A cross-sectional survey on patient perception of subject payment for research
Bibliographic record
Abstract
Background: Research subjects may receive payment for their participation. Multiple models for payment have been proposed, however, the most ethical model is not completely clear.Objective: The purpose of the present study is to evaluate and quantify the public’s perception and to identify demographic determinants influencing said perceptions.Methods: Patients from a New York City medical clinic were queried using an adapted survey on medical research compensation consisting of 6 opinion-style questions pertaining to the payment of subjects enrolling in clinical trials and 9 demographic questions. Pearson’s chi-squared tests of independence with two-tailed alpha of 0.05 and correction for multiple testing were performed to determine statistical significance.Results: 440 respondents were recruited for participation, with broad distribution across age, race, and socioeconomic levels. For research payment, surveyed respondents preferred the market model (n = 265, 62%) compared to the reimbursement model (n = 72, 16.8%) or wage payment model (n = 64, 15%) and no payment (n = 27, 6.3%). Patients under the age of 60 were more likely to choose the market model (p = .01) compared to those over 60 selecting the reimbursement model (p = .001). 88.7% (n = 377) of respondents indicated they did not perceive clinical trial payment to be a bribe, with non-white patients being more likely to identify payment as a bribe (p = .025). 73.2% of respondents (n = 344) believed that poorer individuals were more likely to enroll. Patients without high school education and patients 60 years of age or older were more likely to believe that payment (p = .006 and p < .001, respectively) would have no influence on enrollment than those with high school education.Conclusions: Differences in mind-set towards clinical trials demonstrate older patients and individuals without a high school education may have differing opinions with regards to financial incentives in clinical trials. Sensitivity towards these attitudes may require alternative models of payment for future clinical 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 | 0.006 | 0.024 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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; a candidate call from one teacher head, 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".