A longitudinal qualitative study of 18 US users finds that LLMs deliver socioemotional support but also foster dependency, one-sided validation, and privacy risks because their designs prioritize engagement over well-being and lack care-based governance.
arXiv preprint arXiv:2509.19515 , year=
3 Pith papers cite this work. Polarity classification is still indexing.
3
Pith papers citing it
years
2026 3representative citing papers
CTEM framework links behavioral history to evolving emotional states with user feedback updates, instantiated as Auri agent and tested in a 21-day study showing gains in naturalness, coherence, and emotional harmony.
Warmth and cognitive empathy in LLMs drive higher anthropomorphism, trust, and relational closeness, especially on personal topics, while competence affects usefulness but not perceived human-likeness.
citing papers explorer
-
Engagement-Optimized Care: When LLMs become Mental Health Infrastructure
A longitudinal qualitative study of 18 US users finds that LLMs deliver socioemotional support but also foster dependency, one-sided validation, and privacy risks because their designs prioritize engagement over well-being and lack care-based governance.
-
Toward Natural and Companionable Virtual Agents via Cross-Temporal Emotional Modeling
CTEM framework links behavioral history to evolving emotional states with user feedback updates, instantiated as Auri agent and tested in a 21-day study showing gains in naturalness, coherence, and emotional harmony.
-
Anthropomorphism and Trust in Human-Large Language Model interactions
Warmth and cognitive empathy in LLMs drive higher anthropomorphism, trust, and relational closeness, especially on personal topics, while competence affects usefulness but not perceived human-likeness.