Patient Partner Perspectives: The Experience of Participating in a Co-Designed Virtual Reality Project
Bibliographic record
Abstract
Patient partners (PP) are well positioned to make meaningful contributions to healthcare through their lived experiences and personal narratives. However, researchers must ensure that patients are engaged authentically and collaboratively in knowledge generation. As part of a larger project, 4 PP were engaged in the co-design of a virtual reality video aimed at promoting an understanding of patients' lived experience with COVID-19 during the initial phase of the pandemic. This paper reports on findings from follow-up evaluation interviews with PP about their experiences participating in this project. Thematic analysis of interview transcripts resulted in 2 major themes as well as facilitators and barriers to PP engagement. Primary reasons to participate in the project were to contribute and give back to the community and make a difference for patients impacted by COVID-19. Engagement resulted in positive experiences and impacts for PP. Facilitators to engagement included feeling heard, being valued, and treated with respect. Barriers included length of time required to complete the project as well as PP health status.
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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 | 0.013 | 0.032 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.006 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.002 | 0.014 |
| Research integrity | 0.004 | 0.006 |
| 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".