Patient engagement in a national research network: barriers, facilitators, and impacts
Bibliographic record
Abstract
Abstract Background Little is known about patient engagement in the context of large teams or networks. Quantitative data from a larger sample of CHILD-BRIGHT Network members suggest that patient engagement was beneficial and meaningful. To extend our understanding of the barriers, facilitators, and impacts identified by patient-partners and researchers, we conducted this qualitative study. Methods Participants completed semi-structured interviews and were recruited from the CHILD-BRIGHT Research Network. A patient-oriented research (POR) approach informed by the SPOR Framework guided the study. The Guidance for Reporting Involvement of Patients and the Public (GRIPP2-SF) was used to report on involvement of patient-partners. The data were analyzed using a qualitative, content analysis approach. Results Twenty-five CHILD-BRIGHT Network members (48% patient-partners, 52% researchers) were interviewed on their engagement experiences in the Network’s research projects and in network-wide activities. At the research project level, patient-partners and researchers reported similar barriers and facilitators to engagement. Barriers included communication challenges, factors specific to patient-partners, difficulty maintaining engagement over time, and difficulty achieving genuine collaboration. Facilitators included communication (e.g., open communication), factors specific to patient-partners (e.g., motivation), and factors such as respect and trust. At the Network level, patient-partners and researchers indicated that time constraints and asking too much of patient-partners were barriers to engagement. Both patient-partners and researchers indicated that communication (e.g., regular contacts) facilitated their engagement in the Network. Patient-partners also reported that researchers’ characteristics (e.g., openness to feedback) and having a role within the Network facilitated their engagement. Researchers related that providing a variety of activities and establishing meaningful collaborations served as facilitators. In terms of impacts, study participants indicated that POR allowed for: (1) projects to be better aligned with patient-partners’ priorities, (2) collaboration among researchers, patient-partners and families, (3) knowledge translation informed by patient-partner input, and (4) learning opportunities. Conclusion Our findings provide evidence of the positive impacts of patient engagement and highlight factors that are important to consider in supporting engagement in large research teams or networks. Based on these findings and in collaboration with patient-partners, we have identified strategies for enhancing authentic engagement of patient-partners in these contexts.
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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 | 0.063 | 0.093 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.005 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.002 | 0.013 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 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".