Executive summary
To design, implement and monitor effective child well-being policies, policy-makers need data that capture what is going on in children’s lives, that measure what is important to them, and that can detect emerging problems and vulnerabilities before they take hold.
In recent decades, great strides have been made in measuring child well-being and understanding the richness of children’s lives and experiences. National statistical offices, international organisations and academic researchers alike have engaged in a range of activities aimed at developing better data. 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 advance what we know and understand about children at different points in childhood in a range of areas. At the national level, in many countries, a growing number of country-specific surveys and datasets have greatly expanded the evidence base on child well-being. Yet despite these efforts, most OECD countries do not have good data to base their child well-being policies on, nor strong data infrastructures for policy monitoring.
Measuring What Matters for Child Well-being and Policies aims to push forward the child data agenda to inform the development of better child well-being policies. It lays the groundwork for improvements in child well-being measurement. It outlines a new “aspirational” conceptual framework for child well-being measurement, setting out which aspects of children’s lives should be measured in order to best monitor child well-being. It also outlines priorities for child data development and identifies key data gaps, all with a view of motivating improvements in child data infrastructures.
The conceptual framework has its roots in the understanding that children should be able to both enjoy a “good” childhood in the here and now, and have the opportunity to develop skills and abilities that allow them to prepare for the future. It is “aspirational” is the sense that it is not guided by immediate data availability considerations, but instead by research findings on the key aspects of well-being that matter for children and for supporting their full development.
The framework seeks to overcome a common shortcoming in child well-being measurement: treating the different dimensions of child well-being – material well-being, physical health, social, emotional and cultural well-being, and cognitive development and educational well-being – as if they are separate or independent from one another. Well-being needs to be understood as a whole because its dimensions develop alongside one another.
The framework innovates on child well-being measurement in several ways. First, its multi-level structure helps clarify the importance of children’s environments, relationship, and other potential influences, emphasising that these potential drivers of well-being are distinct from outcomes. Second, it pays greater attention to ways in which the things that children want, need and should be able to do change through childhood. Finally, it looks to reinforce efforts to integrate children’s own thoughts, views and perspectives across layers of child well-being measurement.
As a whole, comparable cross-national data on child well-being is scant and limited in scope. However, comparable data on children’s cognitive development and learnings outcomes, for example, is relatively widely available – especially with respect to the traditional core areas of reading, maths and science – as is information on adolescent health and physical well-being. Children’s social and emotional well-being is less well covered, in part due to the lack of a consistent conceptual and statistical framework. Comparable information on children’s material living standards is also relatively scarce, especially for many OECD countries outside Europe. There is also a general lack of comparable cross-national data on children’s well-being during early childhood.
Even though 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 experiencing maltreatment and children in out-of-home settings – are frequently either not easily identifiable or a missing entirely in the data. As a result, comparable cross-national information on the well-being outcomes of these children is often lacking. Greater efforts are required to better document well-being outcomes of marginalised child populations.
While innovative instruments like the Children’s Worlds survey go a long way towards ensuring children’s perspectives are better reflected, there are still many gaps in the availability of cross-national data that capture children’s thoughts and views about their own lives. For example, there is limited cross-national information available on adolescents’ views on several important areas, including their own material and social and emotional well-being. There also is a lack of data on children and adolescents’ “social capital”, including on perceptions and confidence in their social and cultural identities, their participation in group activities, their trust in institutions, and their knowledge of global and societal issues.
Existing cross-national child data are not well suited to the inter-connected nature of child well-being. Cross-national child data, to the extent that they are available, typically come from a range of separate and disconnected surveys and datasets, each with their own particular focus. While understandable from a survey management perspective, the limited scope of child surveys makes it difficult to track the many linkages across areas of child well-being and examine how outcomes in areas (e.g. physical health) affect well-being in others (e.g. cognitive and socio-emotional well-being).
Further improvement of cross-national child data infrastructure will require significant investment. The key to progress here is the synchronisation of efforts by the many actors in field, from governments and international organisations to the wider international statistical and policy communities. Collecting comparable data requires either widespread support for international data collections, or a strong degree of co-operation to promote the 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.