Short video recommendations cause more distress for users with ADHD
Quantifying the Engagement Trap: Impact of Short-form Video Recommender Systems on Users with ADHD
Human-Computer InteractionArtificial Intelligence
Summary
Short videos on apps use smart algorithms to keep people watching longer. This study shows that people with ADHD find these videos just as interesting but end up losing track of time more, feeling regret, and getting upset more than others. The researchers measured these effects by comparing people with and without ADHD. They suggest changes to make these systems friendlier to different brain types and reduce negative feelings.
What this means in practice
- •For mobile app developers: Design video recommendation algorithms that reduce negative time awareness and regret impacts on users with ADHD based on quantified user experience differences.
- •For ui ux designers: Incorporate neuro-inclusive design principles to create interfaces that help users with ADHD manage engagement and emotional distress when consuming recommended short videos.
Authors
Vedad Misirlic, Gregor Mayr, Elisabeth Lex
Abstract
Short-form video platforms use recommender systems to maximize engagement through highly efficient personalized recommendations. However, the impact of these recommendations on users with ADHD compared to users without ADHD remains underexplored. Through this study, we introduce and operationalize the Engagement Trap, illustrating how recommender systems, while successfully optimizing for engagement, disproportionately disadvantage users with ADHD. This stratified study of 302 participants, recruited via the online platform Prolific, compares experiences between participants with and without ADHD. Our results show that while recommendations are perceived as relevant across groups, participants with ADHD report significantly higher levels of time blindness, post-usage regret, and emotional distress when consuming recommendations. Moreover, we collect feedback for several proof-of- concept, theoretical design interventions for neuro-inclusive design principles. These findings provide quantitative evidence of systemic differences in engagement-optimized recommender systems and highlight the unbalanced negative effects and interactions these systems create for participants with ADHD. We argue for neurodiversity-aware, human-centered design approaches that mitigate such algorithmic harms and support more equitable experiences.