Characterizing Collective Efforts in Content Sharing and Quality Control for ADHD-relevant Content on Video-sharing Platforms

2025-01-22

AI Summary

Low-quality and inaccessible ADHD-related content on video-sharing platforms impedes symptom recognition and support access for affected individuals. Method: We systematically collected 373 ADHD-related videos and associated comments from YouTube and TikTok, applying mixed-method analysis—quantitative statistics and qualitative thematic coding—to develop a dual-dimension evaluation framework for content quality and accessibility. Contribution/Results: This study provides the first empirical evidence of an emergent, self-organized governance mechanism within the ADHD community, characterized by authority co-construction, collective fact-checking, and accessibility optimization. We identify three core risks: misleading diagnostic claims, knowledge fragmentation, and sensory overload. Five user-driven quality control practices are distilled, and seven evidence-informed, neurodiversity-centered design recommendations are proposed for video-sharing platforms (VSPs). These findings establish a novel paradigm for trustworthy digital health content governance and inclusive platform design in the algorithmic era.

Technology Category

• Application Domains: Misinformation & Fake News
• Data Mining & Knowledge Management: Mining of Visual, Multimedia & Multimodal Data
• Computer Vision: Video Understanding & Activity Analysis

Application Category

• Web Mining and Content Analysis: Web data quality in the era of algorithmically-generated content
• Responsible Web: Mitigating misinformation and disinformation
• Economics, Online Markets and Human Computation: LLM based quality controls for crowd work

Abstract

Video-sharing platforms (VSPs) have become increasingly important for individuals with ADHD to recognize symptoms, acquire knowledge, and receive support. While videos offer rich information and high engagement, they also present unique challenges, such as information quality and accessibility issues to users with ADHD. However, little work has thoroughly examined the video content quality and accessibility issues, the impact, and the control strategies in the ADHD community. We fill this gap by systematically collecting 373 ADHD-relevant videos with comments from YouTube and TikTok and analyzing the data with a mixed method. Our study identified the characteristics of ADHD-relevant videos on VSPs (e.g., creator types, video presentation forms, quality issues) and revealed the collective efforts of creators and viewers in video quality control, such as authority building, collective quality checking, and accessibility improvement. We further derive actionable design implications for VSPs to offer more reliable and ADHD-friendly contents.

Problem

• Attention Deficit Hyperactivity Disorder
• Video Sharing Platforms
• Information Quality

Innovation

• ADHD
• Video Sharing Platforms
• Information Quality