Adaptability to the audience is an important feature for conversational systems, especially in the healthcare dissemination field, where scientific concepts have to be delivered to a potentially wide range of users. This work presents an evaluation of the capability of LLMs to support style transfer according to the target user’s age group. Two complementary evaluation methods were employed: an automatic assessment based on the ARI readability index, and a human experts evaluation focusing on appropriateness depending on the user’s educational level as well as content accuracy. Results show that LLMs efficiently switch style when provided with information about the user’s age while managing content still requires the adoption of safety measures.