arXiv subjects

Yunan Chen

Publications and source records attributed to Yunan Chen.

13 recordsLinked to original sources

arXiv2026

We Need Granular Sharing of De-Identified Data-But Will Patients Engage? Investigating Health System Leaders' and Patients' Perspectives on A Patient-Controlled Data-Sharing Platform

Patient-controlled data-sharing systems are increasingly promoted as a way to empower patients with greater autonomy over their health data. Yet it remains unclear how different stakeholders, especially patients and health system leaders, perceive the benefits and challenges of enabling granular control over the sharing of de-identified medical data for research. To address this gap, we developed a high-fidelity prototype of a patient-controlled, web-based consent platform and conducted a two-phase mixed-methods study:semi-structured interviews with 16 health system leaders and a survey with 523 patient participants. While both groups appreciated the potential of such a platform to enhance transparency and autonomy, their views diverged in meaningful ways. Leaders viewed transparency and granular control through the lens of informed consent and institutional ethics, whereas patients interpreted these factors as safeguards against potential risks and uncertainties. Our findings underscore critical tensions such as individual control and research integrity. We offer design implications for building trustworthy, context-aware systems that support flexible granularity, provide ongoing benefit-centered transparency, and adapt to diverse literacy and privacy needs.

cs.HC↗

arXiv2026

From Efficiency to Meaning: Adolescents' Envisioned Role of AI in Health Management

While prior research has focused on providers, caregivers, and adult patients, little is known about adolescents' perceptions of AI in health learning and management. Utilizing design fiction and co-design methods, we conducted seven workshops with 23 adolescents (aged 14-17) to understand how they anticipate using health AI in the context of a family celiac diagnosis. Our findings reveal that adolescents have four main envisioned roles of health AI: enhancing health understanding and help-seeking, reducing cognitive burden, supporting family health management, and providing guidance while respecting their autonomy. We also identified nuanced trust and a divided view on emotional support from health AI. These findings suggest that adolescents perceive AI's value as a tool that moves them from efficiency to meaning-one that creates time for valued activities. We discuss opportunities for future health AI systems to be designed to encourage adolescent autonomy and reflection, while also supporting meaningful, dialectical activities.

cs.HC↗

arXiv2026

Hiding in Plain Sight: Understanding the Everyday Practices and Challenges of Car Dwellers

Vehicle dwelling has increased significantly in recent years. While HCI research has explored vehicle dwelling through the lens of digital nomadism and vanlife, it has largely overlooked the complexities of vehicle dwelling as a form of housing insecurity, as well as the unique constraints of living in smaller vehicles. Drawing on a qualitative analysis of posts and comments from an online community, we examine car dwellers' infrastructuring work to manage daily life under social, spatial, and infrastructural constraints. We further explore the motivations and identity negotiations of car dwellers, whose experiences fall between homelessness and nomadism, and highlight how developing infrastructural competence can shape identity. We discuss implications for future HCI research on mobility and dwelling under conditions of uneven access to infrastructure and provide design recommendations for technologies that better account for car dwellers' diverse needs, circumstances, and identities.

cs.HC↗

arXiv2025

Supporting Patients in Managing Electronic Health Records and Biospecimens Consent for Research: Insights from a Mixed-Methods Usability Evaluation of the iAGREE Portal

De-identified health data are frequently used in research. As AI advances heighten the risk of re-identification, it is important to respond to concerns about transparency, data privacy, and patient preferences. However, few practical and user-friendly solutions exist. We developed iAGREE, a patient-centered electronic consent management portal that allows patients to set granular preferences for sharing electronic health records and biospecimens with researchers. To refine the iAGREE portal, we conducted a mixed-methods usability evaluation with 40 participants from three U.S. health systems. Our results show that the portal received highly positive usability feedback. Moreover, participants identified areas for improvement, suggested actionable enhancements, and proposed additional features to better support informed granular consent while reducing patient burden. Insights from this study may inform further improvements to iAGREE and provide practical guidance for designing patient-centered consent management tools.

