Chapter 4: Results
4.2. General findings
The following is a report of descriptive results of the major variables in the current study.
Internet self efficacy
The survey on Internet self efficacy items indicated that the large majority of participants were able to find information online with 87.5 % answered or agree or strongly agree. When it comes to understanding terms related to Internet and explaining why a task will not run on the Internet, participants were less confident with 54.6 % and 50.7%
responded agree or strongly agree respectively. The highest self efficacy was found on “I feel confident using an e-mail” item, with 96.6% answered agree or strongly agree. The results also showed that the majority of participants are able to navigate social media (82.1% answered agree or strongly agree). Other items being asked included “I feel confident chatting with other people online“ (82.1% agree or strongly agree), “I feel confident installing an application or software” (74.4% agree or strongly agree), and “I feel confident filtering or blocking websites with inappropriate contents (59.4%).”
Parental mediation
In regards to interaction restrictions, 59.4% of parents would stay nearby when the child is online, with 25% were neutral, and 15.5% disagreed. 84.5% of parents would not put computer in child’s bedroom, while 87.4% would set rules about time child spent online. 76.2% of parents also found it helpful to talk to their child about Internet use. When it comes to technical restrictions and monitoring strategies, 58 % of parents would set up filters on the website, while more than half the parents would monitor child’s visited websites (58.3%), check child’s SNS (52.2%), and check child’s online chat partners (55.1%), however only 43% agree to check child’s email messages. Another thing worth of note is that about 44% of parents disagree on forbidding child to use SNS, with 37.2% were neutral about it and only 18.3% agreed to do so. Other results include most parents
agreeing to forbid child’s online shopping (70%), and agreeing to forbid child to give out personal info online (67.2%).
Risk perception
The majority of the parents agreed or strongly agreed that their child may be exposed to inappropriate contents (61.9%), while 60.1% of parents agree that these
contents are likely to severely affect their child. Slightly less parents agreed that their child is likely to experience risky online interaction (54.6%), but slightly more parents agreed that their child would be severely affected by risky online interaction (61.9%). Last but not least, when asked whether their child is likely to initiate or produce risky contents or interactions online, more parents disagreeing (40.1%) than agreeing (33.3%) with 26.6%
were neutral. In regards to the severity of the conduct risk, about 40.1% agree that it will severely affect their child.
Media usage
In terms of which media outlet do parents hear more about Internet risk news, television (54.2% answered often or common) and Internet (56.3%) are the two major sources. Newspapers were rated lower as the source of Internet risk news, with only 26.1%
of parents answered common or often. In terms of the media that parents normally use to read or watch news, Internet had a slight edge with 74% of parents answered 5 to 7 days, followed by television (66.8% answered 5 to 7 days), and newspapers (55.4% answered 5 to 7 days).
4.3. Tests of hypotheses
In this section, the previously stated hypothesis will be tested in relation with the data acquired. The Statistical Package for the Social Sciences (SPSS) program was utilized to validate, compute, and describe the relations between variables that shape the
hypothesis.
H1: Parents’ exposure to Internet risk news would increase their risk perception of Internet use for their children.
In order to test the first hypothesis, Pearson’s correlation was used to test the relationship between Parents’ exposure to Internet risk news and parents’ risk perception towards Internet. Partial correlation was used for the analysis, taking into account the participants’ age and gender. The result showed a positive correlation (r = .20) with a significance of p<.01 level therefore supporting the hypothesis one.
RQ1: How do different media (i.e. television, newspapers, and Internet) influence parents’ perceptions and attitude towards Internet risk?
A more comprehensive look on Pearson’s correlations among parents’ exposure to risk news and parents’ risk perception showed there was a moderate positive correlation between exposure to Internet risk news via Internet and parents’ risk perceptions towards Internet (r = .303) with a significance of p<.001 level. No significant results were found between exposure to Internet risk news via television, via newspapers, and parents’ risk perception. The number of days parents see news online also correlated (r=.320, p<.001) with how often they see the Internet risk news online. No such results were found with television and with newspapers.
