, & Dornbusch, 1994;
Steinburg, Lamborn, Dornbusch, & Darling, 1992).
35
These parenting styles create an emotional climate in which the parent’s
behaviors are expressed (Darling & Steinberg, 1993) and produce unique parenting
practices, which produces the specific developmental outcomes of interest. For
example, parenting practices include supervision of homework, involvement of school
activities, monitoring of children’s use of media, and so on. Therefore, these same
parenting practices may have different outcomes when implemented with one
parenting style than with another (Steinberg & Silk, 2002). Parenting practices also
include parental awareness or monitoring, supportiveness, strictness, family routines
(Paschall, Ringwalt, & Flewelling, 2003; Smetana, Crean, & Daddis, 2002), and
parent involvement (Hair, Moore, Garrett, Ling, & Cleveland, 2008).
Research indicates that parents who do not practice proper parental discipline
and supervision are more likely to have hostile coercive relationships with their
children (Hetherington, 1993). For example, when parental hostility toward their
children increases, parental monitoring often decreases (Kim, Hetherington, & Reiss,
1999). When parents engage in decreased parental monitoring they are also less aware
of their children’s well-being (Smetana, Crean, & Daddis, 2002). In addition, it was
found that unsupportive parenting is also related to internalizing problems from
childhood to early adolescence (Eisenberg, Fabes, Shepard, Guthrie, Murphy, &
Reiser, 1999). Coercive parenting and the lack of parental monitoring has been found
36
to contribute not only to boys’ antisocial behaviors, but also to their delinquent acts
(Simons, Johnson, Beaman, Conger, & Whitbeck, 1996). Conversely, parental
awareness predicts positive psychological adjustment of preadolescents (Brody,
Murry, Kim, & Brown, 2002) and a decrease in adolescents’ behavioral problems
(Smetana, Crean, & Daddis, 2002). Furthermore, Patterson and colleagues (1984)
showed that inept parental discipline is related to negative exchanges between siblings,
which in turn correlated with boys’ physical aggression and other externalizing
behaviors.
Parental Expectations and Adolescents’ Academic Achievement
The academic success of Korean and East-Asian students has been well
documented (Coleman, Hoffer, & Kilgore, 1982; Matute-Bianchi, 1986; Schneider,
Hieshima, Lee, & Plank, 1994; Schneider & Lee, 1990). For example, Korean
students were top achievers in math, science, and literacy in the thirty-one-nation
study of grade nine students (Organization for Economic Cooperation and
Development, 2003) and the international studies of academic achievement of middleschool students (National Center for Educational Statistics, 2000). On standardized
tests, East-Asian students typically outperform Western students (Schneider, Hieshima,
Lee, & Plank, 1994).
37
The Chicago field study conducted by Northwestern University to understand
the contributing factors to the high academic achievement among Asian populations
(Schneider & Lee, 1990) revealed that the academic success of East-Asian students is
linked to a) the shared values and aspirations about academic success among parents
and students, b) the home learning environment and parental active involvement, and
c) the shared expectations among family members and the interactions with teachers
and classmates. It has already been suggested that parents make a strong contribution
to their child’s school performance through the relationships they nurture with their
child (Astone & McLanahan, 1991). Among parental contributions, parental
expectations and belief systems have been considered one of the strongest predictors
of children’s academic achievement (Wentzel, 1994). The comparison study by
Schwarz and colleagues (2005) of German and Korean families also reported high
levels of parental educational expectations among Korean parents, which were
positively related to the degree of parental support and warmth.
The positive relationship between parental expectations or aspirations and their
children’s educational achievement has been consistently supported through empirical
studies (Furstenberg, & Hughes, 1995; Zhan, 2006; Sandefur, Meier, & Campbell,
2006) and among diverse populations (Neuenschwander, Vida, Garrett, & Eccles,
2007; Seyfried, & Chung, 2002). For example, Smith and colleagues (1995) found
38
that parental expectation of their children’s college attendance is a significant positive
predictor of actual subsequent college attendance of their children regardless of the
place of residence. A longitudinal study revealed that parental expectations and
children’s academic achievement are highly related through parental involvement
(Englund, Luckner, Whaley, & Egeland, 2004). Some researchers have also found that
parental expectations for their children’s educational attainment have a stronger
relation to children’s academic achievement than other parental factors, such as
parent-child communication and parental school involvement (Fan, 2001; Fan & Chen,
2001; Singh, Bickley, Trivette, Keith, Keith, & Anderson, 1995).
Furthermore, direct positive relationships between parental expectations and
children’s achievement were found after controlling for earlier achievement among 3rd
and 4th graders (Halle, Kurtz-Coster, & Mahoney, 1997). Another study showed that
parents’ and teachers’ expectations exert a significant influence on youth’s academic
competency and performance, while low adult expectations have a disruptive effect.
More interestingly, high mother expectations have buffering effects in the face of low
teacher expectations (Benner & Mistry, 2007). Indirect effects of parental expectations
on children’s academic achievement may also be mediated through parental
involvement (Croswell, O’Connor, & Brewin, 2008; Englund, Luckner, Whaley, et al.,
2004; Seyfried, & Chung, 2002) and parenting practices (Hill, 2001).
39
The direct relationship between parental expectations and children’s academic
achievement has not been consistently found. For instance, Goldenberg and colleagues
(2001) found that children’s achievement predicted parental expectations, but that
parental expectations have no significant effects on children’s achievement in a
longitudinal study of kindergarten through sixth-grade children. Discrepancies in
developmental and behavioral expectations between parents and adolescents have
been found to be associated with the amount of intergenerational conflicts (Dekovic,
Noom, & Meeus, 1997). Also, a qualitative study described the potential harmful
effect of excessive parental expectations among Chinese immigrant families, which
might put tremendous pressure on children and also might blind parents to the social
and emotional needs of their children (Qin, 2008).
Historically, Koreans hold a very strong aspiration of education (Chung, 1991a).
After the Korean War, Koreans were expected to rebuild their country and those who
had educational qualifications were the ones that were called on first. Therefore,
Koreans believe in the strong power of educational background; 98% of mothers and
77% of fathers of high school seniors reported their hopes were for their children to
enter a college (Kim, Kim, Park, You, Yoon, et al., 1994). Korean parents have
undertaken enormous sacrifices for their children in order to help them achieve
academic success (Kim, Park, & Koo, 2004), and Korean parents press their children
40
to acquire a college diploma (Bong, 2008). Consequently, school curriculum and
schedules are run in preparation for children’s future college entrance. For example, it
is normal for high school students to arrive home from school at midnight, after
intensive "self-study" sessions supported by the school. When students finish their
classes, some of them go to private institutions to boost their academic performance
and others stay in school to prepare for the collage entrance exam, and then finally
come back home late at night. According to the 2003 survey, 83.1% of elementary
students, 75.3% of middle school students, and 77.6% of high school students are
receiving private lessons (Choi, 2004).
Although middle school education is mandatory in Korean educational system,
97% of young adults complete high school education, which is the highest percentage
among OECD (Organization for Economic Corporation and Development) countries
(BBC NEWS, 2005, September 13). Korean adolescents' allocation of time devoted to
schoolwork increases as students approach their high school senior year. Some studies
showed that Korean 12th graders report spending as much as 14 to 18 hours a day
studying, giving up sleep and leisure activities to devote every possible minute to
college exam preparation (Chung, 1991b; Chung, Kim, Lee, Kwon, & Lee, 1993). A
common slogan among Korean 12th graders is "Pass with four, fail with five," which
refers to the hours of sleep thought allowable to maximize exam preparation. Actually,
41
about 80% of high school graduates went to colleges or universities in 2004. The rate
of entrance into secondary educational institutions has continuously increased since
1970, which was 38.6% in 1993 and 79.7% in 2003 (Korean Statistical Information
Service, 2004).
Because of the importance of the university entrance examination in
determining one's career prospects, Korean adolescents devote large amounts of time
to studying (Bong, 2008, 2003; Chung, 1991a; Park & Kim, 2006; Schwarz,
Schafermeier, & Trommsdorff, 2005). Students are under intense pressure to study
long hours, and the emotional stress to do well on the standardized test is very great
(Chung, 1991b). Many students get burned out because during the high school years,
students have little chance to do much except study. It is not uncommon for a handful
of students in each classroom to fall asleep from exhaustion. Students are encouraged
to see themselves as being in fierce competition with their friends and peers (Bong,
2008, 2003). As a national survey showed, their greatest concerns are academic
matters (48.9%), health and appearance (18.4%), and family issues (6.8%; National
Internet Development Agency of Korea, 2007).
Asian children incorporate their high parental aspirations and feel obligated to
satisfy their parents (Bong, 2008). Children’s success and failure is often met with
parents’ approval and disapproval (Kim & Park, 1999; Markus & Kitayama, 1991;
42
Park, Kim, & Chung, 2004). Their need to preserve strong emotional bonds with their
mothers is related to children’s willingness to accept their mothers’ values on
educational success as their own (Iyengar & Lepper, 1999). In Korea, maintaining
good relationships with parents is as important as success in school and academic
achievement (Kim, Park, & Koo, 2004). Heavy emphasis on the academic
achievement of students and their parents make school and classroom highly
competitive (Bong, 2003). As a result, grades and test scores tend to be
overemphasized (Bong, 2004). School culture emphasizing academic achievement
only, strong parental pressure on academic success, and a sense of indebtedness
toward parents may play a unique role in the parent-adolescent relationships and
adolescents’ well being in Korea.
South Korean adolescents tend to define and sustain themselves with respect to
significant relationships within the family. Because of cultural norms and expectations,
parents play a salient role in the development and adjustment of their adolescent
children, particularly their children’s education (Kim, Kim, Park, et al., 1994). This
expectation places excessive pressure on their children to become high achievers
(Fuligni, 1997; Mau, 1997). Korean adolescents in turn internalize their parents’
educational expectations (Kim, Kim, Park, et al., 1994) and try hard not to disappoint
their parents (Heine, 2001). Korean families’ congruency in academic achievement
43
may be understood by the importance and emphasis on the interdependent relationship
between parent and child under the influence of Confucianism. Confucianism is a
complex system of moral, social, political, philosophical, and quasi-religious thought
that has had tremendous influence on the culture and history of East Asia, including
China, Japan, Korea, Singapore, and Vietnam. Confucianism is typically characterized
as collectivistic and interdependent, and emphasizes the importance of relationships
with in-group members (Markus & Kitayama, 1991). Under the Confucian framework,
individuals are connected to each other via relationships and with respect to the roles
that are inherent in those relationships. These various relationships constitute clear
roles and duties with a coherent hierarchy (Kitayama, Markus, & Kurokawa, 2000).
The maintenance of one’s interpersonal harmony within five principle relationships
(e.g., parent-child, husband-wife, elder-younger, governor-minister, and friend-friend)
is central to Confucianism. Since Confucian culture heavily emphasizes respect to
elders and seniors, intergenerational relationships are considered the most important
one among these five relationships (Su, Chin, Hong, Leung, Peng, & Morris, 1999).
As individuals’ relationships and roles are often determined within a given
situation and the people surrounding them, according to Confucianism, Koreans are
more likely to describe themselves with reference to social roles or memberships than
are Americans (Markus & Kitayama, 1991). Within East Asian culture, the individual
44
must be responsive to the needs of others and the obligations associated with their
social roles. They are encouraged to harmonize with others and to adjust themselves to
the social environment (Morling, Kitayama, & Miyamoto, 2002). Individuals’
commitment to others and fulfillment of cultural obligations contributes to the group’s
success. Therefore, individuals should be sensitive to cultural demands, so that they
do not fail to live up to the group standards (Heine, 2001). For example, East Asian
children are more willing to follow their mothers’ decisions than are Euro-American
children (Iyengar & Lepper, 1999). Additionally, Asian American children do not
show negative reactions when their mothers’ make choices for them, unlike EuroAmerican children (Iyengar, Lepper, & Ross, 1999).
Theoretical Frameworks and Proposed Conceptual Models
Uses and Gratifications Theory
Few theoretical frameworks have been used to help explain the impact of the
Internet on users. The uses and gratifications framework, previously been applied to a
wide range of mass media usage and interpersonal communication areas, has been
used to explain expected positive outcomes associated with Internet use (LaRose,
Mastro, & Eastin, 2001). According to the uses and gratifications framework,
audiences seek out media, such as the Internet, in an attempt to gratify a variety of
needs (LaRose, Mastro, & Eastin, 2001). Some Internet uses, considered factors of
45
gratification including communication, information, and entertainment, have been
identified as having strong explanatory power in individual Internet use (Charney &
Greenberg, 2001; Eighmey & McCord, 1998; Flanagin & Metzger, 2001; Papacharissi
& Rubin, 2000). The theory is further supported in research investigating individuals’
online activities. Researchers report that Internet users have primarily accessed the
Internet for communication, entertainment, and for seeking information (Gross,
Juvonen, & Gable, 2001; Jackson, et al., 2006; Korean Statistical Information Service,
2007; Lenhart, Rainie, & Lewis, 2001; Mesch, 2003, 2006; Policy Information Center
of the Educational Testing service Network, 1999; Suler, 1998).
It is apparent that the Internet is used to fulfill individuals’ gratification needs,
yet it is less clear which on-line activity individuals find most gratifying. Gratification
may be based on cultural values, such as respect for one’s elders or expectation for
educational excellence. Research to date has not consistently found one activity
among these three (communication, entertainment, and for seeking information) as
being the predominant motivator for Internet use in American or Korean society. For
instance, some researchers have reported that the primary reason for Internet use is for
interpersonal communication among American adolescents (Gross, 2004; Lenhart,
Madden, & Hitlin, 2005; Papacharissi & Rubin, 2000; Valkenburg & Peter, 2007b),
whereas Korean adolescents have been reported to primarily use the Internet for
46
gaming (Korean Educational Development Institute, 2003) or for data/ information
seeking behavior (Korean Statistical Information Service, 2007). The Korean
Statistical Information Service reported in 2007 that data/ information seeking
behavior is the primary use of the Internet, accounting for by 88.7% of use, far
exceeding all other uses.
Observational Learning Theory
The direct effect of the Internet on adolescents’ academic achievement can be
framed using the observational learning theory; which contends that information is
stored in memory through the process of attention and retention. Repeated covert and
mental rehearsal of images strengthens stored information and memories, and then
makes them more available for activation at a later time (Baundura, 1994). Program
content may contribute to children’s cognitive scripts. Repeated viewing leads
children to retrieve, rehearse, solidify, and expand existing scripts, resulting in
cumulative long-term effects (Huesman & Miller, 1994). Similarly, traditional
communication research on television viewing and cognitive functioning, which
focuses on the effects of viewing, can be used (Shin, 2004). This theory is divided into
two hypotheses: the stimulation hypothesis and the reduction hypothesis. The
stimulation hypothesis proposes that watching well-designed TV programs may
enhance children’s academic achievement.
47
Informational Processing Theory
The information processing model can also be applied to the effects of the
Internet use, by explaining the process of cognitive development via the Internet
through mental processes such as attention, perception, comprehension, memory, and
problem solving (Johnson, 2006). Meta-cognitive processes such as planning,
searching strategies and evaluation of information are exercised when using the
Internet in congruence with the nature of the Internet as a multimodel interactive tool
for both input and output (Johnson, 2006; Tarpley, 2001). Internet use has been
described in regard to its benefits including enhancing “visual processing of
information, increase language and literacy skills, build knowledge base, and promote
meta-cognitive abilities such as planning and evaluation” (Johnson, 2006, p.3044). It
seems that increased time spent engaged in Internet activities and resources may
improve adolescents understanding of school concepts, increase cognitive ability, and
boost memory ability (Li & Atkins, 2004), spatial skills (Subrahmanyam, et al., 2000),
and enhance the quality of adolescents' existing friendships (Bryant, Sanders-Jackson,
& Smallwood, 2006; Gross, 2004; Subrahmanyam, et al., 2000; Valkenburg & Peter,
2007b). The stimulation hypothesis would predict that Internet use; especially
educational use, would result in academic achievement because adolescents can learn
48
a wide range of academic content, as the Internet provide repeated exposure to
educational material.
Increased Internet use has also been associated with many negative outcomes.
For example, researchers have found that increased time on the computer or Internet is
associated with increased obesity (Adachi-Mejia, Longacre, Gibson, Beach, TitusErnstoff, & Dalton, 2007; Hill & Peter, 1998), the risk of repetitive strain injuries
(Harris & Straker, 2000), seizures (Chuang, 2006: Trenité, van der Beld, Heynderickx,
& Groen, 2004), and decreased general physical well-being (Mutti & Zadnik, 1996;
Sheedy & Shaw-McMinn, 2002; Yan, Hu, Chen, & Lu, 2008). Moreover, increased
adolescent Internet use has been positively associated with antisocial behaviors
(Mesch, 2001), sexual risk behaviors (Wolak, Finkelhor, & Mitchell, 2004; Ybarra &
Mitchell, 2004b), and compromised psychological well-being (Caplan, 2002, 2003).
Time Displacement Theory
The time displacement hypothesis, which stems from the reduction hypotheses,
assumes that adolescents have a limited amount of time (Mutz, Roberts, & van
Vuuren, 1993). Therefore increased amounts of time in non-educational use of the
Internet may hinder adolescents’ academic achievement. When adolescents increase
the time they spend online engaging in social and/or recreational activities, time
sacrifices will have to be made in other areas, such as time spent on studying, reading,
49
and doing homework (Neuman, 1991). This displacement may happen because the
Internet, which entertains adolescents with stimulating images as well as visual and
auditory effects, is more attractive and immediately gratifying than are school-related
activities. Consequently, using the Internet will result in the displacement of academic
activities, as television once did, and will eventually decrease the adolescent’s
academic achievement (Aderson, Huston, Schmitt, Linebarger, Wright, & Larson,
2001; Koshal, Koshal, & Gupta, 1996; Shejwal, & Purayidathil, 2006; Shin, 2004;
Valkenburg & van der Voort, 1994).
Researchers have further reported that problematic Internet use among
adolescents brings negative outcomes in school performance, as well as to social skills
(Caplan, 2005). Therefore, it is anticipated that Korean adolescent educational use of
the Internet will be positively associated with academic achievement, and their noneducational use of the Internet, especially their recreational use, will be negatively
associated with adolescents’ academic achievement.
Human Ecology Theory
Human ecology theory assumes that human development takes place within the
context of relationships (White, 1991), and manifests in role performance and
specialization in a family. This study defines the family as an interdependently
connected social system. Just as technological innovations change societies
50
(Bronfenbrenner, 1990; Watt & White, 1999), computers and the Internet bring about
changes within the context of the family, resulting in changes to the nature of the
relationships within each of the family’s subsystems. For example, when adolescent
internet use increases, so do may conflicts between parents and adolescents over the
child’s Internet usage. Such conflict is likely to involve parental attempts to assert
their authority over their child as their adolescent attempts to assert their autonomy
over their use of time (Fuligni, 1998).
Conflict within families is normative, particularly between parents and children
during adolescence. Adolescence marks a developmental period in which families
need to adjust and adapt their relationships to accommodate adolescents’ emerging
autonomy and attachment-related issues (Steinberg, 1998). Many negotiations are
likely to occur and result in concessions to the degree of parental regulation of
adolescents’ everyday lives. Some families perceive this transitional process of
negotiation and disengagement as an opportunity for their adolescent children to foster
emotional autonomy, facilitate individuation, and improve social reasoning (Steinberg,
1998). However, others experience this process as overly stressful, as they experience
difficulties in communication that generates tension and conflict and also amplifies
emotional turmoil within the family (Buchanan, Eccles, & Becker, 1992).
51
Parents may try multiple ways to monitor and control their child’s use of the
computer. For example, some parents restrict the time of Internet-related activities so
that Internet usage does not interfere with schoolwork and socializing (Livingstone &
Bovill, 2001). When parents’ increased restrictions coupled with adolescents’ growing
need for autonomy can create conflicts within, as adolescents demand more
independence and autonomy in use of their personal time and show more open
disagreement with their parents conflicts become larger (Fuligni, 1998; Lenhart,
Rainie, & Lewis, 2001). The sharp increase of conflict and negative emotions in the
parent-adolescent relationship may lead to decreased positive interactions and
emotions about one another during the adolescent years (Kim, Conger, Lorenz, &
Elder, 2001; Larson, Richards, Moneta, Holmbeck, & Duckett, 1996). One reason for
intergenerational conflict may be based on parental concern over the activities the
adolescent is engage in on-line (Mesch, 2006). Actually, much of the public debate
over youth Internet use has been dominated by concerns about the dark side of online
culture (Mitchell, Finkelhor, & Wolak, 2003). Fears about children’s exposure to
pornography and violence even prompted Congress to pass several laws to regulate
cyberspace (Voedisch, 2000). In addition to concerns about children’s exposure online,
parents, while viewing the Internet as an inevitable yet necessary evil in this
information age, also have concerns about the potential harm the internet can have on
52
children; specifically in regards to children’s privacy and the reliability of accessed
information (UCLS Center for Communication Policy, 2003).
