 So welcome to today's webinar, Introducing Data on Information and Communication Technologies. I'm Marguerita, I work at the UK Data Service and I'm based in Manchester. And today I'm presenting with Cara Booker, our research fellow at the Institute for Social and Economic Research at the University of Essex. Right, before we start, just a couple of things. So all attendees are muted throughout the webinar so we won't be able to hear you. However, if you do have any comments or any questions, you can type them in the questions box, which you should see on the go-to-webinar interface. Also on the interface, you should see a expandable menu called the handouts. And I have uploaded a presentation in PDF format if any of you wants to download it before the end of the presentation and wants to note an air or click on the links or so on. That's available to you. It should also be available on our website a couple of days from today with the recording of the webinar if everything goes smoothly. Right, so before I start the actual presentation, I have a question for you. And I'm going to launch a poll and just to check that everybody can hear me. Right, you should see it appear on screen now. Okay, most of you have voted. Right, give it a couple more seconds, three, two, one. Oh, and as you can see, all of you can hear me, which is great. So the next slide is not necessary, fortunately. Right, so overview of today's webinar. I'm going to talk about some data on information and communication technologies. And I'm going to show you how to search and find it on our website. I'm also going to talk through the supporting documentation and useful resources that the UK Data Service holds. And then Kara will talk about her research. So she will give an overview of the aim of this study, the data used, which is understanding society, the methodology, and the discussion. And at the end, we'll take your questions. Right, so information and communication technologies are reshaping the world, transforming the way in which we communicate, work, manage crisis to business, and even spend our free time. And these changes, in turn, drive new policy development to address the societal impacts of digital technologies. So it's an important element of the social world, and there's lots of research that's being conducted around this topic. The UK Data Service holds data on a wide range of ICT topics, such as mobile communication, telework, social media, radio, television, internet use, mass media, security trust, and so on. These key research areas help you understand how the fast evolving world of digital technology impacts people, lives, and communities. And it also changes the way we interact, and that's why it is one of the key areas of interest for many social scientists. So many surveys collect data on information and communication technologies, but the information collected can vary. So the first task in the beginning to research ICT is to search for a good source of data. And that's where the UK Data Service can help. So for those who are unfamiliar with the UK Data Service, we provide a single point of access to a wide range of social science data. If you're new to the service and want to know more about how to search and access our data holdings, you can find many video tutorials, and there's a link here at the bottom, and especially if you've downloaded the slides, you'll be able to click on it. Right, just very quickly, let's talk about how to find and search for ICT-related data on our website. So this is our homepage, ucdataservice.ac.uk, and obviously you can type a keyword in our Discover search box, or you can go to data types if you already know which type of data you're looking for. So if it's census data, international data, longitudinal data, UK service, or so on. However, we do also have theme pages, and information and communication technologies is one of the themes that we have them on. So let me just give you short demonstration of these pages. So you get to them on our website, we're going to get data, and then data by theme, and this one is information and communication. So under the key data tab, so the first tab, you just find a list of the main studies that we hold that are related to ICT, and you can see, for example, the British cohort study, British social attitudes survey, community life survey, and so on. It gives you an idea of the coverage and of the topics. These are only the main studies, it's important to remember. So if you go onto the Discover search box, you can see the links for this Discover tab here. There's links to just all the range of studies related to information and communication, and just also links to discovering other resources that we hold. Under the Analyzing tab, we've got some video tutorials on how to visualize and analyze ICT data using our platforms. For example, Nesta and UKDS.stat. Under Research, we've got some examples of how data has been used in research, so our case studies. The first one is the research Kara is going to talk about later on. Then here, for example, we've got one about broadband access in the UK. Then last but not least, we've got a tab on internal and external resources that could help researchers conducting research on ICT. Right, so back to the presentation. I just wanted to give you a few examples of what kind of data statistics you'll find. So I just have some simple frequencies to show you. So for this one, I've used Nesta and the dataset that it comes from is the Opinions and Lifestyle Survey, Internet Access Module, January, February and March, 2014. And you can see there at the top. And the question that has been asked to respondents is do you or anyone in your household have access to the internet at home by any device, regardless of whether it is used? And you can see the percentage of people that responded yes, for example, which is 83.6%. The percentage who said no, don't know, refusal, and then the valid cases, the missing cases and so on. So this is an example