H2: Parents who perceive Internet as a high risk to their children’s safety would be more likely to mediate children’s Internet use.
For testing the second hypothesis (and third), regression analysis was used to examine different variables that might explain or predict parental mediation behavior. As shown in Table 3, the hierarchical regression model that included self efficacy, risk perception, media usage and exposure overall explained for about 43% of variance in predicting parental mediation behavior (R square=.427). In particular, when risk perception was entered at the
second level after demographic variables were controlled, the variance explained increased drastically (β= .429, p< .001, R square change = .236). Such finding indicated risk
perception as an important positive predictor for parental mediation behavior. The variable resulted in it can be concluded that parents’ risk perception towards Internet has a moderate to strong positive correlation with Parental Mediation, therefore supporting H2.
Table 4
Hierarchical multiple regression analysis of parental mediation
Level Variables β t p-value
1 Sex .068 .945 .346
Parent’s age -.140 .-1.637 .103
Children’s age
.003 .038 .970
Household Income .192 2.549 .012*
R square =.043
2 Risk Perception .498 7.788 .000***
R square change =.235
3 Self Efficacy .322 4.227 .000***
R square change = .095
4 Days Watching TV News -.098 -1.570 .118
Days Reading Newspapers -.001 -.019 .985
Days Seeing Internet News -.007 -.096 .924 R square change = .009
5 Issue Exposure on TV 227 2.997 .003**
Issue Exposure on Newspapers 060 .872 .385 Issue Exposure on Internet -.080 -.960 .338 R square change = .045
R square total = .427 Note: ***=p <.001, **=p<.01, *=p<.05
RQ2: How do different types of risk perceptions (i.e. content, contact, or conduct) correlated with different use of parental mediation strategies?
To answer RQ2, Pearson correlations were conducted between different types of risk perception (Content, Contact, Conduct) and parental mediation. Partial correlation method was used to control participants’ sex and age variables. Results showed that all three types of risk perception have a moderate to strong positive correlations with parental mediation, with Content reported as the highest (r = .478), followed by Contact (r=.410) and Conduct (r
=.393). The results were all significant at p <.001.
H3: Parents’ Internet self efficacy is positively correlated with use of technical restrictions and monitoring strategies.
As the regression table suggested, self efficacy had some effect on parental mediation (R square change =.094), ( R square =.115) and further regression analysis was conducted on interaction restrictions, active co-use strategies of parental mediation and the one with technical restrictions, monitoring strategies of parental mediation. The results indicated that internet self efficacy had a slightly bigger impact on technical restrictions and monitoring strategies (R square =.115) than on interaction restrictions and active co-use strategies (R square =.053). Partial Pearson’s correlations were also conducted to test the H3 while
controlling the participants’ sex and age variables. The results showed that parents’ Internet self efficacy correlated positively with technical restrictions and monitoring strategies of parental mediation (r = .348, p<.001), therefore both the correlations and the regression analysis supported H3. In regards to two other types of parental mediation strategies, results also showed a positive correlation between interaction restrictions, active & co-use strategies and parental mediation (r=.248, p<.001) albeit slightly weaker than the other two strategies.
Chapter 5 Discussion
5.1. Major findings and implications
As expected, the participants from Taipei sample showed less proof of digital divide when it comes to household income and Internet access, based on their general competence in operating Internet technology. A large majority of sample knew how to find information online, chat with others online, and navigate social media. Results from the media usage section also revealed that people read more Internet news and read fewer newspapers, with television news ranked in between. According to the survey, participants read news related to Internet risk the least amount in the newspapers. While television and Internet fare pretty similar with each other in this regards, television was found to be one medium that significantly affects parental mediation, while Internet was found to significantly affect parents’ risk perception. This confirmed that parents’ fear and behavior on Internet mediation had been influenced or aggravated by media portrayals of Internet risk. Clark’s (2009)
argument that such apprehension is to be documented more so among parents from lower income families was also not found in this study, as there was no negative correlation between parents’ household income and either parents’ risk perception or their mediation behavior.
