Preparing for patient partnership: A scoping review of patient partner engagement and evaluation in research
Bibliographic record
Abstract
BACKGROUND: Realizing patient partnership in research requires a shift from patient participation in ancillary roles to engagement as contributing members of research teams. While engaging patient partners is often discussed, impact is rarely measured. OBJECTIVE: Our primary aim was to conduct a scoping review of the impact of patient partnership on research outcomes. The secondary aim was to describe barriers and facilitators to realizing effective partnerships. SEARCH STRATEGY: A comprehensive bibliographic search was undertaken in EBSCO CINAHL, and Embase, MEDLINE and PsycINFO via Ovid. Reference lists of included articles were hand-searched. INCLUSION CRITERIA: Included studies were: (a) related to health care; (b) involved patients or proxies in the research process; and (c) reported results related to impact/evaluation of patient partnership on research outcomes. DATA EXTRACTION AND SYNTHESIS: Data were extracted from 14 studies meeting inclusion criteria using a narrative synthesis approach. MAIN RESULTS: Patient partners were involved in a range of research activities. Results highlight critical barriers and facilitators for researchers seeking to undertake patient partnerships to be aware of, such as power imbalances between patient partners and researchers, as well as valuing of patient partner roles. DISCUSSION: Addressing power dynamics in patient partner-researcher relationships and mitigating risks to patient partners through inclusive recruitment and training strategies may contribute towards effective engagement. Further guidance is needed to address evaluation strategies for patient partnerships across the continuum of patient partner involvement in research. CONCLUSIONS: Research teams can employ preparation strategies outlined in this review to support patient partnerships in their work.
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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 | 0.180 | 0.365 |
| Meta-epidemiology (narrow) | 0.003 | 0.003 |
| Meta-epidemiology (broad) | 0.008 | 0.010 |
| Bibliometrics | 0.035 | 0.036 |
| Science and technology studies | 0.003 | 0.005 |
| Scholarly communication | 0.012 | 0.012 |
| Open science | 0.005 | 0.008 |
| Research integrity | 0.006 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".