The quality of YouTube videos on endoscopic third ventriculostomy and endoscopic third ventriculostomy with choroid plexus cauterization procedures available to families of patients with pediatric hydrocephalus
Bibliographic record
Abstract
OBJECTIVE: YouTube has become an important information source for pediatric neurosurgical patients and their families. The goal of this study was to determine whether the informative quality of videos of endoscopic third ventriculostomy (ETV) and endoscopic third ventriculostomy with choroid plexus cauterization (ETV + CPC) is associated with metrics of popularity. METHODS: This cross-sectional study used comprehensive search terms to identify videos pertaining to ETV and ETV + CPC presented on the first 3 pages of search results on YouTube. Two pediatric neurosurgeons, 1 neurosurgery resident, and 2 patient families independently reviewed the selected videos. Videos were assessed for overall informational quality by using a validated 5-point Global Quality Score (GQS) and compared to online metrics of popularity and engagement such as views, likes, likes/views ratio, comments/views ratio, and likes/dislikes ratio. Weighted kappa scores were used to measure agreement between video reviewers. RESULTS: A total of 58 videos (47 on ETV, 7 on ETV + CPC, 4 on both) of 120 videos assessed met the inclusion criteria. Video styles included "technical" (62%), "lecture" (24%), "patient testimonial" (4%), and "other" (10%). In terms of GQS, substantial agreement was seen between surgeons (kappa 0.67 [95% CI 0.55, 0.80]) and excellent agreement was found between each surgeon and the neurosurgical resident (0.77 [95% CI 0.66, 0.88] and 0.89 [95% CI 0.82, 0.97]). Only fair to moderate agreement was seen between professionals and patient families, with weighted kappa scores ranging from 0.07 to 0.56. Academic lectures were more likely to be rated good or excellent (64% vs 0%, p < 0.001) versus surgical procedure and testimonial video types. There were significant associations between a better GQS and more likes (p = 0.01), views (p = 0.02), and the likes/dislikes ratio (p = 0.016). The likes/views ratio (p = 0.31) and comments/views ratio (p = 0.35) were not associated with GQS. The number of likes (p = 0.02), views (p = 0.03), and the likes/dislikes ratio (p = 0.015) were significantly associated with video style (highest for lecture-style videos). CONCLUSIONS: Medical professionals tended to agree when assessing the overall quality of YouTube videos, but this agreement was not as strongly seen when compared to parental ratings. The online metrics of likes, views, and likes/dislikes ratio appear to predict quality. Neurosurgeons seeking to increase their online footprint via YouTube would be well advised to focus more on the academic lecture style because these were universally better rated.
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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 | 0.003 | 0.037 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".