Taking risks when communicating on the Internet: the role of offline social-psychological factors in young people's vulnerability to online risks

Abstract

Children and young people encounter a range of risks on the internet relating to communication. Making friends online has attracted particular attention as a risky behaviour, especially when this leads to offline meetings, as has giving out personal information online. This article, based on the ‘UK Children Go Online’ survey, seeks to explain the online communication of 9–19-year-olds in terms of their offline socio-psychological characteristics (shyness, life satisfaction, risk-taking), family communication patterns and online behaviour/skills. Findings show that older teens engage in more online communication activities than do younger children and so encounter more communication risks. Although girls communicate more on the internet, this seems not to put them more at risk. It was found that children's offline social psychological characteristics, particularly their levels of life satisfaction and risk-taking, influence their online communication, with different online communication activities being predicted by different patterns of off- and online characteristics. There are weak indications that, in families which have a more conversational style of communication, teens may take fewer risks online, including a lower likelihood of meeting online friends offline. Multiple regression analyses show that those children and teens who are less satisfied with their lives and who have become more frequent and skilled internet users are more likely to value the internet as a communicative environment in which they feel more confident than they do offline, particularly in relation to the potential for anonymous communication. Since this in turn leads some into risky activities, the implications for research and policy are discussed.

Keywords:

• Children and young people
• online communication
• contact risks
• anonymity
• trust

Acknowledgements

This article reports on research funded by an Economic and Social Research Council grant (RES-335-25-0008) as part of the ‘e-Society’ Programme, with co-funding from AOL, BSC, Childnet-International, Citizens Online, ITC and Ofcom (see http://www.children-go-online.net). Thanks to Magdalena Bober, Michael Slater, the project's Advisory Panel, its Children's Advisory Panel and BMRB International.

Notes

1 In random location sampling, interviewers are given little choice in the selection of respondents. Respondents are drawn from a small set of homogenous streets selected with probability proportional to the population after stratification by their postcode characteristics and region. Quotas are set using characteristics known to have a bearing on individuals' probabilities of being at home and available for interview. Strict rules are given which govern the distribution, spacing and timing of interviews. For a detailed explanation of the scales, see Livingstone et al. (2005). Skills scale. This summed the internet-related skills that respondents claimed to be ‘good at’ (scale 0–6): finding the information you need on the Web, setting up an email account, sending an instant message, setting up a filter for junk mail or pop-up adverts, getting rid of a virus on your computer and fixing a problem by yourself when something goes wrong. The reliability coefficient for this scale was acceptable (alpha = 0.70). Self-efficacy: four-point scale (beginner–average–advanced–expert), from Eastin and LaRose (2000). Frequency of use: eight-point scale, from 8 (uses more than once day) through 5 (uses once a month) to 1 (never uses). Average time per day online: Respondents estimated time spent online on a typical weekday and weekend day. A composite score was calculated for average time spent online per day: 1 = none, 2 = about 10 minutes, 3 = about half an hour, 4 = about an hour, 5 = 1–2 hours, 6 = 2–3 hours, 7 = 3 + hours.

2 Specifically, these 9–19-year-olds say that they have revealed their hobbies (27 per cent), email address (24 per cent), full name (17 per cent), age (17 per cent), name of their school (9 per cent) phone number (7 per cent) or sent a photograph (7 per cent) to someone that they met on the internet.

3 Across the whole sample, 40 per cent say that they have pretended about themselves online – using, for example, a different name (27 per cent), changing their age (22 per cent), appearance (10 per cent) or gender (5 per cent). And though they often know the safety rules, a minority (7 per cent) admit to forgetting about safety guidelines online while 17 per cent enjoy being rude or silly on the internet (Livingstone & Bober 2005).

4 Socioeconomic status is measured according to the standard UK market research categories: A – Upper middle class (Higher managerial administrative or professional occupations, top-level civil servants), B – Middle class (Intermediate managerial administrative or professional people, senior officers in local government and civil service), C1 – Lower middle class (Supervisory or clerical and junior managerial administrative or professional occupations), C2 – Skilled working class (Skilled manual workers), D – Working class (Semi- and unskilled manual workers), E – Those at lowest levels of subsistence (all those entirely dependent on the State: long-term, casual workers, those without regular income). Socioeconomic status is strongly correlated with measures of parental occupation, education and income.