1. Overview and summary

Children have a right to well-being. Just like everyone else, their current quality of life is important in itself. Children have a right to feel loved, valued, supported and cared for; they have a right to the best possible health, to the best possible education, and to an enjoyable childhood, today, in the here and now. But childhood is also a critical time for growth and development, and the things that children do, learn, feel and experience matter, for today but also for their futures. Childhood living conditions and the ways children develop leave deep impressions that can affect their lives for years to come. Overwhelming evidence attests to the importance of children’s well-being in shaping who they are, how they behave, and what they do when they grow up.

OECD governments are increasingly recognising the critical importance of childhood and child well-being. Over the past few decades, a number of governments have established cross-cutting national policy strategies and frameworks aimed at promoting child well-being and offering children the best possible start in life. These include Ireland’s Better Outcomes, Brighter Futures framework (DCYA, 2014[1]), New Zealand’s Child and Youth Wellbeing Strategy (DPMC, 2019[2]) and, most recently, Finland’s National Child Strategy (STM, 2021[3]).

Good child policy needs good child data. Child well-being policy development requires deep and sound information on a range of areas, including children’s material living standards, their physical and mental health, their social lives, and their learning and education. Data on the settings and environments in which children live their lives – their families, their schools, their communities and their neighbourhoods – are important too, as there is increasing evidence on the importance of children’s environments for their outcomes, especially for those growing up in the most vulnerable families and communities (OECD, 2019[4]). In recent decades, national statistical offices, international organisations and academic researchers alike have engaged in a range of activities aimed at developing better data to better capture children’s lives. At the cross-national level, international instruments like the Children’s Worlds survey, the Health Behaviour in School-Aged Children (HBSC) survey, and the OECD Programme for International Student Assessment (PISA) have helped push forward what we know and understand about children’s lives in a range of areas. At the national level, in many countries, a growing number of country-specific surveys and datasets have helped do something similar.

Still, there is more to do. As discussed throughout this report, there remain a number of important gaps in child data, especially but not only from a cross-national perspective. Some of these gaps are long-standing. The OECD has long highlighted the need for better data on children’s well-being during early childhood (0- to 5-year-olds), for instance, and on the well-being of children in the most vulnerable or marginalised positions (OECD, 2009[5]; Richardson and Ali, 2014[6]). Other information gaps are newer, and have been exposed by advances in scientific knowledge on what makes for a good childhood, as well as societal change and developments in the ways that children live their lives. One example is the importance of children’s socio-emotional well-being – both in itself, and for its interactions with other areas of well-being – which is often not well covered in existing data. Data gaps hamper the development of better child policies.

This report aims to push forward the child data agenda. Building on past OECD work on child well-being measurement and data, including Doing Better for Children (2009[5]), How’s Life for Children (2015[7]), and the OECD Child Well-being Data Portal (2019[8]), as well as the Organisation’s experience with well-being measurement more generally (OECD, 2020[9]), it highlights key gaps in child data, especially from a comparative cross-national perspective, and outlines priorities for the improvement of child data infrastructures. The over-arching objective is not just to motivate improvements in child well-being measurement in and of itself, but also to build better data to inform the development of better child well-being policies.

The report assesses and reviews the current state and availability of cross-national data on child well-being. To provide the basis and structure for the assessment, it starts in Chapter 2 by outlining a new “aspirational” framework for child well-being measurement. Using an in-depth review of research evidence on child well-being and development as its starting point, this framework sets out which aspects of children’s lives should be measured in order to best monitor child well-being, and in what way. It is “aspirational” in the sense that it is not guided by immediate data availability considerations, but instead by research findings. The framework also provides a data “roadmap” that can be used both to improve the use of existing child data and, in the longer term, to guide better data collection and motivate improvements in child data infrastructures.

Guided by this conceptual framework, subsequent chapters (Chapters 3-6) examine and assess cross-national data in different domains of child well-being. They identify areas where existing cross-national data are limited or lacking, and highlight priority areas for better data collection. Chapter 3 (“Do children have the things they need?”) concentrates on children’s economic and material well-being. Chapter 4 (“Are children active and physically healthy?”) looks into data on children’s physical health and well-being. Chapter 5 (“Do children feel safe and secure, respected, included and happy?”) focuses on children’s social, emotional and cultural well-being. Chapter 6 (“Are children learning and achieving in education?”) covers children’s education, learning and cognitive well-being. In each case, the chapters start with a review of the research evidence on what matters most for the given domain of child well-being, before turning to discuss data availability, data gaps, and data priorities.