While Clark (2009) previously stated that parents who have less experience with communication technology may express more concerns on the matter, the current study revealed that parents’ risk perception actually escalated among parents who are high on Internet self efficacy. Savolainen (2002) also suggested that parents’ Internet literacy would make parents supervise less, which was also not supported by the current study. The possible explanations to all these is that the familiarity to communications technology may make parents become more aware of the issues related to the Internet and therefore encouraging parents to take a more active role in managing it. Such awareness might also explain parents’
relative unwillingness to forbid children to use social media, as they might have perceived it as a beneficial tool for children’s development and social interaction.
Despite the fact that most literature on parental mediation focused on television as medium, the risks are greater on the Internet, and the parents are well aware of it. This is evinced by parents’ relatively equal apprehension between content risk and contact risk, which is a variable that did not previously exist in media studies with television. Parents’
anxiety in (especially) content risk and contact risk would then translate to how parents mediate children’s Internet, as risk perception was indeed found to be the biggest predictor of parental mediation. The study showed parents employed different kind of strategies to get a control of the situation. While the majority of parents felt communication was key and decided to talk about Internet usage to their children, some found it helpful to monitor some
of the child’s activities on the Internet. The results from this section were for the most part comparable to those of the study conducted by Livingston and Helsper in 2008.
With parent’s Internet self efficacy was found to affect parental mediation, how and to what extent does the process work? Using Livingston and Helsper (2008)‘s categorization of four different strategies of parental mediation, it was originally hypothesized that parents with high Internet self efficacy would be more likely to use mediation strategies that indeed required more Internet skills, namely technical restrictions and monitoring strategies. While the positive correlation was found between them, the positive correlation was also found between parent’s Internet self efficacy and two other strategies that did not require high Internet skills, namely active and co-use and interaction restrictions. The results suggested that what Internet self efficacy might have brought to the parents were not a mere certain technical advantages in parenting, but instead, an overall willingness and motivation to take an active role in mediating children’s Internet.
5.2. Limitations and future research
One major limitation to the study would be the use of convenient sampling, as parents who were available in the afternoon to pick up their child may have shared certain traits or profiles. The question of whether the parent who picked up the child at school would be the same one who set up the rules at home also could only be answered with a mere guess at the moment. That is, the survey was done by one half of the parents and therefore may not have told the whole story. It would also be insightful to do an in depth interview with some of the parents to find the motivational factor behind their behavior, as it would explain why certain parents choose to adopt certain methods and to find out
whether some parents actually learn the Internet skills to better for a purpose of mediating children’s Internet behavior better.
In regards to questionnaire items, certain questions in this study were more difficult to answer among parents who had younger child as some of the situations may not have applied to the child as yet and therefore could only be answered hypothetically, including questions such as banning the use of e-mail, social media, and online shopping. With this in mind, future research may benefit from narrowing and focusing on particular age group (e.g. 6-9 years old or 10-12 years old) to prevent such inconsistencies. Some questions also did not take into account Internet access through mobile phone / Smartphone. Survey item such as “I would not put computer in my children’s bedroom” may not be sufficient to explain parents’ mediation behavior and children’s Internet usage in current situation.
While Smartphone may not be owned by all of the children, especially considering some of their ages, its inclusion into the variables will still be helpful in explaining the whole picture. As Smartphone starts booming in a highly digital city nowadays such as that of Taipei, children’s uses of Internet are consequently more sporadic and even more difficult to track down. As such, Internet’s risks for children are more likely to increase, and the dynamics of parents’ Internet mediation may have been slightly altered, which in turn, demand future research in this area.
References
Ajzen, I. (1991). The theory of planned behavior. Organizational behavior and human decision processes, 50(2), 179-211.
Bandura, A. (1977). Self efficacy: toward a unifying theory of behavioral change.
Psychological review, 84(2), 191.
Bawden, D. (2008). Origins and concepts of digital literacy. Digital literacies: Concepts, policies and practices, 17-32.
