Co‐production in the PREVENT Next Generation Study: methodology and outcomes
Bibliographic record
Abstract
Abstract Background Involving patients and the public as stakeholders (hereafter described as contributors) in the design and management of research studies is increasingly recognised as central to conducting ethical, meaningful and translatable research. Consulting and co‐producing are two methods for involving public contributors in the research cycle. This abstract describes the methodology used to establish a co‐production model for the PREVENT Next Generation (NextGen) research program, alongside initial impact the contributors have had on the program. The NextGen research programs aims to explore brain health in young adults (aged 18‐39), and all contributors represent this age group. Method Adverts appealing for public contributors were sent to voluntary and community sector enterprises, universities, promoted on social media and spread via word of mouth. The first round of recruitment focused on contributors living in North America and Europe, with recruitment underway in Ghana. Contributors watched an introductory video, completed a form to indicate interest and were sent an invite to a virtual meeting. The aim of the initial work was to consider and feedback on the NextGen proposal, beginning the co‐production by identifying topics of interest for inclusion in planned work. Result Public contributors joined the initial meetings and were supportive of the need to understand more about brain health in young adults. Public contributors were interested in exploring topics such as the role of sex differences, social relationships and air pollution on brain health. Considering the focus groups (Phase 1 of NextGen), contributors advised having a choice of times that would support adults in work or education to join, as well as expressing a preference for virtual engagement for such studies. Conclusion Employing a public involvement and co‐production model from the initial design stage of the NextGen study has proven invaluable to identifying topics of importance to include in future studies involving this age group. Future work will continue to develop the NextGen research program work with public contributors. Expansion of the public contributors to represent different global regions is underway, and will be critical to designing an inclusive study that is meaningful to the populations from which participants are enrolled.
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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 | 0.195 | 0.232 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.005 | 0.005 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.003 | 0.009 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.017 | 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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".