Social connections are shaped by socio-economic, environmental and structural factors, and policies to combat loneliness in OECD countries increasingly include multi-sector community-level interventions for broad-based results. This chapter highlights two contextual drivers of social (dis)connection that are particularly relevant for such policies, and outlines next steps to improve their measurement. First, social infrastructure (spaces that foster interaction) can enhance connection across groups and strengthen belonging. Aging populations and rising numbers of people living alone heighten the importance of such infrastructure. Second, much of the concern about deteriorating outcomes for young people has centred on the role of social media and digital technology. These tools present both benefits (ease of contact, building community) and risks (withdrawal from offline interactions, problematic Internet use) for social connection. However, open questions remain about the effects of moving in-person interactions online, as well as the most effective policy approaches to support positive online connections.
Social Connections and Loneliness in OECD Countries
Abstract
To effectively design policies aimed at reducing loneliness and isolation, and to ensure that existing policy actions do not inadvertently cause harm to people’s connectedness, it is essential to identify and target the upstream factors that shape people’s opportunities to connect with others. Both the extent and quality of a person’s social connections can be influenced by a wide range of factors, including genetics and personality traits,1 life events2 and aspects of people’s social, economic and environmental well-being, such as their income, work, leisure, health and housing.3
So far, the majority of the limited, but growing, evidence on interventions aimed at boosting social connectedness has focused on interventions targeted at (disconnected or lonely) individuals. These include strategies focused on self (e.g. self-guided social skills training) or inter-personal (e.g. social skills or psychoeducation led by healthcare professionals) delivery mechanisms, rather than community- or even population-based delivery mechanisms, targeting the structural causes of disconnection (Welch et al., 2023[1]; Holt‐Lunstad, 2024[2]; WHO, 2025[3]). Despite the lack of evidence, there is growing awareness of the importance of community-level interventions. For example, many of the government action plans and strategies designed to combat loneliness and social isolation in OECD countries, introduced in Chapter 1, highlight the importance of community-level interventions and underscore the need for multi-sector collaboration – across levels and departments of government, and with non-government partners (civil society, research and the private sector) (HM Government, 2018[4]; Government of the Netherlands, 2023[5]; Asahi Shimbun, 2024[6]; BMFSFJ, 2022[7]; AGE Platform Europe, 2023[8]; Seoul Metropolitan Government, 2024[9]; Kunta Liitto, 2024[10]; Folkhälsomyndigheten, 2025[11]).
This chapter contributes new evidence on social infrastructure and digitalisation as two contextual drivers of social (dis)connection that are increasingly relevant for policymakers, particularly when considering several of the at-risk groups identified in earlier chapters of this report: the elderly, those living alone and more recently, the young. Indeed, both social infrastructure and digitalisation have been highlighted as promising areas of social connection promotion by experts in the field (WHO, 2025[3]; Holt‐Lunstad, 2024[2]; Schnepf, d’Hombres and Mauri, 2024[12]), and have been flagged as priorities in government strategies to address loneliness. For example,4 as a part of its “Seoul without Loneliness” campaign, the municipal government of Seoul will introduce “Seoul Mind Convenience Stores”, open spaces where city residents can come to share a meal and interact with others in their community (Seoul Metropolitan Government, 2024[9]). The United Kingdom’s Strategy for Tackling Loneliness explicitly identifies examples of community infrastructure – green spaces and public parks, youth community hubs, conversation clubs hosted in job centres, etc. – that can facilitate connection (HM Government, 2018[4]). The Lithuanian government has developed a series of social welfare programmes to address loneliness and isolation among the elderly, including a social prescribing programme run through municipal health offices: seniors are referred by general practitioners or mental health practitioners to free group activities with others in their local area (Lietuvos Respublikos sveikatos apsaugos ministerija, 2025[13]). In a related vein, the Austrian Platform against Loneliness in Austria provides residents of all ages with a database of social infrastructure and group activities that provide social support (Plattform Gegen Einsamkeit, 2021[14]). And lastly, both the British and Swedish strategies highlight the role that digital technologies can play in complementing in-person interactions and sustaining social connection across physical distance (HM Government, 2018[4]; Folkhälsomyndigheten, 2025[11]), and the Finnish action plan outlines the need to better understand and address the potential adverse effects of digitalisation (Kunta Liitto, 2024[10]).
This chapter outlines what is known so far about how these phenomena are shaping whether and how people connect with one another, what open questions remain, and which data are needed to fill important evidence gaps. Forthcoming work from the OECD, the World Health Organization, the European Commission and the Global Initiative on Loneliness and Connection will focus on addressing some of these gaps, particularly around the effectiveness and feasibility of community strategies.
The role of the built environment and social spaces for meeting – so called social infrastructure – and how these shape in-person interactions will be particularly important given demographic trends. As outlined in Chapters 3 and 4, more people of all age groups, but in particular the elderly, live alone; those who live alone may be more at risk of isolation and loneliness, and therefore particularly benefit from spaces that lower the barrier to socialising while providing needed services (Klinenberg, 2016[15]; Kawachi, Subramanian and Kim, 2008[16]; Aldrich and Kyota, 2017[17]). Even for those who do not live alone, growing housing unaffordability (OECD, 2025[18]) can inhibit people’s ability to have a private space for hosting and socialising with others, and prevent them from living in neighbourhoods that are close to their friends or family, both of which contribute to loneliness and isolation (Bower et al., 2023[19]) – in this context, public social spaces are all the more important. In order to ensure equitable access to high quality social infrastructure, policymakers need better information on their supply (stock and funding) and demand (how often each are frequented, and how the spaces are used). Combining data from administrative sources and big data or web scraping with select indicators on household questionnaires could enable interested policymakers to better assess the state of social infrastructure in their local areas.
Worsening social connections outcomes for young people (and young men in particular) are not yet well understood. Debate has partly focused on the role of social media and digital tools. Much work has gone into the study of the broader well-being risks and benefits of the digital transformation,5 however open questions related to how social connections in particular are affected remain: to help fill this evidence gap, emerging national strategies to regulate digital technology and social media use should expand the outcomes that are monitored to also include the quantity and quality of social interactions. While on-going academic research finds mixed results on the impact of digital technology on feelings of loneliness and disconnection, there is consensus that how digital tools are used, as well as the types of online behaviours, matter. Furthermore, understanding the impacts of moving socialising online is particularly important in the face of declining trends in getting together with friends and family in person, and rising trends in regular remote contact (see Chapter 4). Here, preliminary evidence suggests that the well-being benefits to online socialising pale in comparison to real-world interactions.
A substantial share of in-person interactions take place in public and semi-public places – whether running into a neighbour while walking the dog in the park, joining a friend for a drink or meal at a restaurant or bar, or meeting other parents at the playground or during school pick-up. The spaces that make up a neighbourhood shape day-to-day interactions, encourage socialising between different members of a community – often spanning social groups – as they go about their daily tasks and engage with service providers. All of this makes community-level interventions, as opposed to individual-level treatments, a promising avenue for policy.
Social infrastructure refers to the spaces and organisations that encourage social interactions and thereby strengthen social capital and feelings of belonging (Figure 5.1):6 examples include public institutions (libraries, schools, playgrounds, parks, sidewalks), community organisations (places of worship, civic associations) and commercial establishments (cafes, barbershops, bookstores) (Klinenberg, 2019[20]). The availability, accessibility and hospitability of these (semi-)public places all play an important role in forming, maintaining and expanding social relationships (Klinenberg, 2019[20]; Latham and Layton, 2019[21]; Enneking, Custers and Engbersen, 2025[22]), and in improving social mobility (OECD, 2025[23]).
