Patient, Family, Caregiver, and Community Engagement in Research: A Sensibility Evaluation of a Novel Infographic and Planning Guide
Bibliographic record
Abstract
Background: Engaging patients, families, caregivers, and the community (PFCCs) throughout the research cycle ensures that research is meaningful for the target population. Although tools have been developed to promote PFCC engagement, many are lengthy, complex, and lack recommended behaviours. This study evaluated the sensibility of an infographic and accompanying planning guide for facilitating engagement of PFCCs in research. Methods: Thirteen rehabilitation researchers reviewed the PFCC engagement tool and planning guide, participated in a semi-structured interview, and completed a 10-item sensibility questionnaire. Interviews were transcribed, imported into NVivo, and analyzed using direct content analysis. Median scores and proportions of responses for each of the 10 items in the questionnaire were calculated. Results: Median scores for all questionnaire items were ≥ 4 on a 7-point Likert Scale. Participants reported the tool was easy to navigate, contained relevant items to promote PFCC engagement, and followed a logical sequence. Suggested modifications of the tool related to formatting, design, and changing the title. Conclusions: The tool was deemed sensible for overt format, purpose and framework, face and content validity, and ease of usage and provides guidance to engage PFCCs across the research cycle. Further studies are recommended to assess the effectiveness of the tool to engage PFCCs in research.
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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 | 0.077 | 0.152 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".