aceModerate evidence
Published recordLifestyleGood Space
More
How emotional response styles of generative AI companions shape adaptive emotion regulation and short-term AI reliance
- Truvace record
- TRV-2026-2548raw data (JSON)
- Version
- v2Revised
- First published
- Evidence type
- Randomized controlled trial
- Sources
- 1 sourcePeer-reviewed
- sha256
- aa164e53b1ec…check it
Introduction Generative artificial intelligence (GenAI) companions increasingly respond to users' negative emotions with validation, reassurance, reframing, and personalized guidance. However, immediate emotional relief does not establish improved independent emotion regulation or emotional dependence. Methods In a two-condition randomized experiment with 380 adults, we compared adaptive regulation-oriented responses with relational reassurance-oriented responses. We assessed immediate negative affect, emotion-r…
The gain
In a randomized trial of 380 adults, AI replies that coached emotion regulation led to higher self-efficacy and better affective recovery in a later no-AI task (0.99 vs 0.71 points) than reassurance-style replies.
What this doesn’t fix
The study used a single three-turn interaction with mild non-clinical material, adults in Guangzhou, one text-only model snapshot and a written lab task, so it cannot establish emotional dependence or real-world coping; the AI-necessity and reliance scales were study-specific and need independent validation.
Sources
1 on file- Frontiers in Psychologydoi:10.3389/fpsyg.2026.1950163
Cite this record
v2Truvace Impact Record TRV-2026-2548, v2: “How emotional response styles of generative AI companions shape adaptive emotion regulation and short-term AI reliance.” Truvace, 2026-11-12. /record/TRV-2026-2548 (accessed on the day you copy it). sha256 aa164e53b1eca65f…
Change history
2 versionsEvery change made to this record since it was first published, and why.
Moved from Policy to Lifestyle, where its subject belongs. The record's text is unchanged.
Certified into the record
Check this record hasn’t been altered
How to check it yourself, without trusting this page
Download any version from /api/record/TRV-2026-2548 and hash its canonical field yourself, for example with shasum -a 256. You should get its content_hash. Each version’s text also ends with prev:and the hash of the version before it (version 1 points to 64 zeros). If anyone had changed a single character of any version after it was saved, those hashes wouldn’t line up.