A growing number of people in OECD countries now live alone (see Chapter 4): while living alone is not in and of itself a deprivation (Klinenberg, 2013[24]), it can be a risk factor for poor social connections outcomes (see Chapter 3). Elderly people who live on their own may be at particular risk for social isolation (National Academies of Sciences, Engineering, and Medicine, 2020[25]; Victor et al., 2000[26]), making social infrastructure a particularly useful way for them to engage in the community (Klinenberg, 2016[15]; Aldrich and Kyota, 2017[17]). Indeed, some existing policy approaches are designed to provide older people with information on which services and public spaces are available to them in their local area (National Governors Association, 2025[27]; Vermont Agency of Human Services, 2025[28]). It is not just the elderly, however, who can benefit. Providing safe and accessible spaces for young people to congregate can provide them with well-being benefits, furthermore, the creation of inter-generational spaces can improve outcomes for multiple age groups simultaneously, making this an attractive avenue for policy (BMFSFJ, 2022[7]; OECD, 2025[29]).
The benefits of social infrastructure to social connections and broader well-being
Increasing access to social infrastructure has many benefits for well-being. To begin with, these places provide individuals with the opportunity to connect with others, and are particularly instrumental in strengthening “bridging” (connections to others from different groups, or socio-demographic backgrounds) and “linking” (connections to individuals or institutions who can provide access to resources – job opportunities, services, etc.) social ties, both of which strengthen social cohesion and social mobility (Putnam, 2000[30]; Woolcock, 2001[31]).7 Libraries and daycares, in particular, have been shown to foster bridging social interactions between different groups of people who would otherwise not cross paths (Fraser et al., 2024[32]; Klinenberg, 2019[20]) (see Box 5.1 for a detailed discussion of public libraries). Social infrastructure encourages these cross-group interactions by lowering the barrier for engaging with strangers. By way of illustration, a case study of Australian community gardens found that participating in the activities of the space – gardening, reading, drinking coffee – encouraged people to engage with one another more frequently, building relationships over time (Dolley, 2020[33]). Studies have shown that reducing obstacles to socialising by frequenting senior centres (Jing et al., 2024[34]), all-age community centres (Aldrich and Kyota, 2017[17]), restaurants and cafes (Rosenbaum, 2006[35]; Jing et al., 2024[34]) and local services such as shopping areas, banks and post offices (Alidoust, Bosman and Holden, 2019[36]) have been beneficial to the elderly, in particular.
By serving as a publicly accessible meeting space, where services are provided to a wide variety of people free of charge, libraries can facilitate social interaction and help build networks (Corble and van Melik, 2021[37]), generate trust and increase social capital (Vårheim, 2014[38]) and nurture social inclusion (Peterson, 2023[39]). Libraries are “one of the few remaining community-wide spaces for all residents” (Lankes, 2016, p. 13[40]), providing “free access to the widest possible variety of cultural materials to all people of all ages, from all ethnicities and groups” (Klinenberg, 2019, p. 37[20]).
Libraries provide many services, beyond the provision of books. They supply a quiet place to study, digital (and AI) literacy support, cultural and social engagement activities, free Internet access (via access to Internet enabled computers, or a free wireless connection for visitors’ personal devices), job application support, homework help for young people, parenting courses, book clubs and more (Klinenberg, 2019[20]; Lankes, 2016[40]). Services can be tailored to the specific community. Evidence from a multifunctional library in an impoverished area of Rio de Janeiro, Brazil, shows how libraries can improve information literacy and strengthen community bonds by providing access to Internet services (Da Silva and Olinto, 2015[41]). Libraries in Australia provide English language lessons to newly arrived immigrants; some have even employed library-based social workers to serve the local community (Bourget, 2025[42]). In the wake of the Russian invasion of Ukraine in 2022, Polish and Hungarian libraries have introduced a broad range of activities to support displaced Ukrainian refugees, including providing places of refuge, information access, mental health support, job search facilities and functioning as aid and resource collection points (Johnston et al., 2024[43]).
Despite their wide array of services, since the early 2000s, in several OECD countries with data, the number of libraries, membership rates and number of staff employed have all declined. For example, in the United Kingdom almost one-fifth of libraries closed between 2010 and 2019 (Bogue and Ouillon, 2023[44]), while in the Netherlands roughly one-quarter of libraries closed between 2014 and 2018, and adult membership declined by 12% during the same period (Corble and van Melik, 2021[37]). In the United States, public library visits decreased from 1.53 billion in-person visits in 2011 to 1.2 billion in 2019, despite the number of libraries remaining roughly stable, at around 9 000 (Institute of Museum and Library Services, n.d.[45]) (however, it should be noted that many libraries now offer digital services, meaning library users can still access e-books without making in-person visits).
More recently, however, concerns among policymakers about loneliness, polarisation and community building has led to renewed attention on libraries and their ability to foster social connections (Heck et al., 2024[46]). Across OECD countries, more governments are looking to expand libraries into multifunctional community centres with a range of services. For example, in 2014 the Korean Ministry of Culture, Sports and Tourism (MCST) announced a policy to build 50 new libraries a year over the next five years (Korea.net, 2014[47]); by 2019, the number of publicly funded libraries had reached 1 134, up from 828 in 2012 (Korea.net, 2014[47]; Korea Bizwire, 2020[48]). Public libraries in Korea provide many services, including reading programmes for young children, cultural programmes and career training for young adults, and initiatives related to employment (job search, how to start a business) for adults. The role of the library is expanding, as well: in 2024, the City of Seoul announced 122 libraries would have extended hours to serve as climate shelters during abnormal weather conditions (heat waves, cold snaps, heavy rain and flooding) (Seoul News, 2025[49]). In the Netherlands, a 2022 bill requires every municipality to offer a library facility to inhabitants, offering services for education and development, social gatherings and debates, and introducing people to arts and culture (Ministerie van Onderwijs, 2022[50]). And in 2024, the Costa Rica Ministry of Culture and Youth introduced “Books, Reading, and Libraries Strategy” to encourage a love of reading in the population; among other activities, the initiative will create “Reading Points” in vulnerable communities, increasing their access to literature (Latina Republic, 2024[51]). Beyond the provision of a wider array of services, expanded access to libraries – for example, via opening hours that enable those with full-time employment to visit, or improving public transit systems so that those without private transport are still able to frequent libraries – can ensure libraries remain a vital social resource for communities.
While many OECD countries collect data on investment in, and use of public libraries, international comparisons remain difficult due to patchy data and different measurement approaches. One programme, the Public Libraries 2030 initiative, in collaboration with the International Federation of Library Associations, publishes factsheets with key statistics on public libraries in European countries (Public Libraries 2030, 2022[52]). It provides a useful resource for cross-country comparisons, however time series are limited. Improved data collection and harmonised measurement in this regard could improve understanding of the role libraries play in social life and civic engagement.
