The study used a qualitative descriptive design to examine experiences with AI-based and digital health technologies. The researchers purposively recruited nine patients with chronic illnesses from Riyadh and conducted semi-structured interviews over Zoom, with each interview lasting 20 to 30 minutes. Interview guides were informed by the Technology Acceptance Model. Recordings were transcribed verbatim and analyzed thematically using Braun and Clarke’s methodology, while member checking, peer review and an audit trail were used to establish trustworthiness.

Thematic analysis produced four main themes: the usability of AI-based health tools, participants’ perceptions and understanding of AI technologies, digital health literacy, and integration into self-management behaviors. Patients most often regarded the tools as easy to use, particularly when they were accessed through smartphones, and described frequent use within everyday routines. Within the interviews, participants said the systems helped them monitor health and understand health information better. They also described increasing trust and reliance over time. These findings represent the experiences reported by a small, locally recruited sample rather than measured improvements in disease control, treatment adherence or healthcare use.

Digital health literacy emerged as a central factor in how participants interpreted information and applied digital tools. In the study’s account, literacy was not simply separate from technology adoption: patients’ capacity to understand and use health information shaped their ability to engage with AI-supported functions. The authors concluded that the usefulness of AI and digital health tools depends on usability, positive user perceptions and substantial digital health literacy. They also identified user-centered design and improved literacy as important considerations for supporting the incorporation of these systems into chronic disease self-management, but the research did not test either factor as an intervention.

Participants viewed AI-based systems as supporting tools rather than substitutes for healthcare professionals. The technologies assisted with self-monitoring and decision support while supplementing, not replacing, engagement with conventional care. This was a qualitative account from nine patients in one Saudi city, so its findings cannot be treated as population-level estimates or as evidence that AI causes better health outcomes. Within that scope, the study identifies several reported influences on use: whether a tool is easy to operate, how patients understand and trust AI, and how well they can interpret health information. Its central finding is that technical access alone does not fully describe adoption; patients’ perceptions and digital health literacy also shape how AI-based tools fit into chronic disease self-management practices.

Subject of Research: Patient experiences of AI-based digital health tools and digital health literacy in chronic disease self-management

Article Title: Exploring patients’ experiences with artificial intelligence and digital health literacy in chronic disease self-management: a qualitative study

Article References: AL-Anazi, E. F., & Alyousef, S. M. (2026). Exploring patients’ experiences with artificial intelligence and digital health literacy in chronic disease self-management: a qualitative study. BMC Public Health. https://doi.org/10.1186/s12889-026-29711-0

Image Credits: AI Generated

DOI: 10.1186/s12889-026-29711-0

Keywords: artificial intelligence, digital health literacy, chronic disease, self-management, patient experience, qualitative research, health technology, smartphone health tools, Saudi Arabia, Riyadh, Exploring, patients