ArticlePatient preference and adherence2025
Knowledge, Attitudes, and Perceptions of Chronic Patients in Saudi Arabia Regarding the Use of Artificial Intelligence to Improve Medication Adherence.
Article in Patient preference and adherence, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 2 of them syntheses that pooled it.
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
6 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Pooled it
- Barriers and Facilitators to Patient Acceptance of Artificial Intelligence in Health Care: Systematic Review.Journal of medical Internet research · 2026Pooled it
- Assessment of the knowledge, attitudes, and practices of pharmacy students toward self-medication using artificial intelligence: a cross-sectional study.BMC medical education · 2026Article
- Knowledge, Attitude, and Practice of Chinese Parents Regarding Myopia in Children and Adolescents: A Cross-Sectional Study with Structural Equation Modeling.Patient preference and adherence · 2026Article
- AnFrontiers in psychiatry · 2026Article
- Artificial Intelligence in Medication Adherence: A National Assessment of Knowledge, Attitudes, and Perceptions Among Chronic Disease Patients in Jordan.Patient preference and adherence · 2026Article
Corrections and comments
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Authors and funding
11 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Artificial intelligence (AI) is advancing healthcare globally and in Saudi Arabia, enhancing patient care, diagnostics, and administrative efficiency, despite challenges such as data privacy and regulation. This study explores knowledge, attitudes, and perceptions (KAP) regarding AI in medication adherence among chronic patients in Makkah region, Saudi Arabia. Methods: A cross-sectional study was conducted among patients with chronic diseases in the Makkah region, Saudi Arabia, from 1 July to 31 December 2024. The study included adult patients with chronic diseases (≥18 years) receiving primary care in the Makkah region. KAP levels were analyzed using descriptive statistics and composite scores, with demographic associations evaluated through Pearson chi-square tests (p<0.05). Results: A total of 385 participants were included in the study. Most participants were women (60%), and those belonging to the 50 years or older group comprised the highest percentage (51.2%). The most reported chronic conditions were diabetes (30.7%), hypertension (19.7%), and asthma (14%). Knowledge levels were at a good level among 72.7% of the study participants, and 45.5% expressed a positive attitude towards AI's role. Perception was high among 50.9% of the respondents but low among 23.4%. Demographic factors, particularly age, significantly improved KAP (p-values of 0.048, 0.046, and 0.031, respectively). A positive attitude towards AI's role in medication adherence was observed in 58.2% of the participants with good knowledge levels compared to only 11.4% of those with poor knowledge (p=0.001). Variations in perception levels regarding AI's role in medication adherence were evident across demographics, with statistically significant associations found for age and overall knowledge level (p-values of 0.031 and 0.001, respectively). Conclusion: The results highlight AI's potential to enhance medication adherence and healthcare efficiency while maintaining a human-centred approach. To ensure effective integration, it's crucial to address concerns related to privacy, trust, and reduced human interaction. AI should be positioned as a supportive tool that complements-not replaces-human care, with transparent governance and targeted education playing key roles.
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