Use of social infrastructure can have knock-on benefits to other areas of well-being, in addition to improved social connection and cohesion. Aside from encouraging social interactions (Krellenberg, Welz and Reyes-Päcke, 2014[53]), frequenting public parks encourages physical activity and increases time spent in nature, both of which have physical and mental health benefits (OECD, 2023[54]). Frequenting social infrastructure establishments is associated with long-term health benefits (Klinenberg, 2019[20]; Fraser et al., 2022[55]), including longevity, mediated at least in part through social interactions (Rosenbaum, 2006[35]). Evidence from Japan finds that older people in local areas that had invested more in community centres for the elderly – flexible spaces that serve as a library, café or general meeting area for older people who otherwise have few social interactions – report having more friends, higher levels of efficacy (i.e. a belief they have the ability to change their environment) and a greater sense of belonging to their neighbourhood (Aldrich and Kyota, 2017[17]). Data collected in the years following the 2011 earthquake, and subsequent Fukushima nuclear accident, show that attendance at these same community centres was associated with higher perceived neighbourhood recovery from the disasters (Lee et al., 2022[56]).
Considering how inclusive a particular social infrastructure space is – rather than assuming it benefits all parts of society equally – should be an explicit priority in its design and accessibility. To begin with, different cultures – or different population groups within a country – may experience spaces differently, and have diverging views as to which places are socially welcoming. For example, in many Western societies, bars, cafés and pubs serve as common forms of social infrastructure (Jeffres et al., 2009[57]), while in other (sub-)cultures barbershops, public bathhouses, parks, plazas, libraries or community centres may be more fitting (Sugiyama et al., 2023[58]; Wexler and Oberlander, 2017[59]). Additionally, for some marginalised groups, including LGBTI youth, social infrastructure that may be considered “neutral” by others and therefore welcoming – such as libraries, and parks – may be anything but, with individuals feeling their behaviours are socially policed (Littman, 2022[60]). Socio-economic divisions can complicate the role of commercial social infrastructure. Coffee shops, for example, have historically served as meeting places for individuals across socio-economic strata or classes, where the primary activity is to converse over a beverage (Oldenburg and Christensen, 2023[61]). While indeed providing a sense of community to some, for others high-end coffee shops may represent gentrification and exclusion (Hyra, 2017[62]), leading to boycotts and anti-gentrification protests (Ferreira, Ferreira and Bos, 2021[63]). Considerations of who feels included, or excluded, in (semi-)public places are necessary to ensure that the well-being benefits of social infrastructure are afforded to all (Middleton and Samanani, 2022[64]).
Existing evidence assessing the state of social infrastructure
Given different cultural and geographic designations for what constitutes social infrastructure, there are few harmonised measurement efforts. This can make it difficult to assess the current stock of social infrastructure, and whether accessibility and quality have been declining – or growing – over time, and for whom. Individual studies in specific environments, however, have shone light on inequality in access to social infrastructure, as well as changing patterns in funding, use and quality of these spaces.
Equality of access
Convenient access to social infrastructure is not always equitably distributed. Using a large geospatial dataset at the United States census tract level, one study finds that tracts with higher poverty rates and higher shares of Hispanic and Black populations have the least social infrastructure: inhabitants of these neighbourhoods have fewer resources to spend in commercial spaces, and less political capital to advocate for more communal areas (Rhubart et al., 2022[65]). Another study in the United Kingdom finds post-financial crisis austerity measures may have had a detrimental effect on the availability of social infrastructure in more financially deprived neighbourhoods (Hickman, 2013[66]). A Swedish study nuances these findings to show that patterns in which types of establishments people frequent may vary by neighbourhood type. Using geospatial data of users of the platforms Foursquare, Google Places and Twitter in Gothenburg, the authors show that individuals in neighbourhoods with lower income levels and more ethnic diversity are more likely to visit open public spaces (such as parking lots and basketball courts), while those in more affluent and ethnically homogenous areas are more likely to frequent commercial places (Adelfio et al., 2020[67]). Further research using geospatial data from census or social media data can help to expand the evidence base for inequalities in social infrastructure accessibility and affordability (see Fraser et al., (2022[55]) and Figure 5.2 for more information on this approach).
Trends in the supply (stock and funding) of social infrastructure
In terms of trends, notions of deteriorating (semi-)public spaces and lack of investment in social infrastructure have been around for some time. According to Oldenburg (1989[68]), in the United States, the decline of what he terms the “third place” (widely accessible and informal spaces – beyond home, school or the workplace – where people come together predominantly for conversation and social interaction without needing an invitation or requiring significant expense) began after the second World War, when old neighbourhoods made way for car-centred single-use neighbourhoods, with little possibility for informal social gatherings. In a similar vein, the writer and activist Jane Jacobs argued that the focus on car-centric urban planning hastened the decline of walkable neighbourhoods and sidewalk culture, leading to neighbourhood decay (Jacobs, 1989[69]).
More recent research has tried to show this empirically. Robert Putnam (2000[30]) showed the downward trend in participation in civic life in the United States (which has strong overlaps with aspects of social infrastructure and spending time in (semi-)public places) – less participation in community organisations, lower voter turnout, more time spent on solitary activities like watching television – in the years from 1950 to 2000. Using a United States business microdata set for 1990-2015, another study shows a decline in commercial social infrastructure (Finlay et al., 2019[70]), which can in part be explained by the effects of the Great Financial Crisis (GFC) and ensuing economic hardship. Comparable quantitative evidence of trends outside of the United States is limited, however, a study in the United Kingdom and the Netherlands found that post-GFC austerity measures led to a decline in the number of communal places (Corble and van Melik, 2021[37]). While also highlighting declining trends, this differs from the United States study in that in the United States commercial spaces declined with no effect on communal or public spaces (Finlay et al., 2019[70]). Few internationally comparable studies yet exist to compare trends in the investment in, maintenance and development of, freely available public spaces.
Trends in the demand for social infrastructure, and the ways in which social spaces are used
Beyond understanding the supply of social infrastructure, understanding the dynamics of the public’s demand for these spaces is also key. Rising inflation and the cost-of-living crisis in recent years have seen households dealing with rising food prices, and devoting a larger share of household income to food (Arend, Botev and Fraisse, 2024[71]; OECD, 2023[72]). This affects peoples’ ability (and willingness) to frequent certain types of commercial social infrastructure. In a 2023 survey, more than half of Canadians reported they would eat out at restaurants less frequently given rising food costs (Wunsch, 2024[73]); a Boston Consulting Group consumer panel survey in Germany the year prior found that similar rates of Germans – 62% – reported eating out less often, and 68% reported using food delivery apps less frequently (Manager Magazin, 2022[74]). Credit and debit card transaction data from Barclays show that spending on restaurant meals in Britain fell 3% in February 2023 compared to the year prior (Barclays, 2023[75]). These changing behavioural patterns – in the face of squeezed household budgets and financial pressures – mean people are spending less time in commercial social infrastructure like cafes and restaurants, which could hurt the viability of these establishments in the long-term. However, these studies only speak to the demand for a particular type of social establishment, and cannot reveal whether cost-of-living pressures may have shifted use patterns to other types of (public) social infrastructure: that is, there is a difference between people spending more time alone, or in private spaces vs. spending less time at (more expensive) restaurants and more time having a (free) picnic in a public park.
Demand and use of (semi-)public spaces therefore varies over time depending on broader social conditions. Recent studies illustrate the usefulness of geo-located social media data to define and measure the frequency of visits to different places, tracking demand for social infrastructure in almost real-time. For example, in the immediate aftermath of the COVID-19 pandemic, social interactions moved to open-air places such as parks and forests, but when the risks and fear of contagion faded, consumers moved back to inside spaces such as bars and cafés (Jay et al., 2022[76]; Our World in Data, 2022[77]; Uthpala and Meetiyagoda, 2022[78]). In the future, data on the geographic mobility of individuals – and which places they frequent – will help policymakers better understand demand for, and accessibility of, social infrastructure. However as of yet, the quality of longitudinal data needed to say something conclusive about trends is insufficient (Adelfio et al., 2020[67]; Borsellino, Charles-Edwards and Corcoran, 2021[79]).