Overall, the report finds that comparable cross-national data on child well-being remains scant and limited in scope. While the availability of cross-national child data has improved considerably in recent decades, there are still many areas of children’s lives that are not covered well or, in some cases, at all by existing cross-national data. Furthermore, age group and country coverage remains an issue, while some children, often those in the most vulnerable positions, are frequently missing or not easily identifiable in the data. There is, in general, a need for co-ordinated action from governments, international organisations, and the wider community to improve the availability of cross-national child data. This is a sizable task. It will require both significant investment and medium- to long-term commitment from all actors involved.

Well-being is a multifaceted phenomenon that requires a diversified set of measures. Measuring the well-being of children requires an even larger set of measures that capture not just how children are doing, but also how they’re developing. Children’s well-being is also tightly related to and embedded in their environment. Especially in early childhood, children’s well-being depends heavily on their parents or carers. More so than for adults, it is difficult to get a full picture of children’s well-being without taking their family, school, community, neighbourhood and policy environment into account.

In the wider well-being field, many OECD countries have in recent decades developed well-being frameworks, dashboards, and indicator sets to help formalise and improve the measurement of well-being (Exton and Shinwell, 2018[10]; OECD, 2011[11]; OECD, 2020[9]). Building on decades of international work on measuring societal progress beyond GDP, in 2011, the OECD established a framework for measuring well-being (Box 1.1). The framework stands at the centre of the Organisation’s well-being monitoring activities and informs monitoring efforts in a large majority of OECD members. While national well-being initiatives come with country-specific features, they have a lot in common, providing a holistic picture of well-being along a range of similar dimensions, as well as a focus on both distributional and sustainability aspects.

Well-being measurement initiatives have helped push forward the well-being agenda in several ways (Durand and Exton, 2019[12]). By fostering a more comprehensive approach to measurement, they have helped draw attention to important aspects of people’s lives – for example, subjective well-being – that were often neglected in standard analyses. In several OECD countries, they have been integrated systematically into the policy making process. To varying extents, they have been used in agenda setting, in policy formulation, and in policy evaluation (Exton and Shinwell, 2018[10]). In some countries, well-being metrics are used by government to help set policy priorities and inform budget allocations (Durand and Exton, 2019[12]).

In an effort to improve the measurement of children’s well-being, a smaller but growing number of OECD countries have in recent years developed child-specific well-being measurement activities (Table 1.1). In some cases, these activities are explicitly tied to and motivated by policy initiatives to enhance child well-being. Both Ireland (BOBF) and New Zealand, for example, have established measurement activities as part of (and in support of) their wider whole-of-government child strategies. In both, the measurement activities are closely aligned with and informed by the objectives of the wider strategy. In others (e.g. Australia, Ireland (NSCWBI), the United Kingdom, the United States), the frameworks have been developed as part of initiatives to improve monitoring more generally and are not directly tied to specific policy activities.

International organisations have also developed child well-being frameworks and initiatives applicable at the cross-national level (Table 1.1). UNICEF was an early mover in this area, establishing through its Innocenti Research Centre Report Card series an influential approach to cross-national child well-being comparisons. The OECD has also played a central role. Its initial child well-being measurement framework, introduced in Doing Better for Children (2009[5]), focused heavily on key child outcomes across six dimensions: material well-being; housing and environment; education; health; risk behaviours; and quality of school life. This framework was later revised (in 2015) to increase consistency with the OECD’s wider Well-Being Framework (see Box 1.1).

These national and international initiatives are underpinned by a relatively common understanding of child well-being. All adopt a multi-dimensional approach and use multiple indicators to capture children’s well-being. Several use a combination of objective and subjective measures, with some (e.g. New Zealand, the United Kingdom) putting particularly strong emphasis on making sure that children’s own thoughts and views are well heard. Several national initiatives (e.g. Ireland (NSCWBI), Finland, New Zealand, the United Kingdom) also ran child consultations at the design stage, with a view to ensuring the aspects covered and measures used are meaningful to children themselves.

