Expectations of Benefit and Tolerance to Risk of Individuals with Spinal Cord Injury Regarding Potential Participation in Clinical Trials
Bibliographic record
Abstract
We conducted a survey of individuals living with spinal cord injury (SCI) to determine their receptivity to participating in clinical trials of drug therapies or stem cell therapies, their anticipation of therapeutic benefits, and their tolerance to risk. A 46-item questionnaire was administered to individuals with cervical or thoracic SCI identified through a provincial database. The average age was 42 years and the individuals were, on average, 5.5 years post-injury. Receptivity to neuroprotective drug trials in the acute setting was very high, but somewhat less so for stem cell trials in the subacute or chronic (current) setting. With respect to expectation of functional benefit, approximately one third of the respondents indicated that they would want a 5-25% chance of achieving some functional recovery if enrolling in a stem cell therapy clinical trial in the current, chronic injury state. Whereas the majority typically would require the risk of spinal cord damage, cancer, infection, and nerve pain from invasive cell transplantation trials to be ≤1%, 15-30% would participate regardless of the risk of these complications. The factors associated with this high risk tolerance were gender (males>females), age (elderly>young), and self-reported knowledge of SCI research (greater knowledge>less knowledge). Injury severity or chronicity did not have a significant correlation with risk tolerance. Whereas previous studies have shown that the understanding of stem cell science is limited among individuals with SCI, here we show that many still have high hopes for the possibility of neurological benefit, are anxious to participate in invasive stem cell trials, and, in many cases, have high tolerance for risk in such trials. Taken together, the data underscore the need for careful communication with individuals with SCI to avoid unrealistic expectations and therapeutic misconception in experimental trials.
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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 | 0.009 | 0.035 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".