Byron, T. (2008). Safer children in a digital world: the report of the Byron Review: be safe, be aware, have fun. London: Department for Children, Schools and Families, and the Department for Culture, Media and Sport.
Cassell, J., & Cramer, M. (2007). High tech or high risk: Moral panics about girls online.
Digital Youth, Innovation, and the Unexpected, 53-75.
Cassidy, W., Brown, K., & Jackson, M. (2012). " Making Kind Cool": Parents' Suggestions for Preventing Cyber Bullying and Fostering Cyber Kindness.
Journal of Educational Computing Research, 46(4), 415-436.
Clark, L. S. (2009). Digital media and the generation gap: Qualitative research on US teens and their parents. Information, Communication & Society, 12(3), 388-407.
Clark, L. S. (2011). Parental mediation theory for the digital age. Communication Theory, 1(4), 323-343.
DeHue, F., Bolman, C., & Völlink, T. (2008). Cyberbullying: Youngsters' experiences and parental perception. CyberPsychology & Behavior, 11(2), 217-223.
Eastin, M. S., & LaRose, R. (2000). Internet self‐efficacy and the psychology of the
digital divide. Journal of Computer‐Mediated Communication, 6(1).
Elena, A., Laouris, Y., & Taraszow, T. (2010). Identifying and Ranking Internet Dangers.
2010 Social Applications for Life Long Learning, 68.
Henke, L. L. (1999). Children, advertising, and the Internet: An exploratory study.
Advertising and the World Wide Web, 73-80.
Kerr, M., & Stattin, H. (2000). What parents know, how they know it, and several forms of adolescent adjustment: further support for a reinterpretation of monitoring.
Developmental Psychology, 36(3), 366.
Lee, S. J. (2013). Parental restrictive mediation of children’s Internet use: Effective for what and for whom?. New Media & Society, 15(4), 466-481.
Liau, A. K., Khoo, A., & Ang, P. H. (2008). Parental awareness and monitoring of adolescent Internet use. Current Psychology, 27(4), 217-233.
Lin, C. W. (2007). E-Learning Strategies for Aboriginal Children in Taiwan.
International Journal of Learning, 14(6).
Livingstone, S., Bober, M., & Helsper, E. (2005). Internet literacy among children and young people: Findings from the UK Children Go Online Project.
Livingstone, S., & Helsper, E. J. (2008). Parental mediation of children's Internet use.
Journal of Broadcasting & Electronic Media, 52(4), 581-599.
Livingstone, S., & Helsper, E. (2010). Balancing opportunities and risks in teenagers’ use of the Internet: The role of online skills and Internet self efficacy. New Media &
Society, 12(2), 309-329.
Lou, S. J., Shih, R. C., Liu, H. T., Guo, Y. C., & Tseng, K. H. (2010). The influences of
the sixth graders’ parents’ Internet literacy and parenting style. Turkish Online Journal of Educational Technology, 9(4).
Lwin, M. O., Stanaland, A. J., & Miyazaki, A. D. (2008). Protecting children's privacy online: How parental mediation strategies affect website safeguard effectiveness.
Journal of Retailing, 84(2), 205-217.
Masters. J., & Yelland. N .(2010). Changing learning ecologies: Social media for cyber-citizens. In S. Shariff., & A. Churchill. (Eds.), Truths and Myths of Cyber-Bullying:
International Perspectives on Stakeholder Responsibility and Children's Safety (pp.229-248) . New York, NY: Peter Lang Publishing, Inc.
Munro, M. C., Huff, S. L., Marcolin, B. L., & Compeau, D. R. (1997). Understanding and measuring user competence. Information & Management, 33(1), 45-57.
Nathanson, A. I. (1999). Identifying and explaining the relationship between parental mediation and children's aggression. Communication Research, 26(2), 124-143.
Nathanson, A. I. (2001). Parent and child perspectives on the presence and meaning of parental television mediation. Journal of Broadcasting & Electronic Media, 45(2), 201-220.
Prensky, M. (2001). Digital natives, digital immigrants part 1. On the horizon, 9(5), 1-6.
