20.500.12556/DKUM-91860 Exploring the feasibility of generative AI in persona research a omparative analysis of large language model-generated and human-crafted personas in obesity research This study investigates the perceptions of Persona descriptions generated using three different large language models (LLMs) and qualitatively developed Personas by an expert panel involved in obesity research. Six different Personas were defined, three from the clinical domain and three from the educational domain. The descriptions of Personas were generated using qualitative methods and the LLMs (i.e., Bard, Llama, and ChatGPT). The perception of the developed Personas was evaluated by experts in the respective fields. The results show that, in general, the perception of Personas did not significantly differ between those generated using LLMs and those qualitatively developed by human experts. This indicates that LLMs have the potential to generate a consistent and valid representation of human stakeholders. The LLM-generated Personas were perceived as believable, relatable, and informative. However, post-hoc comparisons revealed some differences, with descriptions generated using the Bard model being in several Persona descriptions that were evaluated most favorably in terms of empathy, likability, and clarity. This study contributes to the understanding of the potential and challenges of LLM-generated Personas. Although the study focuses on obesity research, it highlights the importance of considering the specific context and the potential issues that researchers should be aware of when using generative AI for generating Personas. user personas obesity large language models value sensitive design digital health interventions uporabniki debelost jezikovni modeli digitalno zdravje true true false Angleški jezik Slovenski jezik https://www.mdpi.com/2076-3417/15/4/1937 © 2025 by the authors Članek v reviji 2025-02-14 12:21:01 2025-02-14 12:21:01 2025-02-24 08:43:49 0000-00-00 00:00:00 2025 0 0 19 str. iss. 4, [article no.] 1937 Vol. 15 2025 0000-00-00 Zaloznikova Objavljeno NiDoloceno 2025-02-05 2025-02-11 2025-02-13 004.5 226175491 10.3390/app15041937 2076-3417 applsci-15-01937-v2.pdf applsci-15-01937-v2.pdf 1 06E543B88DBC1421E53B56339ECE90F7 1b376d168689732aee5eb01323eea7be2579834ab08f9f7ffd0852bdef7a9602 0bcd3112-eac6-11ef-bdc3-00155d000105 https://dk.um.si/Dokument.php?lang=slv&id=188677 Fakulteta za elektrotehniko, računalništvo in informatiko Filozofska fakulteta 0 0 0