Social media networking in pediatric hydrocephalus: a point-prevalence analysis of utilization
Bibliographic record
Abstract
OBJECTIVE A recent survey has shown that caregivers of children with shunt-treated hydrocephalus frequently use social media networks for support and information gathering. The objective of this study is to describe and assess social media utilization among users interested in hydrocephalus. METHODS Publicly accessible accounts and videos dedicated to the topic of hydrocephalus were comprehensively searched across 3 social media platforms (Facebook, Twitter, and YouTube) throughout March 2016. Summary statistics were calculated on standard metrics of social media popularity. A categorization framework to describe the purpose of pages, groups, accounts, channels, and videos was developed following the screening of 100 titles. Categorized data were analyzed using nonparametric tests for statistical significance. RESULTS The authors' search identified 30 Facebook pages, 213 Facebook groups, 17 Twitter accounts, and 253 YouTube videos. These platforms were run by patients, caregivers, nonprofit foundations, and patient support groups. Most accounts were from the United States (n = 196), followed by the United Kingdom (n = 31), Canada (n = 17), India (n = 15), and Germany (n = 12). The earliest accounts were created in 2007, and a peak of 65 new accounts were created in 2011. The total number of users in Facebook pages exceeded those in Facebook groups (p < 0.001). The majority of users in Facebook groups were in private groups, in contrast to public groups (p < 0.001). The YouTube videos with the highest median number of views were for surgical products and treatment procedures. CONCLUSIONS This study presents novel observations into the characteristics of social media use in the topic of hydrocephalus. Users interested in hydrocephalus seek privacy for support communications and are attracted to treatment procedure and surgical products videos. These findings provide insight into potential avenues of hydrocephalus outreach, support, or advocacy in social media.
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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 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.002 |
| 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".