cs.HC↗

arXiv2025

Healthy Lifestyles and Self-Improvement Videos on YouTube: A Thematic Analysis of Teen-Targeted Social Media Content

As teenagers increasingly turn to social media for health-related information, understanding the values of teen-targeted content has become important. Although videos on healthy lifestyles and self-improvement are gaining popularity on social media platforms like YouTube, little is known about how these videos benefit and engage with teenage viewers. To address this, we conducted a thematic analysis of 44 YouTube videos and 66,901 comments. We found that these videos provide various advice on teenagers' common challenges, use engaging narratives for authenticity, and foster teen-centered communities through comments. However, a few videos also gave misleading advice to adolescents that can be potentially harmful. Based on our findings, we discuss design implications for creating relatable and intriguing social media content for adolescents. Additionally, we suggest ways for social media platforms to promote healthier and safer experiences for teenagers.

cs.HC↗

arXiv2025

"I've talked to ChatGPT about my issues last night.": Examining Mental Health Conversations with Large Language Models through Reddit Analysis

We investigate the role of large language models (LLMs) in supporting mental health by analyzing Reddit posts and comments about mental health conversations with ChatGPT. Our findings reveal that users value ChatGPT as a safe, non-judgmental space, often favoring it over human support due to its accessibility, availability, and knowledgeable responses. ChatGPT provides a range of support, including actionable advice, emotional support, and validation, while helping users better understand their mental states. Additionally, we found that ChatGPT offers innovative support for individuals facing mental health challenges, such as assistance in navigating difficult conversations, preparing for therapy sessions, and exploring therapeutic interventions. However, users also voiced potential risks, including the spread of incorrect health advice, ChatGPT's overly validating nature, and privacy concerns. We discuss the implications of LLMs as tools for mental health support in both everyday health and clinical therapy settings and suggest strategies to mitigate risks in LLM-powered interactions.

cs.HC↗

arXiv2025

Understanding Adolescents' Perceptions of Benefits and Risks in Health AI Technologies through Design Fiction

Despite the growing research on users' perceptions of health AI, adolescents' perspectives remain underexplored. This study explores adolescents' perceived benefits and risks of health AI technologies in clinical and personal health settings. Employing Design Fiction, we conducted interviews with 16 adolescents (aged 13-17) using four fictional design scenarios that represent current and future health AI technologies as probes. Our findings reveal that with a positive yet cautious attitude, adolescents envision unique benefits and risks specific to their age group. While health AI technologies were seen as valuable learning resources, they also raised concerns about confidentiality with their parents. Additionally, we identified several factors, such as severity of health conditions and previous experience with AI, influencing their perceptions of trust and privacy in health AI. We explore how these insights can inform the future of design of health AI technologies to support learning, engagement, and trust as adolescents navigate their healthcare journey.

cs.HC↗

arXiv2024

Investigating the effects of housing instability on depression, anxiety, and mental health treatment in childhood and adolescence

Housing instability is a widespread phenomenon in the United States. In combination with other social determinants of health, housing instability affects children's overall health and development. Drawing on data from the 2022 National Survey of Children's Health, we employed multiple logistic regression models to understand how sociodemographic factors, especially housing instability, affect mental health outcomes and treatment access for youth aged 6-17 years. Our results show that youth facing housing instability have a higher likelihood of experiencing anxiety (OR: 1.42, p<0.001) and depression (OR: 1.57, p<0.001). Furthermore, youth experiencing both mental health conditions and housing instability are significantly less likely to receive mental health services in the past year, indicating the substantial barriers they face in accessing mental health care. Based on our findings, we highlight opportunities for digital mental health interventions to provide children experiencing housing instability with more accessible and consistent mental health services.

cs.HC↗

arXiv2024

Transitioning Together: Collaborative Work in Adolescent Chronic Illness Management

