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Direct pathways from anthropomorphism to self-disclosure in artificial intelligence Chatbot use: a mixed-methods multi-study investigation

Truvace record
TRV-2026-2506raw data (JSON)
Version
v1Published
First published
Evidence type
Controlled or validated comparison
Sources
1 sourcePeer-reviewed
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Anthropomorphic design is widely assumed to shape self-disclosure and emotional dependence by first cultivating felt empathy and trust, and the safety measures platforms deploy, such as labelling and disclosure of artificial origin, target those perceptions. Across a twelve-country survey, forty-seven interviews, and three experiments, this research tests that mediation model and identifies the route that carries the behavioural effect. A twelve-country survey ( N = 1480) found empathy and trust negligibly relat…

The problem

In two experiments (390 and 300 people), a human-like chatbot raised behavioural disclosure to 63% from 35% under a neutral prompt, and the effect ran through perceived anonymity rather than empathy or trust, so labelling safeguards may not reduce it.

What this doesn’t fix

The authors call the anonymity and reduced evaluation apprehension account the most defensible interim account of the mechanism, so it is not settled.

Sources

1 on file
  1. Addictive Behaviors Reportsdoi:10.1016/j.abrep.2026.100762
    Peer-reviewed2026-10-20

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v1

Truvace Impact Record TRV-2026-2506, v1: “Direct pathways from anthropomorphism to self-disclosure in artificial intelligence Chatbot use: a mixed-methods multi-study investigation.” Truvace, 2026-11-12. /record/TRV-2026-2506 (accessed on the day you copy it). sha256 db784d94fde90988…

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