Development and formative evaluation of patient research partner involvement in a multi-disciplinary European translational research project
Bibliographic record
Abstract
Plain English summary Patient and public involvement (PPI) improves the quality of health research and ensures that research is relevant to patients’ needs. Though PPI is increasingly evident in clinical and health services research, there are few examples in the research literature of effective PPI in translational and laboratory-based research. In this paper, we describe the development and evaluation of PPI in a multi-centre European project (EuroTEAM – Towards Early biomarkers in Arthritis Management) that included both translational and laboratory-based and psychosocial research. We found that although most PPI in EuroTEAM was centred around the psychosocial research, there were examples of PPI in the laboratory studies. As the project evolved, researchers became better at accommodating PPI and identifying PPI opportunities. It was generally agreed that PPI had a positive impact on the project overall, particularly on public engagement with the research. We concluded that the inclusion of both psychosocial and laboratory-based research in the same project facilitated PPI across all aspects of the research. In future projects, we would try to specify individual PPI activities in more detail at the project-planning stage, and better accommodate patient partners who are not native speakers of English. Abstract Background Patient and public involvement (PPI) enhances research quality and relevance and is central to contemporary health policy. The value of PPI has been recognised in rheumatology research, though there are limited examples of PPI in basic and translational science. The EU FP7 funded ‘EuroTEAM’ (Towards Early biomarkers in Arthritis Management) project was established to develop biomarker-based approaches to predict the future development of rheumatoid arthritis and incorporated psychosocial research to investigate the perceptions of ‘at risk’ individuals about predictive testing, and to develop informational resources about rheumatoid arthritis (RA) risk. Patient involvement was central to EuroTEAM from the inception of the project. The objective of this paper is to describe the development of PPI in EuroTEAM, formatively assess the impact of PPI from the perspectives of researchers and patient research partners (PRPs), reflect on successes and lessons learned, and formulate recommendations to guide future projects. Methods Two mixed-methods surveys (for PRPs and researchers) and a teleconference were undertaken to assess the impact of PPI on individual work packages and on EuroTEAM overall. Results There was consensus about the positive impact of PPI on the research and on the experiences of those involved. In particular, the positive impact of PPI on the personal development of researchers, and on effective public engagement with EuroTEAM research were highlighted. Researchers described adapting their practice in future projects to facilitate PPI. Spin-off projects and ongoing collaborations between PRPs and researchers reflected the value of PPI to participants. PPI was more frequently integrated in psychosocial research, though examples of PPI in laboratory/translational science were also described. PRPs asked for more opportunities to contribute meaningfully to basic scientific research and for more extensive feedback on their contributions. Conclusions The findings were used to formulate recommendations to guide effective involvement of patients in future similar projects, including identifying specific training requirements for PRPs and researchers, the identification of PRP focused tasks/deliverables at the project planning stage, and supporting access to involvement for all PRPs. Importantly, the distinctive multidisciplinary approach of EuroTEAM, incorporating both basic science and psychosocial research, facilitated patient involvement in the project overall.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.442 | 0.391 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.006 | 0.005 |
| Scholarly communication | 0.012 | 0.007 |
| Open science | 0.006 | 0.030 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.015 | 0.005 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".