About

As a researcher, I have broad interests in the design and social impact of information technologies in our personal lives, in small groups, and in organizations. I conduct research in the five major areas below. You can see my latest research on these topics by going to my articles or books page.

Research topics

• Psychiatry
• Clinical psychology
• Medicine
• Psychology

Selected publications

• Systematic review and meta-analysis of AI-based conversational agents for promoting mental health and well-being

  npj Digital Medicine · 2023 · 413 citations

  • Psychology
  • Medicine
  • Clinical psychology

  Conversational artificial intelligence (AI), particularly AI-based conversational agents (CAs), is gaining traction in mental health care. Despite their growing usage, there is a scarcity of comprehensive evaluations of their impact on mental health and well-being. This systematic review and meta-analysis aims to fill this gap by synthesizing evidence on the effectiveness of AI-based CAs in improving mental health and factors influencing their effectiveness and user experience. Twelve databases were searched for experimental studies of AI-based CAs' effects on mental illnesses and psychological well-being published before May 26, 2023. Out of 7834 records, 35 eligible studies were identified for systematic review, out of which 15 randomized controlled trials were included for meta-analysis. The meta-analysis revealed that AI-based CAs significantly reduce symptoms of depression (Hedge's g 0.64 [95% CI 0.17-1.12]) and distress (Hedge's g 0.7 [95% CI 0.18-1.22]). These effects were more pronounced in CAs that are multimodal, generative AI-based, integrated with mobile/instant messaging apps, and targeting clinical/subclinical and elderly populations. However, CA-based interventions showed no significant improvement in overall psychological well-being (Hedge's g 0.32 [95% CI -0.13 to 0.78]). User experience with AI-based CAs was largely shaped by the quality of human-AI therapeutic relationships, content engagement, and effective communication. These findings underscore the potential of AI-based CAs in addressing mental health issues. Future research should investigate the underlying mechanisms of their effectiveness, assess long-term effects across various mental health outcomes, and evaluate the safe integration of large language models (LLMs) in mental health care.

  DOI

Recent grants

• SCH: INT: Collaborative Research: FITTLE+: Theory and Models for Smartphone Ecological Momentary Intervention

  NSF · $847k · 2013–2017

• RAPID: Collaborative Research: Social interactions. social connectedness, and health outcomes during the COVID-19 pandemic

  NSF · $174k · 2020–2021

• IBSS-L: Developing, Testing, and Designing from a Computational Theory of Online Communities

  NSF · $920k · 2016–2020

• ITR: Managing human attention

  NSF · $2.0M · 2003–2008

• HCC-Large: Collaborative Research: Designing Online Volunteer Communities

  NSF · $664k · 2008–2013

Frequent coauthors

• Sara Kiesler

  Carnegie Mellon University

  29 shared

• Haiyi Zhu

  Carnegie Mellon University

  28 shared

• Aniket Kittur

  California Miramar University

  27 shared

• Susan R. Fussell

  Cornell University

  25 shared

• Diyi Yang

  21 shared

• Moira Burke

  Meta (United States)

  20 shared

• Laura Dabbish

  Carnegie Mellon University

  18 shared

• Robert Fish

  16 shared

Labs

• Robert E. Kraut LabPI

Awards & honors

• CHI 2016 SIGCHI Lifetime Research Award

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