In spite of the Internet pitfalls, most parents in the HomeNet Too project in U.S.
have reported positive attitudes about their children’s Internet use (Jackson, et al.,
2003). Parental participants agreed that using the Internet helps children do better in
school, and Internet skills will be necessary for their children to acquire a good job.
Based on potential positive parental attitudes about the Internet, it is assumed that
adolescents’ Internet use is associated with parent-adolescent closeness and parentadolescent conflicts. However, due to the uniqueness of Korean culture, parents may
be actively involved in the on-line lives of their adolescents as they guide their
children toward academic success.
It is widely known that Korean parents have high aspirations for higher
education and high expectations for their children’s academic achievement (Bong,
2008, 2003; Cho & Yoon, 2005; Chung, 1991a; Park & Kim, 2006; Schwarz,
Schafermeier, & Trommsdorff, 2005; Shin, 2007). Parental expectation reflects
parental interest, concern, involvement, and support in the lives of their children
(Sandefur, Meier, & Campbell, 2006). Parental expectations can be expressed in many
different ways; such as the investment made by many Korean parents who invest
heavily in school education and private tutoring. In 1997 alone, it was estimated that
53
Korean parents spent more than 8.06 billion dollars on private tutoring for their
children (Kim, 2001). Korean parents have also been reported to exert excessive
amounts of pressure on their adolescents to excel academically, unfortunately to the
neglect of the child’s psychological needs (Cho, & Yoon, 2005; Kim, & Park, 1999).
Parental expectations and excessive pressure may further be related to
intergenerational conflicts. Researchers have found that differences in the
developmental expectations of parents and their children are associated with the
amount of conflict within their relationship (Dekovic, Noom, & Meeus, 1997; Barber,
1994). Conversely, other researchers have found high parental expectation to be
beneficial, as parents, who had high expectations, are also found to be more
supportive of their children providing warmth and understanding (Kim & Park, 2006).
Moreover, mothers who value higher education for their daughters are likely to have
daughters with egalitarian attitudes, nontraditional gender-typed cognitions, and
greater autonomy (Kilbourne, Farkas, Beron, Weird, & England, 1994), which may
contribute to greater intergenerational emotional closeness (Schwarz, Schafermeier, &
Trommsdorff, 2005). Incongruence between parental and adolescent educational
expectations would be considered non-normative, as most Korean adolescents also
express a strong desire to enter college (Kim, Kim, Park et al., 1994; Kim & Park,
2006). Congruency has also been found to relate to low levels of conflict in empirical
54
research; when parents and adolescents show similar views on achievement, they
experience low levels of conflict in their relationships (Dekovic, Noom, & Meeus,
1997). Furthermore, high congruency between Korean parents and their children on
educational aspiration may be related to parental support and intergenerational
closeness, under the Confucianism culture, which stresses the importance of
intergenerational relationships.
Attachment Theory
Association between intergenerational relationships and adolescent adjustment
may be explained by attachment theory. The attachment theory by Bowlby (1982)
provides insight into the development process of intergenerational relationships. He
refers to the bond between mother and child as an attachment. The development of a
secure attachment has lasting consequences on intergenerational relationships (Bell &
Ainsworth, 1972). The child develops a sense of trust in the parent and has a desire for
independence based on a feeling of security in the relationship with the parents.
The concept of trust is provided from the work of Erik Erickson (Bigner, 2009).
He developed this theory on the premise that young children must resolve a series of
psychological tasks, and trust is the first and fundamental task. Through resolution of
each stage, a child gains important social skills that facilitate social interaction. A
failure to resolve one of these stages impedes a child’s psychosocial development and
55
adjustment (Bigner, 2009). Bowlby (1982) suggested that the relationship between
parent and children has a significant effect upon the child’s psychosocial development.
Attachment theory states that the bond between the mother-child relationships
contributes to development in the emotional system of the child.
Based on a secure attachment, the child successfully obtains more complex
aspects of affect, empathy, and social skills. Erickson described these aspects as ideas
of trust, autonomy, initiative, industry, and identity (Bigner, 2009). All of these
aspects are gained through secure attachment between mother and child. The quality
of the attachment formed during early childhood affects social relationships in later
life (Bowlby, 1982). These theoretical assertions indicate that positive
intergenerational relationships foster affective development, which leads to more
effective performance in relationships with others and later facilitates educational
performance (Maier, 1978).
Previous research evidence suggests that close parent-child relationships are
related to positive outcomes in psychosocial adaptation of children, adolescents, and
young adults (Lucia & Breslau, 2006; Merz, Schuengel, & Schulze, 2008; Richmond
& Stocker, 2006; Rivera, Guarnaccia, Mulvaney-Day, Lin, Torres, & Alegria, 2008).
For example, McHale & Rasmussen, (1998) report that harmonious family
functioning during infancy predicts lower levels of preschooler aggression. A family’s
56
emotional bonding predicts frequency of delinquent acts for adolescents in
nontraditional families (Matherne & Thomas, 2001). Family cohesion is identified as
a protective factor against external stressors (Hovey & King, 1996) and positive
parent-child relationships play a protective role for children living in homes high in
conflict (Marcus & Betzer, 1996). In addition, parental warmth, support, and parentchild connectedness has been associated with reduced adolescent pregnancy risk with
an increase in sexual abstinence, postponing intercourse, having fewer sexual partners,
and/or using contraception more consistently than adolescents without warm and
supportive relationships (Miller, Benson, & Galbraith, 2001). Preschool children who
had good relationships with their parental figures are less likely to engage in
disruptive classroom behavior (Campbell, 1994; Campbell, March, Pierce, Ewing &
Szumowski, 1991). Therefore, it is anticipated that positive parent-adolescent
closeness will be associated with adolescents’ positive academic and behavioral
outcomes.
A conceptual model tested in this study is presented below. Based on the
attachment theory and the time-displacement hypothesis, it is assumed that family
relationships (parent-adolescent conflict and closeness) are a major component
contributing to the associations between adolescent Internet use and adolescents’
outcomes. The implication of this argument lies in the expectation that a
57
direct/indirect effect of adolescent Internet use on academic achievement and
problematic behaviors exists, mediated by parent-adolescent relationships between
these two variables. In addition, the role of parental expectations on the parent
adolescent relationships between type of Internet activity and intergenerational
relationships is expected.
Parental
Expectation
Gender
Parent-Adolescent
Relationships
Adolescents’
Internet Use
Adolescent
Outcomes
Conceptualization
Use of the Internet
The Internet is a vast computer network that connects computer networks and
organizational computer facilities around the world (Random House Dictionary, 2005).
For the purpose of this study, the Internet will be defined as the interconnected system
of networks that connects computers and Internets around the world via the Internet
Protocol. Access to and use of the Internet will be defined as occurring on a laptop or
desktop computer. Thus, other devices, such as cell phones, will be excluded from this
58
definition. The use of the Internet in this study will be considered a multi-dimensional
variable that includes the type of Internet activities engaged in and the amount of
Internet use.
Numerous surveys have attempted to measure the amount of general Internet
use – including the length of time people spend online per unit of time. Estimates vary
widely, depending on how Internet usage is measured (e.g., self-report, automatically
recorded), the ages of respondents sampled, when data was collected (i.e., year of the
study), and how Internet use is defined (e.g., length of time online, frequency of use;
Jackson et al., 2006). There is a need to empirically distinguish the amount of time
spent on-line in various types activities (Lee & Kuo, 2002), even though most studies
do not categorize or weigh Internet use according to the various activities and content
(Joinson, 2001), it should be considered important since people use the Internet for a
variety of purposes, which may vary by characteristics such as age, culture and gender.
The 2007 National Survey about Internet use by the Korean Statistical
Information Service revealed that the three primary purposes for Internet use were
data/information seeking (88.7%); leisure activities, such as movies, games, and music
(86.0%), and communication through chatting and emailing (84.7%). However,
Korean teens’ Internet uses were found to deviate from these statistics in the Korean
Educational Development Institute study in 2003 on the life of Korean teens. The
59
three main types of Internet use were categorized as a) recreational activities such as
gaming, searching information about music, movie, and entertainment; b) educational
use, such as information seeking for school project and homework, downloading data,
and programming; and c) communicative activities, such as chatting, e-mailing,
involvement in online communities, and social networking websites, which is similar
to that of the general population. Moreover, these categorizations have been
consistently found in American populations (DeBell & Chapman, 2006; Gross,
Juvonen, & Gable, 2001; Jackson, 2006; Lenhart, Rainie, & Lewis, 2001; Policy
Information Center of the Educational Testing service Network, 1999; Suler, 1998)
and other countries (Mesch, 2003, 2006).
Therefore, for the purpose of this study, type of Internet use will also be
examined using these three categories: educational use, social use, and recreational
use. The frequency of Internet use and it’s functional use experienced by children and
young people has been measured in a number of studies (Bayraktar, & Gun, 2007;
Hunley, Evans, Delgado-Hachey, Krise, Rich & Schell, 2005; Malamud, & PopEleches, 2008; Mesch, 2006; Rhee, & Kim, 2004; Wainer, Dwyer, Dutra, Covic,
Magalhães, Ferreira et al., 2001; Willoughby, 2008). In this study a second dimension
of Internet use, time, will also be examined, including the amount of time spent online per week and the longevity of Internet use. Time spent on-line per week will
60
include the number of hours the adolescents put on using the Internet per week, and
longevity of Internet use will assess how long the adolescent has used the Internet
over their lifespan.
Educational Use of the Internet
Educational use of the Internet will be defined in this study as using the Internet
and computer technologies for obtaining information for academic purposes from a
vast multimedia online library covering numerous topics. Adolescents use the Internet
to search for information for school research projects and other school assignments,
and to enhance their learning and understanding. In addition, communication with
people regarding schoolwork will be included.
Social use of the Internet
Social use of the Internet will be defined as using the Internet and computer
technologies for social communication and interaction with people such as e-mailing,
using Internet phone, text messaging, joining chat rooms, instant messaging, visiting
blogs, and exchanging e-cards primarily with friends, family members, teachers, and
so on. Text messaging using cell phone is excluded in this study.
Recreational Use of the Internet
Recreational use of the Internet will be defined as using the Internet for
recreational and entertaining purpose such as online gaming, downloading pictures,
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listening to music, searching for information pertaining to leisure activities, and
reading online news reports.
Parent-Adolescent Conflict
Conflict has previously been conceptualized as “the amount of openly expressed
anger and conflict among family members (Moos & Moos, 1994, p.1) or
“disagreement” (Adams & Laursen, 2007). In the large body of literature, parent-child
conflict is assessed by the amount and the intensity of conflicts, such as an open
expression of disagreement (Adams & Laursen, 2007; Dekovic, 1999) and argument,
fighting, aggression and anger (Barber & Delfabbro, 2000; Hanna & Bond, 2006;
Hawkins, Catalano, & Miller, 1992; Ingoldsby, Shaw, Winslow, Schonberg, Gilliom,
& Criss, 2006). The amount of conflict is typically rated on Likert-type scales. For
example, Dixon, Garber, and Brooks-Gunn (2008) assessed conflict as occurring from
monthly to daily and/or Bradford, Vaughn, & Barber (2008) assessed conflict from
never to almost every day. The intensity of conflict is also rated on Likert-type scales,
such as from not heated to very heated (Dixon, Garber, & Brooks-Gunn, 2008), and
from calm to angry (Prinz, Foster, Kent, & O’Leary, 1979).
Parent-adolescent conflict is defined in the current study, as the amount and
intensity of openly expressed anger, disagreement, and argument between children or
adolescents and their parents regarding the use of the Internet and general matters.
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Parent-Adolescent Closeness
Parent-adolescent closeness has been determined by the amount of continuing
contact between parents and adolescents (Buchanan, Maccoby, & Dornbusch, 1991),
the degree of feelings of closeness with each other (Buchanan, Maccoby, &
Dornbusch, 1991, 1996; Olson, Sprenkle, & Russell, 1979) and/or closeness
characterized by open communication, positive feelings and expressed affection
(Ramirez, 1997). Many researchers have measured closeness through cohesion (Olson,
Sprenkle, & Russell, 1979; Richmond & Stocker, 2006; Rivera, Guarnaccia,
Mulvaney-Day, et al., 2008; Steinberg, 1998), emotional bonding (Hovey & King,
1996; Kapinus & Gorman, 2004; Salgado de Snyder, 1987), as well as togetherness,
unity, and closeness (Lindahl & Malik, 2000). Also, closeness has been measured
through connectedness, parental support, and warmth as a dimension of parenting
(Feldman & Brown, 1993; Miller, Benson, & Galbraith, 2001; Resnick, Bearman,
Blum, Bauman, Harris, Jones, et al., 1997). In this study, parent-adolescent closeness
will be assessed as the degree of overall feelings of closeness between parent and
adolescent.
Parental Expectation
Parental expectation has been defined as parent’s ideal for children’s ultimate
educational and occupational attainment or a parent’s current expectations for
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children’s academic performance (Christenson, Rounds, & Gorney, 1992). In this
study, parental expectation will be measured to the degree of parent’s aspiration of
children’s current academic performance and future educational attainment using the
Revised Asian Value Scales (AVS-R; Kim & Hong, 2004).
Adolescent Behavioral Problems
In the larger body of literature, behavioral problems are characterized by both
externalizing problems (e.g., anti-social behavior, aggression, and conduct problems)
and internalizing problems (e.g., depression, anxiety, withdrawal, somatic complaints,
and low self-esteem) (Bradford, Vaughn, & Barber, 2008; Choi, He, & Harachi, 2008;
Formoso, Gonzales, & Aiken, 2000; Stevens, Vollebergh, Pels, & Crijnen, 2005a, b;
Stevens, Vollebergh, Pels, & Crijnen, 2007). Adolescent externalizing and
internalizing problems will be used to assess adolescents’ behavioral outcomes in this
study.
Academic Achievement
Academic achievement is defined as the level of individual’s education and/or
educational outcomes accomplished successfully, as a result of learning at school. It is
usually determined by comparing his or her score on a school test and/or a
standardized test with the average score of other people of the same age. Standardized
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test scores on school tests will be used to define Academic achievement for the
purpose of this study.
Research Questions and Hypotheses
As proposed in the stimulation hypothesis, using the Internet for educational
purposes may enhance adolescent’s academic achievement. On the contrary, based on
the time displacement hypothesis, increased amounts of time in non-educational use of
the Internet may sacrifice time in educational activities, such as studying, reading, and
doing homework. Consequently, using social and/or recreational use of the Internet
will result in the displacement of academic activities and will eventually decrease the
adolescent’s academic achievement.
This study focuses on the relationships among adolescent Internet use, parentadolescent conflict, parent-adolescent closeness, and adolescent’s behavioral
outcomes and academic achievement. Four research questions and hypotheses will be
tested in this study. These questions and hypotheses are:
Research question 1. Are there gender differences in the nature of Korean adolescents’
Internet use?
H1. Boys and girls are different in the frequency and the intensity of
educational, social, and recreational use of Internet.
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Boys
Girls
Educational Internet use
Social Internet use
Recreational Internet use
Social Internet use
Research question 2-1. Are there direct effects of adolescents’ Internet use on their
academic achievement and problematic behaviors?
H2-1.1. Adolescents’ Internet use has a direct effect on their academic
achievement.
H2-1.2. Adolescents’ Internet use has a direct effect on their internalizing
problematic behaviors.
H2-1.2. Adolescents’ Internet use has a direct effect on their externalizing
Research question 2-2. Are these direct pathways different for boys and girls?
H2-2.1. Boys and girls are different in the association between adolescents’
Internet use and their academic achievement.
Internet use and their internalizing problematic behaviors.
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Internet use and their externalizing problematic behaviors.
Adolescent’s
Gender
Social Internet use
Behavioral Adjustment
The attachment theory suggests that intergenerational relationships have a
significant effect upon the child’s academic and behavioral adjustment; previous
research evidence indicates that close parent-child relationships are related to positive
outcomes in the psychosocial adaptation of children (Hair, Moore, Garrett, Ling, &
Cleveland, 2005; Steinberg, 2008). Parent-adolescent closeness has been positively
associated with reduction of problematic behaviors (Fanti, et al., 2008; Hair, et al.,
2005; Miller, Benson, & Galbraith, 2001) and academic achievement (Amato &
Gilbreth, 1999; Englund Egeland, & Collins, 2008). On the contrary, parentadolescent conflict has been positively associated with problematic behaviors and
negatively associated with academic achievement (Adams & Laursen, 2007; Lee,
Wong, Chow, & McBride-Chang, 2006; Marmorstein & Iacono, 2004).
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Parent-adolescent closeness may serve as a buffer for adolescents from negative
effects of non-educational Internet use on their academic achievement and behavioral
adjustment. Conversely, intergenerational conflict is a strong predictor of negative
youth outcomes in families from diverse cultural backgrounds (Ong, Phinney, &
Dennis, 2006; Rivera, et al., 2008). Parent-child conflict may also serve as a potential
mediator of the relationship between adolescent Internet use and youth adjustment.
Research question 3-1. Does the nature of adolescents’ Internet use affect their
academic achievement/ behavioral adjustment through P-A closeness/ conflict
(Mediation effects)?
H3-1.1. Adolescents’ Internet use has an effect on academic achievement through
parent-adolescent relationships.
H3-1.2. Adolescents’ Internet use has an effect on internalizing behavior
problems through parent-adolescent relationships.
H3-1.3. Adolescents’ Internet use has an effect on externalizing behavior
problems through parent-adolescent relationships.
Research question 3-2. Are these pathways different for boys and girls? (Moderating
role of adolescent gender)
H3-2.1. Boys and girls are different in the pathways from adolescents’ Internet use
to their academic achievement through parent-adolescent relationships.
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to their internalizing behavior problems through parent-adolescent relationships.
to their externalizing behavior problems through parent-adolescent relationships.
Adolescent’s Gender
Social Internet use
Parent-Adolescent
Relationships
The association between parental expectation and children’s academic
achievement has been constantly explored and a general conclusion that can be drawn
is that academic achievement is consistently correlated with high parental expectations
(Boersma & Chapman, 1982; Cohen, 1987, Marjoribanks, 1988; Sandefur, Meier, &
Campbell, 2006; Thompson, Alexander, & Entwisle, 1988; Wentzel, 1994). In
addition, previous research shows that excessive parental expectation is related with
intergenerational conflicts (Dekovic, Noom, & Meeus, 1997; Barber, 1994). Therefore,
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in the present study, effects of parental expectation as moderator will be examined. It
is anticipated that adolescent Internet use for educational purposes will be positively
associated with parent-adolescent closeness and negatively associated with parentadolescent conflict, especially when parental expectations are high. Furthermore,
adolescent’ educational Internet use is positively associated with adolescent’ academic
achievement, especially when parental expectations are high.
Research question 4. Do indirect pathways between the adolescent Internet use and
academic/behavioral adjustment (through P-A relationships) vary by the level of
parental cultural expectations (Asian values)?
H4-1. The level of parental expectations has different effects on the pathways from
adolescents’ Internet use to their academic achievement through parentadolescent relationships.
H4-2. The level of parental expectations has different effects on the pathways from
adolescents’ Internet use to their internalizing behavior problems through parentadolescent relationships.
H4-3. The level of parental expectations has different effects on the pathways
from adolescents’ Internet use to their externalizing behavior problems through
parent-adolescent relationships.
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Parental
Expectation
Social Internet use
Parent-Adolescent
Relationships
Methodology
This study explores the relationships among adolescent Internet use, parentadolescent relationships (conflict and closeness), and adolescent’s outcomes
(academic achievement and problematic behaviors) among Korean adolescents and
their parents.
Population
The city in which the study is conducted is located on the west side of central
Korea, which is Seoul. Seoul is the capital of South Korea with a population of
10,297,004 and 3,871,024 households covering 605.52 square kilometers. The average
household income is ₩ 3,182 per month.
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Korean schools are divided into elementary schools, middle schools, high
schools, and colleges. Children attend elementary school for six years, middle school
for three years, and depending on their middle school grades, the student's high school
acceptance is determined. The initial nine years of school (elementary and middle
school) is considered the duty of children. Middle school graduates, or those with
equivalent academic background may enter high schools. The high school period of
study is three years, and students bear the expenses of the education. In high school,
students study Korean language, English, Mathematics, Science, Social Studies,
Korean History, Ethics, Home Economics-skills, Art, Music, and Physical Science.