Rideout, V. (2007). Parents, Children & Media: A Kaiser Family Foundation Survey.
Henry J. Kaiser Family Foundation.
Savolainen, R. (2002). Network competence and information seeking on the Internet:
From definitions towards a social cognitive model. Journal of documentation, 58(2), 211-226.
Shariff, S., & Churchill, A. (2010). Appreciating complexity: detangling the web of
stakeholder influence and responsibility. In S. Shariff., & A. Churchill. (Eds.), Truths and Myths of Cyber-Bullying: International Perspectives on Stakeholder Responsibility and Children's Safety (pp.1 – 23) . New York, NY: Peter Lang Publishing, Inc.
Shariff, S., & Churchill, A. (Eds.). (2010). Truths and Myths of Cyber-Bullying:
International Perspectives on Stakeholder Responsibility and Children's Safety.
New York, NY: Peter Lang Publishing, Inc.
Stald, G. (2003). Outlook and insight: Young Danes' uses of the Internet, navigating global seas and local waters. The Wired Homestead, 227-260.
Staksrud, E., & Livingstone, S. (2009). Children and online risk: Powerless victims or resourceful participants?. Information, Communication & Society, 12(3), 364-387.
Turow, J., & Kavanaugh, A. L. (Eds.). (2003). The Wired Homestead: An MIT Press Sourcebook on the Internet and the Family. MIT Press.
Valcke, M., Bonte, S., De Wever, B., & Rots, I. (2010). Internet parenting styles and the impact on Internet use of primary school children. Computers & Education, 55(2), 454-464.
Valcke, M., De Wever, B., Van Keer, H., & Schellens, T. (2011). Long-term study of safe Internet use of young children. Computers & Education, 57(1), 1292-1305.
Walrave. M., & Heirman. W. (2010). Appreciating Complexity: Detangling the Web of Stakeholder Influence and Responsibility. In S. Shariff., & A. Churchill. (Eds.), Truths and Myths of Cyber-Bullying: International Perspectives on Stakeholder Responsibility and Children's Safety (pp.27-47) . New York, NY: Peter Lang Publishing, Inc.
Warren, R., & Bluma, A. (2002). Parental mediation of children's Internet use: The
influence of established media. Communication Research Reports, 19(1), 8-17.
Wolak, J., Finkelhor, D., Mitchell, K. J., & Ybarra, M. L. (2010). Online “predators” and their victims. Psychology of Violence, 1, 13-35.
Zinga, D. (2010). Boundaries in Cyber-space. In S.Shariff., & A. Churchill (Ed.), Truths and Myths of Cyber-Bullying: International Perspectives on Stakeholder
Responsibility and Children's Safety (pp.105-127) . New York, NY: Peter Lang Publishing, Inc.
Appendix A – Questionnaire (Chinese version)
網路內容。 電視 ____ ____ ____ ____ ____ ____ ____
報紙 ____ ____ ____ ____ ____ ____ ____
網路 ____ ____ ____ ____ ____ ____ ____
第
_____ 80001 元–110000 元 _____110001 元 - 140000 元 _____140001 元–160000 元 _____
160001 元以上
如果您對本研究有任何相關問題，或是您希望得到關於本研究之後續發展、結果，歡迎與我 聯繫：Vittorio Adrianus (vawritten@yahoo.com).您亦可與本研究之指導教授聯絡：:鄭
怡卉(icheng@nccu.edu.tw) , 副教授, 傳播學院廣告學系, 國立政治大學,
台北市文山區指南路二段 64 號
Appendix B – Questionnaire (English version)
Hello, my name is Vittorio Adrianus . I came from Indonesia. I am currently a second year Master degree student in National Chengchi University, majoring in International
communication. I am currently doing a research on how parents in Taiwan handle elementary school students’ Internet use. The survey will take around 10 minutes to complete. I really appreciate your help and cooperation to make this happen.
communication. I am currently doing a research on how parents in Taiwan handle elementary school students’ Internet use. The survey will take around 10 minutes to complete. I really appreciate your help and cooperation to make this happen.