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When AI Venting Helps or Harms: How Perceived Anonymity Shapes Supportive Interactions With Conversational Agents

Year: 2026

Type: article

Abstract: Artificial intelligence conversational agents are increasingly used for emotional venting, yet their psychological implications remain paradoxically unclear. AI-assisted venting can both support and harm well-being, raising questions about when human-AI interactions are beneficial and how specific design features are associated with more supportive or more stressful outcomes. Drawing on a cross-sectional survey of 408 AI chatbot users in China, this study tests a dual-pathway model. More frequent AI-assisted venting was positively associated with perceived stress directly but negatively associated with stress indirectly through perceived AI support and emotion regulation. Perceived anonymity moderated these associations: at higher levels, the positive direct venting–stress association was attenuated, whereas the negative indirect association was stronger. These findings position perceived anonymity as a design-critical boundary condition in AI-mediated interactions. The study advances HCI theory by showing how a design perception relates to psychological pathways, offering implications for designing safer, more supportive conversational agents.

Source: International Journal of Human-Computer Interaction

DOI: 10.1080/10447318.2026.2719169

Authors: Piper Liping Liu, Tien Ee Dominic Yeo

Institutions: Shenzhen University, Hong Kong Baptist University

Language: English

Topic: Social Robot Interaction and HRI

Subfield: Social Psychology

Field: Psychology

Domain: Social Sciences

SDG: Good health and well-being

Open Access status: hybrid

Funder: Shenzhen University