The role of digital exclusion in social exclusion

Preparing to load PDF file. please wait...

0 of 0
The role of digital exclusion in social exclusion

Transcript Of The role of digital exclusion in social exclusion

The role of digital exclusion in social exclusion
Chris Martin, Steven Hope, Sanah Zubairi, Ipsos MORI Scotland September 2016

b Digital Participation and Social Justice in Scotland

The Carnegie UK Trust would like to thank the Scottish Government for funding this research study. In particular, we would like to thank Alyson Mitchell for her support and insight throughout the research process.

The text of this work is licensed under the Creative Commons AttributionShareAlike 3.0 Unported License. To view a copy of this license visit, by-sa/3.0/ or send a letter to Creative Commons, 444 Castro Street, Suite 900, Mountain View, California, 94041, USA.

This report is printed on paper that is FSC certified.


1 Introduction


2 Literature review


2.1 Digital exclusion


2.2 Changes in digital exclusion over time


2.3 Social exclusion


2.4 Linking digital and social exclusion


2.5 Discussion


3 Availability of SHS data for examining internet access and social exclusion


3.1 Information on internet access and related variables


3.2 Social exclusion


3.3 Indicators of deprivation and other confounding factors


4 Creating indicators of social exclusion


4.1 Summary of internet access and usage


4.2 Digital inclusion and potential indicators of social exclusion


4.3 Grouping the potential indicators into dimensions of social exclusion


5 Is internet access a driver of social exclusion?


5.1 Approach to modelling


5.2 Modelling access to the internet.


5.3 Modelling the Social Exclusion dimensions


6 Discussion and conclusions


7 Detailed logistic regression tables


8 Extracts from the CHAID Models


9 Bibliography


List of Tables and Figures

Table 4.1: Summary of access to the internet by deprivation, tenure and household income, SHS 2014


Table 4.2: Summary of internet usage by age group, tenure, to the internet by deprivation,

tenure and household income, SHS 2014


Table 4.3: Household access and personal use of the internet


Table 4.4: Frequency of internet use among personal users


Table 4.5: Social inclusion indicators by whether have internet access?


Table 4.6: Factor analysis of potential social inclusion indicators


Table 4.7: Convenience of services by internet access


Table 4.8: Active living scale by internet access


Table 4.9: Transport scale by internet access.


Table 4.10: Socially connected scale by internet access.


Table 4.11: Mental health and wellbeing by internet access.


Table 4.13: Use of selected local services by internet access.


Table 4.12 Long term illness or disability by internet access.


Table 5.1: Logistic regression model of internet access: Conditional forward, SHS 2014


Figure 5.1: Selection from CHAID model of internet access.


Table 5.2: Summary of Access to services modelling


Table 5.3: Summary of Active lifestyle logistic regression modelling


Figure 5.2: Selection from CHAID model of active lifestyle.


Table 5.4: Summary of Transport logistic regression modelling


Table 5.5: Summary of Socially connected logistic regression modelling


Table 5.6: Summary of mental health and wellbeing logistic regression modelling


Table 5.7: Summary of use of local services logistic regression modelling


Table 5.8: Summary of whether anyone has an illness or disability.


Table 7.1: Access to services. Multinomial logistic regression


Table SEDIM7.2: Active life scale


Table 7.3: Transport (compared to no access to a car, does not use public transport)


Table 7.4: Socially connected scale


Table 7.5: Mental health and wellbeing


Table 7.6: Use of selected local services


Table 7.7: Whether anyone has an illness or disability in the household.


Figure 8.1: Top two levels of CHAID model of number of services considered convenient.


Figure 8.2: Top three levels of CHAID model of Active Lifestyle scale.


Figure 8.3: Top two levels of CHAID model of Transport indicator


Figure 8.4: Top two levels of CHAID model of Socially Connected scale.


Figure 8.5: Top two levels of CHAID model of Mental health and wellbeing scale.


Figure 8.6: CHAID model of Use of selected local services scale.


