Patient trust in medical professionals might hinge on what artificial intelligence (AI) has to say, according to a team led by Penn State researchers. Using an AI chatbot roleplaying as a human doctor, the team identified how people perceive medical professionals when they think a “human” doctor consults an AI system for a second opinion during mental health consultations. They found that when the AI system agreed with the proxy doctor’s recommendation, patients viewed the professional’s assessment as more credible. But when the AI disagreed with the doctor’s assessment, patient perceptions of medical uncertainty and doctor laziness increased.

Home visits are a core part of community nursing. For nursing students, they are not simply a checklist of health assessments. A home visit asks students to observe the family environment, recognize safety risks, communicate with patients and relatives, and turn classroom knowledge into practical care decisions.  Yet such situations are hard to recreate in a classroom. A real home may be cluttered. An older adult may hesitate, question the visitor, become impatient, or respond in unexpected ways. Traditional role-play can help students rehearse the process, but scripted scenarios may not fully capture the uncertainty of entering someone’s home as a nurse.  A study published in the Chinese Journal of Medical Education Research explored whether a virtual–physical integrated scenario simulation could bring students closer to that reality. Researchers from Peking Union Medical College School of Nursing, Beijing Xicheng District Desheng Community Health Center, and Beijing Fengtai District Fangzhuang Community Health Center tested the approach in undergraduate nursing education. They found that the new simulation model increased students’ learning immersion compared with conventional scenario simulation. However, the study did not show a clear short-term advantage in improving students’ home visit attitudes or skills.