What actually happens in partnered health research? A concordance analysis of agreement on partnership practices in funded Canadian projects between academic and knowledge user investigators
Bibliographic record
Abstract
BACKGROUND: Collaborations involving partnerships between academic researchers and knowledge users can improve the relevance and potential adoption of evidence in health care practices and decision-making. However, descriptions of partnering practice characteristics are often limited to self-report from the lead academic researcher, with no comparison among team members. The primary objective of this study was to determine the extent to which nominated principal investigator (NPI) respondents of a questionnaire about funded Canadian partnered health research projects agreed with other team researchers and knowledge users (KU) on partnership practices. METHODS: We conducted secondary analysis of a subset of data from 106 respondents from 53 partnered Canadian health research projects funded between 2011 and 2019. We organized projects into NPI-researcher and NPI-KU dyads, and analyzed 23 binary variables about types of knowledge users involved and approaches for involving knowledge users in the project. We calculated Kappa scores and examined if agreement varied by dyad type and time across three blocks of years of project funding using a two-way ANOVA. We also explored how agreement varied by question type (independent t-test) and by variable (Pearson Chi-Square). RESULTS: Overall agreement on partnership practices was minimal (mean Kappa = 0.38, SD 0.27). NPI- researcher dyads had higher Kappa scores than NPI-KU dyads (p = 0.03). There were no significant differences across funding year blocks (p > 0.05). Agreement on the types of knowledge users engaged in the project was weak (mean Kappa = 0.43, SD 0.32), and there was no difference by dyad type. Agreement was minimal on the approaches for involving knowledge users the project (mean Kappa = 0.28, SD 0.31), and NPI-researcher dyads had significantly higher Kappa scores than NPI-KU dyads (p = 0.03). Variable-level agreement ranged between 47 and 98%. CONCLUSIONS: The overall low level of agreement among team members responding about the same project has implications for the continued study and practice of partnered health research. These findings highlight the caution that must be used in interpreting retrospectively assessed self-report practices. Moving forward, prospective documentation of partnered research practices offers the greatest potential to overcome the limitations of recall-based retrospective analyses.
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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 | 0.241 | 0.421 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.008 | 0.012 |
| Science and technology studies | 0.007 | 0.007 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.003 | 0.013 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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; the direct Gemma label and the distilled Codex classifier 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".