Guide to enable health charities to increase recruitment to clinical trials on dementia
Bibliographic record
Abstract
INTRODUCTION: The Alzheimer Society embarked on a project to improve ways that the 60 provincial and local Societies in Canada can work with local researchers to support recruitment of volunteers to clinical trials and studies. A Guide to assist these offices was produced to design ethical recruitment of research volunteers within their client populations. METHODS: Consultations with individuals from provincial and local Societies, as well as researchers and leaders from health-related organizations, were conducted to identify in what ways these organizations are involved in study volunteer recruitment, what is and is not working, and what would be helpful to support future efforts. The Guide prototype used scenarios to illustrate study volunteer recruitment practices as they have been or could be applied in Societies. An implementable version of the Guide was produced with input from multiple internal and external reviewers including subject-matter experts and target users from Societies. RESULTS: Society staff reported that benefits of using the Guide were that it served as a catalyst for conversation and reflection and identified the need for a policy. Also, it enabled Society readiness to respond to requests by persons with dementia and their caregivers wishing to participate in research. A majority (94%) of participating Society staff across Canada agreed that they would increase their capacity to support research recruitment. DISCUSSION: Charitable organizations that raise funds for research have a role in promoting the recruitment of persons with dementia and their caregivers into clinical trials and studies. The Guide was produced to facilitate organizational change to both create a positive culture regarding research as well as practical solutions that can help organizations achieve this goal.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Other About the Canadian research system: no · About a Canadian topic: no | Not applicable | low |
| gpt | no category Domain: not available · Genre: Commentary About the Canadian research system: no · About a Canadian topic: no | Other design | low |
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 | 0.037 | 0.110 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.004 | 0.005 |
| Research integrity | 0.008 | 0.004 |
| Insufficient payload (model declined to judge) | 0.045 | 0.038 |
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, unvalidatedLabeled directly by 2 models reading the full record.
The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.
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".