This study examines the influence of demographic factors and parenting on Chinese teenagers' internet use and usage at home, highlighting the impact of both adolescents and their parents in shaping internet behaviors. Findings indicate that teenage boys, younger adolescents, and those with higher internet literacy tend to use the internet more frequently, while parental warmth fosters educational internet use. The research suggests that effective parental involvement, rather than strict control, plays a crucial role in guiding teenagers' internet engagement.

1. Internet use and usage of Chinese
teenagers at home: Understanding
demographic and parenting influence
Dr. Wilfred W.F. Lau
Faculty of Education,
University of Hong Kong
13 June 2014

2. Outline of the presentation
Introduction
Literature
Method
Results
Discussion
Conclusion

3. Introduction
It is increasingly being realised that students’ home use of ICT has a significant
positive effect on their academic achievement. Jackson, von Eye, Biocca,
Barbatsis, Zhao, and Fitzgerald (2006) found in their study of low-income
children that increased home internet use was associated with higher
standardized reading achievement scores and grade point averages.
Parents often express their worries and concerns over their teenage internet use
at home (Sorbring, 2014), and this raises the need for parental strategies to
ensure children’s internet safety (Byrne et al., 2014, Livingstone and Helsper,
2008).

4. Introduction
The present study draws on the theoretical framework of Bronfenbrenner’s
Bioecological Systems Theory (1979, 2005), which conceptualises human
development under the influence of the external environment.
In families with adolescents, parents, as the primary socialisation agents in the
microsystem, are expected to have a great influence on their adolescent’s
internet use and usage. On the other hand, it is highly likely that adolescent
demographics also affect adolescents’ use of the internet.
Thus, it is justifiable to consider parents and adolescents as the two most
important contextual factors influencing adolescents’ internet use and usage at
home.

5. Literature Review
Conceptualisation of internet use and usage
In this study, internet use refers to the time spent on the internet and internet
usage refers to the actual use of the internet for different purposes (Yuen et al.,
2014).
This study used the uses and gratifications theory (UGT) to classify the motives
of internet activities as it has provided a good theoretical basis for the
conceptualisation of internet usage in many previous studies (Kalmus, Realo, &
Siibak, 2011).
Central to the theory is that individuals select specific media to gratify their
different needs. It is the differences in demographics and needs that determine
how and why media are used.

6. Literature Review
Demographic influence
Livingstone and Helsper (2007) found that boys used the internet more
frequently than girls; boys had more internet experience and spent a longer time
online than girls.
The authors also found that the young to mid-teens (aged 12-17) tended to be
frequent internet users and to spend more time online.
Appel (2012) indicated that students who were more computer literate tended to
spend more time playing computer games. These students were also frequent
users of social media.

7. Literature Review
Parental influence
Studies have examined the influence of the following parental variables on
teenage internet use and usage: parenting style, parental educational level, and
parental mediation.
Recent studies usually use parental warmth and control to represent parenting
style in regard to ICT use.
Lwin, Stanaland, and Miyazaki (2008) found that parental control reduced the
levels of internet usage. However, Eastin et al. (2006) reported that parenting
style did not affect time spent online. On the other hand, Lee and Chae (2007)
found that parental warmth appeared to be associated with more educational
use of the internet and positive internet behaviours.
Parental educational level has been found to enhance internet usage. Sun et al.
(2005) found that parental educational level was positively related to internet
usage among adolescents.

8. Literature Review
Parental influence
In terms of parental mediation, Lee and Chae (2007) showed that parental
restrictions on the time span and type of web sites did not alter children’s actual
internet usage.
On the other hand, Lee (2013) demonstrated that restrictive mediation
negatively predicted time spent online during weekdays and during the
weekend.

9. Literature Review
Internet use and usage of teenagers in China
According to the 2012 Research Report of China Youth Internet Behaviors
(CNNIC, 2013a), middle school students on average spent 13.3 hours online
every week. The three most popular internet usages among these students were
instant messaging (87.1%), information search (86.9%), and online music
(84.2%).
Huang (2014) reported that many teachers complained parents for not properly
control their children’s social media use at home and believed that this caused
social media addiction among teenagers. On the other hand, parents found it
difficult to exercise effective control of their children’s social media use at home.