While focusing largely on outcomes, several of the initiatives (e.g. Australia, New Zealand, UNICEF) emphasise that children’s well-being is embedded in their family, social, community and physical environments (UNICEF, 2020[13]); they recognise that children’s outcomes are influenced by and interwoven with different levels of (inter-connected) social influence, and stress the importance of children’s connections and relationships with their environment(s). The need to pay attention to child-environment relational quality is emphasised, for instance, in the framework that underpins New Zealand’s Child and Youth Well-Being Strategy that was set in 2019 to guide child well-being policies and data collection (DPMC, 2019[2]; DPMC, 2021[14]). This notion is also central to the “multi-level” framework adopted in UNICEF’s most recent Report Card, which specifies various levels of influences stretching from children’s activities and behaviours to the wider policy and country context (UNICEF, 2020[13]).

With respect to thematic coverage, children’s physical health outcomes and education and learning outcomes feature in all the initiatives, while (aspects of) children’s material well-being and their social and emotional are included in many (Annex Table 1.A.1). There are, however, some differences across the initiatives. For example, only a few of the national initiatives (e.g. Ireland (NSCWBI), Ireland (BOBF), the United Kingdom) include measures of children’s life satisfaction and overall subjective well-being, and only a minority of all initiatives (Australia (KNICHDW), Ireland (BOBF), New Zealand) cover aspects relating to children’s identities, social identities and broader social needs.

One area where initiatives differ considerably is in the treatment and coverage of environmental factors and other potential influences on outcomes. While family income (or related measures) and certain aspects of children’s behaviours (especially children’s health behaviours) along with various other aspects of children’s home and family environment (e.g. family work status) are covered in many of the initiatives (Annex Table 1.A.1), coverage of other environmental factors, e.g. children’s school and ECEC environment and the wider community and physical environment, is inconsistent across initiatives. UNICEF’s latest Report Card (2020[13]) has made a significant contribution in this area by placing greater emphasis on children’s relational, community and household resources.

Chapter 2 of this report sets out an “aspirational” conceptual framework for measuring child well-being. Grounded in an in-depth review of the child well-being literature, the framework builds on and extends the OECD’s existing approach to child well-being measurement. It provides a renewed structure and set of guidelines detailing what aspects of children’s lives need to be measured, and how, in order to fully monitor child well-being and its determinants. It is “aspirational” in the sense that it is not constrained by immediate data availability concerns; rather, it sets out how child well-being should ideally be measured according to the research, and can serve as a medium- to long-term ”roadmap” for the improvement of child well-being data collections.

The starting point for the framework is a concept of child well-being that is multi-dimensional (encompassing a range of aspects of children’s lives) and forward-looking. Similar to much of the OECD’s past work on child well-being measurement, the framework has its roots in the idea that children should be able to both enjoy a “good” positive childhood in the here-and-now, and have the opportunity to develop skills and abilities that set them up well for the future. Child development – and the changing nature of what is needed for development as children grow up – feature heavily, alongside other measures of children’s quality of life.

Reflecting increasing recognition in child well-being research of the importance of the environments and settings in which children grow up, the framework adopts a multi-level or “ecological” structure, covering both child well-being outcomes and potential drivers and influences (Bronfenbrenner, 1979[22]; 1989[23]; Minkkinen, 2013[24]). This in line with several recent child well-being measurement initiatives, including the approach developed by UNICEF mentioned above (UNICEF, 2020[13]). Children’s well-being outcomes are at the centre of the framework (Level A), surrounded by a series of drivers and influences (Figure 1.2). Level B covers child-level influences: the things that children do or are engaged in that can contribute to their well-being outcomes, including their activities, attitudes, behaviours, and relationships. Level C covers environment-level influences: aspects of children’s settings and environments that can impact well-being, either directly or indirectly, for example by shaping opportunities and influencing attitudes and behaviours. This includes children’s family and home environments, the environments they face at school or in childcare, and their wider physical and community environments. Level D covers child-relevant public policies, such as public family and housing policies and public health policies. 1

In terms of thematic content, the framework focuses on child well-being outcomes in four core areas, which are inter-connected and frequently interact with one another (see Box 1.2):

  • Material outcomes, which covers children’s access to material resources, including essential or important goods, services and activities. This includes their access to basic necessities like food, clothing and housing, but also other material goods and activities (e.g. a computer and the internet) that are important for children growing up in OECD countries today.

