In this work, we empirically evaluated expert-led debunking of health misinformation on TikTok with n=420 survey and n=20 interview participants. Unlike fact-checkers, health professionals debunk misinformation non-anonymously through video-against-video formats (stitching/''duetting''), rather than using labels. We analyzed 5,161 such posts to select six misinformation and six debunking videos across three common topics - two general health, two mental health, and two nutrition - for statistical comparison. Participants exposed to debunking videos believed misinformation claims significantly less than those exposed to misinformation videos in all six conditions. Experts were seen as more credible than misinformation creators, except in one instance involving mental health. Thematic analysis showed that expert-led debunking succeeded because experts’ videos aligned with the Debunking Handbook method for effective refutation. Experts’ credibility is derived mainly from being perceived as non-typical influencers who maintain reputable TikTok personas by providing qualified medical evidence and advice.
Large language models (LLMs) have been increasingly adopted to support patients' healthcare-seeking in recent years. While prior patient-centered studies have examined the capabilities and experience of LLM-based tools in specific health-related tasks such as information-seeking, diagnosis, or decision-supporting, the inherently longitudinal nature of healthcare in real-world practice has been underexplored. This paper presents a four-week diary study with 25 patients to examine LLMs' roles across healthcare-seeking trajectories. Our analysis reveals that patients integrate LLMs not just as simple decision-support tools, but as dynamic companions that scaffold their journey across behavioral, informational, emotional, and cognitive levels. Meanwhile, patients actively assign diverse socio-technical meanings to LLMs, altering the traditional dynamics of agency, trust, and power in patient-provider relationships. Drawing from these findings, we conceptualize future LLMs as a longitudinal boundary companion that continuously mediates between patients and clinicians throughout longitudinal healthcare-seeking trajectories.
Eating disorder (ED) recovery extends beyond therapy sessions, unfolding in vulnerable moments embedded in everyday life and relationships. Yet empirical understanding of how these moments arise, how supporters contribute, and how technologies might offer timely, contextual assistance remains limited. To address this gap, we conducted a design session and two-week diary study with 27 individuals with ED and 12 social supporters. Our analysis identified diverse contexts in which patients and supporters perceived support to be needed, and the forms of support they envisioned digital tools could offer. While many needs were mutually recognized, the actual practice of support often involved mismatches, suggesting opportunities for technologies to help mediate supportive engagement. Our study contributes empirical insight into everyday support moments in ED recovery and highlights opportunities to design digital interventions that provide context-sensitive assistance, empower supporters, and extend care beyond clinical settings.
Large Language Models (LLMs) are increasingly used for mental health support, yet little is known about how people with mental health challenges engage with them, how they evaluate their usefulness, and what design opportunities they envision. We conducted 20 semi-structured interviews with people in the UK who live with mental health conditions and have used LLMs for mental health support. Through reflexive thematic analysis, we found that participants engaged with LLMs in conditional and situational ways: for immediacy, the desire for non-judgement, self-paced disclosure, cognitive reframing, and relational engagement. Simultaneously, participants articulated clear boundaries informed by prior therapeutic experience: LLMs were effective for mild-to-moderate distress but inadequate for crises, trauma, and complex social-emotional situations. We contribute empirical insights into the lived use of LLMs for mental health, highlight boundary-setting as central to their safe role, and propose design and governance directions for embedding them responsibly within care ecosystem.
Personal informatics literature has typically examined how fitness trackers can support understanding of cardio-based exercises, like running, which are closely associated with the step counts central to these devices. Although this focus has supported individuals in gleaning fruitful data discoveries, it confines the manner in which a body moves to these movement domains. In this paper, we contend with pole dance, a physical activity whose movement affordances (e.g., rotational, artistic, feminine) differ greatly from those centralized in the self-tracking technologies. We qualitatively interviewed 20 polers, and gathered their reflection on pole dance and how they view the use self-tracking devices for the activity. Using their insights on the inherent dynamicity of poling, independently, and upon interaction with fitness trackers, we offer suggestions to our discipline to challenge ourselves to re-imagine sensing as a pluralistic endeavor.
Providing mental health support for loved ones across a geographic distance creates unique challenges for the remote caregivers, who sometimes turn to online communities for peer support. We qualitatively analyzed 522 Reddit threads to understand what drives remote caregivers’ online help-seeking behaviors and the responses they receive from the community. Their purposes of posting included requesting guidance, expressing emotions, and seeking validation. Community responses included providing emotional support, suggesting informational strategies, and sharing personal experiences. While certain themes in posts (emotional toll, monitoring symptoms, and prioritizing caregiver well-being) are shared across remote and non-remote contexts, remote caregivers’ posts surfaced nuanced experiences. For example, they often rely on digital cues, such as voice, to interpret care receivers’ well-being while struggling with digital silence during crises. We discuss the need for supporting communication and information sharing between remote caregivers and receivers, care coordination for crisis management, and design recommendations for caregiver communities.
Subliminals are audiovisual routines that claim to induce change through mental programming, promising transformations across many aspects of modern life. While the idea of subliminal influence is not new, contemporary subliminals have become popular online commodities for pursuing implausible bodily modifications mediated by social media. This study applies a mixed-methods and computational approach to characterize the desires that motivate subliminal use and the social reinforcement that legitimizes unverified practices. The findings show that subliminal users are strongly oriented toward Western beauty ideals and frequently participate in adjacent magical thinking communities alongwith weight-loss and eating disorder forums. In terms of community interaction, posts that share positive results receive higher support and visibility, whereas skeptical reports tend to be unpopular and less endorsed. Taken together, this research contributes an empirical understanding of how unscientific attitudes toward rapid self-transformations are sustained and normalized in online spaces.