Engaging in risky online behaviour - prevalence and associated factors: initial findings

2. Introduction

Online communication is prevalent in today's society, especially among older children and adolescents. This rise in online communication has increased the opportunity for online risk taking, as well as the potential for harm.

Considering crime in Scotland, it is estimated that around half of the growth in all sexual crimes recorded by the police between 2013-14 and 2016-17 was due to a rise in cyber crime (Scottish Government, 2017). Cyber crime are crimes where the internet is used as a means to commit the crime. These cyber crimes were reported to account for around half of 'Other sexual crimes'^[3] recorded in Scotland between 2013-14 and 2016-17. The most common crime within this category was 'Communicating indecently and cause to view sexual activity or images'. When this crime was committed online, victims and perpetrators tended to be much younger than when it was offline. Three quarters of victims of this cyber crime were under the age of 16 in 2016-17, with an average age of 14. In a quarter of cases both the victim and perpetrator were under the age of 16.

Using 2017-18 data from the Growing up in Scotland (GUS) study (see Section 2.1), this report seeks to provide an initial insight into children's online risk taking. It aims to estimate the prevalence of risky online behaviours in Scotland amongst 12-year-olds using pre-existing data. It also aims to provide an insight into associations between online risk taking and individual, family, peer relationship, and online safe guarding factors. In doing this, this report offers a first step towards understanding the frequencies and associations with children's online risk taking in Scotland.

2.1 COVID-19

However, it is important to recognise the current context of the COVID-19 pandemic, and its potential implications in relation to this report's findings. It should be noted that the data collection and analyses for this report were conducted between 2017 and 2019 before the COVID-19 pandemic. As a result, the findings do not consider the impact of the pandemic, and the potential consequent changes in the factors examined. For example, since the COVID-19 pandemic, school closures, and social distancing restrictions have increased children's use of online digital platforms (Generation Scotland, 2020). As a result, the frequencies of time spent online are likely to have increased from the frequencies reported here. Additionally, there are concerns regarding the increased risk of online child harassment and sexual exploitation (UNICEF, 2020). The Internet Watch Foundation (IWF) reported a 50% increase in reports of online child sexual abuse during lockdown (IWF, 2020). However, the relationships between these risks (online child harassment and sexual exploitation) and engagement in risky online behaviour has not yet been explored.

Another important point to regard is the potential changes in frequencies of the associated factors as a result of the COVID-19 pandemic. Despite that analyses conducted in this report do not allow for the drawing of causal conclusions regarding the relationships assessed, changes in risk factors and their potential impact on risky online behaviours should be borne in mind.

2.2 Growing up in Scotland (GUS)

GUS^[4] is a longitudinal study which follows several different nationally representative cohorts of children in Scotland at key stages of their childhood. This report uses data gathered as part of birth cohort 1 (BC1), set up in 2005/6 when children were aged 10 months. These children and their families have been periodically followed-up at annual and biennial intervals (termed 'sweeps'). The most recent data available for analysis is from sweep 9 (2017/18) when children were aged 12 years old. Fieldwork for sweep 10 was completed in 2019/20 and data will be available mid-2021.

At sweep 9, questionnaires were administered to the children themselves, their main parent/carer and their second parent / parent's partner (if applicable). Across the sweeps, some questions are repeated each time, some new questions and measures are included at different sweeps and some are dropped. GUS is a robust and rich source of data for understanding the lives of children and young people in Scotland.

2.3 What are risky online behaviours?

Online risks are multi-faceted (Staksrud & Livingston, 2009), and can include sending personal information, sending personal photos or videos, and agreeing to meet up with strangers. For children, online risks can also involve lying to parents about their online activities, or doing something online of which they know their parents would not approve. This report has focussed its definition for risky online behaviour around the content of the GUS sweep 9 questionnaire, centring on six key questions/ behaviours summaried in Figure 1.

2.4 How are behaviours and their associations explored?

This report presents a cross-sectional analysis, using sweep 9 data gathered as part of the GUS study. Data for this sweep were collected in 2017-18 when the children were aged around 12, with most being in their second term of their first year at school. For more information on the GUS data, see Appendix 10.1.

Questions in the GUS dataset were mapped onto groups of risk factors (individual, family, peer, online safeguarding) identified from the literature review. Exact questions used for the analyses are discussed at the beginning of each section. First, frequencies were calculated for all six risky online behaviours. Second, the frequencies of risky online behaviours within each risk factor group were calculated. Finally, statistical analyses were used to analyse the associations between engaging in risky online behaviour and each factor group. For more information on analyses performed, on how each measure was constructed, and on the methodology used in analyses, see Appendix 10.1.

2.5 Considerations and limitations

Only statistically significant associations are presented in the main body of this report, with supplementary data included in Appendix 10.2.

While care has been taken to ensure the results here are reliable, there are several considerations that should be kept in mind when interpreting the results:

• Analyses in this report are based on data relating to one point in time (i.e. cross-sectional analysis). As such, the presence of associations between risky behaviours and potential risk factors cannot be taken to imply causation.
• Bivariate analyses were performed to examine the associations between two variables. This method does not account for other factors that may influence both variables.
• The proportion of children who engage in risky online behaviours is relatively low (see section 3). It should therefore be understood that, while factors discussed are significantly associated with risky online behaviours, these apply to a minority of children.
• The recent impact of the COVID-19 pandemic should be considered when interpreting the results of this report. Reported frequencies of risky online behaviour and their associated risk factors should be understood as being examined in a pre-pandemic context. Therefore, potential changes in these factors due to the COVID-19 pandemic should be kept in mind.