Adolescents with chronic illnesses need to learn self-management skills in preparation for the transition from pediatric to adult healthcare, which is associated with negative health outcomes for youth. However, few studies have explored how adolescents in a pre-transition stage practice self-management and collaborative management with their parents. Through interviews with 15 adolescents (aged 15-17), we found that adolescents managed mundane self-care tasks and experimented with lifestyle changes to be more independent, which sometimes conflicted with their parents' efforts to ensure their safety. Adolescents and their parents also performed shared activities that provided adolescents with the opportunity to learn and practice self-management skills. Based on our findings, we discuss considerations for technology design to facilitate transition and promote parent-adolescent collaboration in light of these tensions.

cs.HC↗

arXiv2024

Inconsistencies in Masked Language Models

Learning to predict masked tokens in a sequence has been shown to be a helpful pretraining objective for powerful language models such as PaLM2. After training, such masked language models (MLMs) can provide distributions of tokens in the masked positions in a sequence. However, this paper shows that distributions corresponding to different masking patterns can demonstrate considerable inconsistencies, i.e., they cannot be derived from a coherent joint distribution when considered together. This fundamental flaw in MLMs can lead to self-contradictory behaviors during inference. On various benchmark datasets including MMLU, MLMs can give different predictions to the same input question. From BERT-base to UL2-20B, we show that such inconsistencies exist ubiquitously in MLMs of diverse sizes and configurations. In light of our observations, we further propose an inference-time strategy for MLMs called Ensemble of Conditionals. It jointly considers a selected range of inconsistent conditionals directly produced by the MLM for the final prediction, which often leads to considerable accuracy improvement.

cs.CL↗

arXiv2023

Self-Expression and Sharing around Chronic Illness on TikTok

While prior work has investigated the benefits of online health communities and general purpose social media used for health-related purposes, little work examines the use of TikTok, an emerging social media platform with a substantial user base. The platform's multimodal capabilities foster creative self-expression, while the content-driven network allows users to reach new audiences beyond their personal connections. To investigate users' challenges and motivations, we analyzed 160 TikTok videos that center on users' first hand experiences living with chronic illness. We found that users struggled with a loss of normalcy and stigmatization in daily life. To contend with these challenges, they publicly shared their experiences to raise awareness, seek support from peers, and normalize chronic illness experiences. Based on our findings, we discuss the modalities of TikTok that facilitate self-expression around stigmatized topics and provide implications for the design of online health communities that better support adolescents and young adults.

cs.HC↗

arXiv2023

Perspectives on Privacy in the Post-Roe Era: A Mixed-Methods of Machine Learning and Qualitative Analyses of Tweets

Abortion is a controversial topic that has long been debated in the US. With the recent Supreme Court decision to overturn Roe v. Wade, access to safe and legal reproductive care is once again in the national spotlight. A key issue central to this debate is patient privacy, as in the post-HITECH Act era it has become easier for medical records to be electronically accessed and shared. This study analyzed a large Twitter dataset from May to December 2022 to examine the public's reactions to Roe v. Wade's overruling and its implications for privacy. Using a mixed-methods approach consisting of computational and qualitative content analysis, we found a wide range of concerns voiced from the confidentiality of patient-physician information exchange to medical records being shared without patient consent. These findings may inform policy making and healthcare industry practices concerning medical privacy related to reproductive rights and women's health.

cs.HC↗

arXiv2023

Mobile Apps for Children's Health and Wellbeing: Design Features and Future Opportunities

Mobile health apps hold great potential for promoting children's health and wellbeing. However, there is limited understanding of how these technologies are currently designed to support children with their health concerns or wellness goals. To gain insight into the current landscape of mobile apps designed for children's health, we retrieved and reviewed 43 apps from IOS and Google Play store that are specifically marketed for children. Our qualitative analysis identified the dominant health focuses and goals of children's mobile health apps. We analyzed the primary users and their expectations as well as the methods of engagement and involvement adopted. Based on our findings, we discussed the opportunities to support children with chronic illnesses through mobile apps, design for dual use, and design for age appropriateness and digital health safety. This study provides insights and recommendations for app designers, health researchers, and policymakers on strategies for engaging children and parents while also promoting children's health and wellbeing through mobile technology.

cs.HC↗