The quality of social interactions taking place within a given space – i.e., how effective the place is at fulfilling the qualities that define social infrastructure – is also important. With the rise of digital technology, some scholars have argued that the tenor of social spaces has changed. With so many people in close proximity, but focusing solely on their phones, a café, train station or park “is no longer a communal space but a place of social collection: people come together but not to speak to each other” (Turkle, 2012, p. 155[80]). This can be difficult to measure. One innovative approach was used by a team of researchers in the United States to compare pedestrian behaviour in three metropolitan areas over a 30-year period. By analysing video recordings and CCTV footage of pedestrians, researchers found that walking speeds have increased by 15% and time spent lingering on public sidewalks has declined – this has led to an overall decrease in frequency of group encounters, and interactions in public spaces (Salazar-Miranda et al., 2024[81]).
Next steps for closing evidence gaps
Better measures of the stock and quality of social infrastructure would enable the creation of a “social infrastructure report card” (Klinenberg, 2019[20]): benchmarking communities and countries on the quantity and quality of their social infrastructure,8 in a similar manner to the way physical infrastructure is assessed in some places (McBride, Berman and Siripurapo, 2023[82]). More advances in the measurement of social infrastructure must be made before a standardised scorecard can be proposed. Yet despite known challenges to measurement, there are many new data collection initiatives underway that use a variety of methodologies to triangulate the stock of social infrastructure, including at the local level. Combining data from a variety of sources, including administrative and business records, social media and web scraping, and self-reported indicators on household surveys, can provide a clearer picture.
Administrative data
Administrative data on publicly funded public spaces – public libraries, museums, parks – and commercial establishments – restaurants, cafes, bars, salons – capture the existence, and location, of different types of public infrastructure. In European countries, Eurostat publishes harmonised data on cultural enterprises (Eurostat, 2024[83]); government expenditure on recreation, culture and religion (Eurostat, 2025[84]); and household expenditure on culture (Eurostat, 2023[85]). While not administrative data, the National Neighborhood Data Archive (NaNDA) in the United States provides a census-tract level database of different types of social infrastructure,9 including eating and drinking places; religious, civic, and social organisations; parks; personal services; arts, entertainment, and recreation; and social service organizations (Rhubart et al., 2022[65]). Lastly, the OECD’s Built Environment through a Well-being Lens report showcases harmonised data on the built environment and different types of physical infrastructure from national sources across OECD countries (OECD, 2023[86]).
Big data and web scraping
A team of researchers at Cornell and Northeastern University in the United States has developed a methodology combining information from Google Map API to build neighbourhood-level datasets of social infrastructure in cities in the United States. The algorithm classifies locations as community spaces (libraries, city facilities), social businesses (cafes, bookstores, salons), places of worship (churches, mosques, synagogues) and parks (green space, squares, sports fields, gardens). By validating with on-the-ground verification methods, the researchers deem the Google Map API to provide accurate measures with an acceptable margin of error (Fraser et al., 2022[55]); the methodology was first applied to Boston, but has since been applied to other cities in the United States (Fraser et al., 2024[32]).
Note: “Neighborhoods of color” refer to areas where the local population is predominantly Black or Hispanic.
Source: Fraser, T. et al. (2022[55]), “Trust but verify: Validating new measures for mapping social infrastructure in cities”, Urban Climate, Vol. 46, p. 101287, https://doi.org/10.1016/J.UCLIM.2022.101287.
Overlaying social infrastructure data with information on socio-demographic characteristics taken from the census provides detailed, neighbourhood-level mapping of inequalities in access to different types of social infrastructure and variations in density of social infrastructure (i.e., cold vs. hot spots) (Figure 5.2). Applications of this approach in the city of Boston highlight socio-demographic inequalities in the density of social infrastructure, both overall and by type. For example, city blocks that are predominantly inhabited by Black or Hispanic/Latino residents have less social infrastructure, and in particular fewer social commercial establishments (bookstores, cafes and coffee shops) compared to majority white neighbourhoods; conversely, predominantly Black neighbourhoods have a higher density of places of worship (Fraser et al., 2022[55]).
Self-report measures in household surveys
Another approach is to include direct questions to respondents on household surveys, asking whether they have access to, and/or frequent, the types of spaces that fit the definition of social infrastructure. This can be captured by asking about frequency of visits to a specific type of place (e.g., how often do you go to museums in a typical year?), with the list of places chosen depending on the cultural or local context. Another approach is to ask whether the respondent frequents a place defined by a series of characteristics. For example, an academic study in the United States conducted qualitative interviews with respondents to better understand local examples of social infrastructure. To guide the conversation, interviewees were asked: “What are the opportunities for communication in public places in your neighbourhood, for example, places where people might chat informally or where friends and neighbours might go for a conversation?” These could then be adapted to multi-item response questions (Jeffres et al., 2009[57]). As another approach, Statistics Canada fields a series of questions asking respondents about their sense of belonging to their local community, to their province and to Canada as a whole.10
Although an imperfect metric for capturing specific aspects of the quality of social infrastructure, the Gallup World Poll includes a question asking people whether they are (dis)satisfied with opportunities to meet people and make friends in the area where they live. The results also highlight the comparative value of survey questions, vis-a-vis the non-survey data collection approaches outlined before, in capturing socio-economic inequalities. Indeed, as Figure 5.3 shows, those earning a lower income are consistently more dissatisfied with the social opportunities of their neighbourhoods. Those with lower levels of education, those who are single and/or live alone, and women are also more dissatisfied.
Share of respondents who are dissatisfied with opportunities to meet people and make friends in the area where they live, OECD, 2022-2023
Source: Gallup (n.d.[87]), Gallup World Poll (database), https://www.gallup.com/analytics/318875/global-research.aspx.
One of the most important changes over the past decades in how we socialise – with friends and family as well as with strangers – is our increased use of digital technology, and in particular, our use of social media.11 As was shown in Chapter 4, compared to 10-15 years ago there has been a decrease in the number of people who report regular in-person interactions with friends and family, however the share who report daily contact with friends and family through digital devices has been rising. These trends have been particularly pronounced in young people.
Digital communication refers to any interaction between people that makes use of digital tools or technologies, which can encompass digital devices (computers, smartphones), video games, Artificial Intelligence (AI) and social media, among others (Lee and Žarnic, 2024[88]). Interactions vary by digital tool, with different characteristics associated with texting, speaking over the phone or video calls. Additionally, within the broader category of social media, interactions can vary by platform: all enable users to connect and engage with others, but some are geared towards a large audience (e.g., X (Twitter) or Instagram) whereas others target smaller, more specific groups with whom a user connects (such as with Whatsapp or Telegram) (Meier and Reinecke, 2021[89]).
Importantly, tools and platforms enable users to engage in different types of online interactions, all with different implications for social connections outcomes, although the dynamics of these relationships are still being unpacked by researchers. Much work – including at the OECD – has been devoted to the broader impacts of digital technologies on well-being, including for young people (OECD, 2025[90]); this section homes in on the effects of these technologies on social connections, specifically. While on-going academic research finds mixed results on the impact of digital technology on feelings of loneliness and disconnection, consensus is growing that how digital tools are used matters, and the types of online behaviours we engage in are more likely to induce better, or poorer outcomes. Another key question is to better understand the implications of shifting social interactions to online spaces, and away from in-person engagement. Preliminary evidence suggests that the well-being benefits to online socialising pale in comparison to real-world interactions, however on-going efforts to assess these differences more rigorously using time use data will provide higher quality evidence in future.
