Digital Technologies and Well-being
The impact of digital technologies, such as social media and AI, on mental health and well-being has been the subject of ongoing debate. Public discourse often frames digital technologies as detrimental to social and emotional well-being. However, technology use is socially embedded and culturally contingent. My research examines how individuals actively engage with and through digital technologies to seek social support, cope with stress, and foster resilience. By focusing on these contextualized practices, my work challenges simplistic narratives and highlights the nuanced ways technology mediates and shapes human well-being.
Selected publications:
1. Zhang, R., Meng, H., Neubronner, M., & Lee, Y. C. (2025). Computational and ethical considerations for using large language models in psychotherapy. Nature Computational Science, 5(10), 854-862. [link]
2. Zhang, R., et al. (2025). The dark side of AI companionship: A taxonomy of harmful algorithmic behaviors in human-AI relationships. Proceedings of the 2025 ACM CHI Conference on Human Factors in Computing Systems. [link]
3. Li, H., & Zhang, R. (2024). Finding love in algorithms: Deciphering the emotional contexts of close encounters with AI chatbots. Journal of Computer-Mediated Communication, 29(5), zmae015. [link]
4. Zhang, R., Eschler, J., & Reddy, M. (2018). Online support groups for depression in China: culturally shaped interactions and motivations. Computer Supported Cooperative Work (CSCW), 27(3), 327–354. [link]
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Online Social Support and Emotional Disclosure
As people increasingly express their emotions, feelings, and thoughts online, new challenges emerge, such as privacy management and context collapse. Understanding the motivations, processes, and outcomes of online self-disclosure is essential for fostering safe and supportive digital spaces. My research examines how personal, interpersonal, technological, and sociocultural factors shape emotional and personal disclosure on social media, and explores the social and psychological outcomes of such sharing. This work aims to provide insights into how online platforms can better support meaningful connections while safeguarding user well-being.
Selected publications:
1. Zhang, R., Bazarova, N. N., & Reddy, M. (2021). Distress disclosure across social media platforms during the COVID-19 pandemic: Untangling the effects of platforms, affordances, and audiences. Proceedings of the 2021 ACM CHI Conference on Human Factors in Computing Systems. [link]
2. Zhang, R., & Fu, J. S. (2020). Privacy management and self-disclosure on social network sites: The moderating effects of stress and gender. Journal of Computer-Mediated Communication, 25(3), 236-251. [link]
3. Zhang, R. (2017). The stress-buffering effect of self-disclosure on Facebook: An examination of stressful life events, social support, and mental health among college students. Computers in Human Behavior, 75, 527–537. [link]
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Digital Interventions to Improve Mental Health
As mobile apps and wearable devices become increasingly common for health monitoring, research has documented their potential to improve health outcomes. However, less is known about the mechanisms through which these effects occur. My research uses mixed-method approaches to examine the role of mobile technologies in mental health support. This work explores not only whether digital interventions are effective, but also how they can be designed to foster emotional well-being, enhance user engagement, and provide personalized support in meaningful and sustainable ways.
Selected publications:
1. Zhu, Z., Tan, Y., Yamashita, H., Lee, Y.C., & Zhang, R. (2025). The benefits of prosociality towards AI agents: Examining the effects of helping AI agents on human well-being. Proceedings of the 2025 ACM CHI Conference on Human Factors in Computing Systems.
2. Zhang, R., Ringland, … & Reddy, M. (2021). Designing for emotional well-being: Integrating persuasion and customization into mental health technologies. Proceedings of the 2021 ACM CHI Conference on Human Factors in Computing Systems. [link]
2. Zhang, R., Nicholas, J., … & Mohr, D. C. (2019). Clinically meaningful use of mental health apps and its effects on depression: Mixed methods study. Journal of Medical Internet Research, 21(12), e15644. [link]