Science and Social Studies are very specific in curriculum, and a second language is
also learned as an elective. High schools contain three grades (from 10th to 12th grade)
and class size is about 30 to 35 students.
The Korean school system is divided into two semesters. The academic year
starts in March. The First semester lasts from March to July, while the second
semester lasts from September to December. Summer vacation takes place in August,
and winter vacation lasts for about 35 days. Korean students typically spend most of
their time in school; Monday through Friday from 8:30 a.m. to 3:00 p.m., and
Saturday until noon. Korean students are under a lot of pressure to study very hard, as
they must either attend college or find a job after high school.
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There are 74 general public high schools out of a total 670 high schools, mostly
comprised of private general schools, vocational public schools, private vocational
schools, and specialty high schools. Each class in a particular school has an average of
32.5 students. In public schools, there are 10 to 15 classes for every grade.
Procedure
From an initial list of public high schools in Seoul, South Korea, principals of
five high schools in Seoul, South Korea agreed to participate in the study. All
principals were contacted and provided with an opportunity for study participation.
Primary contact with principals involved providing information about the study,
including its benefits and risks, and the overall study procedure. Five principals out of
nine agreed to allow the research to be conducted in their high schools. Next, with the
official cooperation letters from these principals, I met with the chief teachers of
grades 10 and 11 and explained the study purpose and procedure. Subsequently, the
chief and homeroom teachers informed students in these classes about the study and
asked for their participation. Interested and assenting children were given a sign-up
sheet with consent statement and a description of the study. Parents, who agreed to
have their children participate in the study, provided their contact information (e-mail
address) and signed on the consent form. Then, surveys were distributed to students
and their parents. Students who filled out the survey forms returned their own surveys
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and their parents’ surveys to teachers. Finally, teachers passed completed surveys to
this investigator. In order to acquire significant statistical power, samples sizes
between 200 and 400 for running models tend to be used (Byrne, 2001). Therefore,
the sampling goal has been set to a minimum of 250 families, consisting of data from
adolescents, mothers, and fathers. A total 1370 sets of surveys were distributed and
613 sets of surveys were obtained.
Each survey begins with a short overview and directions for the participants.
The overview section gives a short description of the primary and secondary
researchers and the connection to Syracuse University. The overview clearly defines
the aim of the study, defines the survey as confidential and informs the participants
that their participation can be withdrawn at any time.
Since the survey instruments was administrated in Korean, all the measurements
for this study were translated from English into Korean, and subsequently translated
back to English. Two graduate students, and one professional translator from Korea,
who were all fluent in English and Korean, were involved throughout the translation
process. The original English version and the back-translated English version were
compared and discrepancies were reworded in order to rectify any items that had not
retained their original meaning. Then two different Korean natives reviewed the
translations and reworded the items they believed were not explicable or applicable.
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Finally, graduate students fluent in English only, read through all of the items again,
explaining their understanding of each item in English to ensure that the translations
were still accurate. The pre-research process resulted as productive and necessary to
the research instruments.
The survey was pilot tested by administering the survey to three Korean
adolescents and one of their parents. Each adolescent was asked to read and answer
the survey items and report incomprehensible questions, as well as provide
suggestions and express concerns for survey improvement. Necessary revisions were
again made based on pilot testing.
Participants
Three high schools in this study are general public high schools. Compared to
other high schools in South Korea, students of the general public high schools in
Seoul are considered relatively homogeneous because student selection is equivalent
for these schools; selecting students according to their school activities records only.
Therefore, public school classes are equally mixed with the different student
achievement levels, and the levels are normally distributed and almost identical with
other classes in the same school. Two high schools in this study are general private
schools. Since students of the private schools in Seoul are selected through an
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entrance exam and their middle school private school students are expected to be in
higher academic levels than public school students.
This study sample consists of adolescents of 10th and 11th grade, who reside and
attend general public/private high schools in Seoul. In Korean society, a person’s
educational attainment determines his/her social position. Families from these three
schools come from different SES, since each school is located at a different area in the
city.
Adolescents were asked to provide information about their date of birth,
gender, family members and relationships, religious preference, and their parents’
employment status. Parents were also asked to provide information about their age,
gender, level of education, occupation, income, religious preference, and marital
status (see Appendix A).
Measurements
Adolescent Internet use. The Internet use scale includes general questions
about adolescent Internet use, such as their access, the primary location of their
Internet use, the extent of the Internet experience. Access to Internet use is measured
with responses to four of questions, such as (a) “How many PCs/ Laptops with
internet access does your family home have?”, (b) “If you go online at the school, do
you use it during your break or free time or use it during the classes?”, and (c) “If you
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go online at the school, are you able to use it alone or under adult’s supervision?” The
primary location of Internet use is measured with responses to two questions, such as
“If you use a computer in your home, is it located in a private area like your own
bedroom or in an open family area like a living room, den, or study?” The extent of
Internet experience is assessed by a single item for each different type of Internet
activity assessed, such as e-mailing, searching for information, gaming, etc.
Responses are answered by ranking their preference and actual time spent engaged in
that activity (see Appendix B).
Adolescent Internet Use is measured with the intensity and frequency of
Internet use in three areas: educational, recreational, and social use. Educational
Internet use is measured by six questions. Sample survey items about Educational
Internet use scale include (a) Doing homework and other school assignments, (b)
Searching information about school-related and academic information, (c) Talking to
teachers about homework, exams, and school related matters, and so on. Recreational
Internet use scale includes three items, (a) Playing a game, (b) Watching and/or
downloading movies, songs, etc., (c) Searching for information about TV programs,
movies, concerts, etc. Social Internet use includes four items, such as (a) To chat with
peers and friends about non-academic related matters, (b) Going to my blog, Internet
community, or mini-homepage to make new friends and to talk with my friends, etc.
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(see in Appendix B). Responses are reported by actual number of minutes/hours with
higher numbers indicating higher frequency of Internet use.
Parent-Adolescent relationships. Two aspects of parent-adolescent
relationships are assessed: (a) parent-adolescent closeness and (b) parent-adolescent
conflict. The parent-adolescent closeness scale includes eleven items modified from
the Parent-Child Closeness scale developed by Buchanan, Maccoby, and Dornbusch
(1991), as well as the cohesion subscales of the Family Adaptation and Cohesion
Evaluation Scales II (Olson, Sprenkle, & Russell, 1979) that pertain to the parents’
and adolescents’ overall feelings of closeness. Close feelings are measured with
responses to statements; (a) I feel close to my mom, and (b) I am confident that my
mom would help me if I had a problem. Responses range from 1=Not at all, 2=Little
true, 3=Somewhat true, 4=Often true, to 5=Absolutely true, with higher scores
indicating higher degrees of closeness (Appendix C).
The original scales are developed to assess adolescents’ feelings of closeness
with each parent after divorce in a normative samples, reported Cronbach’s alpha
from original samples are from .89 to .90 (Buchanan, Maccoby, & Dornbusch, 1991).
Closeness scales have exhibited good validity and reliability (from
= .71 to
= .84), and good internal consistencies for normative American samples and across
different ethnic groups, including immigrant families (Harris, 1999; Lam, Cance, Eke,
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Fishbein, Hawkins, & Williams, 2007; Rude, 2000). However, cultural validity has
yet to be established. Therefore, the generalizations inform the current study should be
made with caution.
Parent-adolescent conflicts are measured with two dimensions. The first
dimension assesses overall disagreement and conflict between parents and adolescents
using 7-item questions modified from the Parent Environment Questionnaire (PEQ).
The PEQ is a 42-item self-report inventory that assesses five aspects of the
relationship of each parent-child dyad in the family; Conflict, Parent Involvement,
Regard for Parent, Regard for Child, and Structure (Elkins, McGue, & Iacono, 1997).
The PEQ scale consists of 12 items (internal consistency reliability [ ] = .82) that
assess the extent to which the parent-child relationship is characterized by
disagreement, tension, and anger. Sample questions were (a)”My parent often
criticizes me”, and (b)”My parent often hurts my feelings.” Each item is answered on
a 4-point scale ranging from 1=definitely false, 2=probably false, 3=probably true, to
4=definitely true. Higher scores indicate greater conflicts between parents and
adolescents (Appendix C).
The second dimension is measured with responses to the 13 questions adapted
from the Parent-Adolescent Conflict Issues Checklist scales, which includes a list of
13 issues that have been found to be the source of present discord between parents and
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adolescents dyad (Robin & Weiss, 1980). The utilized Parent-Adolescent Conflict
Issue Checklist in this study is a modified version of the Conflict Issues Checklist
developed by Prinz, Foster, Kent and O’Leary (1979) and Robin and Foster (1989).
The original scale includes a 44-item questionnaire that addresses the extent to which
parents and adolescents argue and/or disagree about each issue. The questionnaire is
designed to be administered to both parents and their children. First, respondents are
asked to indicate whether or not the issue has been a topic of conversation during the
last two weeks. A sample item is: “Doing homework”, “Grades in school”, and “Using
Internet”. The respondents indicate the intensity of these issues using a 5-point Likert
scale ranging from 1=very calm, 2=calm, 3=angry to 4=very angry (Appendix C).
The Issue Checklist can yield three scores for each member of the dyad: (a) the
quantity of issues discussed, (b) the mean anger-intensity level of the endorsed issues
(the average level of intensity of conflict across all issues discussed, and (c) the
weighted average of the frequency and anger-intensity level of the endorsed issues
(Robin & Weiss, 1980). In this study, all three scores are computed for each
participant and the third score was used for analysis (Appendix C).
The scale has been widely used in research (Prinz, Foster, Kent, & O’Leary,
1979; Silverberg & Steinberg, 1987). Test-retest reliability is reported as relatively
low due to the fluctuating nature of conflict during adolescence; ranging from 0.63 -
80
0.81 for mothers and 0.47 – 0.72 for adolescents. The Issues Checklist is reported to
have good discriminant / criterion-related validity, however parent-adolescent
agreement on whether an issue had been discussed was low; ranging from 38% - 86%.
Evidence of validity is found in studies showing agreement averaging 67.5% between
parents and adolescents, as to whether an issue had been recently discussed (Robin &
Foster, 1989). Although one researcher using a Russian sample showed good
Cronbach alpha values (from .76 to .90) (Glebova, 2002), Cronbach alpha has not yet
been reported for a Korean sample; therefore reducing the generalizability of this
study’s findings should be applied.
Parental cultural expectations. Parental cultural expectations are measured by
questions from the Revised Asian Value Scales (AVS-R; Kim & Hong, 2004). The
AVS-R contains 25 items and was developed based on the Asian Values Scale (Kim,
Atkinson, & Yang, 1999), which is one of the few instruments that assess Asian
cultural values. The scale includes eight values such as “collectivism, conformity to
norms, family recognition through achievement, deference to authority figures,
emotional restraint, filial piety, hierarchical family structure, and humility” (Kim &
Hong, 2004, p.19).
Kim and Hong reported adequate reliability of the AVS-R (i.e., person
separation reliability of .80), which is comparable to the internal consistency
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coefficients of .81 and .82 reported by Kim et al. (1999) for the original 36-item AVS.
In the current study, alpha for the AVS-R is .53 to .57. Kim and Hong found a
correlation of .93 between the AVS and AVS-R, supporting the validity of AVS-R.
The AVS has been through multiple reliability and validity procedures. As indicated
above, it has significant validity and reliability data (a two week retest reliability
of .83; Kim et al., 1999). Discriminant validity is demonstrated by the low correlation
between AVS scores, which primarily reflect enculturation, and Suinn-Lew Asian
Self-Acculturation Scale (Suinn, Rickard-Figueroa, Lew, & Vigil, 1987) which is a
scale that primarily measures behavior acculturation. Additional reliability and
validity information for the instrument has not yet been published.
Example statements include (a) One should not deviate from familial and social
norms, and (b) One need not achieve academically in order to make one’s parents
proud. Respondents rated how much they agreed or disagreed with each statement by
using a 4-point Likert-type scale (1=Strongly disagree, 2=Disagree, 3=Agree, and
4=Strongly agree). Higher scores indicate greater enculturation to Asian values.
Adolescent outcomes. Two areas of adolescent outcomes are assessed: a)
academic achievement and b) behavioral problems. Adolescents’ academic
achievement is assessed using adolescents’ and parental reports of adolescent’s
standardized test grades in Social Studies, Mathematics, Korean Language, Science,
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and English. Response sets range from 1 (highest) to 9 (lowest) grades. The mean
across subjects are used from each reporter.
Behavioral problems: Two dimensions of behavioral outcomes are assessed: (a)
externalizing behavioral problems and (b) internalizing behavioral problems.
Adolescents reported their own behaviors using the Youth Self-Report Inventory
(Achenbach, 1991b) and parents also reported their children’s behaviors using the
Child Behavior Checklist (Achenbach, 1991a). The Youth Self-Report (YSR) is the
self-report form of the Child Behavior Checklist (CBCL) for adolescents between the
ages of 11 and 18 years, which are designed to measure adolescents’ emotional and
behavioral problems.
The behavior problems scale of the YSR contains 120 items that assess nine
core syndromes of problems relevant for both girls and boys: (a) somatic complaints,
(b) anxious/ depressed behaviors, (c) social withdrawal, (d) thought problems, (e)
attention problems, (f) self destructivity/identity, (g) withdrawal, (h) aggressive
behaviors, and (i) delinquent behaviors. As suggested by Achenbach, a T-score >=65
on a scale for Korean children constitutes clinically significant symptoms (Oh, Lee,
Hong, & Ha, 1997).
For each item of the scale, respondents were asked to report their behaviors on a
3-point scale ranging from 0=Not True, 1=Somewhat or Sometimes True, to 2=Very
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True or Often True. In this study emphasis are given to two major areas of problem
syndromes -58 items: internalizing and externalizing. The internalizing problems scale
for this study consists of a total score of items that are answered in the social
withdrawn, somatic complaints, and anxious/ depressed scales. Externalizing problem
scale for this study is comprised of sum scores of items in the delinquent behavior and
aggressive behavior syndrome scales. Examples of internalizing items are: “I feel
worthless or inferior” and “I am unhappy, sad, or depressed.”
Achenbach (1991b) reported the mean seven days test-retest reliability for the
problem scales was r= .65 for 11 to 14 years old and r= .83 for 15 to 18 years old. It is
reported that internal consistencies for the syndrome scales ranged from alpha= .68 for
social problems to alpha= .89 for externalizing problems and alpha= .91 for
internalizing problems. Content validity of the YSR is assessed and supported through
discriminant analyses, which show the ability of most YSR items to discriminate
significantly between demographically matched referred and non-referred adolescents.
Adolescents’ behavior problems are also reported by parents using the parental
version and the Child Behavior Checklist.
Analytic Strategy
For this study, quantitative analysis in this study is based on a variety of
different questionnaire items from the survey and different research questions.
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Because of differences among these items and the nature of questions, a number of
different statistical techniques are employed to analyze the data. These techniques
included analysis of descriptive statistics, correlation, multivariate analysis of variance,
multiple regression, and path analysis.
Preliminary analysis was conducted. The correlation analysis was performed
between parent reporting and child reporting of the same construct, in order to find out
the overall pattern of associations between these variables of the same construct. In
addition, correlation analysis was conducted among all variables in the parent report
and child report model separately.
In order to examine which baseline demographic characteristics are associated
with adolescent’s Internet use, multiple logistic regressions were run, stratified by sex.
Predictors of the model were included some categories of demographic characteristics,
(a) individual predictors, such as birth order and religious preference; and (b) familial
predictors that included SES, parental education level, parental marital status, and
family structure.
Then a series of theoretical models were tested using the AMOS 5.0 software
package. The model was simultaneously assessed for boys and girls using path
analysis. Path analysis is an extension of multiple regression. Its aim is to provide
estimates of the magnitude and significance of hypothesized causal connections
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between sets of variables. The regression weights predicted by the model are
compared with the observed correlation matrix for the variables, and a goodness-of-fit
statistics is calculated.
Since the analyses of each model begin with full recursive model, several
goodness of fit statistics should be used to assess model fit (Kline, 2005), such as
Goodness of Fit Index (GFI), Adjusted Goodness of Fit Index (AGFI), Comparative
Fit Index (CFI), the Root-Mean-Square Error of Approximation (RMSEA), and Chi
Square Index are evaluated to determine the overall acceptability of the conceptual
model. The GFI and AGFI are two of the most commonly used measures of fit. Both
measures assess absolute fit by comparing the covariances actually found in the data
to the covariances proposed by the fixed and free parameters of the proposed model
(Kline, 2005). Both GFI and AGFI ranged from zero to one and values .90 to .99 are
considered acceptable although it is more difficult to achieve an AGFI of that
magnitude (Gerbing, & Anderson, 1993). CFI is evaluated to determine the
incremental fit of the measures and it is recommended that .90 cutoffs is stringently
utilized (Kline, 2005). The RMSEA takes into account the error of approximation in
the population. A valued of .05 or lower indicates adequate or good fit (Kline, 2005).
For a good model fit, a fitting function value of close to 0 is desired. However,
Ullman (1996) argues that if the ratio between X 2 and the degrees of freedom is less
86
than two, the model is a good fit. Also, he discusses a variety of non- X 2 – distributed
fitting functions. Ullman (1996) calls this “comparative fit indices.” As comparing the
fit of an independence model to the fit of the estimated model, the result of this
comparison is usually a number between 0 and 1. As Ullman suggests, the use of
multiple indices is a better idea to determine model fitness. Thus, at every stage of
model testing, several goodness-of-fit indices including GFI, AGFI, and CFI will also
be assessed to determine the acceptability of the conceptual model.
In order to test moderating effects of gender in conceptualized models, critical
ratio of a given path will be examined. As the SEM estimates are calculated on the
basis of Z statistic, if the absolute value of the critical ratio is equal to or higher than
1.96, it can be inferred the path is variant across the variable at p < .05. If the absolute
value of the critical ratio is equal to or greater than 2.56, it can be inferred the path is
variant across the variable at p < .01.
An indirect effect is defined as the product of the two unstandardized paths
linking X to Y through a mediator (M). Estimates of indirect effects and their standard
errors are used to determine the significance of the effect through a mediator
(Preacher & Hayes, 2008). Support for mediation relies on whether the indirect
pathway from A to M to Y is statistically significant (Shrout & Bolger, 2002). A re-
87
sampling method (bootstrapping) was used to determine the significance of the
indirect effect in the current study.
In addition, to provide a final check for mediation effects, indirect pathways
were tested for significance using Sobel’s test (1982). The Sobel test examines the
strength of the indirect effect of the independent variable on the dependent variable
through a mediator by calculating the z value. It is determined that the reduction in the
associations between the independent variables and the outcome variables are
statistically significant. The Sobel test is the last step for identifying whether the
mediator is significant or not. The formula for calculating z value is:
z=
Where b = path estimates for the link between the independent variable and the
mediator, c = path estimates for the link between mediator and dependent variables:
Sb = standard
error for b; Sc = standard error for d. According to Sobel (1982), a z
score valued 1.96 or larger, indicates a significant indirect effect (p < .05).
To provide a final check for mediation effects, indirect pathways were also
tested for significance using the bootstrap method. Bootstrapping is a popular method
used to accommodate non-normal data. Bootstrapping does not make the assumptions
of normal theory associated with SEM such as theoretical sampling distributions
(Finney & DiStefano, 2006) and instead empirically estimates the sampling
88
distribution (Preacher & Hayes, 2008; Shrout & Bolger, 2002). Many researchers (e.g.,
Cheung & Lau, 2008; MacKinnon, Lockwood, Hoffman, West, & Sheet, 2002;
Preacher & Hayes, 2008) recommend employing bootstrap methods to test mediation.
It was found that the bootstrap method more accurately produces confidence intervals
than other methods which assume the data follows a normal distribution (e.g., Sobel
test; Sobel, 1982) (Cheung & Lau, 2008). This recommendation is supported by
findings of MacKinnon et al. (2002) who recommend bootstrapping be implemented
over the Sobel test (or causal stpes approach) to maintain power and control over Type
I errors. Finney and DiStefano (2006) recommend this method because even under
extreme non-normality, bootstrapping outperforms other methods used to adjust or
rescale the non-normal data.
Bootstrapping randomly samples cases with replacement, from the original data
in to create a bootstrap sample. This method adjusts the chi-square and standard error
of path estimates to help with non-normality (Bollen & Stine, 1992). Bootstrapping
can be repeated numerous times and mimics collecting numerous samples from a
population (Kline, 1998). In the current study, empirical standard errors were obtained
through 2000 bootstrap samples and the model was fit to each bootstrap sample.