As researchers continue to unpack these relationships, aided by more granular and more frequently collected data, many parents, teachers and policymakers – concerned by what they perceive to be a growing crisis among young people, in particular – have begun taking action, introducing initiatives to ban or limit digital devices and social media access for children below a certain age, and/or in specific contexts (such as in school classrooms). It will be important to design rigorous evaluations of these new interventions, as the OECD plans to support countries in upcoming work, to understand which are most effective at promoting good outcomes, including for social connectedness.
Benefits and risks of digital technology and social media for social connections
There have been growing concerns from policymakers and citizens alike as to the potential effects that the increased use of digital technology has on how we connect with one another. Data from three OECD countries and two accession states shows that between a quarter and half of respondents believe social media makes people feel less connected, and in all but one country 50-80% believe social media makes people feel lonelier (Figure 5.4).
Note: Share of respondents who believe that social media makes people “more lonely” and “less connected”, as compared to less lonely and more connected.
Source: Data for Good at Meta (2022[91]), Social Connections Survey. https://data.humdata.org/dataset/social-connections-survey.
Belief in the detrimental effects of social media on social connections rises with age across all five countries, though the United States is an exception – here, the younger age groups are more likely to feel that social media makes people lonelier (although the majority of respondents in all age groups believe this to be true).12 Separate data from the Pew Research Center show that 36% of teenagers in the United States think they use social media too often and 32% believe that social media has a negative effect on people their age. However, their feelings are complicated – only 9% believe social media has a negative effect on themselves, personally, and over half say it would be hard to give up social media (Vogels and Gelles-Watnick, 2023[92]).
However, the ongoing debate among researchers is more nuanced and not all agree that digital technology has causal negative impacts on social connections, mental health and broader well-being, and different theoretical and empirical arguments support both positive and negative impacts of digital tools. These are summarised in the following.
Quantity of social connections: Online vs. offline
On the one hand, displacement theory posits that connecting over the Internet can increase feelings of loneliness by reducing face-to-face interactions (Kraut et al., 1998[93]). According to this hypothesis, feelings of loneliness increase when physical interaction is replaced by social media use, and stronger offline social ties are replaced by weaker online encounters (OECD, 2019[94]; Dienlin, Masur and Trepte, 2017[95]).13
On the other hand, some aspects of digital technology and social media have been found to facilitate and increase the total number of social interactions. Digital tools offer a means of communication independent of time and place, and social media has made it easier than before to actively connect with people and stay in touch with friends and family across large physical distances (OECD, 2019[94]; Masur, 2021[96]). Stimulation theory hence argues that online communication can facilitate increased face-to-face interactions (OECD, 2019[94]; Dienlin, Masur and Trepte, 2017[95]; Valkenburg and Peter, 2007[97]). Advocates of this theory argue that social media encourages communication with existing friends, for example by using social media to organise more in-person gatherings (Valkenburg and Peter, 2007[97]), and helps manage close relationships, particularly in cases where people live far from their family, friends and other social contacts (Cui, 2016[98]).
Quality of social connections: Online vs. offline
Beyond the quantity of social interactions, some evidence points to the fact that increasingly interacting online can lead to worse quality interactions both online and in the real world. Online interactions are characterised by anonymity, disembodiment and disinhibition, which can lead to behavioural differences in communication and interaction style (OECD, 2024[99]). Even when engaging in interactions with offline peers, the nature of online communication – e.g. fewer non-verbal cues – can lead to more miscommunication, and less of a sense of connection to the other person (Lieberman and Schroeder, 2020[100]). Engaging in fewer face-to-face interactions may decrease the development of important psychological skills in young people, as real-world encounters require a different social skillset than that of online interactions:14 this can lead to younger people feeling more sensitive and anxious engaging in real-world social interactions, causing them to further shy away from social engagement, leading to increased isolation and worse mental health (Haidt, 2024[101]). Others argue that digital technology harms social interactions and empathy – for all age groups, not just young people (Turkle, 2015[102]). One study of 8- to 12-year-old girls in North America, analysing the relationship between their social relationships and digital technology (social media, texting, video chats, etc.) use, found that face-to-face conversations were highly correlated with good social well-being, but online communication, video (YouTube, television, etc.) and media multitasking (an index that calculates how many forms a media each girl consumed simultaneously) were all associated with worse social outcomes (Pea et al., 2012[103]).15
In general, research into the effects of social media on mental health outcomes in young people show stronger effects for girls rather than boys (Liu et al., 2022[104]): girls are more affected by social comparisons, and more likely to feel dissatisfied with their own bodies and engage in disordered eating after seeing edited images of peers, celebrities and influencers online (OECD, 2025[90]; Choukas-Bradley et al., 2024[105]; Haidt, 2024[101]). In 2021-2022 across OECD countries, 12% of young girls self-reported engaging in problematic social media use, compared to 7% of boys (OECD, 2025[90]). Boys, however, are more likely to report problematic video game usage (Nagata et al., 2022[106]). Another risk factor on social media is cyberbullying, particularly for children and adolescents (OECD, 2025[90]; 2024[107]); however, evidence indicates substantial overlap in rates of victimhood/perpetration of cyberbullying and traditional bullying, which suggests that digital platforms themselves are not the root cause.16
Despite the above concerns, other research on the quality of social connections online vs. offline has come to opposite conclusions. A recent overview of the literature has highlighted how social media and technology can facilitate empathetic interactions in a variety of ways (James et al., 2025[108]). For example, one study of surgical patients in Canada found that those who texted with a partner or stranger and engaged in empathetic exchanges prior to the procedure required less pain relief medication than those who received standard post-operative care, or were provided with game-based distractions: this shows how social support via digital technology provides well-being benefits (Guillory et al., 2015[109]). Another study in the United States found that a text-message empathy-building intervention was successful in improving empathy and pro-social behaviours among participants (Konrath et al., 2015[110]). Multiple studies have shown the link between online (liking a post, sharing a story on social media) and offline (donating to a cause, volunteering) prosocial behaviours (James et al., 2025[108]), particularly for young people. A long-term study of empathy levels among college-aged youth in the United States found that rates declined between 1979 and 2009 (Konrath et al., 2023[111]), however began to rise again between 2009 and 2018 (Konrath, O’Brien and Hsing, 2011[112]); while the causes are unknown, the more recent uptick dispels earlier theories that the decline was directly linked to growing digital technology and social media use.
More broadly, empirical studies find mixed results for establishing an association between online interactions and perceptions of social connections and/or mental health.17 One potential confounding factor for most studies (which often rely on cross-sectional data) is that associations between loneliness and social media use do not infer causality. A positive correlation between the outcomes could be because people who are already lonely may be more likely to engage in certain types of behaviours online. Evidence from the literature supports this, showing that people who experience loneliness may be more prone to certain types of social media use (Nowland, Necka and Cacioppo, 2018[113]). Lonelier individuals have a higher preference for communicating online, as they feel more in control of their interactions and are better able to be themselves than in face-to-face interactions (OECD, 2024[99]; Morahan-Martin and Schumacher, 2003[114]).
