Empowering schools to identify fundamental movement skill difficulties: reducing inequalities and improving outcomes for children

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The acquisition of motor skills is an essential component of childhood development. A child's ability to use sensory information to guide their movements enables learning about the world around them. One particular group of motor skills which is known to be a risk factor for education and wellbeing outcomes is fundamental movement skills (FMS). Born in Bradford (BiB) have demonstrated that a disproportionately high proportion of children within deprived and ethnic minority communities have FMS problems, yet are less likely to access help for such difficulties. My PhD developed a school-based universal screening tool for FMS (FUNMOVES) to reduce inequalities and expedite the identification of neurodiverse children that would benefit from additional educational support. This fellowship would enable me to extend the reach of FUNMOVES, increasing the likelihood of happy and healthy lifespans for children. This fellowship would also have a significant impact on my professional development. The work within this fellowship will fall within four broad categories:(i) Conducting further research. Data will be collected from children in Years 1-6 across 10 Primary schools in Bradford (n = ~3600). These data will be used to begin understanding what scores on FUNMOVES constitute 'normal development', so that a cut-off value can be applied to identify children with additional needs. During my PhD, children were compared against other children in their year at their school. By gathering data from Primary schools across the district, difficulties identified will be a more accurate representation of the general population. The data collected on these ~3600 children will also be fed into the Connected Bradford dataset, whereby the educational and healthcare records have been linked for all children living in the area. By integrating FUNMOVES information within this dataset, it will enable a large-scale evaluation of the role that childhood motor skills play in inequalities in education and wellbeing.(ii) Sharing my findings. I would host a co-production event to present FUNMOVES to school staff, policy makers (e.g. the Department for Education) and relevant stakeholders. During which I would ask about lived experiences to shape how FUNMOVES can be feasibly scaled up in real-world settings. I would present my findings from the co-production event, and the further research planned at large international conferences which bring together academics from a range of disciplines including Psychology and Education. I would also write these two pieces of work up for (i) publication in leading academic journals and (ii) briefing letters for the Department for Education.(iii) Enhance my research skills and collaborative networks. In order to analyse the data from the additional research outlined above, I would need to gain advanced quantitative analysis skills as a social science researcher. Drawing upon expertise within Computer Sciences at the University of Bradford I would attend courses to improve my data analytic abilities. I would also undertake a study visit at Stanford University within their Population Health Sciences department to improve my ability to work with large-scale datasets and learn about the latest techniques in the field. I would also attend grant writing courses, to increase the likelihood of further funding applications being successful.(iv) Develop funding applications. During the fellowship, I would apply for two further funding schemes. The first will support national roll-out of FUNMOVES, to further increase the accuracy of cut-points for 'needing additional support', and to enable children from across the UK to benefit from expedited assessment and intervention. The second will co-develop with teachers, policy makers and relevant stakeholders, a training programme for school staff which will enable them to tailor Physical Education in response to FUNMOVES data, so that their pupils can receive targeted support.