ArticleProceedings of the SIGCHI conference on human factors in computing systems. CHI Conference2020
"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.
Article in Proceedings of the SIGCHI conference on human factors in computing systems. CHI Conference, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
4 citing papers in PubMed, 16 citations in OpenAlex.
- Exploring How Children and Young People With Sickle Cell Disease and Their Families Want to be Involved in Research: A Qualitative Study.Health expectations : an international journal of public participation in health care and health policy · 2025Observational
- Lessons Learned from Designing and Evaluating a Robot-assisted Feeding System for Out-of-lab Use.ACM/IEEE International Conference on Human-Robot Interaction : [proceedings]. ACM/IEEE Conference on Human-Robot Interaction · 2025Article
- 'Building bridges': reflections and recommendations for co-producing health research.Research involvement and engagement · 2023Article
- Supporting Remote Survey Data Analysis by Co-researchers with Learning Disabilities through Inclusive and Creative Practices and Data Science Approaches.DIS. Designing Interactive Systems (Conference) · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
25 authors at 1 institution in 1 country.
Funding
Abstract
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.
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Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.