Attitudes of people with multiple sclerosis toward brain donation
Bibliographic record
Abstract
Objective: Research directly examining brain tissue has played an important role in understanding the pathology and pathogenesis of multiple sclerosis (MS) and other diseases of the central nervous system. Such research relies heavily on donations of post-mortem brain tissue yet little is known about the attitudes of people with multiple sclerosis (MS) about brain donation. We aimed to assess the attitudes of people with MS toward brain donation, their preferences related to discussions of brain donation, and factors associated with attitudes toward brain donation including sociodemographic and clinical characteristics, health literacy and religiosity. Methods: In a cross-sectional study, we surveyed participants in the North American Research Committee on Multiple Sclerosis (NARCOMS) Registry regarding their attitudes toward brain donation, reasons for participating or not participating in brain donation, and related communication preferences. We used multivariable logistic regression analyses to test factors associated with attitudes regarding brain donation. Results: Most of the 4,520 participants were women (80.8%), self-identified as white (88.1%), with a post-secondary education, functional health literacy and moderate-severe disability. Sixty-two percent of participants would consider brain donation. Factors associated with considering brain donation included female gender, having a post-secondary education, being physically active, having moderate-severe disability and more comorbidities, and alcohol intake. Seventy-five percent of participants indicated that they preferred to receive information regarding brain donations from physicians. Conclusion: Two-thirds of people with MS would consider brain donation. People with MS desire to hear about brain donation from their health care providers rather than other sources.
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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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".