  • Physical health outcomes, which covers children’s physical health status and physical development. In broad terms, this area covers outcomes relating to whether children are healthy, free from illness, injury and disease, and developing and functioning well physically, given their circumstances.

  • Social, emotional and cultural outcomes, which covers outcomes relating to children’s behaviours, emotions, and thoughts and feelings towards themselves and others, as well as related outcomes tied to social and cultural identities. This area covers many of the more “subjective” aspects of children’s well-being, ranging from basic emotional security and children’s sense of safety, to their sense of identity and social identity (including sexual, gender and cultural identities), their sense of belonging, and their over-arching life satisfaction. It also covers children’s socio-emotional skills, mental health status, and psychological well-being.

  • Cognitive development and education outcomes, which covers outcomes relating to children’s learning, knowledge, and cognitive skill and ability development. This are includes measures of children’s cognitive development as well as their progression through the education system, their educational attainment, and their satisfaction with what they learn.

Other key features of the framework include:

  • A requirement that measurement is sensitive to children’s age (or stage of development), with age- (or stage-) appropriate (variations in) in concepts and measures used where relevant.

  • An emphasis on children’s own voices, and a belief that children’s views and perspectives should be reflected throughout the measurement process wherever possible, including in both the indicators design and selection stage (in order to reflect what matters most to children themselves), and in the measures themselves, through the use self-report and subjective child data.

  • A requirement that measures capture not just average levels of well-being but also the distribution of well-being across children, including through measures that reflect inequalities and disparities across different groups of children (e.g. by sex, by living arrangement, and by migrant background). Wherever possible, measures should also be flexible and responsive to the needs and challenges faced by children from diverse backgrounds and in different or vulnerable positions (e.g. children with disabilities, children in out-of-home care, children experiencing maltreatment).

This framework innovates on child well-being measurement in several ways. First, its multi-level structure acknowledges and helps clarify the importance of children’s activities, relationships, environments, and other potential influences of child well-being, emphasising that these potential drivers are distinct from (though often have an important role to play in) children’s well-being outcomes. Second, through the emphasis it places on age-sensitive concepts and measures, it pays greater attention to the ways that the things children need, want and should be able to do change through childhood. Finally, through the weight placed on children’s voices, it looks to reinforce efforts to ensure that children’s own thoughts, views and perspectives across all stages of child well-being measurement. Later chapters in this report develop this approach further by reviewing and identifying the key mechanisms and specific factors that impact children’s current and future outcomes.

Guided by this conceptual framework, subsequent chapters in this report – Chapters 3, 4, 5 and 6 – discusses the current state and availability of cross-national child data, and how the available data matches up to the identified aspects of child well-being. These chapters highlight priority areas for better data collection, and identify areas where existing cross-national data are limited or lacking.

The sub-sections below summarise the key priorities and data gaps identified in the chapters. Some of these gaps are broad and stretch across many or most aspects of child well-being. Others are more specific and relate to selected areas of well-being, only.

Some dimensions of children’s lives are covered better than others by existing cross-national data. Data on children’s cognitive development and educational outcomes, for example, tend to be relatively widely available (Chapter 6). This is especially the case with respect to the traditional core areas of reading, mathematics and science, which, for children in middle childhood and adolescence, are covered comprehensively through the major international student assessments programmes like Trends in International Mathematics and Science Study (TIMSS), Progress in International Reading Literacy Study (PIRLS), and the OECD Programme for International Student Assessment (PISA). Comparable information on adolescent health and physical well-being is also fairly well covered (Chapter 4). For many (but not all) OECD countries, the HBSC survey provides valuable information on a range of health outcomes and behaviours among 11- to 15-year-olds.

But for several other aspects of children’s lives, coverage is incomplete and measures are limited. Children’s social and emotional well-being provides the most acute example (Chapter 5). While certain aspects of socio-emotional well-being are covered in some cross-national child surveys, including those mentioned above, these surveys tend to look at the issue from different angles. In general, measurement is not based on a common understanding of social-emotional development across childhood, leading to a lack of alignment in the dimensions explored. The OECD’s Study on Social and Emotional Skills (SSES), which covers students age 10 and 15 years old, goes some way towards tackling this issue. Results from the first round cover 10 cities from across the globe.

Children’s economic and material well-being provides a second example of an area where cross-national data are limited in scope (Chapter 3). For European OECD countries, the European Union Statistics on Income and Living Conditions (EU SILC) survey provides valuable comparable information on aspects of children’s material living standards, but these data are not comprehensive. For many OECD countries outside Europe, available instruments are often not directly comparable with those from other countries or have often been designed mostly for other purposes, such as PISA.

There is also a general lack of comparable cross-national data on children’s well-being during early childhood. Most dedicated international child surveys cover children during middle- or, more often, late-childhood, only. Some general-purpose household surveys like EU SILC can provide data on children of all ages, but the information provided, while valuable, is not always child-centred and is limited in breadth and scope. There are, of course, a number of challenges involved with collecting data on young children, especially child-centred and self-reported data (see below). Nonetheless, there are a growing number of techniques available for this purpose. One promising example is the OECD’s International Early Learning and Child Well-being Study (IELS), which uses a combination of direct (child-completed) and indirect (adult-completed) methods to collect information on 5-year-old’s early learning and well-being. However, this study is still in its early stages: the first round, run in 2018, covered only three countries (i.e. England (United Kingdom), Estonia and the United States).

Some children are also better covered than others by existing data. While cross-national surveys generally strive to cover populations as comprehensively as possible, those in the most vulnerable or marginalised positions – such as children with disabilities, children in care institutions, children in homeless families, and children experiencing maltreatment – are frequently either not easily identifiable or a missing entirely in the data. As a result, as is stressed across all chapters of this report, comparable cross-national information on the well-being of vulnerable children2 is often lacking.

In some cases, at least part of the issue lies in the questions asked in cross-national surveys. Few surveys contain questions about child disability, for example. Another issues lies in survey coverage. Most cover private households only, and exclude people (including children) living in other types of living arrangement, such as children in homeless families and those in care institutions. More generally speaking sample size requirements are insufficient to adequately capture the situation of a group that often makes up a small proportion of the overall child population. Thus, even if vulnerable children were both included and identifiable, too few children would be covered in the absence of specific over-sampling (OECD, 2019[4]).

One major trend in child well-being research in recent decades has been the increased emphasis placed on children’s own voices and concerns (Clark et al., 2020[36]). Experts increasingly see value in listening to children’s thoughts and views on (aspects of) their own lives, for multiple reasons. First, children's feelings and perceptions matter for many aspects of their well-being, and often impact behaviours that can shape lifetime well-being. Decisions to improve children's well-being cannot be made without taking account of their worries and concerns, their preferences and aspirations, and also their perceptions and knowledge of the challenges for their well-being now and in the future. There is also growing evidence that, from an early age, children develop a good sense of the economic and social conditions in which they live, which can impact their interactions and engagement with peers and society (Chapter 3). In addition, for some areas of children’s well-being, the best or, at times, only way of collecting relevant information is through children themselves. This is largely the case when looking to collect data on children’s personal relationships, for instance, or on many aspects of their socio-emotional well-being more generally (Chapter 5).

For a number of OECD countries, the Children’s Worlds survey, which covers children from age 8 to 12, provides valuable self-reported data covering a range of areas of well-being. This includes their views towards certain aspects of their own material and socio-emotional well-being, including whether they feel listened to and well supported in different areas of life. Several other cross-national child surveys and instruments – including PISA – now ask children questions about their over-arching life satisfaction, as well as questions about a limited number of specific areas of life, such as their learning and educational aspirations.

However, there are still major gaps in the availability of cross-national data covering children’s views towards their own lives. For example, there is no real equivalent to Children’s Worlds for adolescents. As a result, there is a general lack of cross-national information on older children’s views of many important aspects of life. There is also little information available on the educational attitudes and aspirations of children in middle childhood, and on children’s (of all ages) knowledge of and attitudes towards health issues. Indeed, there is in general a lack of data on children’s understandings of how their actions, behaviours, skills, and abilities may (or may not) impact on their well-being, both now and in the future.

