Generative AI and Two-Tiered Online Mental Health Communities
Manyang Zhang, Jinyang Zheng, Zhijun Yan

TL;DR
This study examines how integrating generative AI into online mental health communities impacts counselor participation, engagement, and platform dynamics, revealing increased activity but varied responses among counselors.
Contribution
It provides empirical evidence on the effects of AI integration in tiered mental health platforms, highlighting changes in counselor activity and platform sustainability.
Findings
Posting intensity increases after AI integration
Average response length remains unchanged
Per-post social recognition declines
Abstract
Online mental health communities (OMHCs) are tiered platforms that connect patients with licensed counselors through public Q&A forums and paid private consultations. Their two-tier structure creates a strategic dilemma for genAI integration. Conversational agents can provide scalable and timely responses to a broader set of patients, alleviating persistent supply shortages, but their large-scale presence may also reshape counselors' participation in providing nuanced expertise, emotionally sensitive support, and paid consultations, which are central to platform revenue and long-run sustainability. Leveraging a quasi-natural experiment from the integration of a genAI-based conversational agent in a leading OMHC, we examine how AI entry affects counselor participation. Using multiple identification strategies, we find that posting intensity increases significantly after AI integration,…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
