Assessment of quality, reliability, and interactive characteristics of age-related macular degeneration short videos on TikTok: a cross-sectional study

Abstract

Abstract Age-related macular degeneration (AMD) is a leading cause of blindness in the elderly. Short-video platforms like TikTok are increasingly important sources of health information, yet concerns persist regarding content quality and reliability. To systematically evaluate the quality, reliability, and user engagement characteristics of AMD-related videos on TikTok. We systematically searched TikTok for AMD-related videos. Quality and reliability were assessed using JAMA benchmark, modified DISCERN, Global Quality Scale (GQS), and Patient Education Materials Assessment Tool (PEMAT). Entropy weight method and cluster analysis were applied to engagement data. Among 145 videos, overall quality was poor. Median scores were 1 for JAMA, 2 for mDISCERN, and 3 for GQS. Understandability was limited (median PEMAT-U: 43%), while actionability was moderate (median PEMAT-A: 60%). High-quality videos were characterized by creation by Western medicine ophthalmologists, inclusion of prognostic information, and monologue narration; physician title showed no association with quality. “Saves” carried the highest engagement weight (35.71%). "Self-test and screening" themes achieved the highest engagement rate (62.5%). Media accounts attained the highest PEMAT-U scores and interaction metrics. Video format and presenter attire showed no significant impact on quality or engagement. AMD-related health information on TikTok is generally poor quality. Information quality and user engagement are driven by distinct factors, highlighting the need for targeted strategies to improve content accuracy and understandability.