10. Literature Review
On the basis of the literature review above, the present study addressed the
following research questions (RQs) and hypotheses (Hs):
 RQ1: What are the effects of teen demographics on internet use and usage
among teenagers in China?
 H1: The young to middle teenagers are more frequent internet users than
teenagers of other ages.
 H2: Male teenagers engage in more internet use and usage than female
teenagers.
 H3: Teenagers with more internet experience engage in more internet use
and usage.
 H4: Teenagers with higher levels of internet literacy engage in more internet
use and usage.
 RQ2: What are the effects of parenting on internet use and usage among
teenagers in China?
 H5: Parental warmth is positively related to learning-related internet usage.
 H6: Parental control has no effect on, or is negatively related to, internet use
and usage.
 H7: Parental educational level is positively related to internet usage.
 H8: Parental restrictive mediation has no effect on, or is negatively related to,
internet usage.

11. Method
Participants
A total of 575 students from six middle schools participated in this study on a
voluntary basis. Of the participants, 288 were male and 278 were female (Nine
students did not report their gender). Their mean age was 13.928 (SD = .874).
The schools are located in the Nanshan District of Shenzhen, China.
Dependent variables
Students’ internet use was measured by students’ responses to a single item: “In
the past two weeks, how many hours on average have you spent on computers /
the internet every day?” The item was measured on a 5-point scale, with 1: less
than two hours; 2: two to three hours; 3: four to five hours; 4: six to seven hours;
and 5: more than eight hours.
Internet usage at home was assessed in relation to two dimensions: (a) learning
and (b) leisure (Kalmus, Realo, & Siibak, 2011).
The first dependent variable, learning-related internet usage, contained seven
items, while the second dependent variable, leisure-related internet usage,
contained five items. All items were measured according to a 5-point Likert
scale, with 1: never, to 5: always.

12. Method
Independent variables
Demographic variables consisted of age, gender, internet experience, and
internet literacy.
Parenting style was measured using a scale based on parental warmth and
control dimensions (Valcke et al., 2010) and previously validated with Hong
Kong parents (Lau & Yuen, 2013). There were 4 subscales: encouragement,
worry, monitoring, and permission. A 5-point Likert scale, from 1: strongly
disagree, to 5: strongly agree, was used for all the items.
Parental educational level was assessed with two items, and three options
provided, with 1: completed elementary school; 2: completed high school; and 3:
completed college or above.
The following item measured parental mediation: “How many hours maximum do
your parents allow you to use computers / the internet every day?” This item was
measured on a 6-point scale, with 1: can only use under supervision; 2: less
than half an hour; 3: half an hour to less than one hour; 4: one hour to less than
two hours; 5: two hours or more; and 6: no restriction.

13. Method
Data analysis
Three pairs of hierarchical multiple regression were conducted to test the effects
of demographics and parenting on internet use and usage.
For each pair of the regression model, the block of demographic variables was
first entered, which was then followed by the block of parenting variables. In the
second analysis of the pair, in order to compare the unique contribution of
demographics and parenting on internet use and usage in terms of the
proportion of variance explained, the order of entry of the two blocks was
reversed (Petrocelli, 2003).

14. Results
As shown in Table 1, students had spent an average of two to three hours on
computers / the internet every day in the two weeks preceding the time of the
survey. They were engaged less in learning-related internet usage than in
leisure-related internet usage. They had, on average, 8 to 11 years of
experience of using computers / the internet and regarded their internet literacy
as good.
The dominant parenting style was permission, which was followed by worry,
encouragement, and monitoring. In terms of educational level, fathers and
mothers had at least completed high school. On average, parents allowed their
children to use computers / the internet from one to two hours every day.

15. Results
Variable Mean SD
Dependent variables
Internet use
2.071 1.273
Learning-related internet usage
2.755 .839
Leisure-related internet usage
3.117
.887
Independent variables
Demographic factor
Age
13.928 .874
Gender 0.491 .500
Internet experience 3.355
1.116
Internet literacy
2.787 .985
Parenting factor
Encouragement 2.952 .897
Worry 3.291 .916
Monitoring 2.874 1.079
Permission 3.475 .899
Father educational level 2.561 .548
Mother educational level 2.422 .624
Parental mediation 4.132 1.524
Table 1. Means and standard deviations of the variables used

16. Results
From Table 2, in the first hierarchical regression analysis, demographic
variables together accounted for 3.6% of the variance in internet use, 4.4% in
learning-related internet usage, and 5.7% in leisure-related internet usage. The
inclusion of parenting variables in the second block increased the variance
explained from 5.3% to 13.6% for the respective dependent variables.
When the two blocks of variables were entered in reverse order in the second
hierarchical regression analysis, parenting variables account for 6.4% of the
variance in internet use, 14.6% in learning-related internet usage, and 16.8% in
leisure-related internet usage. Demographic variables explained an additional
2.5% to 3.0% of the variance in the three dependent variables when they were
included.

