PROLIFERATE: An adaptable framework to evaluate participatory research products
Bibliographic record
Abstract
Abstract Background: Participatory research (PR) – the practice of involving stakeholders in research processes – is growing in prominence in health research because it can enhance the impact of research and the translation of research-based knowledge. Yet, the literature indicates that the products of PR studies are rarely evaluated empirically to track, demonstrate, and expand their claimed effectiveness and impact. This lack of measurement tools and frameworks can limit the effectiveness of knowledge translation (KT). Methods: We introduce a framework for evaluating the products of PR called PROLIFERATE. We use an inductive combination of formative and summative evaluation methods to pilot test the framework on a Frailty PR communication product (a video) to determine the methods’ functionality. Results: PROLIFERATE demonstrates adeptness for evaluating barriers and enablers of PR product uptake, effectiveness, and impact. It can identify ways to address barriers by assessing knowledge user perspectives on the comprehensibility of the product, emotional resonance, motivation to change, and future accessibility. Conclusions: PROLIFERATE can enable longitudinal and cross-sectional measurement of PR products in implementation and integrated KT efforts. It can evaluate and track the effectiveness and impact of different types of PR products in a situational responsive manner which compares users, platforms, and other factors in a replicable way.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.333 | 0.219 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.009 | 0.021 |
| Science and technology studies | 0.015 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.008 | 0.020 |
| Research integrity | 0.003 | 0.049 |
| Insufficient payload (model declined to judge) | 0.011 | 0.015 |
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; both teacher heads 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".