Community-Engaged Research Ethics Training (CERET): developing accessible and relevant research ethics training for community-based participatory research with people with lived and living experience using illicit drugs and harm reduction workers
Bibliographic record
Abstract
BACKGROUND: Community-based participatory research (CBPR) can directly involve non-academic community members in the research process. Existing resources for research ethics training can be inaccessible to team members without an academic background and do not attend to the full spectrum of ethical issues that arise through community-engaged research practices. We detail an approach to capacity building and training in research ethics in the context of CBPR with people who use(d) illicit drugs and harm reduction workers in Vancouver's Downtown Eastside neighborhood. METHODS: A project team comprised of academic and community experts in CBPR, research ethics, and harm reduction met over five months to develop the Community-Engaged Research Ethics Training (CERET). The group distilled key principles and content from federal research ethics guidelines in Canada, and developed case examples to situate the principles in the context of research with people who use(d) illicit drugs and harm reduction workers. In addition to content related to federal ethics guidelines, the study team integrated additional content related to ethical issues that arise through community-based research, and ethical principles for research in the Downtown Eastside. Workshops were evaluated using a pre-post questionnaire with attendees. RESULTS: Over the course of six weeks in January-February 2020, we delivered three in-person workshops for twelve attendees, most of whom were onboarding as peer research assistants with a community-based research project. Workshops were structured around key principles of research ethics: respect for persons, concern for welfare, and justice. The discussion-based format we deployed allowed for the bi-directional exchange of information between facilitators and attendees. Evaluation results suggest the CERET approach was effective, and attendees gained confidence and familiarity with workshop content across learning objectives. CONCLUSIONS: The CERET initiative offers an accessible approach to fulfill institutional requirements while building capacity in research ethics for people who use(d) drugs and harm reduction workers. This approach recognizes community members as partners in ethical decision making throughout the research process and is aligned with values of CBPR. Building capacity around intrinsic and extrinsic dimensions of research ethics can prepare all study team members to attend to ethical issues that arise from CBPR.
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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 | 0.079 | 0.076 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.007 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.003 | 0.015 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.008 | 0.003 |
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".