89
Results
The purpose of this study was to investigate the associations among adolescent
Internet use, parent-adolescent relationships, academic achievement, and behavior
problems among South Korean families. The result section is organized as follows: (a)
Addressing issues of distribution and missing data (b) Demographic characteristics of
participants, (c) Descriptive statistics on the nature of adolescents’ Internet use, (d)
Factor analyses and reliability of constructs, and (e) Hypotheses Testing.
Addressing Issues of Distribution and Missing data
Data were analyzed using the SPSS 17 statistical package. The data were first
checked for missing data and out of range values. The amount of missing data was
small (less than 1%), and hence missing data was substituted with the mean values.
Although this method could be problematic because it underestimates variance,
correlations, and regression coefficients, Allison (2002) indicates that if the
percentage of missing data is low, mean imputation is a very practical and common
strategy utilized by many researchers.
The variables were examined for any outliers by examining univariate
frequency distributions and bivariate scatterplots. Normality was tested using
Skewness and Kurtosis statistics and homogeneity of variance of all variables was
tested using the Levene’s statistic. Highly skewed data and excessive kurtosis can
90
affect overall fit, standard errors, and parameter estimates (Bagozzi & Yi, 1988).
Although there has not been a clear consensus established regarding “acceptable” nonnormality and no general cutoff for acceptable multivariate normality exists (Finney &
DiStefano, 2006), data with a skew above an absolute value of 3.0 and kurtosis above
an absolute value of 8.0 are considered problematic (Kline, 2005). The range of
standard errors of skewness and kurtosis of variables in this study were within the
expected range of chance fluctuation (Brown, 1997).
Demographic Characteristics of Participants
Adolescent participants and their parents were recruited from students from five
high schools among 10th and 11th grade in Seoul, Korea. One thousand three hundred
and eighty six (1396) surveys were distributed and a total 926 sets of data were
returned by the participants (66.8% response rate). Average of class size of Korean
high schools is 36 (The New York Times, 2010).
Principals from two high schools located in Seoul and Kyoungki-Do agreed for
their 10th and 11th graders to participate in this study. Of the 926 surveys that were
returned, 317 surveys were excluded for the following reasons: (1) one of parents had
remarried after divorce or loss of a partner (1%), (2) one parent did not return a survey
(9.6%) and (3) incomplete survey completion (23.7%). The final dataset consisted of
609 adolescents (2% of total high school students (total 296,282) in Seoul, Korea) and
91
their parents. There were no significant differences between the study participants and
those not included in the study sample on key demographic variables, which are age,
family income, and parental educational level. Although sibling information was
asked, majority of respondents did not answer.
The demographic characteristics of the fathers, mothers, and their adolescents
who participated in this study are presented in Table 2. The adolescents were
between16 - 19 years old [Boys (n = 253; M = 16.3, SD = .6); Girls (n = 360; M =
16.7, SD = .6)]. All fathers and mothers in this sample were the biological parents of
adolescents. The average age of fathers was 48 years (SD=3.5) at the time of
participation (40 to 65 years old). The average age of the mothers was 45 years old
(SD=3.5) at the time of participation (37 to 61 years old). Among 609 fathers and
mothers, 554 fathers (90.9 %) and 320 mothers (52.5%) were employed outside the
home on a full-time or part-time basis. Sixty nine percent (n = 421) of fathers and
51.5 % (n = 314) of mothers had more than a college education.
Compared to the general population in Korea, parents in this study were more
educated, were generally of a higher socio-economic status, and less than half of the
sample reported that they were Christians. Majority of parents in this study (70.3%
fathers and 52.4% mother 52.4%). were highly educated - college graduates and
higher. Almost half (43.3%) of the families reported incomes of more than 4 million
92
won per month which is considerably higher than the average family income of the
total population (1.1 million won per month in 2009 (Korean Statistical Information
Service, 2011)). Nationally only 16-20% of the population is Christian (Korean
Statistical Information Service, 2011) compared to the half the sample in this study
who indicated that they belonged to the Christian faith.
Table 1. Number and percentage of demographics by participants
Fathers N(%)
Mothers N(%)
30 (4.9)
67 (11.0)
75 (12.3)
292 (47.9)
223 (36.6)
274 (45.0)
46 (7.6)
57 (9.4)
75 (12.3)
241 (39.6)
262 (43.0)
185 (30.4)
Father N(%)
Mother N(%)
13 (2.1)
11 (1.8)
High school
168 (27.6)
279 (45.8)
Some college or Community college
64 (10.5)
79 (13.0)
College
270 (44.3)
201 (33.0)
Master or higher
94 (15.5)
49 (6.4)
Father N(%)
Mother N(%)
Full-time
526 (86.4)
224 (36.8)
Part-time
54 (8.9)
94 (15.4)
Home maker
4 (0.7)
260 (42.7)
Retired
6 (1.0)
23 (1.6)
Unemployed and looking for work
14 (2.3)
4 (0.7)
Too ill or disabled to work
5 (0.8)
4 (0.7)
Religion
Adolescents N(%)
Buddhism
Christianity
Catholic
No religion
Education
Less than high school
Occupation
Family income (Monthly)
Less than ₩200,000 (about $2300)
48 (7.9)
₩200,000 ~ 250,000 (about $2300 ~ $2875)
54 (8.9)
₩250,000 ~ 300,000 (about $2875 ~$3450)
76 (12.5)
₩300,000 ~ 350,000 (about $3450 ~ $4025)
96 (15.8)
₩350,000 ~ 400,000 (about $4025 ~ $4600)
84 (13.8)
More than ₩400,000 (about $4600)
251 (41.2)
Note: Percentages are in parenthesis.
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Table 2. Skewness and Kurtosis of demographic variables
Mean
SD
Skewness
SE
Kurtosis
SE
Age - Mother
44.9
3.50
.82
.09
1.4
.19
Age - Father
47.5
3.43
.75
.10
1.5
.19
Education - Mother
2.97
1.07
.38
.09
-1.07
.19
Education - Father
3.4
1.12
-.32
.09
-1.09
.19
Religion - Mother
2.93
0.96
-.71
.09
-.35
.19
Religion - Father
3.13
0.95
-.93
.09
-.05
.19
Family Income
4.42
1.67
-.68
.09
-.60
.19
Descriptive Analyses on the Nature of Adolescents’ Internet Use
97.4% of adolescents responded that they accessed the Internet at home and
over half of the respondents reported that they used the Internet in school. In all,
49.6% of students used the Internet in PC Bangs and roughly one third of respondents
used the Internet in the library. Only 17.6% of students accessed the Internet in public
places, such as community centers. Fifty two percent (52%) of students responded that
they had their own personal computers in their home. Ninety six percent (96%) of
students had more than one personal computer and 36% of students have more than
one laptop computer at home. Only six students (1%) reported that they did not have
an Internet access at home. Table 3a shows the number of personal computers and
laptops in adolescent homes.
94
Table 3a. Number and types of computers at home
Variables
N (%)
Cumulative %
0
20 (3.3)
3.3
1
462 (75.9)
79.1
2
115 (18.9)
98.0
3
10 (1.6)
99.7
4
1 (.2)
99.8
More than 5
1 (.2)
100.0
0
390 (64.0)
64.0
1
180 (29.6)
93.6
2
31 (5.1)
98.7
3
3 (.5)
99.2
4
3 (.5)
99.7
More than 5
2 (.3)
100.0
0
6 (1.0)
1.0
1
311 (51.1)
52.1
2
215 (35.3)
87.4
3
55 (9.0)
96.4
4
14 (2.3)
98.7
More than 5
8 (1.3)
100.0
Number of personal computers
Number of laptop computers
Total number of computers (PC +
LP)
Close to 4% of adolescents indicated that they secretly accessed the Internet
during class and less than one fourth of students accessed the Internet during class
with teachers’ permission. Over 30% of students used the Internet during lunch
breaks or after school hours (see Table 3b).
95
Table 3b. The nature of adolescent Internet use
Variables
Yes
No
N (%)
N (%)
Use Internet at PC Bang*
302 (49.6)
307 (50.4)
Use Internet at Friend’s House
323 (53.0)
286 (47.0)
Use Internet at Library
208 (34.2)
401 (65.8)
Use Internet at Public Place
107 (17.6)
502 (82.4)
Use Internet at Home
593 (97.4)
16 (2.6)
Have own PC with Internet Access
317 (52.1)
292 (47.9)
PC is in Adolescent’s Room
223 (36.6)
386 (63.4)
PC is in Parent’s Room
115 (18.9)
494 (81.1)
PC is in Dining Room
298 (48.9)
311 (51.1)
PC is in Family Study Room
168 (27.6)
441 (72.4)
Use Internet at School
322 (52.9)
287 (47.1)
23 (3.8)
586 (96.2)
149 (24.5)
460 (75.5)
curricular activities
194 (31.9)
415 (68.1)
Use Internet during lunch breaks or during recess
221 (36.3)
388 (63.7)
Use Internet secretly during class
Use Internet during class with teacher’s
permission
Use Internet after school or during extra-
*PC Bang is a variation of a LAN gaming center, where one can play multiplayer computer
games with others. PC bangs are extremely popular among all ages of South Koreans and
foreigners visiting South Korea alike.
As the tables 4a and 4b indicate, most adolescents use the Internet primarily for
“social blogging” and “watching movies” during weekends. This finding is consistent
with the 2004 data about Internet use among 2000 Korean high school students (Lee,
2005, October). The report indicated that the average of Internet use is around one and
one half hour. And average frequency of Internet use is less than two times per day.
These findings are similar to that found in the previous studies.
96
Table 4a. Descriptive statistics on the number of times adolescents access the Internet for
various educational, social, and recreational activities during weekdays and weekends
Weekdays
Weekends
M (SD)
M (SD)
To do study and do homework
2.14 (.85)
2.03 (.83)
To watch online classes
1.85 (.99)
1.76 (.89)
To do Internet surf for study
1.62 (.79)
1.57 (.74)
To do chatting
1.55 (.89)
1.64 (.92)
To access social blogs
1.53 (.85)
1.68 (.95)
To exchange social e-mails
1.56 (.87)
1.64 (.91)
To do Internet games
1.45 (.87)
1.62 (.92)
To watch/download movies, songs, etc.
1.94 (.93)
2.25 (.95)
To watch sports and surf sport-related information
1.78 (.94)
1.98 (.93)
Variables
* 1= None, 2= 1~2 times a day, 3= 3~4 times a day, 4= More than 5 times a day.
During typical weekdays and weekends, most adolescents reported that they
used the Internet a total of less than one hour. More than two third of the students
reported that they used the Internet for educational purposes for about less than an
hour per day. Around 80% of students watched online classes for less than an hour per
day. Only 16% of the students spent more than an hour doing social blogs on
weekdays, whereas 28% of them visited social blogs during weekends.
Table 4b. Descriptive statistics on the intensity of adolescents’ Internet use for educational,
social, and recreational activities on weekdays and weekends
Weekdays
Weekends
M (SD)
M (SD)
To study and school work
1.59 (.82)
1.69 (.92)
To watch online classes
1.67 (.99)
1.69 (.96)
To do chatting
1.31 (.67)
1.47 (.94)
1.68 (.91)
2.04 (1.00)
To do Internet games
1.35 (.78)
1.69 (.96)
To entertain
1.50 (.81)
1.85 (.94)
Variables
* 1=Less than one hour, 2=One to Two hours, 3=Two to three hours, 4=More than three
hours.
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Fifty percent (50%) of adolescents accessed the Internet for study and
homework for 1 to 2 times per day whereas about 50% of all or the adolescents did
not access the Internet to watch online classes or get study-related answers. Almost
70% of students reported that they did not use the Internet for chatting or e-mail
exchanging. Seventy four percent (74%) of adolescents did not use the Internet for
games during the weekdays (61% during weekends). This figure is not similar to the
numbers reported in the 2003 report about Korean adolescent’s life (Korean
Educational Development Institute, 2003). According the 2003 report, over 45% of
1752 general high school students used the Internet for gaming. In this study,
adolescents indicated that they used the Internet more for watching/downloading
movies and songs than gaming. The frequency of the number of times when
adolescents accessed the Internet is presented in Table 4c.
Almost all the adolescents who participated in this study had access to one or
more computers at home (96.7%) and accessed the Internet more frequently on
weekends than weekdays. Adolescents accessed the Internet more often for
educational purposes on weekdays than weekends and accessed the Internet for social
and recreational purposes more often on weekends than weekdays.
98
Table 4c. The Frequencies for the Numbers of Functional Use of the Internet Use (N=609)
Variables
During a typical
During a holiday or
weekday
weekend
N
%
N
%
None
135
22.2
154
25.3
One to Two times a weekday
306
50.2
332
54.5
Three to Four times a weekday
118
19.4
74
12.2
More than Five times a weekday
50
8.2
49
8.0
None
326
53.5
336
55.2
209
34.3
214
35.1
53
8.7
43
7.1
21
3.4
16
2.6
None
297
48.8
290
47.6
166
27.3
217
35.6
89
14.6
59
9.7
57
9.4
43
7.1
None
393
64.5
359
58.9
126
20.7
155
25.5
58
9.5
52
8.5
32
5.3
43
7.1
None
407
66.8
360
59.1
108
17.7
153
25.1
56
9.2
50
8.2
38
6.2
46
7.6
To do Study and do Homework
To get answers about study-related topics
To Watch Online Classes
To Exchange Social E-mails
To do Chatting
99
Table 4c continued. The Frequencies for the Numbers of Functional Use of the Internet Use
(N=609)
During a typical
During a holiday or
weekday
Variables
weekend
N
%
N
%
None
394
64.7
339
55.7
141
23.2
170
28.0
40
6.6
67
11.0
34
5.6
33
5.4
To Watch or download Movies, Songs, and Pictures
None
231
37.9
132
21.7
233
38.3
280
46.0
93
15.3
109
17.9
52
8.5
88
14.4
None
449
73.7
373
61.2
82
13.5
137
22.5
40
6.6
56
9.2
38
6.2
43
7.1
None
307
50.4
219
36.0
177
29.1
238
39.1
78
12.8
100
16.4
47
7.7
52
8.5
To do Internet Games
To Watch Sports and Surf Information
Factor Analysis and Reliability of Constructs
The purpose of this section is to identify the factor structure of specific
constructs. Factor analysis was run separately for fathers, mothers, and adolescents’
on items related to adolescent Internet use, parent-adolescent closeness, parent-
100
adolescent conflict, parental academic expectations, and adolescents’ behavior
problems.
Adolescent Internet Use
Frequency of Adolescent Internet Use on Weekdays and Weekends. The
variables associated with the frequency of adolescent Internet Use were subjected to
factor analysis using principal component factor analysis and the number of factors
was determined by criterion of eigenvalue greater than 1.00. The Bartlett’s test of
sphericity was significant (p≤.001) and the Kaiser-Meyer-Oklin value was .77 for
weekdays and .74 for weekends. Varimax rotation with Kaiser Normalization was
used to determine the best fit of the variables to each factor based on their loading.
Three factors (educational Internet use, social Internet use, and recreational Internet
use) emerged regarding adolescent Internet use on weekdays and weekends.
Based on the results from factor analysis, three items (the frequency of study email exchange, make new friends, and shopping) were dropped due to weak or double
loading. The factors explained 65.30 % and 62.52% of the variance for weekdays and
weekends respectively. Results of rotated matrix are presented in Table 5a.
101
Table 5a. Rotated Component Matrix – Frequency of adolescents’ Internet use
Factors
Adolescents’ Internet Use for Weekdays
1
2
3
Educational Use – Use Internet for study
.83
Educational Use – Watching Online Classes
.80
Educational Use - Cyber learning
.64
Social Use – Chatting
.91
Social Use – Working on Blogging
.57
Social Use – Exchanging Social Emails
.89
Variable 7 - Recreational Use – Doing Online games
.61
Variable 8 - Recreational Use – Watching and downloading
.72
Movies
Variable 9 - Recreational Use – Visit Sports related websites
.79
Adolescents’ Internet Use for Weekends
Variable 1- Educational Use – Use Internet for study
.84
Variable 2 - Educational Use – Watching Online Classes
.79
Variable 3 - Educational Use - Cyber learning
.63
Variable 4 - Social Use – Chatting
.80
Variable 5 - Social Use – Working on Blogging
.74
Variable 6 - Social Use – Exchanging Social Emails
.78
Variable 7 - Recreational Use – Doing Online games
.92
Variable 8 - Recreational Use – Watching and downloading
.59
Movies
Variable 9 - Recreational Use – Visit Sports related websites
.68
Note: Only factor loadings that equaled or exceeded .40 in absolute value were selected.
Intensity of Adolescent Internet Use on Weekdays and Weekends.
Intensity
of adolescent Internet use was also subject to factor analysis using similar criteria as
mentioned earlier (see Table 5b). The constructs explained 68% and 63% of the
variance for weekdays and weekends respectively.
102
Table 5b. Rotated Component Matrix – Intensity of adolescents Internet use
Factors
Adolescents’ Internet Use for Weekdays
1
2
Variable 1 – Educational Use - Use Internet for study
.67
Variable 2 – Educational Use - Watching Online Classes
.82
3
Variable 3 – Social Use – Chatting
.72
Variable 4 – Social Use – Social Searching
.55
Variable 5 – Recreational Use – Gaming
.91
Variable 6 – Recreational Use – Entertainments
.54
Adolescents’ Internet Use for Weekends
Variable 1 – Educational Use - Use Internet for study
.59
Variable 2 – Educational Use - Watching Online Classes
.82
Variable 3 – Social Use – Chatting
.80
Variable 4 – Social Use – Social Searching
.69
Variable 5 – Recreational Use – Gaming
.85
Variable 6 – Recreational Use – Entertainments
.73
Note: Wording of variables has been shortened for convenience of presentation.
Parent-Adolescent Relationships.
Parent-Adolescent Closeness. The principal-component factor analysis with
Varimax rotation was conducted and a criterion of eigenvalue greater than 1.00 was
used to identify the number of factors. The Bartlett’s test of sphericity was significant
(p≤.00) and the Kaiser-Meyer-Oklin value was .88 for the adolescent report, .89 for
the father report and .90 for the mother report.
Two factors emerged: (a) mother/father-adolescent closeness and (b)
mother/father-adolescent communication. Two items (“Doing things together” and
“Expressing affection”) were eliminated due to double-loading. The two-factor model
explained 65.7% (adolescent reports) and 64.3% (father reports) of the total variance
103
for F-A total closeness and 61.8% (adolescent reports) and 62% (mother reports) of
the variance for M-A total closeness. The results of factor analyses are presented in
Table 6a and 6b.
Table 6a. Rotated Component Matrix –mother-adolescent closeness
Adolescent Reports
Mother – Adolescent Closeness
1
2
Mother Reports
1
2
Variable 1 – Feel close
.75
.70
Variable 2 – Attentive to my problem
.79
.74
Variable 3 – Knows what I like
.70
.80
Variable 4 – Help me if I have a problem
.81
.73
Variable 5 – Expressing affection
.62
.58
Variable 6 – Talk about friends
.79
.85
Variable 7 – Talk about school
.80
.88
Variable 8 – Talk about problems/ concerns
.79
.80
Variable 9 – Talk about upcoming activities
.80
.73
Variable 10 – Talk about future plan
.70
.62
Table 6b. Rotated Component Matrix – father-adolescent closeness
Adolescent Reports
Father – Adolescent Closeness
1
2
Father Reports
1
2
Variable 1 – Feel close
.67
.71
Variable 2 – Attentive to my problem
.79
.73
Variable 3 – Knows what I like
.62
.80
Variable 4 – Help me if I have a problem
.84
.70
Variable 5 – Expressing affection
.62
.49
Variable 6 - Talk about friends
.82
.84
Variable 7 - Talk about school
.81
.87
Variable 8 - Talk about problems/ concerns
.84
.79
Variable 9 - Talk about upcoming activities
.81
.74
Variable 10 - Talk about future plan
.69
.65
Note: Only factor loadings that equaled or exceeded .40 in absolute value are given.
104
Parent-Adolescent Conflict. Parent-adolescent conflict was conceptualized as a
multidimensional construct: frequency of disagreements and conflict-intensity. The
scores on the conflict-intensity items were multiplied by the frequency of
disagreement scores. The principal-component factor analysis was then conducted on
these scores. Factor analysis was run separately on the father, mother, and adolescent
reports. The Bartlett’s test of sphericity was significant (p ≤.001) and the KaiserMeyer-Oklin value was.83 for the adolescent reports, .95 for the father reports,
and .90 for the mother reports. Similar items loaded for mother/father-adolescent issue
conflict-intensity for adolescent, mother, and father reports. This factor solution
explained 38% to 49% in father reports and 43% of the variance in mother reports of
the total variance. Two items (Helping out at home and Relationships with family
members) were excluded due to double loading. The results are presented in Table 7a
and 7b.
