Investigator experiences with financial conflicts of interest in clinical trials
Bibliographic record
Abstract
BACKGROUND: Financial conflicts of interest (fCOI) can introduce actions that bias clinical trial results and reduce their objectivity. We obtained information from investigators about adherence to practices that minimize the introduction of such bias in their clinical trials experience. METHODS: Email survey of clinical trial investigators from Canadian sites to learn about adherence to practices that help maintain research independence across all stages of trial preparation, conduct, and dissemination. The main outcome was the proportion of investigators that reported full adherence to preferred trial practices for all of their trials conducted from 2001-2006, stratified by funding source. RESULTS: 844 investigators responded (76%) and 732 (66%) provided useful information. Full adherence to preferred clinical trial practices was highest for institutional review of signed contracts and budgets (82% and 75% of investigators respectively). Lower rates of full adherence were reported for the other two practices in the trial preparation stage (avoidance of confidentiality clauses, 12%; trial registration after 2005, 39%). Lower rates of full adherence were reported for 7 practices in the trial conduct (35% to 43%) and dissemination (53% to 64%) stages, particularly in industry funded trials. 269 investigators personally experienced (n = 85) or witnessed (n = 236) a fCOI; over 70% of these situations related to industry trials. CONCLUSION: Full adherence to practices designed to promote the objectivity of research varied across trial stages and was low overall, particularly for industry funded trials.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.037 | 0.031 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
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; both teacher heads 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".