ArticleStatistics in medicine2025
Incorporation of Patient and Public Involvement in Statistical Methodology Research: Summary of Workshop Proceedings.
Article in Statistics in medicine, 2025. 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.
- How Do We Achieve Impactful Patient and Public Involvement and Engagement in Statistical Methodology Research? A Qualitative Research Protocol.Health expectations : an international journal of public participation in health care and health policy · 2026Article
- Developing Public-Friendly Visualisations to Improve PPIE Glossaries for Statistical Methodology Research.Health expectations : an international journal of public participation in health care and health policy · 2026Article
- Article
- Incorporation of Patient and Public Involvement in Statistical Methodology Research: Summary of Workshop Proceedings.Statistics in medicine · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
18 authors.
Funding
Abstract
Patient and Public Involvement (PPI) is well-established in applied health research but remains under utilised in statistical methodology research due to perceived irrelevance and communication challenges. This paper summarises a one-day workshop held in February 2024 in Leicester, organised by the University of Leicester and the NIHR Statistics Group, aimed at addressing barriers to meaningful PPI in statistical methodology. The workshop brought together statisticians and experienced public contributors to discuss strategies, share case studies, and offer practical guidance on conducting effective PPI. Key barriers identified included: (1) uncertainty about the relevance of PPI in methodology-focused research; (2) public contributors' anxiety over mathematical complexity; and (3) mismatched expectations due to different backgrounds in applied versus methodological research. Case studies showcased how PPI led to improved model structures, identification of data issues, and enhanced study materials. The importance of communication was a recurrent theme, with recommendations including use of plain English, regular updates, and visual storytelling tools. Feedback from attendees indicated increased confidence and motivation to engage in PPI. Public contributors emphasised the need for respectful, non-patronising interactions and flexible roles within projects. Recommendations include managing expectations, enhancing accessibility, co-developing materials, and fostering diversity among contributors. This paper highlights the need for tailored strategies to integrate PPI into statistical methodology, including the development of resources (e.g., glossaries, animations) and further case study collection. Future work will focus on expanding these resources, addressing challenges of equity and inclusion, and supporting PPI in complex methodological areas like simulation and model development.
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.