Modeling Behavioral Determinants of Following and Verifying AI-Generated Health Advice: The Roles of eHealth Literacy, Cognitive Load, and Technology Self-Efficacy
Anas Ali Alhur, Badr Alnasser · 2026
Read Modeling Behavioral Determinants of Following and Verifying AI-Generated Health Advice: The Roles of eHealth Literacy, Cognitive Load, and Technology Self-Efficacy by Anas Ali Alhur, Badr Alnasser (2026) in the Tower of Babel, a free online library of public-domain works preserved in clean, searchable text. No sign-up. The full text is served as a plain-text file at a predictable URL, where text is present: https://antarctic-labs.com/tower-of-babel/pmc-13251768.txt.
Description
Alhur and Alnasser model why people follow, or check, health advice produced by chatbots. Their 2026 Journal of Multidisciplinary Healthcare survey covers four hundred eighty-seven Saudi adults who had used generative AI for health questions. Digital health literacy, mental load, and confidence with technology were the traits under study.
Stronger online health literacy and technology confidence both predicted more checking of AI advice and less blind following. Heavy mental load pushed the other way, raising following and cutting verification, and it partly carried literacy's effect. Technology confidence softened the harm of mental load in the model. The authors recommend simpler AI outputs, built-in verification prompts, and literacy programs for safer public use.
Catalog record
| CREATOR | Anas Ali Alhur, Badr Alnasser |
|---|---|
| YEAR | 2026 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 43 KB |
| VERSION | 1.0 |
| LICENSE | CC BY 4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |