Incorporation of Patient and Public Involvement in Statistical Methodology Research: Summary of Workshop Proceedings

TL;DR

This paper summarizes a workshop on how to better involve patients and the public in statistical research, highlighting communication strategies and practical steps to overcome barriers.

Contribution

The paper introduces practical strategies and case studies for integrating Patient and Public Involvement in statistical methodology research.

Findings

PPI can improve model structures and identify data issues in statistical research.

Communication tools like plain English and visual storytelling are essential for effective PPI.

Public contributors emphasized the need for respectful and flexible engagement in research projects.

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.