17. Results
Regression Predictors Internet use Learning-related internet usage Leisure-related internet usage
First Step 1 β β β
Age .096* -.014 .045
Gender -.121* .022 -.063
Internet experience .115* .134** .158**
Internet literacy .021 .120* .119*
R2 .036** .044*** .057***
Step 2
Encouragement .040 .297*** -.010
Worry -.035 .108* .060
Monitoring .030 .083 .178***
Permission .115* -.100* .302***
Father educational level -.139* .040 .032
Mother educational level -.082 .083 -.091
Parental mediation .019 -.027 -.031
∆R2
.053*** .132*** .136***
Second Step 1 β β β
Encouragement .047 .289*** -.009
Worry -.035 .103* .057
Monitoring .038 .099* .190***
Permission .141* -.064 .335***
Father educational level -.151* .043 .026
Mother educational level -.067 .103 -.074
Parental mediation .019 -.034 -.034
R2
.064*** .146*** .168***
Step 2
Age .046 .022 .046
Gender -.111* .050 -.040
Internet experience .109* .107* .121*
Internet literacy .024 .107* .066
∆R2
.025* .030* .025*
Total R2
.089*** .176*** .193***
Table 2. Hierarchical multiple regression of demographic and parenting variables on internet use and usage
*p < 0.05. **p < 0.01. ***p < 0.001.
*p < 0.05. **p < 0.01. ***p < 0.001.

18. Discussion
Consistent with the tenets of Bronfenbrenner’s (1979, 2005) Bioecological
Systems Theory, internet use and usage were predicted by a unique
combination of demographic and parenting variables. This provided evidence to
confirm or refute some of the hypotheses made in this study.
For RQ1, internet use was not associated with age and this did not support H1.
Males tended to spend more time on the internet than females and students with
more internet experience were more likely to spend longer time on the internet.
More internet experience also resulted in more internet usage. Those with higher
internet literacy tended to engage in more learning-related activities. This is very
encouraging from parents’ perspective. These findings support H2 to H4 and are
consistent with the findings reported in previous research (Appel, 2012,
Livingstone and Helsper, 2007, Soh et al., 2013).

19. Discussion
For RQ2, internet use was negatively associated with father’s educational level.
Mother’s educational level had no effect on internet use and usage.
It is speculated that better educated fathers may make use of a variety of
parenting strategies including the installation of filtering and blocking software to
limit the time their children spend on the internet, and some of these strategies
may be less known among better educated mothers.
In terms of internet usage, learning-related and leisure-related internet usages
were positively related to parental warmth and parental control respectively. H5
was supported but H6 was not. Internet usage was not associated with parental
educational level and thus H7 was not supported.
Parental restrictive mediation expressed in the form of a limit in the amount of
internet use has virtually no effect in the regulation of use and usage. H8 was
supported. This agrees with the findings of Lee and Chae (2007) that while
parental restrictions on the time span and type of web sites did not alter
children’s actual internet usage, parental warmth was associated with more
educational use of the internet and positive internet behaviours. These findings
indicate that the emotional climate created by parents appears to affect internet
behaviours (Darling and Steinberg, 1993).

20. Discussion
The results from hierarchical multiple regression analysis indicated that parents
played a dominant role in influencing the teenagers’ internet use and usage.
Parenting as a means of socialisation exerted a greater effect on the teenagers’
internet use and usage than the influence of teen demographics. Parents were
able to provide a family socialisation context in which to influence their teenage
children in terms of parental values and goals.
While the majority of previous studies have focused on adolescents’ internet
access and use, this study addressed the issue of internet use and usage. Also,
there is a dearth of related research within the home context in the literature,
and this study attempted to fill this gap and advance our current understanding
of the topic. Overall, the findings of this study provide a snapshot of teenagers’
internet use and usage at home in China today.

21. Conclusion
Home provides an important environment for the growth and development of
young people. Researchers have been exploring the interactive socialisation
process by which parents attempt to transmit their values, attitudes, goals, and
skills to their teenage children.
With the increasing amount of ICT access at home, attention has been paid to
examine parenting within the context of internet use and usage as well as the
educational outcomes. This study sheds light on how individual characteristics
and parenting shape teenage internet use and usage at home in China. Given
that there are potential differences in terms of demographics and parenting
across Chinese cities, there is a need to consolidate the evidence collected in
this study in future research.

22. Q & A Session
Thank
you
very
much