There are, of course, challenges involved with producing data that capture children’s views. Collecting self-reported data can be more difficult for children than for adults, especially in the case of younger children, who may have more trouble fully expressing themselves. For new-borns and the very youngest, it is impossible. There are also concerns about the general reliability and validity of such data. There are techniques available for overcoming these challenges – including visual methods and vignette or story-based methods – and initiatives like Children’s Worlds show that, at least for children over a certain age, it is possible to collect this kind of data in a reliable way (Casas, 2017[37]; Casas and Rees, 2015[38]; Bradshaw, 2019[39]). As the OECD recommends for subjective well-being data more generally (OECD, 2013[40]), subjective and self-report child data can act as valuable complement to (rather than replacement for) other measures of child well-being.

Child well-being, while multi-dimensional, is also complex and inter-connected. Different aspects of children’s lives are intertwined and interlinked (Box 1.2). Various areas of child development, for instance, often depend on each other, with interactions between areas leading to “developmental cascades” from one aspect to another. For example, ample evidence highlights the association between self-regulation in early childhood with children’s learning, and the quality of friendships and social skills developed in middle and late childhood (McClelland and Cameron, 2011[41]; Trentacosta and Shaw, 2009[42]). Aspects of children’s environments too, also often overlap and interact. Children’s lives at home can affect their lives at school and in the community, for example, and vice versa.

As stressed throughout this report, most existing child data are not well suited to capturing the interactions between different aspects of child well-being. Cross-national child data, to the extent that they are available, come from a range of separate and disconnected surveys and datasets, each with their own particular focus. The Health Behaviour in School-Aged Children survey, for example, concentrates primarily on issues around child health, while cross-national education surveys like TIMMS and PIRLS focuses mostly on schooling and learning. While understandable from a survey management perspective, the limited scope of many child surveys makes it difficult to track linkages across areas and examine how outcomes in some dimensions of children’s lives (e.g. physical health) affect well-being in others (e.g. cognitive and social and emotional well-being).

Overcoming these disconnects is not straightforward. In general, there is a need for better, more comprehensive datasets that allow for the assessment of combinations of outcomes at the individual level. One option is to expand the scope of child surveys, though this can requires extensive resources. An alternative is to improve data linking across datasets, including through matching administrative datasets with each other and/or with existing survey data.

Beyond the above-mentioned cross-cutting considerations, the report highlights priorities for collecting better data in each specific area of child well-being.

With respect to children’s material well-being, the conclusions from Chapter 3 highlight the importance of collecting “child-centred” information on material well-being, including on child income poverty and persistent income poverty, on children’s access to basic necessities, and on housing quality and stability. Further steps could be taken to harmonise the information collected, especially on access to adequate food and nutrition, on resources for education and leisure, and on newer deprivation issues gaining increasing attention, such as girls’ inability to afford sanitary products. The chapter also identifies important data gaps, including that:

  • Cross-national data on children with complex and/or precarious living arrangements is severely lacking. There is a general lack of detailed information on children’s living arrangements in mainstream surveys, making it difficult to properly establish the material living conditions of children living between two homes, for example, after parental separation or following family reconstitution.

  • The measurement of families’ financial resilience needs to be improved. The COVID-19 crisis (and, before it, the financial crisis of 2008) highlighted the need to better understand the capacity of families to cope with sudden income shocks, particularly to better gauge the immediate policy response needed. While existing cross-national data provides information on family income levels, there is far less information available on family wealth, assets, and the ability of families to withstand income shocks.

  • As with other areas of child well-being, there is a strong need to better connect data on the many aspects of children’s economic and material well-being both with each other, and with other areas of well-being. This is crucial for better identifying the drivers of child material deprivation, as well as to measure the extent to which children’s economic and material situations is linked to inequalities in other outcomes areas. More connected data requires better data linking and/or new and better survey sources.

Chapter 4 stresses the need for a full and better understanding of the key dimensions of children's physical health and the risks that children face from conception onwards. It also emphasises the need for better data on protective and health-enhancing factors and the resources families can use to improve child health resilience, prevent health problems, and foster children’s physical development. It identifies several areas where data can be improved, including the need for better data to:

  • Capture social gradients affecting child health and better track the formation of health inequalities from the early years, including in the first 1 000 days of life.

