Challenges in the research ethics review of cluster randomized trials: International survey of investigators
Bibliographic record
Abstract
BACKGROUND: Cluster randomized trials (CRTs) complicate the interpretation of standard research ethics guidelines for several reasons. For one, the units of allocation, intervention, and observation often may differ within a single trial. In the absence of tailored and internationally accepted ethics guidelines for CRTs, researchers and research ethics committees have no common standard by which to judge ethically appropriate practices in CRTs. Moreover, lack of familiarity with and consideration of the unique features of the CRT design by research ethics committees may cause difficulties in the research ethics review process, and amplify problems such as variability in the requirements and decisions reached by different research ethics committees. PURPOSE: We aimed to characterize research ethics review of CRTs, examine investigator experiences with the ethics review process, and assess the need for ethics guidelines for CRTs. METHODS: An electronic search strategy implemented in MEDLINE was used to identify and randomly sample 300 CRTs published in English language journals from 2000 to 2008. A web-based survey with closed- and open-ended questions was administered to corresponding authors in a series of six contacts. RESULTS: The survey response rate was 64%. Among 182 of 285 eligible respondents, 91% indicated that they had sought research ethics approval for the identified CRT, although only 70% respondents reported research ethics approval in the published article. Nearly one-third (31%) indicated that they have had to meet with ethics committees to explain aspects of their trials, nearly half (46%) experienced variability in the ethics review process in multijurisdictional trials, and 38% experienced negative impacts of the ethics review process on their trials, including delays in trial initiation (28%), increased costs (10%), compromised ability to recruit participants (16%), and compromised methodological quality (9%). Most respondents (74%; 95% confidence interval (CI): 67%-80%) agreed or strongly agreed that there is a need to develop ethics guidelines for CRTs, and (70%; 95% CI: 63%-77%) that ethics committees could be better informed about distinct ethical issues surrounding CRTs. LIMITATIONS: Thirty-six percent of authors did not respond to the survey. Due to the absence of comparable results from a representative sample of authors of individually randomized trials, it is unclear to what extent the reported challenges result from the CRT design. CONCLUSIONS: CRT investigators are experiencing challenges in the research ethics review of their trials, including excessive delays, variability in process and outcome, and imposed requirements that can have negative consequences for study conduct. Investigators identified a clear need for ethics guidelines for CRTs and education of research ethics committees about distinct ethical issues in CRTs.
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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 | 0.600 | 0.751 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.008 | 0.010 |
| Science and technology studies | 0.004 | 0.010 |
| Scholarly communication | 0.012 | 0.011 |
| Open science | 0.003 | 0.010 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.002 | 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; 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".