Figure 8.7: Top two levels of CHAID model of whether anyone has an illness or disability in the household.


The role of digital exclusion in social exclusion 1

1 Introduction
This research was commissioned by Carnegie UK Trust to examine the relationship between digital exclusion – lacking access to online resources and services – and social exclusion. Social exclusion encompasses a range of impacts but broadly describes a situation where individuals are unable to participate fully in social life to the detriment of individuals and society as a whole.

The project comprised two parts and two broad phases.
Phase 1 of the research involved two elements. Firstly, to review and summarise the available literature on the links between digital exclusion and social exclusion to identify the current state of knowledge about digital and social inclusion. The first phase also involved preliminary analysis of the Scottish Household Survey to assess which survey questions could be used as indicators of social exclusion and the extent to which these varied by internet access. Overall, 7 indicators of social exclusion were created. They were:
• Convenience of local services • Active living • Transport • Socially Connected • Mental Health • Use of local services • Long-term physical and mental illness or
In phase 2, further analysis of the data was carried out to examine whether internet access was an explanatory variable in shaping patterns of social exclusion across these different

dimensions. The data analysis incorporated a broad range of potential causal and explanatory variables to identify and quantify the contribution of digital exclusion to social exclusion
The analysis in phase 2 was not to provide robust complete analysis of each dimension of social exclusion, but rather to examine whether internet access was a significant factor in each. The analysis of the links between social exclusion and digital exclusion has had to be driven by the data that is available. The modelling has been limited by the data that is available in the survey.
The analysis focuses on data relating to ‘access to’ and ‘use of’ the internet. These measures are seen as proxies for digital participation. It is recognised however, that digital participation is in practice a much concept broader than this and requires people to have the required level of digital skills to maximise the opportunities that the internet offers and mitigate the risks. This is particularly significant as the number of people without access reduces and the question of how people use the internet, rather than whether they use it at all, becomes more important. The 2015 Scottish Household Survey contains new questions which focus on this broader interpretation of digital skills and use.

2 The role of digital exclusion in social exclusion

2 Literature review
In this section we provide a brief review of the literature around digital exclusion and social exclusion before moving on to reviewing the relationship between digital and social exclusion.

2.1 Digital exclusion
Digital exclusion involves the unequal access and capacity to use information and communication technologies (ICTs) that are seen as essential to fully participate in society (Schejter et al 2015). Since the 1970s, the use of ICTs has spread unevenly and many still remain digitally excluded (Selwyn 2004, Dutton et al. 2014). Around 1.3 million people in Scotland are either not online or do not have the basic skills to use the internet (RSE 2014).
Van Dijk (2005) identifies a sequential relationship between social inequalities and unequal access to digital technologies. This is supported by RSE 2014. It reports on a strong relationship between SIMD and internet uptake in Scotland with internet uptake among the 10% most deprived in Scotland at 53% compared to 81% for the 10% least deprived. Schejter et al 2015 builds upon Van Dijk’s sequential model of social inequalities and digital exclusion adding that the inclusive and participatory aspects of contemporary ICTs (particularly through the use of social media and online discussion forums) are essential in terms of citizen’s participation in society. The study emphasises the social dimensions of ICT use and suggests the social consequences of exclusion warrants further exploration.
Literature in the area of digital participation emphasises both the material factors that drive digital exclusion as well as the attitudes, skills and cultures of internet use. With 78% of the UK population currently online there are a number of cultures of internet use from those use the internet throughout the day to those who do not have any interest in going online – currently 18% of the UK population (Dutton et al. 2014).