105
Table 7a. Rotated Component Matrix – Parent-adolescent conflict between mothers and
adolescents
Adolescent Reports
Mother Reports
Variable 1 – Money matters
.38
.49
Variable 2 – How you dress
.41
.63
Variable 3 – Your friends
.45
.64
Variable 4 – Behaviors in school
.71
.63
Variable 5 – Doing homework
.45
.44
Variable 6 – Your grades
.68
.59
Variable 7 – Playing video/Internet games
.39
.68
Variable 8 – Drinking or smoking
.79
.66
Variable 9 – Who you date
.78
.74
Variable 10 – Cursing
.53
.64
Variable 11 – General Internet use
.61
.79
Table 7b. Rotated Component Matrix – Parent-adolescent conflict between fathers and
adolescents
Adolescent Reports
Father reports
Variable 1 – Money matters
.44
.63
Variable 2 – How you dress
.54
.63
Variable 3 – Your friends
.47
.66
Variable 4 – Behaviors in school
.78
.60
Variable 5 – Doing homework
.57
.44
Variable 6 – Your grades
.61
.67
Variable 7 – Playing video/Internet games
.70
.76
Variable 8 – Drinking or smoking
.79
.71
Variable 9 – Who you date
.62
.77
Variable 10 – Cursing
.67
.48
Variable 11 – General Internet use
.53
.77
Parental Cultural Academic Expectations. The exploratory factor analysis
was conducted for parental academic expectations using the Principle Component
106
method. Factor analysis was run separately for fathers and mothers. The factor
analysis produced a two-factor solution (Personal achievement: goals around one’s
educational achievement, Family achievement: family recognition through
achievement). The Bartlett’s test of sphericity was significant (p≤.001) and the KaiserMeyer-Oklin value was .51 for the father reports and .50 for the mother reports. This
factor solution explained 40% in father reports and 40% in mother reports of the total
variance. The results were presented in Table 8.
Table 8. Rotated Component Matrix – Parental cultural academic expectations
Fathers
Variable 1 - One need not focus all energies on one’s studies
Variable 2 - One should be discouraged from talking about
one’s accomplishments
Variable 3 - One need not minimize or depreciate one’s own
achievement
Variable 4 – Educational and career achievements need not be
one’s top priority
Variable 5 - One need not achieve academically in order to
make one’s parents proud
Variable 6 - One’s achievements should be viewed as family’s
achievements
Variable 7 – Educational or occupational failure does not bring
shame to the family
Mothers
.79
.75
.39
.31
.3
1
.33
.65
.68
.75
.77
.61
.59
.52
.50
Reliability analyses were performed on all the above scales and the results
indicated that Cronbach’s alphas were in the acceptable range (> .70) (George &
Mallery, 2005) with the exception of parental cultural academic expectations. Table
107
9a shows a summary of the Cronbach’s alphas of the independent variables in the
study.
Table 9a. Cronbach’s alphas of constructs
Cronbach’s alpha
Adolescent Internet
Intensity
Frequency
Use
Weekdays
Weekends
Weekdays
Weekends
Educational Use
.54
.55
.68
.67
Social Use
.52
.49
.84
.79
Recreational Use
.54
.38
.64
.55
Parent-Adolescent
Adolescent Reports
Father Reports
Relationships
Reports
Mother-A Closeness
.90
Father-A Closeness
.92
Mother-A Conflict
.90
Father-A Conflict
.88
Parental Expectations
Mother
.90
.92
.84
.90
.57
.53
The Means and SDs along with the skewness and kurtosis of the constructs are
shown below.
108
Table 9b. Skewness and Kurtosis of Independent Variables
Mean
SD
Skewness
SE
Kurtosis
SE
EDU-Intens-WDays
1.63
.75
1.22
.09
.97
.19
SOC-Intens-WDays
1.49
.65
1.49
.09
2.05
.19
REC-Intens-WDays
1.51
.62
1.16
.09
.89
.19
EDU-Intens-WKEnds
1.69
.77
1.16
.09
.76
.19
SOC-Intens-WKEnds
1.76
.74
.99
.09
.44
.19
REC-Inten-WKEnds
1.68
.74
1.18
.09
.88
.19
EDU-Freq-WDays
1.87
.68
.74
.09
.05
.19
SOC-Freq-WDays
1.54
.75
1.53
.09
1.67
.19
REC-Freq-WDays
1.73
.70
1.01
.09
.62
.19
EDU-Freq-WKEnds
1.79
.63
.90
.09
.89
.19
SOC-Freq-WKEnds
1.65
.77
1.29
.09
.99
.19
REC-Freq-WKEnds
1.95
.67
.68
.09
.06
.19
A-M Closeness
3.30
.58
-.92
.09
.70
.19
M-A Closeness
3.18
.51
-.54
.09
.23
.19
F-A Closeness
2.89
.58
-.29
.09
.18
.19
A-F Closeness
2.98
.66
-.38
.09
-.42
.19
M-A conflict
2.08
.36
-.15
.09
-.05
.19
A-M conflict
1.46
.51
.58
.09
-.02
.19
A-F conflict
1.28
.50
.97
.09
1.04
.19
F-A conflict
1.36
.49
.60
.09
-.03
.19
PE - Mother
2.74
.23
-.04
.09
2.36
.19
PE - Father
2.78
.24
-.36
.09
2.88
.19
Note. WDays – Weekdays, WKEnds = Weekends
Adolescent Behavioral Problems and Academic Achievement
Adolescent Behavior Problems. An exploratory factor analysis was conducted
for items assessing adolescents’ behavior problems using the principle component
factor analysis. The factor analysis produced a five-factor solution (somatic
complaints, anxious/ depressed behaviors, withdrawal, aggressive behaviors and
delinquent behaviors) with 49 items. The Bartlett’s test of sphericity was significant
(p≤.001) and the Kaiser-Meyer-Oklin value was .86 for the adolescent reports. Ten
109
items were eliminated due to double loading or weak loading. The final five-factor
model explained 42% of the total percentages of variance. The results are presented in
Table 10a.
Table 10a. Rotated Component Matrix – Adolescent behavioral problems
Factors
1
Variable 1 -
Feel lonely
.51
Variable 2 -
Cry a lot
.41
Variable 3 -
Deliberately hurt or kill
oneself
Variable 4 -
Afraid of doing something
bad
.60
.61
Variable 5 -
Feel that no one loves me
.42
Variable 6 -
Feel worthless or inferior
.46
Variable 7 -
Nervous or tense
.71
Variable 8 -
Fearful or anxious
.72
Variable 9 -
Unhappy, sad, or depressed
.58
Variable 10
Feel too guilty
.54
Variable 11
Suspicious
.53
Variable 12
Think about hurting or killing
oneself
Variable 13
Worry a lot
2
.52
.70
Variable 14- Shy
.60
Variable 15
.48
Refuse to talk
Variable 16- Self-conscious or easily
.67
embarrassed
Variable 17- Rather be alone than with
.50
others
Variable 18- Secretive or keep things to
myself
.57
3
4
5
110
Table 10a continued. Rotated Component Matrix – Adolescent behavioral problems
Factors
1
2
3
4
5
Variable 19- Feel dizzy
.62
Variable 20- Headaches
.61
Variable 21- Aches or pains
.50
Variable 22- Nausea, feel sick
.73
Variable 23- Problems with eyes
.47
Variable 24- Rashes or other skin problems
.35
Variable 25- Stomach-aches or cramps
.61
Variable 26- Vomiting, throwing up
.52
Variable 27- Feel overtired without reason
.54
Variable 28- Argue a lot
.50
Variable 29- Mean to others
.54
Variable 30- Destroy my own things
.50
Variable 31- Destroy things belonging to
others
.57
Variable 32- Jealous of others
.56
Variable 33- Stubborn
.42
Variable 34- Scream a lot
.48
Variable 35- Moods or feelings suddenly
.45
Variable 36- Disobey at school
.55
Variable 37- Get in many fights.
.50
Variable 38- Louder than other kids
.49
Variable 39- Talk too much
.42
Variable 40- Tease others a lot
.46
Variable 41- Have a hot temper
.51
Variable 42- Rather be with older kids
.37
Variable 43- Rather be with younger kids
.35
Variable 44
Run away from home
.50
Variable 45
Set fires
.54
Variable 46
Steal at home
.54
Variable 47
Steal from places other than
home
.55
Variable 48
Use searing or dirty language
.51
Variable 49
Cut classes or skip school
.49
111
Reliability analyses were performed on adolescent outcome variables and the
results indicated that Cronbach’s alphas were in the acceptable range (> .70) (Greorge
& Mallery, 2005) with the exception of social withdrawal and delinquent behaviors.
Table 10b shows a summary of the Cronbach’s alphas of the independent variables in
this study.
Table 10b. Cronbach’s alphas of constructs
Cronbach’s alpha
Adolescents Behavioral Problems (adolescent report)
.87
Internalizing behaviors
Anxious/Depressed
.81
Social Withdrawal
.66
Somatic Complaints
.73
Externalizing behaviors
.83
Aggressive Behaviors
.78
Delinquent Behaviors
.63
The Means and SDs along with the skewness and kurtosis of these constructs are
shown below (see Table 10c).
Table 10c. Means and SD’s of Adolescents Behavioral Problems
Behavioral Problems
Mean
SD
Skewness
SE
Kurtosis
SE
Depression
1.72
.42
.29
.09
-.61
.19
Somatic Symptoms
1.58
.48
.64
.09
-.36
.19
Withdrawn
1.82
.55
.22
.09
-.82
.19
Aggression
1.71
.40
.28
.09
-.56
.19
Delinquency
1.63
.40
.43
.09
-.31
.19
Adolescent Academic Achievement. Academic achievement was assessed
based on student reported academic grades on 4 subjects – Korean, English, Math,
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and Social Science. In Korea, students are graded on a scale from 1 to 9. Scale 1
represents the highest grade and scale 9 represents the lowest grade. Students receive
the grade based on percentile scores instead of raw scores in the Korean Scholastic
Assessment Test. Scales used for this study were obtained from a pre-KSAT in 2009
fall. Students in this study scored between 1 and 8 grades on all subjects. The
average grade of subjects - Korean, English, Math, and Science- was approximately
3 (see Table 11).
Table 11. Descriptive Statistics for the Adolescent Academic Achievement
Adolescent’s Grades
Mean
SD
Skewness
SE
Kurtosis
SE
Korean
2.81
1.56
.80
.09
.12
.19
English
2.92
1.57
.84
.09
.33
.19
Math
2.99
1.71
.99
.09
.82
.19
Social Science
3.27
1.50
.59
.09
-.13
.19
Testing Hypotheses
Hypothesis 1. Boys and girls are different in the frequency and the intensity
of educational, social, and recreational use of Internet.
H1-1. Nature of Internet use on weekdays and weekends. To assess gender
differences in the nature of Internet use, Yates’ Chi-Square values were computed and
the results are presented in Table 12a. More boys (77%) used the Internet at PC Bang
than girls (30%), while more girls (65%, 41%) used the Internet at school and library
than boys (36%, 25% respectively). Fewer boys (46%) had their own PC than girls
113
(56%). Most boys and girls reported that PCs were located at public place in the home,
such as the dining room and/or family study room. Although more than half of
students reported that they had their own PC, only one third of the students reported
that PCs were located in their room. More boys (81%) did not use the Internet during
classes with teachers’ permission than girls (72%). More girls (37%, 43 %
respectively) reported that they used the Internet during their lunch break and afterschool activities than boys (24%, 27%).
114
Table 12a. The Results of Yates’ Chi-Square Test - Gender Differences/Similarities in the
nature of Internet Use
Boys
Girls
No
Yes
No
Yes
N (%)
N (%)
N (%)
N (%)
x²
At Home
7 (2.8)
244 (97.2)
9 (2.5)
349 (97.5)
.0
At School
160 (63.7)
91 (36.3)
127 (35.5)
231 (64.5)
46.2**
At PC Bang
58 (23.1)
193 (76.9)
249 (69.6)
109 (30.4)
125.5**
At Friends’ House
123 (49.0)
128 (51.0)
163 (45.5)
195 (54.5)
.58
At Library
189 (75.3)
62 (24.7)
212 (59.2)
146 (40.8)
16.3**
At Public Place
211 (84.1)
40 (15.9)
291 (81.3)
67 (18.7)
.61
Student has own PC
136 (54.2)
115 (45.8)
156 (43.6)
202 (56.4)
6.23*
In Parent’s Room
208 (82.9)
43 (17.1)
286 (79.9)
72 (20.1)
.67
In Dining Room
119 (47.4)
132 (52.6)
192 (53.6)
166 (46.4)
2.04
In Student’ Room
166 (66.1)
85 (33.9)
220 (61.5)
138 (38.5)
1.20
In Family Study
185 (73.7)
66 (26.3)
256 (71.5)
102 (28.5)
.26
240 (95.6)
11 (4.4)
346 (96.6)
23 (3.8)
.19
203 (80.9)
48 (19.1)
257 (71.8)
101 (28.2)
6.11*
activities
191 (76.1)
60 (23.9)
224 (62.6)
134 (37.4)
11.82**
During Lunch break
183 (72.9)
68 (27.1)
205 (57.3)
153 (42.7)
14.95**
Variables
Internet use
PC location at Home
Room
Using the Internet
During classes secretly
During classes
with permission
During extra-curricular
*p<.05, **p<.01.
In conclusion, Korean boys and girls differed in the ways that they use the
Internet. Girls were more likely to own their own computers at home than boys. Girls
were also more likely to use the Internet at school and the library then boys, while
boys accessed the Internet at PC Bangs. Since girls used the Internet at school more
often than boys, they were also more likely to access the Internet during classes, extra-
115
curricular activity times, and lunch breaks than boys. Girls were more likely to use the
Internet to watch online education classes and blogged more frequently and for longer
times than boys, whereas boys were more likely to access the Internet more frequently
for playing Internet games than girls.
H1-2. Types of Internet use on weekdays and weekends. There were statistically
significant gender differences in total Internet use on weekdays (F (1, 606) = 14.67, p
≤ .001) with effect size of 0.07, which is quite small (Cohen, 1988), and on weekends
(F (1, 606) = 25.1, p ≤ .001) with a quite small effect size. When the results for the
Internet use were considered separately, Educational use (F (1, 606) = 6.96, p ≤ .001)
and Recreational use (F (1, 606) = 27.89, p ≤ .001) reached statistical significance on
weekdays. Recreational use (F (1, 606) = 55.96, p ≤ .001) was statistically significant
on weekends. Boys reported less frequent use in Educational use (M=1.75, SD= .61)
than girls (M=1.88, SD= .58) on weekdays while they (M=1.77, SD= .04) spent more
hours for recreational use than girls (M=1.40, SD= .03) regardless of the day (see
Table 12b).
116
Table 12b. Multivariate analysis of variance – Types of adolescent Internet use
Male
Female
(N=251)
(N=358)
M(SD)
M(SD)
Educational Use
1.75(.61)
1.88(.58)
6.96**
.011
.008
Social Use
1.62(.78)
1.58(.68)
.46
.001
.003
Recreational Use
1.99(.68)
1.73(.55)
.044
.043
Variables
F (1,607)
Partial Eta
Adjusted
Squared
R
squared
Weekdays
27.89***
*p<.05, **p<.01; Multivariate F (1, 606) = 14.67, p ≤ .001, Wilks’
Lambda= .932, η²= .068.
Male
Female
(N=251)
(N=358)
M(SD)
M(SD)
Educational Use
1.60(.04)
1.70(.04)
2.94
.005
.002
Social Use
1.64(.03)
1.62(.03)
.18
.000
-.002
Recreational Use
1.77(.04)
1.40(.03)
55.96***
.085
.082
Variables
F (1,606)
Partial Eta
Adjusted
Squared
R
squared
Weekends
*p<.05, **p<.01; Multivariate F (1, 606) = 25.1, p ≤ .001, Wilks’ Lambda= .89, η²=.11
Hypothesis 2-1. Adolescents’ Internet use has a direct effect on their
adolescent outcomes.
Hypothesis 2-2. Boys and girls are different in the association between
adolescents’ Internet use and their academic achievement.
H2-1.1. Adolescents’ Internet use has a direct effect on their academic
achievement.
Latent-variable structural equation models were used to empirically test the proposed
theoretical model. To begin the test the proposed conceptual model, first the
distribution of constructs was examined. Although constructs indicated univariate
117
normality, multivariate normality could not be assumed. Blom’s transformation (Blom,
1958) was conducted and all direct and indirect models were run using the
transformed scores.
The fit of the model was assessed through fit indices, which provided an
indication of the proportion of the variance in the sample variance-covariance matrix
that was accounted for by the model. The acceptable range for the GFI is .90 and
above and the acceptable range for the Adjusted Goodness of Fit Index (AGFI) is .90
and above (Byrne, 2001; Kline 2005). The Root Mean Square Error of Approximation
(RMSEA) was also used to determine model fit. Generally accepted guidelines for the
RMSEA are values less that .05; values between .08 and .05 are indicators of
reasonable fit; values between .10 and .08 are indicators of fair fit. RMSEA values
greater than .10 represent a poor fitting model (Tate, 1998).
Models were first run with weekday and weekend Internet use data and the
models indicated similar pathways. Hence, data from both weekdays and weekends
were combined into a single model. Each model was run for the total sample and
separately for boys and girls.
The model of the direct effects of the association between Internet use and
academic achievement indicated a poor fit – χ2 (29, N = 609) = 168.2, p≤.001 with
GFI= .93, AGFI= .87 and RMSEA= .11. Figure 1a indicates that adolescent Internet
118
use was significantly associated with their academic achievement. Among three
structural paths in the hypothesized model, two were significant. Specifically, the path
from the educational use to academic achievement (β = .28, p ≤ .001) was significant
and positive, while the path from social use (β = -.28, p ≤ .01) to academic
achievement was negative. Results indicated that higher educational Internet use was
associated with a higher grade of academic achievement, while higher social Internet
use was associated with a lower grade of academic achievement.
This direct effects model was run to establish the presence of the direct paths
between type of Internet use and academic achievement (as required by Baron and
Kenny, 1986). Although this model only indicated poor fit (as indicated by the AGFI
and RMSEA fit indices above), further improvements to the model were not made as
those adjustments were made to the final model (after the mediators were entered).
Figure 1a. Direct effects between the types of adolescent Internet use and academic
achievement
Note: * p< .05, ** p< .01, *** p< .001.
119
Internet use and their academic achievement.
Simultaneous group analysis was conducted for boys and girls. The models
indicated moderate fit - χ2 (52, N = 609) = 261.5, p≤.001 with GFI= .93, AGFI= .86,
RMSEA= .07. Critical Ratio (CR) of differences in the strength of specific pathways
was examined (if the CR difference was equal to or higher than 1.96, it indicates that
there is path varied in strength across the two groups) (Garson, 2005). The pathway
between educational Internet use and academic achievement was significant for boys
and not for girls. The pathway between recreational Internet use and academic
achievement was significant for boys and not for girls. The link between social
Internet use and academic achievement was significant for girls but not for boys. The
results are presented in Figure 1b.
Figure 1b. Gender differences in the direct relationship between the types of adolescent
Internet use and academic achievement
Note: Boys/ Girls. * p< .05, ** p< .01, *** p< .001
120
H2-1.2. Adolescents’ Internet use has a direct effect on their internalizing problematic
behaviors.
Figure 2a. Direct links between the types of adolescent Internet use and internalizing problem
behaviors
Note:* p< .05, ** p< .01, *** p< .001
H2-2.2. Boys and girls are different in the association between adolescents’ Internet
use and their internalizing problematic behaviors.
Simultaneous group analysis indicated poor fit χ2 (42, N = 609) = 247.9, p
≤ .001with GFI= .92, AGFI=. 83, RMSEA=. 09. The pathway between educational
Internet use and internalizing behaviors was significant only for boys and not for girls.
121
Figure 2b. Gender differences on the direct relationship between the types of adolescent
Internet use and internalizing problem behaviors
Note: Boys/ Girls. * p< .05, ** p< .01, *** p< .001
H2-1.2. Adolescents’ Internet use has a direct effect on their externalizing
The structural model of the direct effects of the Internet use on externalizing
behavior problems yielded the following results:
χ2 (15, N = 609) = 250.6, p
≤ .001with GFI= .93, AGFI= .89, RMSEA= .14 (see Figure 1c) – not a good fit.