of what kind of variables you'd find. And then I've got another example. This one comes from the Community Life Survey, 2014, 2015. And the question is, speak on the phone or video or audio call by the internet with family members or friends. So they're asking if they have these phone or video calls more than once a day, once a day, two to three times per week, about once a week. And I think these are really interesting statistics that you could find on surveys. And then my last example comes from the World Bank, World Development Indicators, 2014. And it's about internet users per 100 people, though, of all countries. As you can see, I've left the first one out, the one in pink, 98.2%. And I've got another question for you. So I'll give you a couple more seconds to look at this bar chart. And then I'm going to ask you, what do you think the first country then is? Let me just launch this poll. So which country had the highest number of internet users per 100 people in 2014, according to the World Bank? And let's see what you think. Right, you can see most of you have voted. Okay, interesting results. I'll give it a couple more seconds. And now I'm going to close the poll and let me share the results. Right, so 50% of you said Iceland, 4% of you said Latvia, 36% said China, 0% said Italy and 11% said Hawaii. And most of you were right. So it is Iceland and I'll show you in the next slide. So Iceland had the highest number of internet users per 100 people in 2014. Well done to whoever said that. Right, and then before I hand over to Kara, I'd just like to talk to you about accessing and downloading the data from the UK Data Service. So access to our data can come from different forms of license and access conditions. The different access arrangements reflect the risk of potential disclosure. All the data are anonymized, but if you had detailed information about say a person's job, which sector of work in the area they live in, as well as the age and gender and other information, there's a cost danger that in some cases you could identify who that person is. Most of our data is in the second category. So under the end user license, which only requires registration. So just a username and password. However, we do also have more restricted data sets, which come under special license or secure access. We've got a small number of open data sets, some international data sets, for example, DOECD, IMF and World Bank data are open. But as I said, if you're not registered with the UK Data Service, you should do so, and then you get access to most of our data. So other resources and support we offer. So we have webinars as this one. They do talk about research. They talk about data types. We also have webinars on particular software. So you can see all of those on our events pages. And we've also got face-to-face workshops. We have guides and video tutorials on different topics, data sets and methods. Case studies that showcase how researchers have used data. And then we have help. So we have a dedicated help desk. And we usually get back to our users within a couple of days. And there's also some very useful FAQs. And you can join our mailing list if you'd like to know what's happening in the service. You can sign up to get our newsletter, which is quarterly. And then we're on Twitter, like understanding societies, and we're on Facebook. And now let me hand over to Kara, who is going to talk to you about her research on screen-based media and youth well-being. Okay, hello, and thank you for attending this webinar. As Marguerita said, I'm going to talk to you on screen-based media use and youth well-being. So a recent off-com report published now a couple of years ago looked at technology and social media use among UK children and adolescents. And they found that 80% of adolescents 12 to 15 years old regularly viewed television. 69% of them used a mobile phone. 49% had a PC or laptop that they used. And 43% used a tablet. And among the same age group, we see that 71% use social networking sites regularly. And the most popular site, which they had a profile on, was Facebook. Although many of them had a profiling site on Facebook, most of them used other social networking, like Instagram or Twitter, more often. And something of note that I thought was interesting was that only 20% of 8 to 11-year-olds also have a social networking profile. So you can see that this starts young, either with parents putting their children up there so they can share with their friends or with other family members, and then it increases as they get older. And just as a comparison, 80% of 35 to 44-year-olds use social networking sites. And among this age group, 78% use them daily, as compared to 92% of 24 to 34-year-olds who use a social networking site daily. What we're really interested to look at is whether social networking is related in any way to adolescents' happiness. So in another report by the Good Childhood Report, which is put out by the Children's Society and the University of York in 2014, used a variety of data, including understanding society to look at well-being and happiness among children in the UK. And what they found was that your six and eight children rated their overall life satisfaction as 8.5 out of 10. So you can see that satisfaction is fairly high among these children. And again, with happiness, their happiness is quite high, 8.6 out of 10. There were differences by age, so younger children are happier than older children. So amongst, say, 10 to 15-year-olds and 10-year-olds are going to be happier than the 15-year-olds. And boys are typically report higher levels of happiness than girls. And when they looked at trends over several years, from 2000 to 2008, they found that among 11 to 15-year-olds, happiness increased. However, starting in 2009, the level of happiness decreased, and it hasn't really gone back up to the 2000-2008 levels. And there's a few reasons for this one, is that in 2009, understanding society started, so it