Reading regularly with young children is an important feature of a positive home learning environment. However, research from the Institute for Fiscal Studies has found that children were less likely to be read to on a daily basis if their mother has lower educational qualifications and if their family has a lower income. The same research also found some differences according to ethnicity; specifically, children were less likely to be read to daily if they were from Black, Pakistani or Bangladeshi backgrounds. 

Unlike face-to-face services, digital reading tools are highly flexible and can be accessed at the time and location most convenient for the caregiver. Many local areas offer services aimed at helping to overcome barriers to parents reading with their babies and young children. However, some caregivers may struggle or prefer not to access these services, such as libraries, storytime and stay-and-play activities. Digital products and services are a promising (and currently underutilised) route to accessing high-quality support that could empower and assist caregivers in improving reading with their child at home. 

We worked with Early Ideas Limited using their app TANDEM, a story creation app powered by generative AI, alongside parents and caregivers, early-years practitioners and private, public and third-sector organisations. TANDEM's goal is to give all children an equitable start in life by enabling every child to experience the early interactions and strong relationships that will set them up for life. The app is designed to assist parents in creating an engaging reading experience with their child in their home.

As an innovation partner, we used the TANDEM app as a probe to understand what would be needed to create a high-quality, scalable and low-cost shared reading experience. Our working hypothesis was that this needed to be a stimulating, fun and tailored experience for low-income families with children under five to use at home and accessible for parents and caregivers across the UK. 

This is the first of a series of updates detailing how we promoted shared reading experiences for families and explores our process for designing for the right audience.

From the outset, we wanted to design with and for the right audience to give us the best chance at unpacking whether the TANDEM app could assist parents from low-income families in increasing reading frequency at home. We created priority parent and caregiver profiles built on insights from previous fairer start mission projects, such as Baby Talk for York and attendance levels in early childhood education and care,  in addition to data taken from external reports such as the IFS Deaton Review of early childhood inequalities. These inputs shaped the parent and caregiver profiles for this project, so we refer to them as ‘our priority families’ or our ‘priority family profiles.’

Using these priority family profiles, we worked closely with our data science team and used Local Insight, a web-based platform that brings together and aggregates data from multiple sources at a small area level to identify locations that may have a high prevalence of our priority families. We intentionally limited our search to London and its boroughs so that we could regularly visit and work with our priority families within the limited timeframe of the project.

We began by inputting key parameters from our priority family profiles into the Local Insights platform. These inputs included criteria related to lower family outcomes, such as whether households were receiving unemployment benefits (Jobseekers Allowance and out-of-work Universal Credit) and whether households were claiming Universal Credit child entitlement. Focusing on the London boroughs, the platform highlighted areas we should recruit from to give us the best chance of learning from and designing with the ‘right’ people. We then looked at Early Years Foundation Stage Profile data from the Department of Education from 2021-2022 to identify the proportion of children eligible for free school meals who had a Good Level of Development at ages 4-5 in each area. These combined datasets informed our shortlist of locations, in no particular order: Barking and Dagenham, Croydon, Enfield, Hounslow, and Newham. After discussing with key internal and external stakeholders, we decided to focus on the London boroughs of Enfield and Hounslow.

Edmonton Green (in Enfield) and Feltham (in Hounslow) were two communities within these boroughs that ‘lit up’ and showed strong alignment with the priority parents we wanted to work with (see Figures 2 and 3). Therefore, these two areas emerged as two focal points for our recruitment efforts. We adopted a dual approach to recruiting priority families, working with QaResearch and engaging directly with the community through cultural immersion that involved getting ‘feet on the ground’ to begin building our relationships with local community contacts. The cultural immersion approach brought added benefits of building stronger relationships with people and place which helped us better understand the environment we would be working in. Building relationships with key contacts meant we could access their trusted communities of families rather than starting from scratch. 

The local community contacts were identified through our on-the-ground effort and desk research had strong connections to parents and caregivers. They included Enfield's Children's Centre, Bounces Road Pantry food bank, Edmonton Green Library, The Salvation Army, Arista Cats, Ladybug Preschool, Community House, The Ark, Mencap, Feltham Library, Alf King Family Hub West, and The Reach Foundation. Pictures of these locations can be seen below in Figure 4.

We conducted visits across several days to meet the local contacts, who then helped distribute the recruitment flyers in the area. We also established a digital presence for community groups by posting in local Facebook groups and collaborating with libraries and local organisations to share posts on their social media channels. 

Despite this multi-pronged effort, recruitment was considerably slower and harder than expected.

In the next update, we will share how we conducted the research and summarise what we learned from our conversations with priority families.