The study compares communication styles of large language models (LLMs) and humans in explaining COVID‑19 misinformation, using a dataset of 1,498 fact‑checking claims and 99 blinded reader evaluations. LLM‑generated explanations scored lower on persuasive strategies, certainty, and alignment with social values, yet over 60% of participants preferred LLM content for clarity, completeness, and persuasiveness. The findings suggest that reader preference may not align with traditional measures of communication quality, highlighting both the promise and limits of LLMs in health communication.
By Jiawei Zhou, Kritika Venkatachalam, Minje Choi, Koustuv Saha, Munmun De Choudhury
arXiv:2605.30273v2 Announce Type: replace-cross
Abstract: Large language models (LLMs) show promise in generating supportive responses for mental health queries, but improving their usefulness, empat...
By Jiwon Kim, Maya Ajit, Sherry Gong, Soorya Ram Shimgekar, Dong Whi Yoo, Eshwar Chandrasekharan, Koustuv Saha
arXiv:2606. 02444v1 Announce Type: new Abstract: Recent evidence shows that people with eating disorders (EDs) are increasingly seeking guidance, advice, and emotional support from Large Language Model (LLM)-based chat systems.
By Giulia Pucci, Emily Hemendinger, Ruizhe Li, Gavin Abercrombie, Tanvi Dinkar, Arabella Sinclair
arXiv:2601. 16529v4 Announce Type: replace Abstract: Large language models (LLMs) deployed in clinical decision support may acquiesce to patient requests for care that conflicts with evidence-based guidelines.
By Dongshen Peng, Yi Wang, Austin Schoeffler, Sun-ha Hong, Brian Suffoletto, David Kim, Carl Preiksaitis, Christian Rose
arXiv:2606. 18129v1 Announce Type: cross Abstract: Recent incidents involving LLMs used for mental-health support reveal a critical evaluation gap: surface-level safety scores do not capture how models behave across realistic, emotionally sensitive interactions over time.
By Abeer Badawi, Moyosoreoluwa Olatosi, Negin Baghbanzadeh, Laleh Seyyed-Kalantari, Frank Rudzicz, R. Shayna Rosenbaum, Sara Pishdadian, Elham Dolatabadi
arXiv:2609.22110v1 Announce Type: new
Abstract: Background: Large language models (LLMs) can improve healthcare information delivery in low-resource settings but may produce inaccurate or culturally...
By Abdulquddus Ajibade, Oluwaseun Odunsi, Iyinoluwa Animasaun, Chioma Nwakanma-Akanno, Oluwasegun Oguntuase, Oluwafunke Akinbuwa, Abiodun Adereni