A scoping review of the globally available tools for assessing health research partnership outcomes and impacts
Bibliographic record
Abstract
Abstract Background Health research partnership approaches have grown in popularity over the past decade, but the systematic evaluation of their outcomes and impacts has not kept equal pace. Identifying partnership assessment tools and key partnership characteristics is needed to advance partnerships, partnership measurement, and the assessment of their outcomes and impacts through systematic study. Objective To locate and identify globally available tools for assessing the outcomes and impacts of health research partnerships. Methods We searched four electronic databases (Ovid MEDLINE, Embase, CINAHL + , PsychINFO) with an a priori strategy from inception to June 2021, without limits. We screened studies independently and in duplicate, keeping only those involving a health research partnership and the development, use and/or assessment of tools to evaluate partnership outcomes and impacts. Reviewer disagreements were resolved by consensus. Study, tool and partnership characteristics, and emerging research questions, gaps and key recommendations were synthesized using descriptive statistics and thematic analysis. Results We screened 36 027 de-duplicated citations, reviewed 2784 papers in full text, and kept 166 studies and three companion reports. Most studies originated in North America and were published in English after 2015. Most of the 205 tools we identified were questionnaires and surveys targeting researchers, patients and public/community members. While tools were comprehensive and usable, most were designed for single use and lacked validity or reliability evidence. Challenges associated with the interchange and definition of terms (i.e., outcomes, impacts, tool type) were common and may obscure partnership measurement and comparison. Very few of the tools identified in this study overlapped with tools identified by other, similar reviews. Partnership tool development, refinement and evaluation, including tool measurement and optimization, are key areas for future tools-related research. Conclusion This large scoping review identified numerous, single-use tools that require further development and testing to improve their psychometric and scientific qualities. The review also confirmed that the health partnership research domain and its measurement tools are still nascent and actively evolving. Dedicated efforts and resources are required to better understand health research partnerships, partnership optimization and partnership measurement and evaluation using valid, reliable and practical tools that meet partners’ needs.
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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 | 0.138 | 0.403 |
| Meta-epidemiology (narrow) | 0.004 | 0.003 |
| Meta-epidemiology (broad) | 0.012 | 0.011 |
| Bibliometrics | 0.078 | 0.075 |
| Science and technology studies | 0.004 | 0.005 |
| Scholarly communication | 0.013 | 0.015 |
| Open science | 0.007 | 0.009 |
| Research integrity | 0.006 | 0.004 |
| Insufficient payload (model declined to judge) | 0.011 | 0.002 |
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".