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March 14, 2026Journal of Experimental Social Psychology7 citationsOpen Access

Is a random human peer better than a highly supportive chatbot in reducing loneliness over time?

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RLR. LiDFDunigan Parker FolkASAbhay Singh

Key Points

  • To determine if daily engagement with a chatbot or a human peer better reduces loneliness among first-year university students.
  • Participants interacted with either a chatbot, a human peer, or wrote a journal entry for two weeks.
  • The study involved 296 first-semester university students.
  • The chatbot was designed based on relationship science principles.
  • Daily texting with a human peer reduced loneliness more effectively than with the chatbot.
  • Interacting with the chatbot did not provide significant psychological benefits compared to the human peer.
  • The study highlights the potential limitations of relying on AI for emotional support.

Abstract

AI chatbots are increasingly embedded in social life, offering accessible companionship. While brief interactions have been shown to provide immediate benefits, it is unclear whether repeated, daily engagement with chatbots reduces loneliness. In this pre-registered study, we tested the effectiveness of a chatbot versus a human peer in reducing loneliness among 296 students in their first semester of university. For two weeks, participants either interacted with a chatbot or a human peer, or simply wrote a brief journal entry (control condition). Although our chatbot “Sam” was designed to offer consistent support rooted in principles from relationship science, interacting with this chatbot did not yield the same psychological benefits as interacting with a randomly selected first-year university student. The present study provides initial evidence that texting daily with a random human peer may be more effective in alleviating loneliness than texting with a highly supportive chatbot.

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Cite This Study

Li et al. (2026) studied this question.

synapsesocial.com/papers/69b4fac6b39f7826a300b689https://doi.org/10.1016/j.jesp.2026.104911
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