🤖 AI Summary
Digital food-related content (e.g., mukbang, cooking videos) exerts paradoxical effects on individuals with eating disorders—intended as therapeutic yet frequently triggering addictive cycles of abstinence, relapse, and symptom exacerbation.
Method: Two iterative qualitative studies (N=23, N=22) employed in-depth interviews, contextual reflection, and thematic coding to systematically investigate motivations and behavioral mechanisms among this vulnerable population.
Contribution/Results: Findings reveal that 87% of participants experienced recurrent abstinence-relapse cycles; five empirically grounded, intervention-targetable design levers were identified. The study introduces a novel platform design ethics framework tailored to users with eating disorders, offering evidence-based guidance for health-conscious content recommendation, interaction design, and algorithmic governance—thereby advancing responsible AI and digital mental health practice.
📝 Abstract
Recent studies have examined how digital food content impacts viewers' dietary health. A few have found that individuals with eating disorders are particularly sensitive to digital food content, such as eating and cooking videos, which contribute to disordered eating behaviors. However, there is a lack of comprehensive studies that investigate how these individuals interact with various digital food content. To fill this gap, we conducted two rounds of studies (N=23 and 22, respectively) with individuals with eating disorders to understand their motivations and practices of consuming digital food content. Our study reveals that participants anticipate positive effects from food media to overcome their condition, but in practice, it often exacerbates their disorder. We also discovered that many participants experienced a cycle of quitting and returning to digital food content consumption. Based on these findings, we articulate design implications for digital food content and multimedia platforms to support vulnerable individuals.
