ArticlePeerJ. Computer science2025
Integrating artificial intelligence (AI) in healthcare: advancing older adults' health management in Saudi Arabia through AI-powered chatbots.
Article in PeerJ. Computer science, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
7 citing papers in PubMed.
- Effects of a Safety User Interface Bundle on Verification Intentions in Generative AI Chat Use Among Older Chinese Adults: Randomized Vignette Survey.Journal of medical Internet research · 2026Trial
- Advancing foundational models in digital health technology adoption: A systematic literature review of multidisciplinary factors.PLOS digital health · 2026Article
- Artificial Intelligence in Social Health: A Narrative Review of Uses, Advantages, Challenges, and Future Directions.Healthcare (Basel, Switzerland) · 2026Review
- Predictors of Trust and Engagement in Personalized Healthcare: A Study of AI-Driven Diagnosis and Treatment in Saudi Arabia.Healthcare (Basel, Switzerland) · 2026Article
- Determinants of AI Adoption in Saudi Arabian Healthcare Institutions.Healthcare (Basel, Switzerland) · 2026Article
- Quantitative evaluation of China's smart aging healthcare policy under the background of silver economy development: based on PMC model.Frontiers in public health · 2026Article
- A Generative AI Framework for Cognitive Intervention in Older Adults: An Integrated Engineering Design and Clinical Protocol.Healthcare (Basel, Switzerland) · 2025Article
Corrections and comments
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Authors and funding
1 author.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: The healthcare sector is experiencing rapid digital advancements, with patients increasingly seeking quick and seamless interactions. Artificial intelligence (AI)-driven healthcare chatbots are becoming an integral part of elderly care, transforming provider-patient engagement and supporting health behavior goals tailored to individual preferences, needs, and limitations. Methods: This study developed a comprehensive research framework incorporating various theoretical perspectives to explore the determinants of sustained use of AI-powered healthcare chatbots among older adults. The framework also examined the mediating influence of perceived humanness. The model was evaluated using partial least squares structural equation modeling (PLS-SEM) on cross-sectional data collected from 158 individuals aged 60 and above. Results: The findings show that satisfaction with AI-powered chatbots is significantly influenced by facilitating conditions, perceived hedonic motivation, confirmation, performance expectancy, and effort expectancy. Perceived security also plays a critical role in shaping satisfaction and the intention to continue using these chatbots. Moreover, the analysis revealed that perceived humanness mediates the relationship between satisfaction and continuous use intentions among elderly users in Saudi Arabia. Discussion: This research provides valuable insights into the factors influencing older adults' acceptance of AI chatbots in Saudi Arabia, particularly in the post-COVID-19 era. These findings enrich academic discourse and offer actionable recommendations for healthcare organizations adapting to the evolving digital landscape.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.