Educational Internet use was negatively associated with externalizing behavior
problems (β = -.19, p ≤ .01). Social Internet use was positively associated with
externalizing behavior problems (β = .34, p ≤ .01). (see Figure 3a).
122
Figure 3a. Direct effect between the types of adolescent Internet use and externalizing
problem behaviors
Note: * p< .05, ** p< .01, *** p< .001
H2-2.3. Boys and girls are different in the association between adolescents’ Internet
use and their externalizing problematic behaviors.
The structural model of the direct effects of the Internet use on externalizing
behavior problems yielded a poor fit - χ2 (28, N = 609) = 205.3, p ≤ .001 with
GFI= .93, AGFI= .81, RMSEA= .10. Educational Internet use is linked to
externalizing behaviors for boys but not girls. The association between social Internet
use and externalizing behaviors is similar for boys and girls. However, the Critical
Ratio (CR) of differences in the strength of this pathway was lower than 1.96, which
indicated that there was not a path varied in strength across the two groups. The
results are presented in Figure 3b.
123
Figure 3b. Gender differences on the direct relationships between types of adolescent Internet
use and externalizing problem behaviors
Note: Boys /Girls. * p< .05, ** p< .01, *** p< .001
Hypothesis 3-1. Does the nature of adolescents’ Internet use affect their
academic achievement/ behavioral adjustment through P-A closeness/ conflict
(Mediation effects)?
Research question 3-2. Are these pathways different for boys and girls?
(Moderating role of adolescent gender)
H3-1.1. Adolescents’ Internet use has a effect on academic achievement through
parent-adolescent relationships. (father-adolescent relationships)
The structural model of the indirect effects of Internet use on academic
achievement yielded a good overall fit X² (62, N = 609) = 225.9, p ≤ .001; GFI=.95,
AGFI=.92, RMSEA=.06. The results are presented in Figure 4a.
124
Figure 4a. Indirect effects linking the types of adolescent Internet use and academic
achievement through father-adolescent relationships
Note: * p< .05, ** p< .01, *** p< .001.
Two significant indirect pathways were found:
(a) Educational Internet use to F-A conflict (β=- .13, p ≤ .05), F-A conflict to
academic achievement (β= -.11, p ≤ .05), and the direct effect between
educational Internet use and academic achievement ( β= .25, p ≤ .01) – partial
mediation
(b) Social Internet use to F-A conflict (β= .29, p ≤ .01), F-A conflict to academic
achievement (β= -.11, p ≤ .05), and the direct effect between social Internet
use and academic achievement (β= -.34, p ≤ .001) – partial mediation
These two pathways were examined its significance using the Sobel test and
bootstrapping. The results were presented in Table 13a.
125
Table 13a. Significance of indirect effects of links between the type of adolescent Internet use
and academic achievement through father-adolescent relationships - Bootstrapping.
Mediational
Unstandardized
Bootstrapping 95% Confidence
Indirect Effect
Interval
(Standardized/ SE)
Z
Pathways
Percentile
Bias-Corrected
Low /Upper
Low /Upper
Unstandardized Direct Effect (Standardized /SE)
EDU→FA CF→AA
.007 (.004/ .015)
2.40
-.031/ .027
-.030/ .028*
EDU→ FA CF: .330 (.200/ .066), EDU→AA: .330 (.200/ .059) FA CF →AA: -.716 (.223/ .047)
SOC→FA CF→AA
-.073(-.073/ .013)
2.72
-.065/ -.013**
SOC→ FA CF: .247 (.157/ .054), SOC→AA: -.663 (-.336/.049)
-.069/ -.015***
FA CF →AA: -.463 (-
.149/ .046)
Note: Standardized effects are presented in parenthesis. Direct effects are presented in lower
row of the model: Unstandardized direct effect (standardized direct effect/ SE). EDU =
Educational Internet use, SOC = Social Internet use, AA = Academic Achievement, FA CF =
Father-adolescent conflict, z value of 1.96 or larger indicates a significant indirect effect (p ≤.
05) (Sobel, 1982).
According to the results of the Sobel test and bootstrapping, two indirect
pathways from educational and social use to academic achievement through fatheradolescent conflict were significant.
H3-1.1. Adolescents’ Internet use has an effect on academic achievement through
parent-adolescent relationships. (mother-adolescent relationships)
The indirect effects model linking the types of adolescent Internet use and
academic achievement through mother-adolescent closeness and conflict indicated
poor fit (X² (64, N = 609) = 650.1, p ≤ .001; GFI= .89, AGFI= .81, RMSEA= .12). To
improve the fit of the model, modification indices were examined. Error terms were
covaried based on information provided in the modification indices and whether
126
covarying the specific error terms made substantive sense. Five error terms were
covaried. Co-varying these error terms allowed for an improvement in model fit (X²
(59, N = 609) = 213.9, p ≤ .001; GFI= .96, AGFI= .92, RMSEA= .06). The X²Δ (5, N
=609) = 436.8, p ≤ .001.
Figure 4b. Indirect effect of adolescent Internet use on academic achievement through motheradolescent relationships
Note: * p< .05, ** p< .01, *** p< .001
Two indirect pathways were found significant between social Internet use to
academic achievement through mother-adolescent conflict social Internet use:
(a) Educational Internet use to academic achievement through mother-adolescent
closeness – educational Internet use to mother-adolescent closeness (β= .25, p
≤ .001), mother-adolescent closeness to academic achievement (β= .14, p
127
≤ .01), and educational Internet use to academic achievement (β= .23, p
≤ .001) – partial mediation,
(b) Social Internet use to academic achievement through mother-adolescent
closeness - social Internet use to mother-adolescent closeness (β= -.26, p
≤ .001), mother-adolescent closeness to academic achievement (β= .14, p
≤ .01), and social Internet use to academic achievement (β= -.31, p ≤ .01) –
partial mediation,
These two pathways were examined its significance using Sobel test and
bootstrapping. The results were presented in Table 13b.
Table 13b. Significance of indirect effects of links between the type of adolescent Internet
use and academic achievement through mother-adolescent relationships - Bootstrapping.
Mediational
Unstandardized
Indirect Effect
Interval
(Standardized/ SE)
Z
Pathways
Percentile
Bias-Corrected
Low /Upper
Low /Upper
EDU→MA
.085 (.052/ .019)
2.15
.019/ .094***
.021/ .098***
CL→AA
EDU→ MA CL: .122 (.210/ .059)
EDU→AA: .250 (.152/ .050) MA CL →AA: .699
(.246/ .056)
SOC→MA
-.084 (-.042/ .018)
1.77
-.078/ -.008*
-.087/ -.014**
CL→AA
SOC→ MACL: -.158 (-.214/ .064)
SOC→AA: -.651 (-.330/ .050) MACL
→AA: .531 (.198/ .063)
Note: Standardized effects are presented in parenthesis. Direct effects are presented in lower
row of the model: Unstandardized direct effect (standardized direct effect/ SE). EDU =
Educational Internet use, SOC = Social Internet use, AA = Academic Achievement, MA CL =
Mother-adolescent closeness, z value of 1.96 or larger indicates a significant indirect effect (p
≤. 05) (Sobel, 1982).
128
According to the results of the Sobel test and bootstrapping, two indirect
pathways were found to be significant.
H3-2.1. Boys and girls are different in the pathways from adolescents’ Internet use to
their academic achievement through parent-adolescent relationships (fatheradolescent relationships).
None of the pathways linking type of adolescents’ Internet use and academic
achievement through father-adolescent closeness and father-adolescent conflict were
significant for boys and girls (see Figure 4c).
Figure 4c. The indirect relationship between adolescent Internet use, father-adolescent
relationship, and academic achievement by youth gender
Note: Only significant paths are presented. Boys (Regular)/ Girls(Italic). * p< .05, ** p< .01,
*** p< .001
129
their academic achievement through parent-adolescent relationships (fatheradolescent relationships).
achievement through mother-adolescent closeness and mother-adolescent conflict
were significant for boys and girls (see Figure 4d).
Figure 4d. The indirect relationship among Internet use, mother-adolescent relationship and
academic achievement by youth gender
Note: Only significant paths are presented. Boys (Regular)/ Girls(Italic). * p< .05, ** p< .01,
*** p< .001
H3-1.2. Adolescents’ Internet use has an effect on internalizing behavior problems
through parent-adolescent relationships (father-adolescent relationships).
130
Although Baron and Kenny (1986) required the significant direct link between
independent and dependent variables, many significant indirect pathways have been
reported without this premise (MacKinnon, Fairchild, & Fritz, 2007).
The structural model of the indirect effects of the Internet use on academic
achievement yielded a good fit X² (50, N = 609) = 176.0, p ≤ .001; GFI= .96,
AGFI= .93, RMSEA= .06 (Figure 5a).
Figure 5a. Indirect effect of Internet use through father-adolescent relationships on
internalizing behaviors
Note: * p< .05, ** p< .01, *** p< .001
Four indirect pathways were found between types of adolescent Internet use and
internalizing behaviors (a) Educational Internet use to F-A closeness (β= .23, p ≤ .001), F-A closeness to
internalizing behaviors (β=-.24, p ≤ .001) – complete mediation,
(b) Social Internet use to F-A closeness (β=-.33, p ≤ .01), F-A closeness to
internalizing behaviors (β=-.24, p ≤ .001) – complete mediation,
131
(c) Educational Internet use to F-A conflict (β=-.12, p ≤ .05), F-A conflict to
internalizing behaviors (β= .16, p ≤ .001) – complete mediation,
(d) Social Internet use to F-A conflict (β= .27, p ≤ .01), F-A conflict to
internalizing behaviors (β=.16, p ≤ .001) – complete mediation,
Four pathways were examined the significance using the Sobel test and
and internalizing behaviors through father-adolescent relationships - Bootstrapping.
Mediational
Unstandardized
Indirect Effect
Interval
(Standardized/ SE)
Z
Pathways
Percentile
Bias-Corrected
Low /Upper
Low /Upper
EDU→FA CF→IT
-.008 (-.008/ .010)
.21
EDU→ FA CF: -.018 (-.037/ .047)
-.028/ .012
-.029/ .010
EDU→IT: .029 (.028/ .040)
FA CF →IT: .470 (.220/ .044)
SOC→FA CF→IT
.097 (.059/ .017)
3.17
SOC→ FA CF: .193 (.259/ .053)
.031/ .101**
.027/ .095***
SOC→IT: -.073 (-.044/ .054)
FA CF →IT: .503 (.227/ .045)
EDU→F-A CL→IT
-.035 (-.035/ .011)
3.31
EDU→ F-A CL: .104 (.145/ .040)
-.060/ -.015***
-.061/ -.015***
EDU→IT: .058 (.057/ .041)
FA CL →IT: -.341 (-.241/ .042)
SOC→FA CL→IT
.137 (.074/ .027)
3.24
SOC→ FA CL: -.281 (-.262/ .066)
.025/ .131***
.028/ .137***
SOC→IT: -.089 (-.048/ .055)
FA CL →IT: -.486 (-.282/ .056)
Note: Unstandardized effects are presented in parenthesis. Direct effects are presented in
lower row of the model (standardized direct effect/ SE). EDU = Educational Internet use,
SOC = Social Internet use, FA CF = Father-adolescent conflict, FA CL = Father-adolescent
closeness, IT = Internalizing problematic behaviors. A z value 1.96 or larger indicates a
significant indirect effect (p ≤. 05) (Sobel, 1982).
According to the results of Sobel test and bootstrapping, three indirect pathways were found
to be significant.
132
H3-1.2. Adolescents’ Internet use has an effect on internalizing behavior problems
through parent-adolescent relationships (mother-adolescent relationships).
The structural model of the indirect effects of the Internet use on internalizing
problem behaviors yielded poor overall fit X² (52, N = 609) = 617.4, p ≤ .001;
GFI= .88, AGFI= .90, RMSEA= .13). Modification indices were examined and
specific error terms were covaried based on whether it made substantive sense. This
was done one by one starting with the largest modification index and done one by one
and the improvement in fit was noted. Three error terms were covaried. Co-varying
these error terms allowed for an improvement in fair model fit (X² (48, N = 609) =
237.7, p ≤ .001; GFI= .95, AGFI= .90, RMSEA= .08). The X²Δ (3, N =609) =397.7, p
≤ .001.
Figure 5b. Indirect effect of types of Internet use on internalizing behaviors through motheradolescent relationships
Note: * p< .05, ** p< .01, *** p< .001.
133
One indirect pathway was found between types of Internet use to internalizing
behaviors through mother-adolescent conflict:
(a) Education Internet use and M-A conflict (β= -.10, p ≤ .05), M-A conflict to
internalizing problem behaviors (β=.29, p ≤ .001) – complete mediation,
These four pathways were examined the significance using the Sobel test and
Table 14b. Significance of indirect effects of links between the type of adolescent Internet use
and internalizing behaviors through mother-adolescent relationships - Bootstrapping.
Mediational
Unstandardized
Indirect Effect
Interval
(Standardized/ SE)
Z
Pathways
Percentile
Bias-Corrected
Low /Upper
Low /Upper
EDU→MA CF →IT
-.008 (-.014/ .018)
2.25
EDU→ MA CF: -.011 (-.039/ .014)
-.051/ .021
-.051/ .014
EDU→IT: .029 (.049/ .024)
MA CF →IT: .737 (.366/ .096.)
Note: Unstandardized effects are presented in parenthesis. Direct effects are presented in
lower row of the model (standardized direct effect/ SE). EDU = Educational Internet use, MA
CF = Mother-adolescent conflict, IT = Internalizing problematic behaviors. A z value 1.96 or
larger indicates a significant indirect effect (p ≤. 05) (Sobel, 1982).
According to the results of the Sobel test and bootstrapping, the indirect
pathway from educational use to internalizing behaviors through mother-adolescent
conflict was significant.
134
their internalizing behavior problems through parent-adolescent relationships.
None of the pathways linking type of adolescents’ Internet use and internalizing
problem behaviors through father-adolescent closeness and mother-adolescent conflict
were significant for boys and girls.
Two of the pathways were statistically significant. However, none of indirect
linking type of adolescents’ Internet use and internalizing problem behaviors through
mother-adolescent closeness and mother-adolescent conflict was significant for boys
and girls (see Figure 5c).
Figure 5c. The indirect relationship between Internet use, mother-adolescent relationship and
internalizing behaviors by youth gender
Note: Only significant paths are presented. Boys (Regular)/ Girls (Italic). * p< .05, ** p< .01,
*** p< .001
135
H3-1.3. Adolescents’ Internet use has an effect on externalizing behavior problems
through parent-adolescent relationships (father-adolescent relationship).
The model linking the types of adolescent Internet use and externalizing
behavior problems through father-adolescent relationships indicated good overall
model fit (X² (39, N = 609) = 144.8, p ≤ .001; GFI= .97, AGFI= .93, RMSEA=. 06).
Among the eleven structural paths, four indirect paths were found to be statistically
significant (Figure 6a).
Figure 6a. Indirect effects of Internet use on externalizing behaviors through father-adolescent
relationships
Note: * p< .05, ** p< .01, *** p< .001.
Four indirect pathways were found between types of Internet use to
externalizing behaviors through mother-adolescent conflict:
136
(a) Educational Internet use to F-A closeness (β= .24, p ≤ .001), F-A closeness to
externalizing behavior (β= -.15, p ≤ .01), educational Internet use to
externalizing behavior (β= -.13, p ≤ .05) – partial mediation
(b) Educational Internet use to F-A conflict (β= -.12, p ≤ .05), F-A conflict to
externalizing behavior (β= .26, p ≤ .001), educational Internet use to
externalizing behavior (β= -.13, p ≤ .05) – partial mediation
(c) Social Internet use to F-A closeness (β=-.38, p ≤ .001), F-A closeness to
externalizing behavior (β= -.15, p ≤ .01), social Internet use to externalizing
behavior (β= .22, p ≤ .05) – partial mediation
(d) Social Internet use to F-A conflict (β= .30, p ≤ .01), F-A conflict to
externalizing behavior (β= .26, p ≤ .001), social Internet use to externalizing
behavior (β= .22, p ≤ .05) – partial mediation
These four pathways were examined its significance using the Sobel test and
137
and externalizing behaviors through father-adolescent relationships - Bootstrapping.
Mediational
Unstandardized
Indirect Effect
Interval
(Standardized/ SE)
Z
Pathways
Percentile
Bias-Corrected
Low /Upper
Low /Upper
EDU→FACF→EX
-.012 (-.023/ .021)
2.14
EDU→FCF: .049 (.074/ .066)
-.063/ .017
-.069/ .013
EDU→EX: .173 (.118/ .062)
FACF→EX: .314 ( .116/.053)
EDU→FACL→EX
-.026 (-.052/ .021)
2.44
EDU→FCL: .148 (.221/ .069)
-.097/ -.014**
-.117/ -.021***
EDU→EX: 074. (.146/ .066)
FACL→EX: .178 (.235/.062)
SOC→FACF→EX
.068 (.062/ .019)
2.84
SOC→FCF: .140 (.193/ .055)
.025/ .100**
029/ .106***
SOC→EX: .334 (.305/ .062)
FACF→EX: .488 (.323/ .052)
SOC→FACL→EX
.075 (.072/ .031)
1.93
SOC→FACL: -.231 (-.258/ .086)
.009/ .134**
.015/ .143**
SOC→EX: .169 (.162/ .083)
FACL→EX: -.326 (-.280/ .065)
Note: Unstandardized effects are presented in (). Direct effects are presented in lower row of
the model (standardized direct effect/ SE). EDU = Educational Internet use, SOC = Social
Internet use, FA CF = father-adolescent conflict, FA CL = father-adolescent closeness, EX =
Externalizing problematic behaviors. A z value 1.96 or larger indicates a significant indirect
effect (p ≤. 05) (Sobel, 1982)
According to the results of the Sobel test and bootstrapping, all of indirect
pathways were significant.
H3-1.3. Adolescents’ Internet use has an effect on externalizing behavior problems
through parent-adolescent relationships (mother-adolescent relationship).
The indirect effects of the Internet use on adolescents’ externalizing behavior
problems through mother-adolescent relationships indicated poor model fit (X² (41, N
= 609) = 575.9, p ≤ .001; GFI= .88, AGFI= .78, RMSEA= .14). Modification indices
138
were examined and specific error terms were covaried based on whether it made
substantive sense, which was done one by one starting with the largest modification
index and the improvement in fit was noted. Six error terms were covaried. Covarying these error terms allowed for an improvement in good model fit (X² (35, N =
609) = 160.3, p ≤ .001; GFI= .96, AGFI= .91, RMSEA= .07). The X²Δ (6, N =609)
=415.6, p ≤ .001.
Figure 6b. Indirect effect of types of adolescent Internet use on externalizing behaviors
through mother-adolescent relationships
Note: * p< .05, ** p< .01, *** p< .001.
One indirect path was statistically significant (Figure 17b).
(a) Educational Internet use to M-A conflict (β= -.11, p ≤ .05), M-A conflict to
externalizing behavior (β=.37, p ≤ .001), educational Internet use to
externalizing behavior (β= -.18, p ≤ .01) – partial mediation,
139
This one pathway was examined its significance using the Sobel test and
Table 15b. Significance of indirect effects of links between the type of adolescent Internet use
and externalizing behaviors through mother-adolescent relationships - Bootstrapping.
Mediational
Unstandardized
Indirect Effect
Interval
(Standardized/ SE)
Z
Pathways
Percentile
Bias-Corrected
Low /Upper
Low /Upper
EDU→MCF→EX
.003 (.005/ .019)
EDU→MACF: .010 (.011/ .044)
0.25
-.033/ .043
-.036/ .041
EDU→EX: -.043 (-.069/ .047)
MACF→EX: .316 (.431/ .045)
Note: Unstandardized effects are presented in (). Direct effects are presented in lower row of
the model (standardized direct effect/ SE). EDU = Educational Internet use, SOC = Social
Internet use, MA CF = mother-adolescent conflict, EX = Externalizing problematic behaviors.
A z value 1.96 or larger indicates a significant indirect effect (p ≤. 05) (Sobel, 1982)
According to the results of the Sobel test and bootstrapping, the indirect
pathway from educational use to externalizing behaviors through mother-adolescent
conflict was not significant.
their externalizing behavior problems through parent-adolescent relationships
(father-adolescent relationships).
None of the pathways linking the types of adolescents’ Internet use and
externalizing problem behaviors through father-adolescent closeness and fatheradolescent conflict were significant for boys and girls (see Figure 6c).
