Cobuilding patient and public capacity in knowledge synthesis: designed and delivered by patient and public partners for patient and public partners
Bibliographic record
Abstract
OBJECTIVES: To describe the Strategy for Patient-Oriented Research Evidence Alliance's cocreation and evaluation of two capacity building courses on knowledge synthesis for patient and public partners. STUDY DESIGN AND SETTING: Two 3-week courses were collaboratively designed by, with, and for patient and public partners on engagement in knowledge synthesis. The first course, offered virtually in 2021, focused on patient and public engagement in systematic reviews and rapid reviews. The second course was offered virtually in 2022 with an expanded scope covering the most common type of knowledge synthesis (eg, systematic reviews with or without meta-analysis, scoping reviews, overview of reviews) under systematic, rapid, and living review contexts. RESULTS: A total of 46 patient and public learners were trained across the two courses. Learners represented 11 provinces and territories in Canada, with two-third of learners residing in Ontario across both years (2021: 39%; 2022: 35%). Weekly formative evaluations and a summative evaluation were conducted for both courses. The evaluations revealed that the majority of respondents agreed (2021: 91%; 2022: 88%) that they achieved their learning goals and that their overall learning experience was valuable (2021: 95%; 2022: 89%). CONCLUSION: The capacity-building courses in 2021 and 2022 successfully engaged 46 patient and public partners across Canada. As a result, these partners are now well-prepared to participate in knowledge synthesis activities. The positive experiences from respondents indicated successful and satisfactory experiences and that similar capacity building opportunities should be offered to continue to address research capacity gaps. PLAIN LANGUAGE SUMMARY: In 2021 and 2022, the Strategy for Patient-Oriented Research Evidence Alliance adopted a cocreation approach to deliver two courses on patient and public engagement in knowledge synthesis for patient and public partners. These courses aimed to build confidence and provide foundational knowledge for patient and public partner engagement in knowledge synthesis. A total of 46 learners were trained across the two courses. Formal evaluations revealed that the courses were effective in meeting their learning goals. Feedback suggests a continued need and opportunity to offer similar courses designed by, with, and for patient and public partners.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.155 | 0.184 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.005 | 0.024 |
| Research integrity | 0.005 | 0.006 |
| Insufficient payload (model declined to judge) | 0.025 | 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".