1. UK Children Go Online: Balancing opportunities and risks in children & teenagers’ use of the internet Sonia Livingstone

2. Aims and methods Two areas of opportunity: Education, informal learning and literacy Communication, identity and participation Two areas of risk: Access, inequalities and the digital divide Undesirable forms of content and contact Phase 1: Qualitative Summer/ Autumn 2003 Children’s focus groups Family visits/ in-home observation Children’s online panel Phase 2: Survey Jan-March 2004 In-home face-to-face survey of 1,511 9-19 year olds Written survey of 906 parents of 9-17 year olds Phase 3: Qualitative Summer/ Autumn 2004 Children’s focus groups Family visits/ in-home observation Children’s online panel

3. Internet access growing rapidly

4. Among 9-19 yr old users (weekly +):  90% schoolwork  94% information  71% email  70% games  55% instant message  46% download music  40% (12+) look for products  34% made a website  26% (12+) read the news  25% (12+) personal advice  21% visit chat rooms  21% (12+) plagiarise Opportunities to explore, create, network, subvert... I use it for like homework, emailing my cousin in Australia and keeping in touch with my friend in Cornwall. (Linda, 13, Derbyshire) You don’t buy CDs anymore, you just get them off the internet or off one of your mates who copies CDs. (Nina, 17, Manchester) It’s just like life, you can do anything really. (Lorie, 17, Essex) “ The best thing about the internet is downloading music, things like that, and MSN. (Ryan, 14, Essex)

5. What are they skilled at?

6. There’s also a downside Porn? There’s more, much more on the internet. (Prince, 16, London) Yeah, these boys just go onto the internet, they download it, they put it on as screensaver… It’s just disgusting. (Tanya, 15, London) It’s like you don’t know who’s doing what, who’s website it is, who wants what, who wants you to learn what. (Faruq, 15, from London) There’s obviously the scare of paedophiles and people like that on chat rooms (Alan, 13, Essex).

7. Towards an explanatory model j Demographics Internet literacy Internet access Internet use Online opportunities Online risks + + + + + + + + + +

8. Interpreting the model  Age: direct +ve effect on access, use, skills, opportunities (not risks)  … and indirect effect on skills/self-efficacy, mediated by access  … and indirect effect on opportunities, mediated by access, use, skills  Gender: direct effect on online risks (boys – more pornography)  SES: direct effect on # access locations – other effects (on use, literacy, opportunities) are indirect, mediated by access (so, improve access…)  Access: direct effect on use, literacy, opportunities (indirectly, on risks)  Use: direct effect on opportunities, indirect effect on risk  Literacy does not reduce risks  Skills (but not self-efficacy)  opportunities (so, improve literacy…)  Opportunities  risks (can’t separate?); but risks discourage opps

9. Do parents make a difference?

10. Technical solutions: some confusion

11. Social solutions: divergent views

12. Parental mediation is widespread  Parents implement more rules and regulations for younger teens, and more if they are skilled/experienced online; but no gender difference  Especially, restrict interactive uses or engage in active co-use; fewer technical solutions or covert monitoring  Multiple regression showed that characteristics of the child (age, gender, use, skills) explained 28% of the variance on online risk  But parent characteristics and parental mediation did not add significantly to the equation  So, more parental mediation does not reduce child’s online risk  Except, specific parental bans on interactivity (chat, email, IM, games, downloading) did reduce risk (and, for teens, the benefits of internet…)

13. Child characteristics matter  Frequency of online communication predicted by age (older), gender (girls), freq. of use, skills, sensation-seeking, value anonymity online  Made online friend predicted by freq. of use, skills, life satisfaction (less), confidence in online communication, value anonymity  Met online friend offline predicted by age (older), years of use (fewer), skills, shyness (less), sensation-seeking, life satisfaction (less), confidence in online communication, value anonymity  Sought personal advice online predicted by age, freq. of use (less), skills, life satisfaction (less), value anonymity  Given out personal information online predicted by age, freq. of use, self-efficacy (less), skills, sensation-seeking, life satisfaction (less), value anonymity

14. Conclusions  Important to balance risks and opportunities  Different picture for different groups of children and parents  Take care in relying on parental regulation, because:  Though parents regulate, it doesn’t seem to reduce risks  Children often more expert than parents online  Parents and teenagers don’t always communicate well  Exact nature of risks (or opportunities) difficult for families to identify/agree  Children relish being playful, experimental, naughty, deceitful online  Children seek to evade parental regulation and protect their privacy online  Parents often confused about online filtering/safety mechanisms  Parents claim more responsible practice than really occurs  Social and parental support are stratified – those with fewest resources may also be most at risk  Need continual research on children and parents, updated for new risks

15. Thank you Sonia Livingstone Department of Media and Communications London School of Economics and Political Science s.livingstone@lse.ac.uk www.children-go-online.net