Video Quality Assessment and Analysis of Gastroesophageal Reflux Disease on TikTok and Bilibili: Cross-Sectional Study

By evaluating the quality of videos on GERD on the two platforms, this can provide new ideas for health education interventions in the clinic and a relevant basis for improving the quality level of the videos.

Authors

Institutions

Publication Details

Journal
Journal of Multidisciplinary Healthcare
Published
2024-12-01
DOI
https://doi.org/10.2147/jmdh.s485781
Citations
17
Primary Topic
Gastroesophageal reflux and treatments
Type
article
Field-Weighted Citation Impact
7.89

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Video Quality Assessment and Analysis of Gastroesophageal Reflux Disease on TikTok and Bilibili: Cross-Sectional Study

B Y Liu, Keyan Wu, Yanbing Ding, Zhangyu Wang et al.
17 citations
Journal of Multidisciplinary Healthcare
Gastroesophageal reflux and treatments
7.89
article

Video Quality Assessment and Analysis of Gastroesophageal Reflux Disease on TikTok and Bilibili: Cross-Sectional Study

B Y Liu, Keyan Wu, Yanbing Ding, Zhangyu Wang, Jean Xia, Wenjie Huo, Ying Liang
article en
17 citations

Abstract

By evaluating the quality of videos on GERD on the two platforms, this can provide new ideas for health education interventions in the clinic and a relevant basis for improving the quality level of the videos.

Journal of Multidisciplinary HealthcareVol. Volume 17
Yangzhou University (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 2%
Gastroesophageal reflux and treatments
7.89
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.