Within the context of explaining digital exclusion, various studies emphasise the benefits of digital participation. For instance, the Royal Society of Edinburgh define it as a ‘right’ and Koss et al. 2014 define it as a ‘virtuous circle’ with benefits for individuals in terms of improving educational outcomes, employability, health and wellbeing and reducing isolation as well as benefits for SME’s, charities and government. The wideranging benefits that are outlined in these studies encompass the factors that have been identified as dimensions of social exclusion in this study.
The benefits of digital participation are echoed in UK and Scottish Government targets to increase digital participation. For instance, the Scottish Governments ‘digital participation’ strategy aims to make Scotland a ‘world-class digital nation by 2020, supporting Koss et al 2014 ‘this is for everyone’ position. In the ‘Digital Participation: a National Framework for Local Action’ the Scottish Government states that internet use has benefits for education and training, finding work and flexible working, healthcare and remote provision, increasing social interaction and enabling the consumption of information and services for those with accessibility issues. With this in mind, the Scottish Government aims to roll out broadband to 95% of premises in Scotland by 20171. Similarly, the UK government digital service has targets to digitise key services and the Department for Work and Pensions has set a target of 80% of Universal Credit applications to be completed online by 2017. In this sense, digital by default is creating further requirements to go online which may have increasing implications for social exclusion.
1 The Royal Society of Edinburgh emphasise the danger in setting a target that excludes 5% of the population as this may serve to exacerbate existing inequalities.

The role of digital exclusion in social exclusion 3

2.2 Changes in digital exclusion over time
How digital exclusion is defined has changed in recent literature. Positions based on a simple ‘user/non user’ and internet ‘have/have not’ understanding have shifted to an exploration of the gradations of internet use and a ‘skills divide’ (van Dijk 2012). For instance Helsper 2008 identifies advancing steps of digital engagement from basic use involving individual communication, intermediate use involving individual networking and advanced use involving civic participation. This nuance highlights not only non-internet use as an aspect of digital exclusion but lack of digital literacy that prevents a fuller engagement. Therefore, access to ICTs becomes more nuanced to include analysis of the attitudes, skills and types of engagement that underlie ICT use (Helsper 2012).
Helsper and Van Deursen’s 2015 study of internet use/non-use among older adults encompasses a number of material and socio-psychological factors and identifies negative attitudes towards the internet related to a lack of trust in digital technologies, perceptions of feeling too old to engage with the internet, the range and types of internet experience, as well as traditional and digital literacy as key explanations why some older adults are offline. They suggest that non-users give a variety of different reasons for non-use, couched in terms of gender, age, and household composition.
For example, the study shows that female non-users were more likely to have an internet connection at home but not use it. This gender difference is most pronounced in older adults who suggest that technologies are a more masculine domain (Helsper and Van Deursen 2015). Further, over-75s perceived themselves to be ‘too old’ to use the internet although this was not necessarily the case for highly educated older adults. For highly educated adults, who traditionally lead a more active lifestyle, the reasons for non-use were described more in relation to available time.
Recent literature focused on areas related to skills and knowledge in terms of understanding digital exclusion as much as internet access. People with higher levels of digital skills will be more able to

take advantage of the benefits that internet access offers. Van Dijk and Van Deursen 2014 address the digital divide in terms of the difference in internet skills. Van Dijk and Van Deursen 2014 build on previous models (2009) to include operational (basic skills), formal (navigation and orientation), information (user information needs), strategic (capacity to use the internet as a means to reach particular goals and improve position in society), as well as social, creative and mobile skills. Helsper and Van Deursen 2015 add that communication and socio-emotional skills should be included in this framework as these are important skills in the context of social media. This reflects a further development in the understanding of digital skills beyond access and functional use to reflect the increasing levels of interaction between people online. Van Dijk and Van Deursen 2011 note that educational attainment is a key explanatory variable in understanding the variance in internet skills.
The development of digital skills is affected by social environments and patterns of learning through family, friends, schooling and workplace. Van Deursen et al 2014 explore digital skills and patterns of seeking support from others in the Netherlands. The study shows that a large majority of internet users are completely selfreliant; this group largely consists of males rather than females and those with higher educational attainment. A second pattern consists of internet users that rely on direct and informal support from family and friends. This group consists of more females than males and those with lower educational attainment. A third identifies users that rely on formal support for internet use through courses, help desks and colleagues that consists of those with lower to medium educational attainment. The study is interesting in pulling out patterns of learning digital skills. Helsper and Van Deursen 2015 point out that traditional literacy is an important factor in determining internet use in the Netherlands and shows a clear explanation of digital exclusion.
In terms of the Scottish context, Ipsos MORI Scotland have previously conducted research for the Carnegie UK Trust (2013) exploring digital exclusion in Glasgow where internet uptake is one of the lowest in the UK, with 40% of households offline.