Lastly, human to AI-chatbot engagement has now emerged as a new type of digital communication. While some use artificial intelligence to improve productivity or supplement work or education tasks, others have begun using chatbots to socialise, as confidantes and in some instances, as surrogate therapists (Moore et al., 2025[115]; Skjuve, Brandtzaeg and Følstad, 2024[116]). Some studies suggest that well developed AI-chatbots can provide therapeutic benefits to those in need, reducing loneliness, isolation and even suicidal ideation, in particular in contexts in which access to human therapists is constrained (De Freitas et al., 2024[117]; Maples et al., 2024[118]; Merrill, Mikkilineni and Dehnert, 2025[119]). However, human therapists remain sceptical (Prescott and Hanley, 2023[120]), and recent evidence suggests caution should be taken: a 2025 study from Stanford University found that when engaged as a pseudo-therapist, large language models (LLMs) expressed stigma towards users with certain types of mental health conditions (in particular harmful consumption of alcohol and schizophrenia), and provided clinically inappropriate responses (for example, encouraging delusional thinking, or failing to recognise suicidal ideation) (Moore et al., 2025[115]). Other studies highlight caution, even in instances in which users are less at risk for such extreme mental ill-health outcomes. A longitudinal randomised control trial found that while engaging with social AI-chatbots was associated with diminished loneliness, this was only the case when the chatbots were used infrequently; at high usage levels, users reported more loneliness, less socialisation with people and higher dependence on the chatbot (Fang et al., 2025[121]).
Types of online communities
Beyond the quantity and quality of social connections at the individual level, increased time spent in digital spaces also has implications for the types of broader social communities and cohesion that is being fostered.
On the one hand, digital platforms can create online echo chambers – spaces where individuals choose or are shown content aligned with their prior beliefs and political opinions – that may have detrimental impacts to social cohesion (Flaxman, Goel and Rao, 2016[122]). More recently, this conversation has expanded to include concern about personalised content through algorithms and machine learning techniques, known as filter bubbles (Kitchens, Johnson and Gray, 2020[123]). One overview of the mechanisms behind online radicalisation finds that it can be both a cause and a consequence of isolation: the former, as individuals may be attracted to online communities when they experience offline alienation or weakening real-world relationships, while the latter may happen as radicalised individuals increasingly withdraw themselves from society (Mølmen and Ravndal, 2023[124]). Additional evidence on the causal pathway between social media use and increased polarisation is inconclusive. A recent overview finds that most people access a diverse set of online media outlets, and that those who do not (and rely on only a small set of outlets) typically use sources that cater to a politically diverse audience (Ross Arguedas et al., 2022[125]). While news outlets may not be the only ‘chambers’ in which people engage with others online, it suggests that media polarisation may be less pronounced than popularly believed. In addition, research using a longitudinal dataset of nearly 200 000 American adults' web browsing behaviour found that increased use of the platform Reddit is linked to increased diversity in information sources, and a tendency toward more moderate websites. The platform, however, matters: increased Facebook use was associated with a shift to more partisan websites (Kitchens, Johnson and Gray, 2020[123]).
On the other hand, digital spaces have been found to actively foster community connections. Social media networks can complement real-life social interactions by connecting people with shared beliefs or interests who may not otherwise be able to connect in the offline world. For example, some scholars argue that high use of social media platforms by teenagers reflects the fact that free time and geographic mobility of modern adolescents are more regulated – by their parents, as well as by proprietors of privately owned spaces like shopping malls – compared to teens in previous generations, meaning online platforms serve as the primary space for offline friends to interact outside school hours (Boyd, 2014[126]; Valentine, 2017[127]). The Internet as a meeting space may be particularly relevant for marginalised groups, for whom social media provides an opportunity to join a community and feel included, in a way that their physical environment may not always provide. For example, a qualitative study incorporating evidence from structured interviews finds that for LGBTQ+ people, social media helps to decrease feelings of loneliness and increase feelings of belonging (Eickers, 2024[128]). Similarly, members of racial and ethnic minority groups can use social media to gain a sense of belonging and support when support in the offline world is lacking (Miller et al., 2021[129]). In addition, individuals with niche interests can find likeminded peers online. A series of interviews with users of Reddit shows that finding a subgroup of likeminded individuals creates feelings of belonging (Hwang and Foote, 2021[130]).
Open questions for policy and research
The mixed conclusions on the link between social connectedness and digitalisation, and the fact that the majority of evidence so far is correlational, points to three main open questions for policy and research going forward:
(1) Which types of digital technology use matter most for social connections?
Evidence so far points to the fact that it is not just the amount or frequency of social media use that matters, but the purpose and way in which the platform is used. Thus, simply collecting data on overall smartphone or social media use does not capture all relevant information; it is important to further distinguish between how digital tools and social media platforms are used (Dienlin and Johannes, 2020[131]; Charmaraman et al., 2025[132]; Masur, 2021[96]).
For instance, one useful categorisation of activity type comes from Frison and Eggermont (2020[133]):
Active communication: chatting via WhatsApp, videocalls via FaceTime, or sending photos through Snapchat
Active participation and creation: posting, commenting, or liking on TikTok, Instagram or LinkedIn
Passive interactions: browsing a feed, watching videos etc.
Each type of interaction may have a different relationship with loneliness, isolation and connection. For example, by manipulating research participants’ social media use, one experimental study found that inducing users to actively post status updates on Facebook led to decreases in loneliness (Deters and Mehl, 2013[134]). On the other hand, passive interactions, such as scrolling or viewing posts, are associated with social comparison and higher levels of loneliness (Verduyn et al., 2015[135]). Recent research in Europe corroborates this, finding that intense passive use of social media is associated with higher levels of loneliness (Dhombres et al., 2024[136]).
(2) Does the shift from real world to digital interactions causally matter for quality of social connectedness?
This topic was studied by researchers in more detail during the COVID-19 pandemic, when confinement policies and enforced isolation meant that people were actively substituting in-person interactions with remote ones. Studies found that digital social interactions were protective of mental health, in particular during the most restrictive periods of lock-downs (Marinucci et al., 2022[137]), and were more associated with positive mental health outcomes than other forms of coping, such as physical activity or spending time outdoors (Stieger, Lewetz and Willinger, 2023[138]). While more frequent social interaction of any sort (in-person or remote) is protective of mental health, multiple studies find that in comparison to all forms of remote connection (video calls, texts or messaging apps, social media), more frequent in-person interactions have a greater association with positive affect and mental health outcome improvements (Liang et al., 2024[139]; Marinucci et al., 2022[137]; Stieger, Lewetz and Willinger, 2023[138]); one study of young people in the United Kingdom found that those who increased the frequency of their usage of social media during the pandemic experienced deteriorations in their mental health (Rouxel and Chandola, 2023[140]).
Ecological momentary assessment (EMA) sampling18 to link digital communication and social media use to mood might provide a more robust answer – this can enable an understanding of how these behaviours can induce feelings of loneliness, isolation and connection alongside other affective states including those relating to poor mental health outcomes. EMA studies collect objective – rather than self-reported – data on how much time an individual spends on a social media platform, texting, etc., and combine this with regular self-reported assessments of mood (see (Garcia et al., 2014[141]) and (Blahošová et al., 2024[142]) for an explanation of the methodology).19
(3) How effective are efforts to limit young people’s screen use, and problematic Internet use, in terms of promoting positive online interactions?
