ArticleCureus2023
Barriers and Facilitators of Artificial Intelligence in Family Medicine: An Empirical Study With Physicians in Saudi Arabia.
Article in Cureus, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
8 citing papers in PubMed, 1 synthesis or guideline pooled it, 12 citations in OpenAlex.
- Pooled it
- Drivers of Artificial Intelligence (AI) Adoption in Supporting Chronic Disease Management in Primary Care: A Scoping Review.Nursing reports (Pavia, Italy) · 2026Review
- From facilitating conditions to intention to use internet hospitals among doctors: multiple mediators of perceived risk and performance expectancy.BMC health services research · 2026Article
- AI and Primary Care: Scoping Review.Journal of medical Internet research · 2025Article
- Enhancing Healthcare for People with Disabilities Through Artificial Intelligence: Evidence from Saudi Arabia.Healthcare (Basel, Switzerland) · 2025Article
- Exploring Opportunities and Challenges of AI in Primary Healthcare: A Qualitative Study with Family Doctors in Lithuania.Healthcare (Basel, Switzerland) · 2025Article
- Adoption of Artificial Intelligence in Rehabilitation: Perceptions, Knowledge, and Challenges Among Healthcare Providers.Healthcare (Basel, Switzerland) · 2025Article
- Theoretical appraisal of explanatory paradigms for artificial intelligence usage by medical doctors.Digital healthReview
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
12 authors at 5 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundArtificial intelligence (AI) is a novel technology that has been widely acknowledged for its potential to improve the processes' efficiency across industries. However, its barriers and facilitators in healthcare are not completely understood due to its novel nature. STUDY PURPOSE: The purpose of this study is to explore the intricate landscape of AI use in family medicine, aiming to uncover the factors that either hinder or enable its successful adoption.
methodsA cross-sectional survey design is adopted in this study. The questionnaire included 10 factors (performance expectancy, effort expectancy, social influence, facilitating conditions, behavioral intention, trust, perceived privacy risk, personal innovativeness, ethical concerns, and facilitators) affecting the acceptance of AI. A total of 157 family physicians participated in the online survey.
resultsEffort expectancy (μ = 3.85) and facilitating conditions (μ = 3.77) were identified to be strong influence factors. Access to data (μ = 4.33), increased computing power (μ = 3.92), and telemedicine (μ = 3.78) were identified as major facilitators; regulatory support (μ = 2.29) and interoperability standards (μ = 2.71) were identified as barriers along with privacy and ethical concerns. Younger individuals tend to have more positive attitudes and expectations toward AI-enabled assistants compared to older participants (p < .05). Perceived privacy risk is negatively correlated with all factors.
conclusionAlthough there are various barriers and concerns regarding the use of AI in healthcare, the preference for AI use in healthcare, especially family medicine, is increasing.
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What OpenQuestion holds
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 OpenQuestion graph.