140
Figure 6c. Link between Internet use, father-adolescent relationship and externalizing
behaviors by youth gender
*** p< .001
their externalizing behavior problems through parent-adolescent relationships
(mother-adolescent relationships).
None of the pathways linking type of adolescents’ Internet use and externalizing
problem behaviors through mother-adolescent closeness and mother-adolescent
conflict were significant for boys and girls (see Figure 6d).
141
Figure 6d. Gender differences on the indirect relationship among Internet use, motheradolescent relationship and externalizing behaviors
*** p< .001
Hypothesis 4. The link between pathways from adolescents’ Internet use to their
academic achievement through parent-adolescent relationships varies by parental
cultural academic expectations (mean split).
H4-1-1. The link between pathways adolescents’ Internet use and academic
achievement through father-adolescent closeness and father-adolescent conflict varies
by father cultural academic expectations.
Pathways were similar for adolescents whose fathers indicated high and low
parental academic expectation. None of the pathways linking type of adolescents’
Internet use and academic achievement through father-adolescent closeness and
142
father-adolescent conflict differed by father cultural academic expectations (see
Figure 7a).
academic achievement by fathers’ academic expectations
Note: Only significant paths are presented. Low PE (Regular)/ High PE (Italic). * p< .05, **
p< .01, *** p< .001
H4-1-2. The link between adolescents’ Internet use to academic achievement through
mother-adolescent closeness and mother-adolescent conflict varies by mothers
cultural academic expectations
achievement through mother-adolescent closeness and mother-adolescent conflict
differed by mothers’ cultural academic expectations (see Figure 7b).
143
academic achievement by mothers’ academic expectations
p< .01, *** p< .001
H4-2-1. The link between pathways from adolescents’ Internet use to internalizing
problem behaviors through father-adolescent closeness and father-adolescent conflict
varies by fathers’ academic expectations
The analysis of the moderating effects of parental education for the indirect
pathways from the Internet use on adolescents’ internalizing problematic behaviors
through father-adolescent relationships indicated good model fit (X² (109, N = 609) =
375.0, p ≤ .001; GFI= .92, AGFI= .87, RMSEA= .06).
Pathways were similar for youth whose fathers indicated high and low parental
academic expectation:
144
(a) Social Internet use and father-adolescent closeness (low PE group: β= -.33, p
≤ .001, high PE group: β= -.22, p ≤ .05) and father adolescent closeness and
internalizing problem behaviors (low PE group: β= -.19, p ≤ .01, high PE
group: β= -.32, p ≤ .001) – full mediation.
Figure 8a. Different effects of parental expectation (PE) among Internet use, father-adolescent
relationships, and internalizing behaviors
p< .01, *** p< .001
H4--2. The link between pathways from adolescents’ Internet use and internalizing
conflict varies by mothers’ academic expectations.
145
None of the pathways linking type of adolescents’ Internet use and internalizing
conflict differed by mothers’ academic expectations (see Figure 8b).
internalizing behaviors by mothers’ parental expectations
p< .01, *** p< .001
H4-3-1. The pathways linking types of adolescents’ Internet use and externalizing
varies by fathers’ academic expectations.
differed by fathers’ academic expectations (see Figure 9a).
146
externalizing behaviors by fathers’ academic expectations
Note: Only significant values are presented. Low PE (Regular)/ High PE (Italic). * p< .05, **
p< .01, *** p< .001
H4-3-2. The pathways linking types of adolescent Internet use and externalizing
conflict varies by mothers’ academic expectations.
conflict differed by mothers’ academic expectations (see Figure 9b).
Parental expectations do not show any moderating effects on the pathways
between the Internet use and adolescents’ outcomes. Considering the low reliability of
the measurement of parental expectation ( .57 - .53), no significant results are
understandable. It may be need to replicate this study using a more reliable or new
measurement.
147
Figure 9b. Different effects of parental expectation (PE) among Internet use, motheradolescent relationships, and externalizing behaviors
Note: Only significant paths are presented. Significant differences were presented as bold (CR
> 1.96). Low PE (Regular)/ High PE (Italic). * p< .05, ** p< .01, *** p< .001
Discussion
The purpose of this study was to investigate the relationships among adolescent
Internet use, parent-adolescent relationships, and academic/behavioral adjustment in
South Korean families. Four main research questions were tested in this study. First,
the nature of Korean adolescents’ Internet use and the frequency and intensity of
educational, social, and recreational Internet usage were examined. Second, the direct
associations between adolescents’ Internet use (frequency and intensity of educational,
social, and recreational use of the Internet) and adolescent academic and behavioral
outcomes were examined. Third, the indirect effects of adolescents Internet use on
academic and behavioral outcomes through parent-adolescent relationships were
148
tested. Fourth, the moderating effects of parental cultural expectations in the
association between adolescent Internet use and academic and behavioral outcomes
through parent-adolescent relationships was finally examined. The patterns of these
relationships in four questions were all examined for gender variations.
Findings from the Nature of Internet Use
Girls and boys accessed the Internet differently. Adolescent girls used the
Internet at school and library more often than boys. A significantly higher number of
adolescent girls owned their own PCs than boys did. At school, adolescent girls used
the Internet during classes, extra-curricular activities, and lunch breaks more often
than boys. However, boys used the Internet at PC Bangs (Internet cafés), which is
consistent with the findings from previous research (Korean Statistical Information
Service. 2004, May; Lee, 2005, October).
The results of this study also indicate that boys and girls used the Internet for
different purposes. Specifically, adolescent girls used the Internet for educational
purposes more often and longer than boys, while adolescent boys used the Internet for
recreational purposes more often and longer than girls. More specifically, an analysis
of educational Internet use results indicated that girls more frequently and intensely
used the Internet for online classes and cyber learning than boys did. This is consistent
with findings from previous studies that found females were more likely than males to
149
use the Internet for academic purposes (Jackson, Zhao, Kolenic III, Fitzgerald, Harold,
& von Eye, 2008).
Second, the results of social Internet use indicated that boys used the Internet
more frequently and for longer hours than girls for chatting. Girls used the Internet
more often than boys for blogging. These findings are not similar to findings from
other studies that found girls were more likely to use the Internet for chatting,
blogging, and e-mails than were boys (Korean Statistical Information Service. 2004,
May, 2008; Lee, 2005, October; Tsai & Tsai, 2010).
Interestingly, boys in this study used the Internet for chatting more frequently
and intensely than girls. Differences in digital skills between individuals may be one
of the potential reasons for this finding. It is unknown, but a lack of some specific
digital skills may result in more use of certain Internet functions, such as chatting,
than other functions, such as blogging, Internet surfing, shopping, and so on. Another
reason may be because of the place of the Internet use. Students appear to use the
computer and the Internet at home far more often than they do at school (van Braak &
Kavadias, 2005; Livingstone, 2002). Boys possess fewer home computers than girls
do. An absence of home computers may force them to go to PC Bangs. Under these
circumstances, those who don’t have home computers may be more likely to do chat
than those who have home computers.
150
Finally, the results of recreational Internet use indicated that boys more
frequently and intensely used the Internet than girls for gaming. This is consistent with
previous literature and the results of a recent national survey, conducted by the
National Internet Development Agency of Korea (2007). However, in contrast to
previous literature, girls used the Internet more for educational purposes than did the
boys in this study.
Why was there a difference between the results of previous literature and this
study? Perhaps, the results of the current study differed from that of previous research
because girls used the Internet more at school than at any other place, such as PC
Bangs. The frequent use of school computers and public computers may increase
educational Internet use. Boys in this study used the Internet significantly more often
than girls at PC Bangs, which possibly explains their greater engagement in
recreational use. School and library computers are more likely to be set up for
educational related purposes only, and recreational access, such as access to gaming
sites, may be blocked. As a result, those who use school computers frequently are
more likely to access the Internet to search for academic information.
Another plausible explanation is that adolescent girls did not want to go to PC
Bangs because they were more intently interested in using the Internet for educational
purpose. Likewise, it is also likely that boys intentionally went to PC Bangs to game,
151
and they were less interested in the Internet for educational use. Since most parents do
not like their children to do games, the children may prefer to go to the PC Bangs to
play games in secret. Girls tend to use the Internet at home for nongaming activities,
but they rarely use the PC Bangs, which is consistent with previous studies (Huh,
2008; Stewart & Choi, 2003).
The PC Bang culture can be interpreted as an unique Korean culture that differs
from those in North America, which is primarily based on home entertainment
systems. The Korean entertainment industry thrives outside of the home, and the PC
Bang is one of the various entertainment “Bangs” (Stewart & Choi, 2003). Since the
“Bang” culture has become an integral part of the socializing environment for Koreans,
this may have unique influences on the nature of Internet use among Korean
adolescents.
Although it is not accounted for in this study, private tutoring for schoolwork
takes up a significant amount of time in the lives of Korean adolescents. Studies of
Korean adolescents have indicated that many of the Korean teen students are involved
in out-of-school education, such as private tutoring and extra-curricular activities (e.g.,
music, karate, etc.). It was reported that 72.6% of Korean students used private
tutoring in 2003 (Choi et al., 2003). In regards to the parents’ expenditures on private
tutoring, it was reported that Korean families spent around 13.6 trillion Korean won
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(approximately 12 billion U.S. dollars) on all forms of private tutoring in 2003 (Choi
et al., 2003). Previous studies indicated that students from high-SES families tend to
participate more in private tutoring than those of low-SES families (Choi et al., 2003).
Considering the nature of this sample, it is anticipated that a significant number of
participants would be involved in any kinds of out-of-school educational activities.
Hence, adolescents may have less time to be involved in the use of PC Bangs etc.
The results from this study differ from other studies conducted in different
countries. Extant research indicates that boys use the Internet more frequently, for
longer periods of time, and for a wider variety of uses than do girls; these findings
were present among samples of American children (Gross, 2004; Haythronthwaite &
Wellman, 2002; Morahan-Martin, 1998; Subrahmanyam, Greenfield, Kraut, & Gross,
2001), European children (Durndell & Haag, 2002; Madell & Muncer, 2004;
Valkenburg & Soeters, 2001), and Asian children (Ho, & Lee, 2001; Nachmias,
Mioduster, & Shelma, 2000). Therefore, these findings of this study may reflect a new
trend of Internet use in industrialized nations.
Recent research reported that 74% of American adults use the Internet,
regardless of gender (Pew Research Center Publications, 2010, May). Multiple
surveys from U.S. and U.K. samples have also found no gender differences in Internet
use, and others have actually found that female users out number male users in the
153
U.S. For example, eMarketer estimated that there were an estimated 97.2 million
female Internet users, ages 3 and older, in 2007, accounting for 51.7% of the total
online population. In 2011, 109.7 million U.S. females will go online, amounting to
51.9% of the total online population (cited in Boing Boing, 2007). A recent study in
the U.K. found that there have been few gender differences in the online experience,
with the notable exception of more online pornographic risk for boys than for girls
(Livingstone & Helsper, 2010). These findings contribute to recent reports of a
decreased gender gap in Internet use (Break News, 2010, Aug. 11). Based on recent
findings, the increase of female Internet use may be an upward trend.
In conclusion, considering the different nature of the place of Internet access in
this study, the evidence of some significant gender differences, in terms of functional
Internet use in this study, seem to correctly reflect the nature of Korean adolescent’s
Internet use and indicate that Korean adolescent boys and girls access the Internet
differently. In terms of intensity and frequency of Internet use, there are some
significant gender differences among Korean adolescents. Similar to previous studies,
Korean adolescent boys are more likely to use the Internet for gaming than girls, and
girls are more likely use the Internet for educational purpose than boys. However, the
results did not support the popular findings of past research in social Internet use
(Papastergiou & Solomonidou, 2005; Tsai, & Tsai, 2010). Also, in general, the gender
154
gap in Internet use seems to have disappeared. The generation gap in Internet use also
seems to have disappeared. Although adolescents spend less time online than adults,
they are more involved in Internet activities than adult. Therefore, it is important to
know the exact nature of the adolescents’ Internet use. And more exploration about
gender differences seems to be necessary to find some evidence of a change in the
next generation regarding Internet use.
Findings from the Direct Models
My second hypothesis was about the direct association between the Internet use
and academic achievement, as behavioral adjustment. It was hypothesized that there
were some direct effects of Internet use on academic achievement, internalizing and
externalizing problematic behaviors. Some gender differences were expected;
however, no gender differences in the direct pathways were found. Although
adolescent boys and girls access and use the Internet differently in the current study,
the effects of Internet use do not differ among boys and girls on academic
achievement and problematic behaviors.
As expected, adolescents’ educational use of the Internet was positively
associated with adolescent academic achievement and negatively associated with
adolescent externalizing problematic behaviors, while social use of the Internet was
negatively associated with adolescent academic achievement and positively associated
155
with adolescent externalizing problematic behaviors. Although the effects of
recreational Internet use were in the expected direction, they did not reach statistical
significance. There was also no significant effect of adolescents’ Internet use on
internalizing behaviors.
These results are consistent with the results of previous studies. Current findings
also expand upon those of Attewell and colleagues (1999, 2001, & 2003), who
reported positive outcomes in association with adolescences’ computer technology.
Other studies about educational computer use and/or educational software programs
have similarly reported positive outcomes in academic domains, such as math
(Clements, 2002; Hess, & McGarvey, 1987; Cuffaro, 1984), and language and literacy
(Cuffaro, 1984; Mioduser, Tur-Kaspa, & Leitner, 2000; Hess, & McGarvey, 1987).
This culmination of current research indicates that the Internet is an effective tool to
enhance students’ learning. Unfortunately, the adolescents’ increased use of
technology has also been accompanied by an increase in attention difficulties
(Anderson & Maguire, 1978; Chan & Rabinowitz, 2006; Levine & Waite, 2000;
Schmidt & Vanderwater, 2008).
Similar findings regarding the negative effects on behavioral adjustment may be
found from Choi (2007) and other professionals, who suggest that the Internet can
have direct negative effects (Sirgy, Lee, & Bae, 2006), such as increased
156
psychological problems, including social isolation, depression, loneliness, difficulties
with time management (Brenner, 1997; Kraut, Patterson, Lundmark, Kiesler,
Mukhopadhyay, & Scherlis, 1998; Young, & Rodgers, 1998), daily routines, family
relationships, school performance, and a wide range of behavioral problems (Block,
2008; Choi, 2007), as a result of excessive Internet use (Rickert, 2001).
Findings indicate that online communication often detracts from the time that
adolescents could have, otherwise, spent outside engaging in social activities (Kraut et
al., 1998; Nie, Hillygus, & Erbring, 2002, Sanders et al., 2000). In the current study,
adolescents’ social and recreational use of the Internet hindered time that could be
used for their studies and/or school work. The findings are supported under the social
displacement paradigm. Jackson et al. (2006) hypothesized that reading achievement
could be improved while navigating the Internet, because students encounter a
significant amount of text during their use. Based on the current study, the
improvement of academic achievement may be a specific result of educational use of
the Internet, while non-educational Internet use consequently hinders academic
achievement. However, these results may be influenced by some advantages of the
high socioeconomic status of the participants. Although the family income variable
was statistically controlled in this study, it is likely that families with the high-income
157
status have easier access to technology, to quality educational resources, to parental
support and to regulations.
Findings from the Indirect Models
Although the significant impact of parent-adolescent relationships on adolescent
development and adjustment has been well documented, the unique influence of
father- and mother-adolescent relationships on adolescent adjustment needs to be
better understood. There are many findings that support the importance and
uniqueness of father-adolescent relationships on adolescent development and
adjustment. For example, Youniss (1987) found that father-adolescent relationships
contribute differently to psychological development; adolescents perceived their
relationships with fathers and mothers differently. Although adolescence represents a
time of independence and autonomy, teens seems to place a great deal of value on
how their parents perceive them. They want their parents to acknowledge that they are
mature enough to be recognized, as an independent individual (Youniss & Smollar,
1985).
Moreover, there is evidence that a unique influence of fathers on adolescents’
adjustment exists. For example, within a nationally representative sample of
adolescents, Videon (2005) found that adolescents have more volatile relationships
with their fathers than with their mothers. This difference in the nature of the parent-
158
child relationship existed, despite indications that both relationships were considered
equally crucial for the adolescents’ well-being. In addition, emotionally close fatheradolescent relationships decreased the likelihood of adolescents’ alcohol consumption
(Habib, Santoro, Kremer, Toumbourou, Leslie, & Williams, 2010).
It has not been common practice to examine father-adolescent relationships and
mother-adolescent relationships separately (Forehand, Wierson, Thomas, Fauber,
Armistead, Kempton, & Long, 1991; Galamos, Sears, Almeida, & Kolaric, 1995). In
order to provide a more accurate picture, this study assessed mother- and fatherrelationships separately, assessing the relational domains of conflict and closeness. In
addition, the data was obtained from multiple sources, including the adolescents,
fathers, and mothers.
Just as previous research has indicated that there are some associations between
familial relationships and outcomes of Internet use (Cho, Kim, Kim, Lee, & Kim,
2008; Lei & Wu, 2007; Liau, Khoo, & Ang, 2005), the findings from the current study
indicates that adolescent educational Internet use is positively associated with
academic achievement through parent-adolescent relationships, while social Internet
use is negatively associated with academic achievement. However, the current study
did not find any effects from recreational Internet use (Figure 4a, 4b). More
specifically, the adolescent’s educational Internet use was positively associated with
159
academic achievement through father-adolescent conflict and mother-adolescent
closeness. Adolescent’s social Internet use was negatively associated with academic
achievement through father-adolescent conflict and mother-adolescent closeness. The
positive effects of educational Internet use seem to be actively affecting their
academic achievement, especially when adolescents have close relationships with
their mothers, and seem to be passively affecting, when they have conflicts with their
fathers. In addition, negative effects of social Internet use have same influence on
academic achievement under conflicts with fathers and close relationships with
mothers.
While adolescent’s educational Internet use was indirectly and negatively
associated with internalized problematic behaviors through the father-adolescent
conflict, the social Internet use was positively and indirectly associated with
internalized problematic behaviors through the father-adolescent closeness and
conflict. Educational and social Internet use seems to have active effects on
internalized problems behaviors, when they have strong relationships with fathers.
While father-adolescent relationships fully mediated the association between
educational/social Internet use and internalized problematic behaviors, motheradolescent relationships didn’t show any significant medicating effects on the
160
association between Internet use and internalized problematic behaviors. And this is
true for the association between Internet use and externalized problematic behaviors.
In addition, the adolescent’s educational Internet use was negatively associated
with externalized problematic behaviors through the father-adolescent closeness and
conflict. Social Internet use was positively associated with externalized problematic
behaviors through both the father-adolescent closeness and conflict. Motheradolescent relationships did not mediate the association between Internet use and
externalized problematic behaviors.
After all, positive effects of educational Internet use and negative effects of
social Internet use on academic achievement are true under the umbrella of parentadolescent relationships. Parent-child relationships are vital to the child’s adjustment;
and as demonstrated in the current study, parent-adolescent relationships play a
significant role in the association between adolescent Internet use and academic
behavioral outcomes.
Specifically, the positive effects of educational Internet use on academic
achievement were actually strengthened by parent-adolescent closeness, and
weakened by parent-adolescent conflict. Adolescent educational Internet use might
lead to parent-adolescent closeness; whereas adolescence social use of the Internet led
161
to parent-adolescent conflict; and both the parent-adolescent conflict and closeness
each uniquely contributed to academic achievement and problematic behaviors.
In conclusion, relationships with fathers and mothers seem to be related to
specific aspects of adolescent adjustment and academic achievement. These findings
support previous empirical studies and provide some evidence of significant
association between the Internet use and parent-adolescent relationship with Internet
use (Liau, Khoo, & Ang, 2005; Ybarra & Mitchell, 2004a, 2005), as well as the
association between parent-adolescent relationships and adolescents’ outcomes (Hair,
Moore, Garrett, Ling, & Cleveland, 2008; Steinberg, 2008).
In this study, some significant mediating effects of the parent-adolescent
relationships on the association between adolescent Internet use and adolescent
adjustment were found. There is some indication of a bi-directional effect with the
adolescents’ behaviors impacting parent-adolescent relationships. To date, there are
few studies that have examined the bi-directional nature of these models. For future
research, bi-directional influence should be explored.