  • Cover children exposed to high physical health risks, such as child victims of maltreatment.

  • Improve information on child health checks and health care service coverage and spending at different stages of childhood.

  • Better track the implementation and outcomes of recommendations on child health.

  • Track children’s exposure to the environmental risks such as unsafe air, contaminated water and food.

  • Provide information on children’s and parents’ knowledge of health issues, the main challenges for current and future health well-being, how they can improve their physical health, and the support they can receive if needs be.

  • Develop cross-cutting data to monitor how children’s physical health affects other aspects of their well-being, such as cognitive and socio-emotional well-being.

Chapter 5 emphasises that all stages of childhood shape children's social-emotional development, in their own important way, and that children’s social and emotional outcomes at all ages strongly depend on their social and physical environment. The chapter also identifies a set of priorities for improving data on children’s social and emotional well-being, including the need to:

  • Bridge the data gap that currently exists on socio and emotional well-being during early- and middle-childhood.

  • Develop data on children's perceptions and confidence in their personal, gender, social and cultural identities, their participation in group activities, their trust in institutions, and their knowledge of global and societal issues.

  • Develop data on the dimensions of children’s social and physical environment that really matter to children. This means asking children which issues are important to them. It also means focusing on children’s perceptions with regards to whether they feel listened to or not, and if they feel supported in their different life domains. While sources such as the Children’s World’s surveys provide valuable cross-national information on some of these areas for children in middle-childhood, there is no equivalent international data available for adolescents.

  • Develop data and evidence on new or emerging risks to children’s social and emotional well-being, such as the potential risks carried by the use of prescription pharmaceuticals (e.g. painkillers, tranquillisers, sedatives) for recreational purposes.

  • Produce data to better inform on the potential linkages between children’s socio-emotional well-being and their outcomes in other well-being areas, including their mental and physical health and education outcomes.

In contrast to many other areas of child well-being, Chapter 6 highlights a relatively wide range of cross-national data on cognitive development and educational outcomes for school-aged children and adolescents. The growth of international student assessment programmes such as TIMMS, PIRLS, and PISA has helped produce a large body of information on school performance at different ages, especially in the traditional core areas of reading, mathematics and science. Over the years, these same programmes have also begun to provide information on children's perceptions of the school environment, their attitudes towards school work, their relationships with teachers and peers, and their perceptions of support from parents. However, this expansion has also led to changes in questionnaires, which can sometimes come at the cost of breaks in series and inconsistencies across years. The chapter also points to data gaps that could be filled to improve the understanding of where to prioritise actions, including the development of data on:

  • Children’s cognitive outcomes in early childhood (i.e. globally before entering in compulsory school) are lacking, despite efforts to harmonise data collection in a few countries. Tracking early learning outcomes is crucial for identifying the key competences children develop from infancy and which are a prerequisite for effective learning throughout childhood.

  • Children’s learning and cognitive development in areas outside reading, mathematics and science. This includes children’s transversal cognitive skills (e.g. problem solving, creative thinking, critical thinking), their self-regulated learning and “learning to learn” skills (e.g. motivation, planning, self-monitoring, self-reflection), and their digital skills (e.g. data and digital literacy). There is increasing recognition that these kinds of competences are or will be crucial for children growing up in today’s world.

  • Skill acquisition and learning achievements of highly vulnerable groups of children such as victims of maltreatment, children with disabilities, in alternative care, or homeless children who are covered in general children’s surveys. Data on learning achievements and needs of these groups of children are crucial to ensure they are not left behind.

  • Children’s educational motivations, aspirations and perceptions of their school environment and of parental support, as well as their knowledge (and parents’ knowledge) of education systems, which are key determinants of education tracks and career choices. While PISA is increasingly providing cross-national data in these areas for 15-year-olds, less information is available for children in middle childhood and early adolescence.

The overarching message from this report is that, while much progress has been made on cross-national child data, there are still many important gaps and areas where knowledge is sporadic at best. Strong efforts are still needed to further improve child data at both national and cross-national levels. Doing so is crucial if policy-makers are to receive a better picture and understanding of children’s lives and the evidence needed to make fully informed decisions on child policies.

