Quality Analysis of Lumbar Spinal Stenosis Videos on Chinese Short Video Platforms

Wenhui Zhao's dataset, last updated May 2026, contains a cross-sectional analysis of 412 short videos related to lumbar spinal stenosis (LSS) from five Chinese platforms. The data includes basic characteristics, engagement metrics, and quality scores (GQS, mDISCERN, JAMA) for videos stratified by platform, uploader type, and category. It was created to systematically evaluate the quality and reliability of LSS-related health information on these platforms.

Use Cases

• Correlating video duration with quality scores based on the reported moderate positive correlations.
• Analyzing inter-platform variation in content quality based on the stratified results for Bilibili, WeChat, and Kwai.
• Comparing quality scores across uploader types and video categories mentioned in the description.
• Investigating the relationship between engagement metrics (likes, saves, shares) and quality scores based on the reported weak correlations.

Strengths

• Includes 412 analyzed videos from five major platforms, providing a multi-source sample.
• Assesses content using three established quality and reliability scoring systems: GQS, mDISCERN, and JAMA.
• Contains stratified analysis by platform, uploader type, and video category, enabling comparative study.

Limitations

• Row count is unknown, which may limit suitability assessment.
• Column-level documentation is absent; field semantics must be inferred after download.
• Data is limited to a specific search snapshot (top 100 results per platform) and may not represent all content.

Provenance

Source

Wenhui Zhao via figshare.

Collection Method

Cross-sectional content analysis; videos were searched, screened, and scored using predefined criteria.

Time Range

The study period is not specified in the provided metadata.

Freshness

Last updated 2026-05-04 05:30:38; freshness should be verified.

Geography

Content is from Chinese short video platforms (TikTok, Bilibili, Xiaohongshu, Kwai, WeChat).