4 The role of digital exclusion in social exclusion

The study emphasised the relationship between poverty and digital exclusion. In contrast to rural areas, where digital exclusion has traditionally been attributed to poor connectivity and infrastructure, exclusion in urban areas is associated with social justice issues. For instance, digital exclusion was most prevalent among the DE socio-economic group, and further segmentation analysis highlighted low take-up among pensioners, nonworking adults and those living in social rented tenures. Further differences by age and gender were identified in terms of attitudes to internet use. For instance, less than a third of those aged 65 and over were interested in accessing the internet. Among reasons for not going online, a preference for face-to-face communication was cited as well as a fear and lack of trust in ICTs and cost. The study differentiated between those who simply reject internet use (43%) compared to potential users (57%) who have a curiosity and inclination towards going online.
2.3 Social exclusion
Social exclusion can be understood in relational terms as the (in) capability to take part in the life of the community that affects individual quality of life and the equity and cohesion of society (Sen 1992, Levitas et al 2007). Social exclusion is multidimensional and involves the lack of economic, social and cultural capabilities/ resources to take part in a social system that move beyond traditional discussions of poverty and deprivation as the inability to meet basic needs (Helsper 2012). Gradations of social exclusion are highlighted with ‘deep social exclusion’ referring to deprivation from multiple capabilities and resources within a social system (Levitas et al 2007). This understanding of social exclusion presupposes digital exclusion as it has been shown that engagement with ICTs is a prerequisite to equal and full participation in society especially given the participatory nature of contemporary ICTs (Schejteret al 2015).
In their report The Multi-dimensional Analysis of Social Exclusion (for the last government’s social exclusion task force) Levitas et al take as their working definition of social exclusion:

“Social exclusion is a complex and multidimensional process. It involves the lack or denial of resources, rights, goods and services, and the inability to participate in the normal relationships and activities, available to the majority of people in a society, whether in economic, social, cultural or political arenas. It affects both the quality of life of individuals and the equity and cohesion of society as a whole.”
This definition of social exclusion is interesting in terms of mapping the relationship between digital exclusion. There has been a relative lack of research into the social impact of digital exclusion as well as the social role of ICT use as a dimension of social exclusion (Schejter et al 2015).
2.4 Linking digital and social exclusion
There are a number of social and personal factors that help us to understand digital exclusion but the relationship between digital and social exclusion remains poorly understood. Helsper and Galacz 2009 attempt to map out the relationship between digital and social exclusion showing that there are a number of different views regarding the interaction of both fields. For instance, digital participation can help to mitigate social exclusion by introducing disadvantaged groups access to the benefits of internet use. However as long as social inequalities remain offline (e.g. in terms of education) these will translate into inequalities online as those who are socially excluded are less likely to have access to the internet and lack digital skills. Norris 2001 and Rodger 2003 identify an S shaped curve model to theorise the relationship between digital and social exclusion. Rodger 2013 shows that those who are socially excluded will catch up over time in terms of their access to ICTs and that will help them to overcome their disadvantage, however Norris 2001 argues that the maximum uptake of ICTs among the socially excluded will remain lower than the average population so inequalities will remain. The discussion hypothesises the way in which digital participation may help to overcome social exclusion however digital participation in and of itself will not tackle social exclusion as inequalities remain in terms of access and types of internet use.