could be a slightly different sample that was used compared to 2000 to 2008, which was more of British household panel. It could also be a reflection of the economic changes that was going on between 2008 and 2009. What was consistent, however, were that boys were consistently higher levels of happiness than girls. Although, when you look at different domains of happiness, for example, satisfaction with school, girls were more satisfied than boys. But the biggest difference was that boys were consistently happier with their appearance than girls. And this is a trend that has been getting wider over time and not narrower. So our research questions is what is the pattern of screen-based media use among UK young people, and is screen-based media use associated with well-being in the same population? So we used Understanding Society, which is a successor to the British household panel survey. British household panel survey members were included in Understanding Society starting from Wave 2. So we do have some people who have been in the study or have been in both the British household panel survey and now Understanding Society since 1991. It's an annual household survey in which we aim to interview all adults 16 years old and older in the household, and all young people tend to 15 years old. And then when those 15-year-olds turn 16, they become part of the adult panel. It was representative of the United Kingdom population in 2009. It's comprised of four sub-samples, and one of those sub-samples is an ethnic minority boost. I will just be using the general population sample. There's also a comparison sample for the ethnic minority boost and an innovation panel sub-sample. At Wave 1, which was in 2009-2010, there were over 100,000 individuals who were interviewed across three of those four samples. Some questions are asked annually and others are asked on a rotating basis, and I will explain a little bit more about that when we come to the questions that I used. So the youth panel of Understanding Society, as I said, is given to young people 10 to 15 years old. It's a paper pen questionnaire that they are given while the adults are given their questionnaire and the youth are usually given the questionnaire in a separate room than the adults in order to protect their confidentiality. Again, similar to the adult interview, there are some questions that are asked annually and some that are asked on rotating modules. At Wave 1, there were just under 5,000 young people who completed the questionnaire and a little bit more than half of them are male. Currently, five waves of data are available from the UK Data Service and it has just over 10,000 young people across the five waves who have participated in this youth panel. So we looked at the following questions. Hours spent on playing computer games on a school day, whether they use the internet for playing computer games, playing games on a games console, chatting on social networking sites such as Facebook and watching television. And we also have questions on happiness. We have six questions and we added those together and then we looked at the top 10% those who scored in the top 10%. We also use the Strength and Difficulties Questionnaire, which is a questionnaire that assesses young people's emotional difficulties. And again, we looked at the top 10%. So we looked at those who had particularly low well-being as compared to those with fewer problems or fewer problem behaviors. So first, we looked at who spends more time on these activities, whether boys or girls spend different amount of time, whether younger or older adolescents spend different amount of time doing different activities. And what you can see from this figure is that there is no difference in computer games between genders. However, older adolescents, 13 to 15, play more computer games than those who are 10 to 12. Not surprisingly, you see that boys play more games on a console than girls. And here, kind of the opposite of what we find earlier, younger people play on a games console. Girls tend to watch television and chat on social networking sites more than boys. Older adolescents use social networking sites more than younger adolescents. Again, not surprising seeing that some of these social networking sites do have an age limit at which you cannot join if you're too young. And there are no differences by age for watching television. And then looking to see if these activities are related to happiness, we looked at compared to those adolescents who reported doing any of these activities less than one hour a day, we looked at those who did activities once in three hours per day or four more hours per day. And this is during a school, your typical school day. So these kids are in school. So if they're doing any of these activities four more hours per day, it's quite obvious. And as you can see, those who played on computer games one to three hours a day were less happy, but no association between those playing four more hours a day. And that might be just because there were very few adolescents reporting playing four more hours a day. You see that games consoles, really, there was no significantly higher association between being less happy or more happy between kids who played less than one hour a day, reported playing games consoles less than one hour a day, and those who played more. We do see that social networking was associated with being less happy for those adolescents who reported chatting for one to three hours per day as compared to those who chatted less than one hour a day. There was no association for the lower amount of watching television compared to those who watched the least amount, but there was for those adolescents who reported watching TV for more hours per day were less happy than those who reported watching television for less than one hour. And then going on and looking at socio-emotional difficulties, so we're kind of now looking at the low well-being part of the scale. We see different patterns