Incorporating and evaluating citizen engagement in health research: a scoping review protocol
Bibliographic record
Abstract
BACKGROUND: Citizen engagement in research is an emerging practice that involves members of the general public in research processes such as priority setting, planning, decision-making, research conduct, implementation, evaluation, and dissemination. Engaging citizens in research, particularly health research, increases the relevance of study findings, minimizes waste by facilitating stewardship over resources, and builds public trust in the research. While several existing frameworks guide the application of citizen engagement principles to health research, it is unclear how citizen engagement can be utilized to maximize benefits and minimize risks and challenges in health research. To address the gaps in knowledge around citizen engagement in health research, we propose a scoping review to synthesize the state of knowledge on methods to incorporate and evaluate citizen engagement in research. A protocol is presented in this manuscript. METHODS: The methodology for our scoping review is guided by Arksey and O' Malley's framework for scoping reviews, and additional recommendations by Levac and colleagues. We will include peer-reviewed and gray literature that report on citizen engagement in health research (including biomedical, clinical, health systems and services, and social, cultural, environmental and population health) and report method(s) to conduct, measure, or evaluate citizen engagement. We will systematically search electronic databases (MEDLINE, EMBASE, CINAHL, JSTOR, PsycINFO, Scopus, and Science Direct) from inception onwards and search relevant organizations' websites for additional studies, frameworks, and reports on citizen engagement. Title and abstract and full-text citations will be screened independently and in duplicate. Data will be extracted independently and in duplicate, including document characteristics, citizen engagement definitions and goals, and outcomes of citizen engagement (e.g., barriers, facilitators). DISCUSSION: This review will synthesize the definitions, goals, methods, outcomes, and significance of citizen engagement in health research, as well as any potential barriers, facilitators, and challenges outlined in existing literature. The findings will provide an evidence-based foundation for developing new or improved guidance for citizen engagement in health research. Overall, we anticipate that our scoping review will be a preliminary step to meaningful engagement of citizens in research and strengthen the relationship between the scientific community and the public through transparency and collaboration. SYSTEMATIC REVIEW REGISTRATION: Open Science Framework https://osf.io/hzcbr .
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 | 0.451 | 0.450 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.018 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.008 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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".