Patient, researcher, and organizational representatives’ experiences conducting or supporting patient-initiated research
Bibliographic record
Abstract
The British Columbia Support for People and Patient-Oriented Research and Trials (BC SUPPORT) Unit is a provincial initiative funded by the Canadian Institutes of Health Research within their Strategy for Patient-Oriented Research that aims to improve the health research landscape in Canada. The BC SUPPORT Unit has had a mandate to partner with patients and community members in its internal operations and support patient-oriented research in BC. As part of this, the Unit explored how it might better support patient-initiated research, a subset of patient-oriented research which empowers patients to assume leadership roles throughout the research process. The Unit launched a quality improvement project to explore the experiences of people who have conducted or supported patient-initiated research to inform how it could better support patient-initiated research arising within the Unit. In this report we provide an overview of a thematic analysis of experiences of various interest-holders involved in patient-initiated research. We identified factors specific to supporting patient-initiated research that the Unit should consider when helping connect patient partners with researchers to ensure successful team building. We conclude that patients who initiate research might require support in developing their research questions, conducting literature reviews, and connecting with research teams. This information can inform the Unit’s approach to supporting patient-initiated research.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.055 | 0.100 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.017 | 0.014 |
| Scholarly communication | 0.010 | 0.005 |
| Open science | 0.003 | 0.014 |
| Research integrity | 0.004 | 0.007 |
| Insufficient payload (model declined to judge) | 0.003 | 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".