The role of digital exclusion in social exclusion 5

Helsper 2008 explores the relationship between social exclusion and digital exclusion, highlighting that 9% of the adult population suffer deep social exclusion and have no meaningful engagement with the internet (Helsper 2008: 11). This corresponds with analysis of the 1999 Scottish Household Survey, which shows that the excluded are less likely to use ICTs (Fitch 2002).
Individuals who are socially isolated are less likely to participate in the advanced networking aspects of ICTs and individuals who are economically disadvantaged are less likely to use ICTs for government and financial services that would provide them access to the services they need (ibid:9). This suggests that those who suffer from particular social exclusions are least likely to benefit from the ICT applications that may help them tackle their disadvantage (Helsper 2012). People who are social excluded are likely to remain socially excluded.
Further studies have emphasised the relationship between digital and social exclusion by exploring children’s’ engagement with ICTs (Helsper and Livingstone 2007). Jackson 2006 has identified a relationship between digital exclusion and educational attainment showing that children from socially deprived backgrounds who use the internet have higher scores on standardised tests, which suggests that digital exclusion has the potential to exacerbate social inequalities.
According to the Technology-Enhanced Learning Research Programme 2012, to ‘prosper in the 21st century, people need to be confident digital collaborators and communicators’ and reflecting this, many schools are incorporating digital technologies into the classroom to create more interactive environments. However, research by Valentine et al 2002, highlights some resistance to ICT use among children based on whether this is seen ‘deviant’ or ‘normal’ identities among young people. This suggests that as with adults, digital exclusion among children is dependent both on access to resources as well as children’s social relations.
Haddon 2000 explores the relationship between digital exclusion and social exclusion by examining the impact of ICT use on single

parents and the young elderly. Studies have previously identified the prevalence of loneliness and economic deprivation among single parents and the young elderly, which make an interesting case study for research (ibid, Hardey 1989). The study shows that engagement with ICTs is dependent on the perception of how useful they are and the extent to which people in their existing social networks use ICTs. Given that ICT use is dependent on prior engagement there can be a low willingness to access services online potentially leading to further exclusions (Haddon 2000). A recent study conducted by the Equality and Human Rights Commission 2015 has shown that two thirds of older people are living alone and at potential risk of social isolation, it is worthwhile to study the impact of digital exclusion on these groups to examine the relationship between social and digital exclusion.
In particular, Koss et al. 2014 discuss the impact of digital participation in minimising social exclusion in terms of the impact on loneliness and depression among older people. Barnes et al 2006 in the ‘social exclusion of older people: evidence from the first wave of the English Longitudinal Study of Ageing (ELSA) final report’ identify that older people who have access to the internet are three times less likely to be socially excluded. Furthermore, a study conducted by the Phoenix Centre 2009 shows that depression is 20% lower in retired adults who use the internet that reflects the effects of digital participation, particularly the use of social networking on mental health and wellbeing. The number of people living in the household effects the reduction of depression, with the largest effect on people living alone.
2.5 Discussion
The relationship between ICT and social exclusion is dependent on the type of usage (Helsper 2012). Exclusion from certain type of ICT usage will impact on social exclusion more than other types of usage (ibid). The economic and social impacts of ICTs are complex and contradictory and a direct impact on social exclusion is hard to measure (Gibbs 2001). However, the perception that digital inclusion will remediate social

6 The role of digital exclusion in social exclusion

exclusion remains within policy domains and is based on the assumption that ICTs are inherently ‘inclusionary technologies’.
Bradshaw et al 2004 identifies the importance of distinguishing between macro drivers that increase social exclusion, risk factors that signal vulnerability to social exclusion and triggers that have a causal impact on social exclusion. Situating digital exclusion within this framework will be useful in eliciting the relationship between social and digital exclusion.
The exact relationship between digital and social exclusion remains poorly understood. Identifying

causality is difficult given that technology and society are deeply embedded and it is unclear how the two interact. For instance, few longitudinal studies have shown a change in individuals’ social inclusion through a sustained engagement with ICTs (Anderson 2005). However, the previously mentioned study by the Phoenix Centre 2009 does show the positive effects of digital participation on indicators of social exclusion. Nevertheless, it is unclear whether internet use in and of itself can help to overcome social exclusion as inequalities mediate access to the internet and types of internet use.
ExclusionInternetInternet AccessRelationshipAccess