arXiv subjects

Jiaying "Lizzy" Liu

Publications and source records attributed to Jiaying "Lizzy" Liu.

5 recordsLinked to original sources

arXiv2025

A review of theories and models utilized by empirical studies about mental health help-seeking and implications for future research

Purpose: With the rise of mental health risks globally, it is urgent to provide effective mental health support. However, a holistic understanding of how people seek help for mental health problems remains limited, impeding the development of evidence-based intervention programs to facilitate help-seeking behavior. This study reviews current theories that guide empirical research on young adults' help-seeking behavior using technologies, identifies limitations in existing frameworks, and proposes directions for future research. Methods: We searched databases that are most likely to contain mental health help-seeking practices in relation to information technology, including PubMed, ACM Digital Library, Web of Science, PsycInfo, ScienceDirect, EBSCO, and Cochrane Library. Results: Of 2443 abstracts reviewed, 43 studies met the criteria and were included in the analysis. We identified 16 theories and models. They represent seven perspectives to view mental health help-seeking and reveal factors such as accessibility, stigma, and social support as key factors influencing help-seeking. Limitations: We summarized the theories and models and categorized them based on their primary perspectives. Cross-perspective connections could be explored in future reviews. Conclusions: A holistic approach to creating culturally sensitive multi-level interventions that consider individual, interpersonal, and community factors is needed to advance effective mental health help-seeking support strategies.

cs.HC↗

arXiv2025

Design for Hope: Cultivating Deliberate Hope in the Face of Complex Societal Challenges

Design has the potential to cultivate hope in the face of complex societal challenges. These challenges are often addressed through efforts aimed at harm reduction and prevention -- essential but sometimes limiting approaches that can unintentionally narrow our collective sense of what is possible. This one-day, in-person workshop builds on the first Positech Workshop at CSCW 2024 by offering practical ways to move beyond reactive problem-solving toward building capacity for proactive goal setting and generating pathways forward. We explore how collaborative and reflective design methodologies can help research communities navigate uncertainty, expand possibilities, and foster meaningful change. By connecting design thinking with hope theory, which frames hope as the interplay of ``goal-directed,'' ``pathways,'' and ``agentic'' thinking, we will examine how researchers might chart new directions in the face of complexity and constraint. Through hands-on activities including problem reframing, building a shared taxonomy of design methods that align with hope theory, and reflecting on what it means to sustain hopeful research trajectories, participants will develop strategies to embed a deliberately hopeful approach into their research.

cs.HC↗

arXiv2025

From Regulation to Support: Centering Humans in Technology-Mediated Emotion Intervention in Care Contexts

Enhancing emotional well-being has become a significant focus in HCI and CSCW, with technologies increasingly designed to track, visualize, and manage emotions. However, these approaches have faced criticism for potentially suppressing certain emotional experiences. Through a scoping review of 53 empirical studies from ACM proceedings implementing Technology-Mediated Emotion Intervention (TMEI), we critically examine current practices through lenses drawn from HCI critical theories. Our analysis reveals emotion intervention mechanisms that extend beyond traditional emotion regulation paradigms, identifying care-centered goals that prioritize non-judgmental emotional support and preserve users' identities. The findings demonstrate how researchers design technologies for generating artificial care, intervening in power dynamics, and nudging behavioral changes. We contribute the concept of "emotion support" as an alternative approach to "emotion regulation," emphasizing human-centered approaches to emotional well-being. This work advances the understanding of diverse human emotional needs beyond individual and cognitive perspectives, offering design implications that critically reimagine how technologies can honor emotional complexity, preserve human agency, and transform power dynamics in care contexts.

cs.HC↗

arXiv2025

Can Large Language Models Grasp Concepts in Visual Content? A Case Study on YouTube Shorts about Depression

Large language models (LLMs) are increasingly used to assist computational social science research. While prior efforts have focused on text, the potential of leveraging multimodal LLMs (MLLMs) for online video studies remains underexplored. We conduct one of the first case studies on MLLM-assisted video content analysis, comparing AI's interpretations to human understanding of abstract concepts. We leverage LLaVA-1.6 Mistral 7B to interpret four abstract concepts regarding video-mediated self-disclosure, analyzing 725 keyframes from 142 depression-related YouTube short videos. We perform a qualitative analysis of MLLM's self-generated explanations and found that the degree of operationalization can influence MLLM's interpretations. Interestingly, greater detail does not necessarily increase human-AI alignment. We also identify other factors affecting AI alignment with human understanding, such as concept complexity and versatility of video genres. Our exploratory study highlights the need to customize prompts for specific concepts and calls for researchers to incorporate more human-centered evaluations when working with AI systems in a multimodal context.

cs.HC↗

arXiv2025

Displaying Fear, Sadness, and Joy in Public: Schizophrenia Vloggers' Video Narration of Emotion and Online Care-Seeking

Individuals with severe mental illnesses (SMI), particularly schizophrenia, experience complex and intense emotions frequently. They increasingly turn to vlogging as an authentic medium for emotional disclosure and online support-seeking. While previous research has primarily focused on text-based disclosure, little is known about how people construct narratives around emotions and emotional experiences through video blogs. Our study analyzed 401 YouTube videos created by schizophrenia vloggers, revealing that vloggers disclosed their fear, sadness, and joy through verbal narration by explicit expressions or storytelling. Visually, they employed various framing styles, including Anonymous, Talk-to-Camera, and In-the-Moment approaches, along with diverse visual narration techniques. Notably, we uncovered a concerning 'visual appeal disparity' in audience engagement, with visually appealing videos receiving significantly more views, likes, and comments. This study discusses the role of video-sharing platforms in emotional expression and offers design implications for fostering online care-seeking for emotionally vulnerable populations.

cs.HC↗