The “aspirational” framework for child well-being measurement developed in Chapter 2 of this report is set out in such a way as to help countries recognise the full implications involved in developing sound data on children's well-being. Together with the key elements and mechanisms of well-being highlighted through subsequent chapters, this framework can be used to help guide better data collection, motivate improvements in child data at all levels, and can serve as a “roadmap” for these efforts. It is not yet, however, a full-fledged model of child well-being, and much work remains to be done to identify precisely which dimensions should be prioritised when countries are building national data and indicator sets. Countries without good data infrastructure at population level could also use the shared understanding of child well-being set out in this report to guide data collection when constructing evaluation frameworks for child intervention programmes.

In general, there are relatively few simple solutions to filing the child data gaps highlighted through this report. In some cases, gaps can be eased by extending existing surveys or data collection instruments through, for instance, the addition of new or alternative survey questions. One example is the current lack of information on children’s knowledge of health issues, which could be tackled by adding new questions to existing child health surveys. In other instances, data relevance and usefulness could be improved by increasing the regularity or timeliness of collection, or by ensuring consistency in questionnaire and variable definitions across waves, which is crucial for policy monitoring. A core set of data and indicators should be defined, against which countries can commit to update at regular intervals. However, many data gaps have their roots in the fundamental scope, coverage, and design of existing child data collections. The limitations of many child and/or household surveys are one of the primary reasons for the scarcity of data on the well-being of young children, for example, and on the lack of data on children in the most vulnerable positions. Tackling gaps like these will often require new (and sometimes novel) or radically revised data collections.

The good news is that there are a growing number of innovative data production methods available to countries and others looking to improve child data infrastructures. One example is data linking and techniques for combining data from multiple sources – including administrative- and register-based data, as well as survey data – which have the potential to widen the breadth and depth of child data. Others include techniques for collecting data on the well-being of young children, such as those used in the OECD’s International Early Learning and Child Well-being Study, and for collecting data that capture and reflect children’s views, like those used in the Children’s Worlds survey.

Fundamentally, however, further improving cross-national child data infrastructures will require significant investment as well co-ordinated action from governments, international organisations, and the wider international statistical and policy communities. The synchronisation of efforts is key. Collecting comparable data requires either widespread support for international data collections, or a strong degree of co-operation to promote and harmonisation of national surveys and datasets. Countries and the wider community can also assist one another through knowledge sharing and the exchange of good and innovative child data collection practices.

This is a sizeable task that cannot be fully realised overnight. It will require a medium- to long-term commitment on the part of countries and the community. As there are likely to be limits on available resources, the development of new and better child data will be gradual. Priorities and preferences will have to be set. In this respect, the areas and gaps highlighted in the previous section can be seen as a working guide, to be developed further in line with countries’ and the community’s own priorities. For example, among the possible priorities, this report stresses a strong need for better statistics on vulnerable children and better data on child outcomes in early childhood. The evidence discussed throughout this report can help with the identification of key areas in which better data is needed to inform policies for young children and children in vulnerable situations. Better cross-national data on children's family living arrangements and material living conditions is another priority, and one that could potentially be tackled by adapting and extending existing household living conditions surveys to better reflect children's lives and experiences in a comparable way. The OECD stands ready to help countries in this work.


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← 1. The framework focuses on child-relevant public policies in five core areas: family policies; housing policies; health policies; education policies; and environmental policies. These are policies areas that have strong, and clear, and specific links with children’s outcomes. Many policies outside these areas also have the potential to impact children’s well-being, but the linkages are typically less direct. Examples of the latter include general income support policies and general labour market and macro-economic policies.

← 2. Vulnerable children are broadly the groups of children most at risk of experiencing low well-being and worthy of the greatest investment (OECD, 2019[4]). Child vulnerability is the outcome of the interaction of a range of individual and environmental factors that compound dynamically over time. Individual factors contributing to child vulnerability stem from cognitive, emotional and physical capabilities or personal circumstances, for instance age, disability, a child’s own disposition or mental health difficulties. Environmental factors contributing to child vulnerability operate at both family and community levels. Family factors include income poverty and material deprivation, parents’ health and health behaviours, parents’ education level, family stress and exposure to intimate partner violence. Types and degrees of child vulnerability vary as these factors change and evolve with children’s age.

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