Project Title: Learning through Everyday Activities with Parents

Community-based parent-delivered early detection and intervention program for infants at high risk of cerebral palsy in a low-resource country: A randomised controlled trial

Chief investigators

Dr Katherine Benfer, Professor Roslyn Boyd, Professor Iona Novak, Dr Nalia Z Khan, Dr Catherine Morgan, Dr Koa Whittingham.


Funding source: Endeavour Queen Elizabeth II Diamond Jubilee Scholarship

Start/ End Date: October 2016-September 2018

About the Study

One in seven people globally have a disability, with 80% of the global burden of cerebral palsy in low income countries. Children with cerebral palsy (CP) in low income countries regularly wait years to begin treatment, missing out on critical opportunities during the period when brain development is greatest. Early interventions with promising effects are available. We need to get them to the right children at the right time. We are aiming to recruit 142 babies at risk of cerebral palsy living in the Indian Sub-Continent to receive a parent-to-parent multi-domain best practice treatment in the home. The intervention targets interaction, movement, nutrition, cognition, and parent coping and wellbeing. Babies will be detected using smart-phone technology (General Movements app), which is able to predict CP with high accuracy from as young as 12 weeks. Parents know their babies best, live in the local community, & can provide effective peer support to other mothers. This makes them powerful change agents to deliver the therapy, particularly in low-income countries. This project is anticipated to result in innovative, accessible and feasible means to detect infants at risk of CP in low income countries and an intervention that can be delivered at scale in similar settings. Improvements to child development and health, and caregiver mental health will have lasting impact on child and family social inclusion, education and workforce productivity.

Summary of Results

This study is commencing in 2016, with data analysed in 2018.


Dr Kath Benfer: