ArticleHealth expectations : an international journal of public participation in health care and health policy2026
Developing Public-Friendly Visualisations to Improve PPIE Glossaries for Statistical Methodology Research.
Article in Health expectations : an international journal of public participation in health care and health policy, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
11 authors.
Funding
Abstract
backgroundPlain-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.
methodsWe 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.
resultsVisualisations 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.
conclusionsResources 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/. PATIENT OR PUBLIC CONTRIBUTION: Two 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.
Indexed as
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.