Developing Public‐Friendly Visualisations to Improve PPIE Glossaries for Statistical Methodology Research
Published online on May 14, 2026
Abstract
["Health Expectations, Volume 29, Issue 3, June 2026. ", "\nABSTRACT\n\nBackground\nPlain‐language definitions help patients and the public engage in research, but some technical terms are easier to understand with visual aids. Furthermore, many people find visual aids more intuitive when learning new concepts. The PPI‐SMART group at the University of Leicester recently created a plain‐language glossary for statistical methodology research terms. This project aimed to develop visualisations for selected glossary terms to support Patient and Public Involvement and Engagement (PPIE) in statistical methodology research, where such resources are scarce.\n\n\nMethods\nWe selected 10 glossary definitions to develop visualisations. The working group sketched initial ideas, which a graphic designer developed into drafts. After refinement, the visualisations underwent two cycles of feedback from public contributors. Suggestions were incorporated through the cycles until a final set of visualisations was created.\n\n\nResults\nVisualisations were created for the terms: Bayesian, calibration, causal inference, censoring, deviance, discrimination, regression, Markov Chain Monte Carlo (MCMC), prognostic model, and simulation study. Feedback highlighted issues such as alternative interpretations of language, layout simplicity, accessibility needs and symbol interpretation. These insights shaped the final designs.\n\n\nConclusions\nResources to support PPIE in statistical methodology research are limited but needed. We developed 10 visualisations to help PPIE members understand complex terminology. These are freely available on the NIHR Leicester Biomedical Research Centre website: https://leicesterbrc.nihr.ac.uk/ppismart/ppismart-definitions/.\n\n\nPatient or Public Contribution\nTwo groups of public contributors reviewed the visualisations. Their feedback, received during online meetings and via email, ensured the visuals met the aim of making statistical terms easier to understand.\n"]