Administrative information, such as the number of children in care, is typically used by local authorities to understand the needs of children they serve. Other approaches include needs assessments that often have little or no scientific rigor and which focus on the processes within these agencies.

Critiquing the traditional methods for collecting information on children, a team of investigators from the Social Research Unit in England argue that needs assessment are not only scientifically poor- typically using small number of children, focusing on what services they and their families feel are needed - but are also coupled with weak justifications for implementing them, such as to support decisions already made. These weaknesses in assessment are responsible for the gap between collecting information on children’s needs and acting on it – claim the investigators.

In two articles in latest issue of Child Indicators Research, Nick Axford, Tim Hobbs and David Jodrell show how they supported a local authority to collect better quality data and make better use of what has been collected through using measures, scales and data collection techniques typically used by social scientists, not by agency staff.

Applying the scientific method to children's services means, the authors point out that, “a balance will need to be struck between scientific rigor, entailing significant expense and time, and practical utility- relating to the functions of the data”.

So, at the early stages of the project, the practicality required by children's service agencies was considered. The instrument needed to be not only scientifically robust but also easy and quick to complete and provide information that is accessible to staff in order to develop better services for children.

However, development of a new scientific instrument based on these specifications was not feasible. Therefore, the research team selected the most appropriate pre-existing measures. Scales were selected if they were proven to measure what they claimed to be assessing and did so consistently. They also needed to be brief and to present outcomes in a simple format, providing data that could be compared with other locations in the UK or elsewhere.

What the scales measured was also of importance: they were selected to cover all five of the main well-being outcomes and many other sub-outcomes in the UK’s Every Child Matters framework, along with known influences on these. This ensured consistency with government legislation. The combination of scales formed two instruments, one for parents to report on the well-being of children 0-6 years, and a child self-report instrument for those aged seven to 18 years.

After the instruments were developed the research team started recruiting children and parents to complete the questionnaires. The main challenge was getting the maximum numbers to participate, while ensuring that the sample was a representative cross-section of children and families within the local authority.

Ensuring that samples reflect the wider population while keeping the project manageable for children’s services staff reflects a compromise between scientific rigor and practicality. “Random sampling methods would have resulted in us having the most confidence in the data, however at the time the funding for this was simply not available” the research team stated. Therefore, for the child self-report survey the research team constructed a random sample of schools to represent the local authority. This also ensured that recruiting children was straightforward.

To close the gap between collecting information about children's needs and acting on it, the authors outline techniques to enable providers to make effective use of this high quality information. They looked at the presentation and distribution of data, such as presenting the findings in different formats for different users, and also relied on service development methods or operating systems (see “Can the meanest streets hide communities that care?”) to produce a uniformly agreed, coherent strategy based on this data.

The authors also show the type of high quality data that can be generated and claim this was completed at reasonable cost, accounting for less than 0.01 per cent of the children's services budget for the local authority.

Balancing rigor against practicality meant that “it is possible to measure child well-being robustly and efficiently for service purposes”. While this costs money, the benefit of a scientific approach to assessment should be weighed against traditional needs analyses “that arguably say far less about far fewer children and with far shaker confidence”, concludes the research team.

Reference:

Axford, N. & Hobbs, T, (2011) Getting the Measure of Child Health and Development Outcomes (1): A Method for Use in Children’s Service Settings, Child Indicators Research, 4(1), 59- 80.

Hobbs, T,. Axford, N. & Jodrell, D. (2011) Getting the Measure of Child Health and Development Outcomes (2): The Picture for a Local Authority in England, Child Indicators Research, 4(1), 81-100.

See Also:
Can the meanest streets hide communities that care?