Trust in AI-Supported Screening in General Practice Among Urban and Rural Citizens: Cross-Sectional Study

Area of Science:

• Medical Informatics
• Public Health
• General Practice

Background:

• Early disease detection is a key task in general practice.
• Artificial intelligence (AI) offers potential for early disease identification in primary care settings.
• General practitioners are frequently consulted, providing an opportunity for AI-enhanced screening.

Purpose of the Study:

• To evaluate public trust in AI-supported early detection measures within general practice.
• To compare trust levels between rural and urban populations.

Main Methods:

• A cross-sectional survey was conducted in Schleswig-Holstein, Germany (Nov-Dec 2023).
• 5000 adult residents from rural and urban areas were invited.
• Data were analyzed using descriptive statistics, subgroup analysis, and regression analysis.

Main Results:

• 44.0% viewed AI screening as modern medicine; 21.7% feared a negative impact on the physician-patient relationship.
• A positive attitude toward AI in medicine was the strongest predictor of trust in AI diagnoses (ß=0.420).
• Trust in physician diagnoses correlated with younger age and shorter waiting times for results.

Conclusions:

• Trust in general practitioner diagnoses significantly exceeds trust in AI applications (approx. 6:1 ratio).
• Despite concerns, about one-third anticipate an increased role for AI in healthcare.
• Fostering a positive perception of AI in medicine is crucial for its acceptance in early detection.