While academics debate the causal relationship between deprivations in social connections and use of digital technologies and social media, policymakers have taken steps or proposed policy initiatives to regulate, limit or ban social media or digital devices for children below certain ages and in specific contexts (Table 5.1), in an effort to safe-guard the learning potential of young people as well as improve their focus, attention, mental health and well-being (OECD, 2024[143]). Part of the impetus for this is the demand for acting in a precautionary manner to safeguard children (as a particularly vulnerable group) voiced by frontline actors who work with children: teachers, clinicians and particularly parents. Indeed, in many OECD countries, parents have organised to issue pledges and proposals to limit social media and smartphone use, such as the Wait until 8th movement in the United States (Wait until 8th, 2024[144]), Smarter Start ab 14 in Germany (S14, 2024[145]), the OFF initiative in Spain (OFFM, 2024[146]) or the Smartphonefri Barndom in Denmark (Smartphonefri Barndom, 2024[147]).
As most of these initiatives are relatively recent, in most instances their impact has yet to be assessed20 – and when evaluations of these policies have been done, the quantity and quality of youth social connections have not been a primary outcome of interest. More systematic evaluations on these initiatives should accompany their roll out to help peer learning on how these policies can most effectively be designed, implemented and enforced. A part of this process should be a discussion of which outcomes will be affected by each initiative – and therefore measured as a part of monitoring and evaluation efforts. Complementing the focus on cognition, attention and learning outcomes, these efforts should also include assessments of mental health, frequency of in-person vs. remote social interactions, feelings of inclusion and connection, and relationship quality.
Note: * For a thorough review of the topic, refer to OECD (2025[175]), Legal and policy landscape of age assurance online for child safety and well-being, OECD Publishing, Paris https://doi.org/10.1787/4a1878aa-en.
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← 1. Certain personality traits have been found to be associated with feelings of loneliness and the propensity to socialise (MacAdams, 1992[205]; Norman, 1963[176]). Extraversion has the strongest negative association with loneliness (Buecker et al., 2020[195]; Abdellaoui et al., 2019[196]). Research using data from longitudinal studies of twins or bio-banks has sought to understand the genetic basis for loneliness and isolation. In general, higher-end estimates come from research using twin or family studies, which find that hereditability may account for up to 50% of individual variation in perceptions of isolation (see (Cacioppo et al., 2011[177]) and (Gao et al., 2016[178]) for an overview). Even assuming the higher end estimates, this still means that at least half of the variation in social connections outcomes stem from other sources – allowing a potentially large role for socio-economic, structural and environmental factors in determining how lonely, isolated or connected an individual is.
← 2. Sudden life events, or transition phases, may also induce feelings of loneliness or social isolation. One reason life transitions can be a vulnerable time for social connections outcomes is because they disrupt existing social networks, and can lead to greater isolation (Evans et al., 2022[200]). This can be true for both young people leaving home for the first time (Lim, Eres and Vasan, 2020[204]), or for the elderly entering into long-term care facilities (Weldrick and Grenier, 2018[179]). Examples of these events – sometimes called triggers – include the loss of a loved one, divorce or separation, the onset of an illness, losing a job or moving away from home (Lim, Eres and Vasan, 2020[204]). The effects of a life transition on any given individual vary widely. Some trigger events are inherently negative (loss of a loved one) whereas others are not inherently positive or negative (moving from home). Additionally, life events may overlap with one another, happen suddenly without warning, or take place over an extended period of time (Lim, Eres and Vasan, 2020[204]). The ways in which people respond to and rebound from triggering life events stems in large part from the underlying risk and resilience factors unique to the individual, but can also be affected by policies that are designed to ease transitions (e.g. youth transitions to the labour force), or ensure the inclusion of socially isolated individuals (e.g. community centres, particularly important for elderly people living alone).
← 3. Outcomes in various dimensions of the OECD Well-being Framework (Figure 1.1), such as income, education, jobs and job quality, health, work-life balance and housing, can all shape people’s time, resources and opportunities to connect with others. A simple illustration of this is provided in Chapter 3, which highlighted how deprivations in socio-economic conditions – earning a low income, being unemployed, having lower levels of education – are all associated with worse outcomes in social connections.
← 4. Various programmes run by Türkiye’s Ministry of Family and Social Affairs and the Ministry of Youth and Sports in the areas of housing, community-based social assistance, youth participation, counselling and psychosocial support, culture and volunteering also focus on social cohesion and intergenerational connection, including through many initiatives that support families and children. The Ministry of Family and Social Affairs also provides parents with resources and services to support raising children in the digital age, including protecting children from digital risks, cyberbullying and – in coordination with the Information Technologies and Communication Authority and Department of Cybercrime – a social media working group.
← 5. Previous work at the OECD has highlighted the well-being impacts of digital technology (OECD, 2019[94]; Lee and Žarnic, 2024[88]), the role of digital technology and social media in adolescent and child mental health and well-being (OECD, 2025[90]; 2018[210]) – which includes discussion of social connections outcomes, including social media use and cyberbullying – and the ways that digital devices are integrated into education systems (OECD, 2024[143]; 2024[208]; 2023[180]).
← 6. Different definitions for social infrastructure exist, and not all stakeholders active in the field use the term synonymously (Latham and Layton, 2022[217]). There are two main definitional approaches: (1) the welfare state perspective and (2) the social cohesion approach (Renner, Plank and Getzner, 2024[211]). The welfare state perspective views social infrastructure as one form of broader infrastructure, encompassing the services, facilities and institutions that enable people to actively participate in society and ensure quality of life. This approach focuses on public service provision, and typically includes education, health, culture, recreation and social services (including public order and safety). Previous OECD statistical work in defining the distinct components of infrastructure (economic vs. social) has been centred in this approach (van de Ven, 2021[214]; Mudde, Dornel and D’ambrières, 2024[207]).
The social cohesion approach has gained traction in recent years, and centres on the physical spaces that foster social interactions and build social capital – especially connection across disparate social groups – rather than the provision of service itself (Klinenberg, 2019[20]; Latham and Layton, 2019[21]). For this reason, the second approach goes beyond publicly funded spaces to also include commercial spaces that have a strong social component: for example, cafes, bookstores, barbershops, etc. This definitional approach builds off the concept of third places: widely accessible and informal spaces – beyond home, school or the workplace – where people come together predominantly for conversation and social interaction without needing an invitation or requiring significant expense (Oldenburg, 1989[68]; Oldenburg and Brissett, 1982[181]). The social cohesion approach is also closely linked to social capital literature, investigating declining trends in civic participation and its implications for connection (Putnam, 2000[30]).
This chapter uses the social cohesion approach to define social infrastructure. Note that other recent policy approaches have taken a much broader definitional view of social infrastructure, marrying together the welfare state and social cohesion perspectives to create a definition of social infrastructure that includes all social policies, rights and services as well as all public resources – including technical infrastructure such as waste water, electricity and telecommunications – that enable people to fully engage in their civic, economic and social lives (WHO, 2025[3]). The narrower definition used in this chapter enables a finer distinction between social infrastructure – physical spaces that encourage interaction – and the outcomes it influences – social connection and social capital. Its narrower scope on physical space, as opposed to spaces, policies, rights and services combined, also allows for more actionable recommendations in advancing the measurement agenda.
← 7. The third categorisation, “bonding” social ties, refers to close relationships with individuals who are a part of the same existing network – close family and friends, members of a social club, etc. (Putnam, 2000[30]). These relationships are also important for well-being, and can be supported by social infrastructure, however are also cultivated in private spaces.
← 8. There are a few existing initiatives to score social infrastructure that provide a suggestive range of inputs for what criteria might be needed to create and structure such a scorecard.