Few studies have addressed the associations between Internet use and parentadolescent relationships. The present study, therefore, addresses the connection
between adolescent Internet use and parent-adolescent relationships and finds
significant associations between them. Further investigations between these two
162
variables should be continued. Specifically, the possible bi-directional nature of the
association between the parent-adolescent relationships and adolescent Internet use
should also be explored. Several previous studies have reported finding a bidirectional association between parent-adolescent relationships and the Internet use
(Ko, Yen, Yen, Lin, & Yang, 2007; Liu & Kuo, 2007; Yen et al., 2007). For instance,
the quality of the parent-adolescent relationships has been found to be negatively
associated with level of Internet addiction among students (Lio & Kuo, 2007). Recent
research, involving Dutch students’ compulsive Internet use, revealed a bi-directional
effect between the frequency and quality of the adolescents’ Internet use and parentadolescent communication (van den Eijnden, Spijkerman, Vermulst, van Rooij, &
Engels, 2010). In the current study, only the effects of Internet use on parentadolescent relationships were explored, so the opposite effects may be explored for
future study.
Adolescents’ gender did not moderate the mediating pathways for either the
mother or father models. Future studies that assess gender effects on Internet use may
include other variables like cell phone usage or other diverse computer technologies
that more closely mirror the modern adolescent world. In other words, gender gaps in
Internet use may still exist, and they should continue to be addressed and rectified.
163
Finally, moderating effects of parental expectations were examined. It was
hypothesized that strong educational expectations of parents might strengthen parentadolescent closeness, when adolescents used the Internet more for educational
purposes. It was expected that when non-educational Internet use was increased, the
level of parent-adolescent may conflict was increased as well. However, significant
effects were not found. The strong effects of parental expectations on their children’s
achievement and adjustment have been consistently well documented (Sandefur,
Meier, & Campbell, 2006; Schneider & Lee, 1990; Schwarz, et al., 2005).
In fact, past research has found parental expectations to be the strongest
influence than any other parenting factor (Fan, 2001; Fan & Chen, 2001; Singh,
Bickley, Trivette, Keith, Keith, & Anderson, 1995). The reason that parental
expectations did not reach significant levels in the current study could be related to
some effects of the adolescents’ own educational expectations. Korean teen students,
in this study, might have their own educational aspirations, regardless of the level of
their parental expectations. Goldenberg and colleagues (2001) also found that parental
expectations have no significant effects on children’s achievement in a longitudinal
study of kindergarten through sixth-grade children.
It has been well known that Koreans hold a very strong educational aspiration
(Chung, 1991a). Korean high school students are allocating the majority of their time
164
to study. Adolescents, who participated in current study, are no exception to this
phenomenon. It could be assumed that high parental expectations might have been
embedded in the adolescents’ personal values, as the parental expectations have likely
been present throughout their school years. Therefore, personal and parental
expectations may not be an entirely separate construct. As a result, parental
expectations do not seem to have a strong or unique contribution to familial
relationships or academic performance in this study. Future research should consider
new variables, such as the adolescent’s own expectation or sibling relationships.
These findings indicate that future research studies should investigate how
Koreans cope with the influx of rapidly developing technology and its use as an
educational tool. The findings from this investigation also highlight the need for
understanding parent-adolescent relationships in a technological world. Parents and
teachers may focus more on the quantity of the adolescents’ educational Internet use
and not on how the Internet use shapes adolescents’ relationships with family
members and others, within a relational context. As found in the study, male and
female adolescents indicated both differences and similarities in the nature of Internet
use. This issue should also be further investigated in future studies on the subject.
165
Theoretical Contributions, Limitations, and Future Research
The findings from this study indicate that modern technologies have brought
about changes in the lives of adolescents, especially in terms of their family
relationships. The closeness and conflicts between parents and adolescents may
facilitate the positive effects of educational Internet use and buffer the negative effects
of non-educational Internet use on adolescent outcomes. While the findings of this
study support the human ecology theory and attachment theory, future research should
investigate how parents can utilize the Internet to provide its benefits to adolescents
within the family context.
One of the strengths of the current study is that Internet use functions were
differentiated into educational, social, and recreational functions. In addition, findings
from this study contribute to the growing body of research that indicates a decrease in
the gap between male and female Internet usage. As noted above, gender differences
on the impact of Internet usage have been mostly descriptive information.
Another contribution is the complexity of the model examined. Multiple
informants were used for the data. For example, parent-adolescent relationships
measurements include adolescents’, their fathers’, and their mothers’ reports. This
study also used a large dataset to evaluate the models. The current study has 609 sets
of families as participants.
166
This study has several limitations that are inherent to survey methodology.
Surveys are a good way to gain exploratory information about a particular
phenomenon, especially when little is known. However, the use of surveys tends to
give researchers rough, broad measures that are unable to divulge deeper
understanding.
Another limitation of the survey methodology is that surveys rely on selfreported data and, therefore, may introduce measurement error into the data (Singleton
& Straights, 1999). In some cases, respondents may report inaccurate information
because of poor memory or misunderstanding of survey questions. In other cases,
respondents may intentionally give false responses because of a desire to be viewed
positively by an unknown investigator, or because of fear related to reporting sensitive
information. This study relied on adolescents’ report of Internet use, which can be
considered a sensitive topic in some families; therefore, intentional inaccurate answers
may play a role in the measurement errors. Although there were multiple informants
in this study, the inclusion of observational data in real-life settings is desirable. Also,
the inclusion of Qualitative information, based on in-depth interviews, contributes to
the picture of adolescent Internet use.
Self-reported data can be inaccurate because of respondent fatigue, and the
respondents in the current study may have found that the surveys were also relatively
167
lengthy. According to Dillman (2000), this may be problematic, as participants may
become tired, bored, or uninterested mid-way through the survey. Therefore, succinct
surveys are preferred. Although I do not have information about the average length of
time required for each survey, a practice run through the survey suggested that it
would take approximately twenty five to thirty minutes to complete. It is possible that
the respondents’ burden may have affected the accuracy of the data.
As adolescents’ technology use has increased, research has been conducted to
explore its effect on adolescent school achievement. The results in this area have been
highly variable, since previous studies didn’t differentiate the function of Internet use.
The nature of Internet use is multi-functional. For example, adolescents use the
Internet to get academic information and help, to communicate with friends and
families, and to enjoy movies and gaming. Inconsistency of previous findings seems
to be due to a lack of clear division of Internet functions, regardless of its multifaceted
nature.
The sample for this study may not adequately represent Korean families. Most
families in this study were from high-income, well educated, and lived in urban
settings. High SES families have access to better resources, social support, and
opportunities (Evans, 2004; Mackner, Black & Starr, 2004). Teen children in this
study may have benefited from having gone to better school districts and family
168
support than children from lower socioeconomic families. Therefore, the findings
from this study may not fully apply to lower income families, where parents may be
less educated and from more traditional families. Parental use of the Internet was not
included in the current study, and the parents’ familiarity with the use of the Internet is
more likely to be more involved in their teenage children’s Internet use.
Since the nature of this study is exploratory, it is hard to actually compare
findings of this study with results of a few previous studies. This is especially true for
association with relationships with parents. Considering the uniqueness of the Korean
culture, results of this study may differ according to the cultural context. Continued
investigation is needed to contextualize the research findings, since the use of Internet
must be continuously evolving. Future research should be directed toward continuing
to investigate the relationship among adolescents’ Internet use, parent-adolescent
relationships, and academic and behavioral outcomes. Since technology is such an
integral part of most adolescents’ lives, it is important to understand the impact on
their academic achievement and behavioral adjustment.
The current study used a survey-based, correlational design, to assess the
relationship between adolescent Internet use, parent-adolescent relationships, and
behavioral adjustment and academic performance. Similar correlational research has
dominated the literature to date on adolescent Internet use (Livingstone, 2002). Such
169
studies should now be complemented by more research using experimental and
longitudinal designs as well as cross cultural studies, to allow conclusions about
causality and long-term effects, including the impact that Internet use by teenagers
might have on the quality and intimacy of their present and future lives across
different populations.
Considering that the majority of populations use the Internet almost every day,
regardless of gender, age, and SES status, this researcher plan to include the following
topics in future research areas. First, longitudinal investigation into the association
between experience and exposure to computer technologies during early childhood
through parental usage and in later youth development and adjustment seem to be
needed.
This study also employed a cross-sectional design, which does not address
causality. This study investigated the effects of Internet use and the parent-adolescent
relationships on adolescents’ outcomes. Conversely, parent-adolescent relationships
may impact an adolescents’ Internet use, and adolescents’ outcomes can also influence
parent-adolescent relationships and Internet use. Parent-child relationships may also
change overtime, and in order to understand potential reciprocal relationships among
these variables, longitudinal studies are necessary.
170
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Appendix A
Survey questions about demographic information
242
These questions are general information questions. Read each question on the list and
check the box that best describes who you are.
1. Today’s date
_______YYYY _______MM_________DD
2. Your date of birth
_______YYYY _______MM_________DD
3. Gender
4.
Female □
Male □
Your relationship to the child in
Bio-Mother
□
Bio-Father
□
Step-Mother
□
Step-Father
□
Grandmother
□
Grandfather
□
this study
Other (please specify) :
5. Please list all the people living in your house starting with yourself and their relationship to
you.
Person’s name
a. yourself
b. your teen child
c.
d.
e.
f.
g.
h.
Relationship
Age
Highest degree earned
243
These are general information questions. Read each question on the list and check the
box that best describes who you are.
6.
What is your highest
Completed middle school
□
Completed high school
□
Completed business or trade school (2-year)
□
Completed college education (4-year)
□
Completed Graduate school (M.S./ Ph.D)
□
level of education?
7.
Are you employed
now?
□
Yes, part-time
□
Yes, full-time
□
Retired; If yes, when? _______ years ago
□
Unemployed and looking for work
□
Home maker
□
Too disabled or ill to work
7-1.
How many hours do you work every week?
8.
What is the family’s total
monthly income before
taxes?
_________________hours/ week
Less than ₩2,000,000
□
₩2,000,000 to less than ₩2,500,000
□
₩2,500,000 to less than ₩3,000,000
□
₩3,000,000 to less than ₩3,500,000
□
₩3,500,000 to less than ₩4,000,000
□
More than ₩4,000,000
□
244
These are general information questions. Read each question on the list and check the
box that best describes who you are.
9.
What is your marital
Married
□
Separated
□
Remarried
□
Widowed
□
Divorced
□
Catholic
□
Buddhist
□
Christian
□
None
□
status?
10.
What is your religious
preference?
Other:
245
Appendix B
Survey questions about Internet use
246
Now I would like to ask you about your use of the Internet. There is no right or wrong
answers. Please answer the questions to the best of your knowledge.
1. I have been using the Internet since the age of ________________.
2. How many computers with internet access are there in your home? (For example, 0, 1, 3…)
______________PCs
________________Laptops
______________Cell Phones
________________Others, Specify:
3. Where do you use the Internet?
Home
School
PC Bang (Cyber café)
Friend’s house
Library, Community facilities
Yes
□
No
□
Yes
□
No
□
Yes
□
No
□
Yes
□
No
□
Yes
□
No
□
Other places, please specify:
4. Do you have a PC, cell phone, laptop with Internet access that you alone use?
Yes
□
No □
5. Where are PCs or laptops with Internet computer in your home?
Parent’s room
Open family area (living room)
My room
Study room
Other place, specify:
Yes
□
No
□
Yes
□
No
□
Yes
□
No
□
Yes
□
No
□
247
6. Do you go on the Internet at school, do you use it ………………….
During class (when the teacher is not watching)
When teacher allows for computer use
After school or extra activities
During lunch breaks
Yes
□
No
□
Yes
□
No
□
Yes
□
No
□
Yes
□
No
□
Other, place explain:
Please indicate how long you stay online to do following activities during weekdays and
weekends respectively for the following purposes. Please circle your best answer
1=Less than 30 mns,
2=½ to 2 hrs,
1. How long do you stay online to do
3= 2 to 3 hrs,
4=More than 3 hrs a day
Monday to Friday
Weekends, Holidays
1
2
3
4
1
2
3
4
1
2
3
4
1
2
3
4
1
2
3
4
1
2
3
4
1
2
3
4
1
2
3
4
1
2
3
4
1
2
3
4
1
2
3
4
1
2
3
4
your study related work or search
study related information?
2. How long do you stay online to
watch online classes?
3. How long do you stay online to chat,
talk and meet with friends and
families?
4. How long do you stay online to visit
blogs and online communities
5. How long do you stay online to have
fun and relax (such as watching
movies, listening songs, playing
games)?
6. How long do you stay online to do
online games.
248
Please indicate how often you use the Internet on weekdays and weekends. Please circle
your best answer.
1=None,
2= 1~2 times a day,
3= 3~4 times a day,
1. How often do you go online to search
4=More than 4 times a day.
Monday to Friday
Weekends, Holidays
1
2
3
4
1
2
3
4
1
2
3
4
1
2
3
4
1
2
3
4
1
2
3
4
1
2
3
4
1
2
3
4
1
2
3
4
1
2
3
4
1
2
3
4
1
2
3
4
1
2
3
4
1
2
3
4
1
2
3
4
1
2
3
4
1
2
3
4
1
2
3
4
1
2
3
4
1
2
3
4
1
2
3
4
1
2
3
4
1
2
3
4
1
2
3
4
for information to do homework and/or
school assignment?
2. How often do you go online to post
study questions?
3. How often do you go online to watch
educational online classes/ programs?
4. How often do you go online to
exchange study related e-mails with
teachers and friends?
exchange personal e-mails with friends?
6. How often do you go online to chat
with your friends?
7. How often do you go online to post
pictures and to write stories on social
networks (e.g., Facebook)?
8. How often do you go online to make
new friends or meet new people?
download movies, tv series, songs, and
music videos?
11. How often do you go online to play
online games?
buying things at internet shopping malls?
13. How often do you go online to visit
sports, movies, and celebrities’ websites?
249
Appendix C
Survey questions about parent-adolescent relationships
250
Below is a list of questions about relationships between you and your MOTHER
and FATHER. Please indicate how much you can agree to following statements
regarding relationships with your mother. Please circle 1, if the following
statements are not true and circle 4 if it is true.
MOTHER
FATHER
1.
I feel close to my parent.
1
2
3
4
1
2
3
4
2.
My parent is attentive to my problems.
1
2
3
4
1
2
3
4
3.
My parent knows what I am really like.
1
2
3
4
1
2
3
4
4.
I am confident that my parent would help me if I
1
2
3
4
1
2
3
4
had a problem
5.
My parent often expresses affection or liking me.
1
2
3
4
1
2
3
4
6.
My parent and I do things together that I enjoy.
1
2
3
4
1
2
3
4
7.
Talk about how things are going with my friends.
1
2
3
4
1
2
3
4
8.
Talk about how things are going in school.
1
2
3
4
1
2
3
4
9.
Talk about problems and/or concerns I have (in
1
2
3
4
1
2
3
4
1
2
3
4
1
2
3
4
1
2
3
4
1
2
3
4
school, community, etc.).
10.
Talk about my activities and things for upcoming
days.
11.
Talk about my plans for the future.
In the last few weeks, how often did the following things happen between you
and your MOTHER and FATHER? Please circle your best answers.
1=Definitely false, 2=Probably false, 3= Probably true, 4=Definitely true
MOTHER
FATHER
1.
My parent often criticizes me.
1
2
3
4
1
2
3
4
2.
Before I finish saying something, my parent often
1
2
3
4
1
2
3
4
interrupts me.
3.
My parent often irritates me.
1
2
3
4
1
2
3
4
4.
Often there are misunderstandings between my
1
2
3
4
1
2
3
4
1
2
3
4
1
2
3
4
parent and myself.
5.
I treat others with more respect than I teat my
parent.
6.
My parent often hurts my feelings.
1
2
3
4
1
2
3
4
7.
My parent does not trust me to make my decisions.
1
2
3
4
1
2
3
4
8.
My parent and I often get into arguments.
1
2
3
4
1
2
3
4
9.
I often seem to anger or annoy my parent.
1
2
3
4
1
2
3
4
10.
My parent often loses her/his temper with me.
1
2
3
4
1
2
3
4
251
Please indicate whether you and your parent discussed following issues over
the last two weeks. If discussed, how heated were you and your parent? Please
circle your best answer.
O=Discussed, X=Not discussed
1=Very calm,
2=Calm,
3= Angry,
MOTHER
4=Very angry
FATHER
8.
Money matters
O
X
1
2
3
4
O X
1
2
3
4
9.
How you dress
O
X
1
2
3
4
O X
1
2
3
4
10.
Your friends
O
X
1
2
3
4
O X
1
2
3
4
11.
Behaviors in school
O
X
1
2
3
4
O X
1
2
3
4
12.
Doing homework
O
X
1
2
3
4
O X
1
2
3
4
13.
Relationships with family
O
X
1
2
3
4
O X
1
2
3
4
members
14.
Your grades
O
X
1
2
3
4
O X
1
2
3
4
15.
Playing video/ Internet games
O
X
1
2
3
4
O X
1
2
3
4
16.
Drinking, or smoking
O
X
1
2
3
4
O X
1
2
3
4
17.
Who you date
O
X
1
2
3
4
O X
1
2
3
4
18.
Helping out at home
O
X
1
2
3
4
O X
1
2
3
4
19.
Cursing
O
X
1
2
3
4
O X
1
2
3
4
20.
Internet use
O
X
1
2
3
4
O X
1
2
3
4
252
Appendix D
Survey questions about parental expectations
253
Below is a list of statement about cultural norms and values. Please use the
scale below to indicate the extent to which you agree with the value expressed
in each statement.
0 = Strongly Disagree
1 = Disagree
2 = Agree
3 = Strongly Agree
1.
One should not deviate from familial and social norms.
0
1
2
3
2.
Children should not place their parents in retirement homes.
0
1
2
3
3.
One need not focus all energies on one’s studies.
0
1
2
3
4.
One
0
1
2
3
should
be
discouraged
from
talking
about
one’s
accomplishments.
5.
Younger persons should be able to confront their elders.
0
1
2
3
6.
When one receives a gift, one should reciprocate with a gift of
0
1
2
3
0
1
2
3
equal or greater value.
7.
One need not achieve academically in order to make one’s
parents proud.
8.
One need not minimize or depreciate one’s own achievement.
0
1
2
3
9.
One should consider the needs of others before considering
0
1
2
3
one’s own needs.
10.
Educational achievements need not be one’s top priority.
0
1
2
3
11.
One should think about one’s group before oneself.
0
1
2
3
12.
One should be able to question a person in an authority position.
0
1
2
3
13.
Modesty is an important quality for a person.
0
1
2
3
14.
One’s
0
1
2
3
achievements
should
be
viewed
as
family’s
achievements.
15.
One should avoid bringing displeasure to one’s ancestors
0
1
2
3
16.
One should have sufficient inner resources to resolve emotional
0
1
2
3
0
1
2
3
problems.
17.
The worst thing one can do is bring disgrace to one’s family
reputation.
18.
One need not remain reserved and tranquil.
0
1
2
3
19.
One should be humble and modest.
0
1
2
3
20.
Family’s reputation is not the primary social concern.
0
1
2
3
21.
One need not be able to resolve psychological on one’s own.
0
1
2
3
22.
Educational failure does not bring shame to the family.
0
1
2
3
23.
One need not follow the role expectations (gender, family
0
1
2
3
hierarchy) of one’s family
24.
One should not make waves.
0
1
2
3
25.
One need not control one’s expression of emotions.
0
1
2
3
254
Vita
EDUCATION
Ph.D., Child and Family Studies, Syracuse University, December 2011
M.A., Creative Art Therapy, Drexel University, 2003
Master’s Thesis Title: The Draw-An-Animal Projective Art Therapy Assessment
Tool as an Expression of Self-Concept in Normal Latency Aged Children – A
pilot study, advised by Nancy Gerber, Ph.D.
B.A., Special Education, Ewha Womans University, R.O.Korea, 2000
B.F.A., Fine Art-Sculpture, Seoul National University, R.O.Korea, 1992.
WORK EXPERIENCE
- Assistant Lecturer, Early Childhood Education, The College of Education,
Idaho State University, 2010-2011
- Teaching Assistant, Child and Family Studies, The College of Human
Ecology, Syracuse University, 2005-2010
- Educational Specialist, CNY Korean School, Syracuse, NY, 2008-2010
-
Medical Art Therapist, Samaritan Sunlin Hospital Handong University,
R.O.Korea, 2004-2005
Behavioral Specialist Consultant/ Therapist, Holcomb Behavioral Health
Center, Allentown, PA, 2003-04
Consultant & Educational Specialist, Northern Home for Children and Family
Services, Philadelphia, PA, 2002
PUBLICATION
Kim, S., & Smith, C. J. (2009). Analysis of intercountry adoption policy and
regulations: The case of Korea. Children and Youth Service Review,
doi:10,1016/j.childyouth.2009.04.006

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