here, so we see no associations for any amounts of playing computer games, but we do see those who played games consoles pretty much more than one hour a day had more difficulties compared to those who reported playing games consoles for less than an hour a day. And like what we saw with social networking sites and happiness, we don't see an association for the moderate amount of social networking sites, so that from one to three hours, but we see those adolescents reported being on social networking sites for four or more hours per day had more difficulties. And here we see no association with television or we didn't see a slight association with happiness. So from this research, we concluded that there were different patterns of social screen media use behavior by both gender and age, and there was an association between screen-based media use and well-being. However, these associations differed by type of screen-based media use and the measure of well-being. So we kind of wanted to look at this a bit more and look at changes over time. So the analysis that I just showed you was from Wave 1, and it was just looking at a snapshot. It was looking at associations right as the study was starting. And we wanted to, now that we have five waves of data, we wanted to look at changes over time and whether social networking use and happiness change with age among UK young people and whether these changes are related. And again, looking at initial levels of social networking use and looking at or happiness and seeing if they're related with changes in the other over time. So this is kind of the overall model. It's very busy, but I hope to be able to explain it to you quite quickly. So at the top, you have social networking use between ages 10 and 15, so as adolescents get older, and we're going to look at their initial use, their level of initial use, that's the intercept, and then we're going to look at the slope, which is the change over time. And we do the same thing with happiness at the bottom. And we look to see if there's any differences by child's gender, by parental marital status, by their parents' ethnicity, and their parents' highest education qualifications. So what I did do is just split these up by males and females, because we saw at the beginning that males and females had higher levels of both social internet use and at levels of happiness. And here, it's just important to note that the top and the bottom, there's no arrows going from social internet, social networking use, and the intercept and happiness intercept, or between the slopes, or going across. So we do see that their adolescents increase their social networking use, males, over time, and their happiness decreases over time, but there's no association between those changes among males. And then among females, you get the same patterns where social networking use increases over time, however it increases more than males, and we see that happiness decreases, and again, happiness decreases more than males. But here we see that there is an association between the social networking use at the beginning and happiness at the beginning, in which we see that there are lower levels of social, those with lower levels of social networking use are happier with the converse, those who are happier use social networking less, and that we didn't see in voice. We can also see that girls whose mothers are Asian or other have lower levels of social net use at the beginning, and those with Asian mothers use social networking less as they get older. So looking at some of the strengths and limitations of this study, it is one of the first longitudinal studies to look at the associations between social networking use and happiness among young people, and it was taken from a large nationally representative sample. Unfortunately, we don't have information on non-school use days, and this is where looking at rotating modules versus annual modules come in. So they do ask about social networking use every year on the youth panel. However, they only ask about non-school days or use on the weekends every other year, and so therefore we weren't able to look at that. We also don't ask about social networking use on other platforms to smartphones and tablets, which most of you know is a much more common way of adolescents accessing their social network these days. However, when the study was planned and started out in the field in 2009, smartphones and tablets were much less common, and it's hard to get these changes into a study as big as understanding society so quickly. We also do not know why they use social networking, so other than chatting for friends, which is what the question asks about, you don't know if they use social networking for other kinds of information. Or which sites are used, which specific sites are used? Do they use Facebook for family and Twitter for friends or Instagram for school friends and Pinterest for other types of friends? We don't know this information. So we do want to look at non-school days and all of the things I just said used on different platforms the reason why they're using social networking apps. The quality of relationships with other users, are they talking to friends that they actually know from school or are they talking to friends that they met on these social networking sites? And the role of parents and policy makers, schools and when they use them and how they're able to use these social networking sites. So quickly I just want to acknowledge our funders from the ESRC who fund all of us, myself and my co-authors Professor Amanda Sacker and Yvonne Kelly who are at UCL and Dr. Alex Andes-Cue who's now at British Airways. There's more information you can contact me or you can contact anything about ICER from our newsletter or on Twitter or on Facebook. And that is me. Thank you very much. Thank you very much for attending. Thank you to Cara for presenting and our webinar and sharing all of this knowledge and have a good afternoon everyone.