Social media platforms have rapidly adopted algorithmic curation with little consideration for the potential harm to users' mental well-being. We present findings from design workshops with 21 participants diagnosed with mental illness about their interactions with social media platforms. We find that users develop cause-and-effect explanations, or folk theories, to understand their experiences with algorithmic curation. These folk theories highlight a breakdown in algorithmic design that we explain using the framework of entanglement, a phenomenon where there is a disconnect between users' actions and platform outcomes on an emotional level. Participants' designs to address entanglement and mitigate harms centered on contextualizing their engagement and restoring explicit user control on social media. The conceptualization of entanglement and the resulting design recommendations have implications for social computing and recommender systems research, particularly in evaluating and designing social media platforms that support users' mental well-being.

翻译：社交媒体平台迅速采用算法推荐机制，却极少考虑其对用户心理健康可能造成的危害。我们通过21位精神疾病确诊参与者开展的设计研讨会，呈现了关于他们与社交媒体平台互动的发现。研究发现，用户会构建因果解释（即民间理论）来理解算法推荐机制下的使用体验。这些民间理论揭示了算法设计的缺陷，我们通过"纠缠"框架对此进行阐释——该现象指用户行为与平台结果在情感层面存在脱节。参与者针对解决纠缠问题、减轻危害的设计方案，主要集中在社交媒体的情境化互动体验重构与显式用户控制权恢复两方面。纠缠现象的概念化及其衍生的设计建议，对社交计算与推荐系统研究具有重要启示，尤其对评估和设计支持用户心理健康的社交媒体平台具有指导意义。