“Waiting for Science to Catch up with Practice”: an examination of 10-year YouTube trends in discussions of chronic cerebral spinal venous insufficiency treatment for multiple sclerosis
Bibliographic record
Abstract
Objective: The objective of this longitudinal study examined, first, whether people with multiple sclerosis who previously advocated for angioplasty to treat chronic cerebral spinal venous insufficiency (CCSVI) through YouTube continued reporting benefits. Second, it examined a new cohort reporting on CCSVI treatment, and third, whether perspectives have changed.Method: YouTube videos from August 2011 to January 2019 related to CCSVI were retrieved. Once retrieved, all videos were compiled, classified and analyzed. Categorical data were reported and a pre-determined code-book was used to code videos. Data from the videos were extracted and analyzed using discourse analysis.Results: 1293 videos related to CCSVI were uploaded by 54 people with multiple sclerosis who met the inclusion criteria. YouTube videos uploaded by people with multiple sclerosis have shifted in volume and message. The initial surge in interest in CCSVI treatment has diminished, but there still exists strong advocates for its use. There appears to be an inconsistency between positive results, actual improvements in symptoms, and the overall messages reported. Very little long-term data was available as the procedure is relatively new.Conclusion: Practitioners may be faced with pressure to provide unproven treatments in the future and should be understanding but evidence-driven when supporting multiple sclerosis therapies.
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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 | 0.000 | 0.000 |
| 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 | 0.000 |
| 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".