When Patient Engagement and Research Ethics Collide: Lessons from a Dementia Forum
Bibliographic record
Abstract
The importance of patient engagement in research has been gaining recognition since the turn of the 21st century. However, little is known about the perspectives of people with dementia on the process of discovery. To fill this gap and to inform priorities in patient engagement in the context of dementia research, the Clinic for Alzheimer Disease and Related Disorders at the University of British Columbia hosted an interactive session for members of the patient community and of the general public to share their views on various ethical aspects of the research process. Results from the session indicate that several current research ethics policies and norms in dementia research are not in line with participants' preferences. Here we discuss the importance of bridging the gap between researchers and patients and call for reforms in current standards of dementia 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 | 0.352 | 0.387 |
| Meta-epidemiology (narrow) | 0.002 | 0.003 |
| Meta-epidemiology (broad) | 0.003 | 0.004 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.049 | 0.064 |
| Scholarly communication | 0.057 | 0.074 |
| Open science | 0.009 | 0.066 |
| Research integrity | 0.043 | 0.060 |
| Insufficient payload (model declined to judge) | 0.010 | 0.004 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".