Quality Assessment of Dry Eye Educational Videos on Xiaohongshu, 136 Videos

Shiyang Niu published a dataset on figshare on June 3, 2026, analyzing 136 dry eye educational videos from the Xiaohongshu platform. The dataset compares video characteristics, content coverage, engagement metrics, and quality scores between videos uploaded by non-medical and medical individual users. It includes assessments using DISCERN, PEMAT-A/V, and Global Quality Score instruments.

Use Cases

• Compare video quality scores based on uploader type mentioned in the description.
• Analyze correlations between content coverage breadth and quality assessment scores described in the results.
• Study the prevalence of incorrect information in health education videos based on the reported metrics.
• Investigate engagement patterns for medical content on social media platforms.

Strengths

• Includes 136 videos with detailed quality assessments using three validated instruments (DISCERN, PEMAT-A/V, GQS).
• Provides comparative statistics between two uploader groups (108 non-medical vs. 28 medical individual users).
• Reports specific statistical findings, such as an odds ratio of 11.23 for incorrect information prevalence.

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 single platform (Xiaohongshu) and a snapshot from April 16, 2026.

Provenance

Source

figshare

Collection Method

Cross-sectional study collecting the first 200 videos from a search for 'dry eye' on Xiaohongshu, screened to 136 eligible videos.

Time Range

Data collected on April 16, 2026.

Freshness

Last updated 2026-06-03 04:47:11; freshness should be verified.