Drivers of Adoption and Credibility in a Source-Grounded Generative AI Wellness Assistant

Authors

  • Venkata Reddy Konasani, Dr. M.R. Jhansi Rani

Keywords:

generative artificial intelligence, retrieval-augmented generation, technology acceptance, AI credibility, source transparency, responsible AI, conversational AI

Abstract

Generative artificial intelligence is increasingly used to deliver conversational health and wellnessinformation, yet continued use and perceived credibility represent different user judgements. Thisstudy develops and tests a dual-path model of user evaluation in a source-grounded generative AI wellness assistant. The adoption pathway examines Query Understanding and Response Relevance

References

1)Abbasian, M., Khatibi, E., Azimi, I., Oniani, D., Shakeri Hossein Abad, Z., Thieme, A., Sriram, R., Yang, Z., Wang, Y., Lin, B., Gevaert, O., Li, L. J., Jain, R., & Rahmani, A. M. (2024). Foundation metrics for evaluating effectiveness of healthcare conversations powered by generative AI. npj Digital Medicine, 7, 82. https://doi.org/10.1038/s41746-024-01074-z

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Published

2026-10-24

How to Cite

Venkata Reddy Konasani, Dr. M.R. Jhansi Rani. (2026). Drivers of Adoption and Credibility in a Source-Grounded Generative AI Wellness Assistant. Journal of Computational Analysis and Applications (JoCAAA), 35(10), 29–49. Retrieved from https://eudoxuspress.com/index.php/pub/article/view/5915

Issue

Section

Articles