Attitudes And Expectations Toward Artificial Intelligence Among Swiss Primary Care Physicians A Cross-Sectional Survey Study 2024

Primary care artificial intelligence adoption among United States (US) physicians accelerated from 38% to 66% within one year. Implementation strategies typically assume physician resistance as the primary barrier; however, emerging evidence suggests a different challenge where enthusiastic adoption precedes adequate knowledge development. Aims: To assess physician readiness for AI implementation in organized primary care, including knowledge levels, attitudes, implementation priorities, and actual usage patterns among Swiss primary care physicians. Methods: Multicentric cross-sectional survey involving four regional subnetworks as study centers (Zurich, Bern, Ticino, Romandie) within mediX Switzerland, conducted August-September 2024. The mediX network comprises 900+ primary care physicians across three Swiss linguistic regions operating within a hybrid managed care model. Online survey of 620 primary care physicians yielding 155 analyzable responses (25.8% response rate). Analysis employed Wilson Score confidence intervals for proportions, Cohens h effect sizes, and sensitivity analyses addressing both non-response bias and knowledge threshold definitions. Results: A pronounced knowledge-attitude gap emerged among respondents. While 69.0% (95% CI: 61.4%-75.8%) expressed positive attitudes toward AI and 81.9% (95% CI: 75.1%-87.2%) sought training opportunities, only 14.8% (95% CI: 10.1%- 21.3%) self-assessed their knowledge as high or excellent (levels 4-5), our primary threshold for adequate knowledge. Even when including moderate self-assessed knowledge (level 3+), only 47.1% met this threshold, indicating a persistent 21.9 percentage point knowledge-attitude gap. Critically, 27.7% (95% CI: 21.3%-35.3%) already use AI tools for clinical purposes notwithstanding acknowledged competency gaps. Non-response sensitivity analyses suggest population-level training interest ranges from 20.5% to 81.3% depending on assumptions about non-responders. Physicians demonstrated clear implementation preferences: immediate priority for administrative support (80.0%) and image analysis (73.5%), medium-term priority for medication management (64.5%) and diagnostic support (61.9%), and long-term perspective for complex applications. Conclusions: Among AI-engaged physicians, this exploratory study reveals a substantial knowledge-attitude gap and documents current AI usage patterns that may precede formal knowledge acquisition. While selection bias limits generalizability, these findings suggest that educational interventions and governance frameworks merit urgent consideration in coordinated care settings where AI adoption is accelerating. What is already known on this topicAI adoption in primary care accelerated from 38% to 66% within one year, creating urgent need for readiness assessment Current implementation strategies assume physician resistance, though evidence suggests knowledge deficits may be a greater barrier Knowledge-attitude gaps have been reported across healthcare systems, but their magnitude and implications for patient safety remain poorly understood What this study addsReveals a 54.2 percentage point knowledge-attitude gap persistent across sensitivity analyses, indicating barriers stem from education infrastructure deficits rather than fundamental resistance Identifies unsupervised AI usage by 27.7% of physicians despite acknowledged knowledge limitations--a patient safety concern absent from previous implementation literature Establishes physician-consensus implementation hierarchy enabling systematic, evidence-based AI deployment: begin with administrative applications ([&ge;]70% support), progress to clinical support (50-69%), reserve complex applications (<50%) for mature phases