The Australian Urban Observatory Social Infrastructure Index ranges from a minimum score of 0 and maximum score of 16, and comprises four sub-domains (Australian Urban Observatory, 2025[199]): health infrastructure (access to residential aged care facilities, dentists, general practitioners, pharmacies, community health centres, and maternal child and family health centres), education infrastructure (access to childcare, public primary and secondary schools), community and sport infrastructure (access to community centres, public swimming pools and sports facilities) and cultural infrastructure (access to museums, art galleries, cinemas, libraries). The index focuses on communal, rather than commercial (or digital) spaces, and does not include public parks or green spaces.
The University of Texas at Dallas has developed a Social Infrastructure Index for 55 large metro areas in the United States and Canada, containing the following input measures: volunteer rate, poverty rate, community centres per capita, libraries per capita, education expenditures per child, police spending per officer, technology sector job growth, five-year population growth, quality of parks and open spaces (measured via total acreage, and expenditure per capita) (Gearey, Foster and Ahmed, n.d.[202]).
← 9. The National Neighborhood Data Archive (NaNDA) collates data from the National Establishment Time Series Database which itself contains private for-profit, non-profit and government agency organisations. NaNDA then classifies each establishment according to North American Industry Classification system codes, resulting in a database of the following types of social infrastructure: eating and drinking places; religious, civic and social organisations; parks; personal services; arts, entertainment and recreation; social service organisations (Rhubart et al., 2022[182]).
← 10. “How would you describe your sense of belonging to the following? a. To your local community b. To your town or city c. To your province d. To Canada” Very strong; somewhat strong; somewhat weak; very weak; no opinion (Statistics Canada, 2020[194]).
← 11. In OECD countries, the number of adults who reported having used the Internet over the past three months increased from 54% in 2005 to 92% in 2023 (OECD, 2024[209]). Furthermore, the percentage of respondents in the EU who have used social networks in the last three months increased from 43% in 2014 to 59% in 2023 (Eurostat, 2024[183]). These statistics are for the general population, but when narrowing in on young people, 2024 data from the United States show that almost half (46%) of young people aged 13 to 17 use the Internet “almost constantly”, and 90% have access to a smartphone (Faverio and Sidoti, 2024[201]). Across all OECD countries, 15-year-olds use digital devices for non-academic purposes for 2.6 hours a day during the week, on average, and 3.9 hours per day on weekends (OECD, 2025[90]).
← 12. The second youngest age cohort in the United States has the highest rate of agreeing that social media makes people feel less connected, however the difference in outcomes between age groups is less than for loneliness (Figure 5.1, Panel A).
← 13. Findings from Chapter 4 show that in-person interactions have been declining over the past 10-15 years, while at the same time, remote connections have been rising. This is suggestive of some degree of displacement, however it is insufficient to make causal claims.
← 14. This line of argument posits that real-world encounters use social cues, happen synchronously (i.e., people speak in turn, reacting to tone, facial cues and body language of the other) and are often one-to-one. Conversely, online interactions tend to be disembodied, asynchronous, characterised by one-to-many modes of communication and take place in short-lived communities with low barriers to entry and exit, which makes relationships more disposable (Haidt, 2024[101]).
← 15. In addition, the simple presence of a digital device can impact not only the quantity but also the quality of real-world interactions (Turkle, 2015[102]): one experimental study found that the presence of a mobile phone negatively affected the quality of conversation and closeness between people in the same room, as a result of it being a distraction (Przybylski and Weinstein, 2013[184]); another finds similar results, with the presence (or absence) of a mobile device influencing perceived empathy levels of one’s conversation partner (Misra et al., 2016[218]). An additional line of research focuses on “phubbing” – when a person focuses on their phone, ignoring others nearby – showing that it can diminish feelings of connection and enjoyment of social interactions (Barrick, Barasch and Tamir, 2022[185]; Capilla Garrido et al., 2021[186]). One study in China, focused on the effects of parental “phubbing” on young children, suggests it can influence social withdrawal in children and worsen parent-child relationship quality (Zhang and Wang, 2025[216]).
← 16. Data from the Health Behaviour in School-aged Children (HBSC) survey shows that between 2017 and 2022, young people reported an increase of cyberbullying victimisation from 12% to 16%, with girls reporting higher rates than boys (conversely, boys report higher rates of engaging in cyberbullying, themselves) (OECD, 2025[90]). The impact of cyberbullying can be exacerbated by the widespread dissemination of harmful content targeting victims. Research highlights links between cyberbullying and various mental health issues, including psychological distress and depression (Giumetti and Kowalski, 2022[188]).
← 17. A meta-analysis of 23 studies investigating the relationship between loneliness and social media use finds a small positive relationship between the two outcomes (Liu and Baumeister, 2016[187]). Another oft-cited study concludes that more frequent digital media use is associated with lower psychological well-being among adolescents, compared to adolescents who seldom use digital media (Twenge, 2019[213]): these findings may be due to a reduction in face-to-face interactions and physical activity, disruptions to sleep and the effects of social comparison.
Other scholars argue that the weight given to social media for changes in mental health and feelings of loneliness and isolation may be overstated: findings are either unclear, or show small effects. A 2019 study finds a negative association between digital technology use and psychological well-being in adolescents, however the authors argue that the effect is too small in magnitude to interpret as relevant in a policy context (Orben and Przybylski, 2019[189]). In a more recent paper, the same authors find no evidence that the deeper integration of social media into the daily lives of adolescents has increased the prevalence of depression or emotional problems (Vuorre, Orben and Przybylski, 2021[215]). Furthermore, a meta-analysis of 196 studies investigating the relationship between social media use and loneliness, specifically, finds no significant relationship (Cheng et al., 2019[190]).
← 18. Ecological momentary assessment (EMA) sampling involves real-time sampling of respondents’ affective states and behaviours; for more information on the methodology refer to (OECD, 2013[193]) and (Kudrna et al., 2024[191]). Increasingly, these surveys are fielded digitally using apps.
← 19. Applications of this approach have shown that day-to-day changes in digital communication and social media use did not affect adolescents’ perceptions of social support (Blahošová et al., 2024[142]); other evidence shows that in-person or mixed in-person and remote interactions are associated with high levels of positive affect, compared to either not socialising or only remote interactions (Kroencke et al., 2022[203]). Another study found that following online interactions with friends and family (who the respondent knows in the real-world – i.e., not “online friends”), depressed adolescent respondents were more likely to report negative emotions than positive (Moukalled, Bickham and Rich, 2021[206]), and yet another study showed that adolescents susceptible to social influences were more likely to feel socially isolated after one hour of social media use (Armstrong-Carter et al., 2022[198]). Indeed, another study of college-aged students finds that socialising via digital technology was associated with higher levels of loneliness, and lower well-being, in comparison to socialising in person – even when users described both types of interactions as meaningful (Roshanaei et al., 2024[212]). Continued applications of this method will help unpack these relationships in greater detail.
← 20. A few studies of school bans have been conducted thus far (although social connections outcomes were not considered). For example, a study of 30 English secondary schools found that restrictive school policies on smartphone usage were not associated with better mental well-being among the student population, and while the policies limited social media use during school hours it had no effect on out-of-school usage (Goodyear et al., 2025[192]). This aligns with previous OECD work, which notes that classroom bans can minimise disruptions during the school day, but that these policies could have the unintended consequence of increasing smartphone and social media use at home (OECD, 2024[208]). Conversely, an assessment of Norway’s guidelines by a researcher at the Norwegian Institute of Health finds that the policy has had mental health benefits for girls, as well as improving their education outcomes (Abrahamsson, 2024[197]).