Supporting Remote Survey Data Analysis by Co-researchers with Learning Disabilities through Inclusive and Creative Practices and Data Science Approaches.

Through a process of robust co-design, we created a bespoke accessible survey platform to explore the role of co-researchers with learning disabilities (LDs) in research design and analysis. A team of co-researchers used this system to create an online survey to challenge public understanding of LDs [3]. Here, we describe and evaluate the process of remotely co-analyzing the survey data across 30 meetings in a research team consisting of academics and non-academics with diverse abilities amid new COVID-19 lockdown challenges. Based on survey data with >1,500 responses, we first co-analyzed demographics using graphs and art & design approaches. Next, co-researchers co-analyzed the output of machine learning-based structural topic modelling (STM) applied to open-ended text responses. We derived an efficient five-steps STM co-analysis process for creative, inclusive, and critical engagement of data by co-researchers. Co-researchers observed that by trying to understand and impact public opinion, their own perspectives also changed.

In the physical to digital transition with friends - a story of performing inclusive research together no matter what life throws at you.

BACKGROUND: As part of 'The Hub' project at Wellcome Collection, a team of eight co-researchers with learning disabilities alongside academics created an online survey to challenge public understanding of learning disabilities. Using creative and arts-based methods, co-researchers remotely co-analysed the survey results amid Covid-19 lockdown challenges. Here, we explore our unexpected 'transition' journey from the physical 'Hub' to the digital space. METHODS: We organised 20 sessions at 'The Hub' and used audio/video/photo recordings to 'capture' key moments. With the lockdown, we ensured that every co-researcher had access to and support for digital technologies. Throughout 2020, we organized 28 Zoom meetings involving all co-researchers. In June, Lilly and Sue conducted Zoom interviews with the co-research team to reflect on our 'transition' journey. In this creative video-form submission accompanied by an accessible report, Lilly puts together a story of how we transitioned and felt throughout this process. FINDINGS: We identify that trust and the social bonds established at 'The Hub' are the key components of our transition to the digital environment. There is the tension between longing for in-person contact and trying to make the most out of the situation to maintain these relationships. At the heart of this is the motivation to 'change the world' and the strive for social justice. Having time and opportunity to improve, and co-researchers' steady growth in confidence, are equally important. CONCLUSIONS: The determination for maintaining friendships among co-researchers and the motivation to 'change the world' overcome Covid-19 related challenges in continuing co-research. SUMMARY: [Table: see text].

"We have been magnified for years - Now you are under the microscope!": Co-researchers with Learning Disabilities Created an Online Survey to Challenge Public Understanding of Learning Disabilities.

Public attitudes towards learning disabilities (LDs) are generally reported as positive, inclusive and empathetic. However, these findings do not reflect the lived experiences of people with LDs. To shed light on this disparity, a team of co-researchers with LDs created the first online survey to challenge public understanding of LDs, asking questions in ways that are important to them and represent how they see themselves. Here, we describe and evaluate the process of creating an accessible survey platform and an online survey in a research team consisting of academic and non-academic professionals with and without LDs or autism. Through this inclusive research process, the co-designed survey met the expectations of the co-researchers and was well-received by the initial survey respondents. We reflect on the co-researchers' perspectives following the study completion, and consider the difficulties and advantages we encountered deploying such approaches and their potential implications on future survey data analysis.