Investigation of artificial intelligence anxiety among healthcare workers in Family Health Centers in Uşak province

Objective: The growing adoption of artificial intelligence (AI) technologies in healthcare has introduced new anxieties for professionals. In primary care—where AI applications are often first encountered and healthcare workers interact with AI both in clinical decision-making and administrative tasks—this can generate uncertainty about their professional roles and patient relationships. This study therefore aimed to determine the level of AI-related anxiety among healthcare workers serving in Uşak Province's family health centers and to examine its associations with demographic, professional, and cognitive-attitudinal variables. Materials and Methods: This descriptive cross-sectional study was conducted between November 1, 2024, and February 1, 2025, in family health centers located in Uşak. The study sample comprised 164 healthcare professionals who voluntarily consented to participate and completed the questionnaire in full. Data were collected through a structured two-part face-to-face survey. The first part included questions related to participants' demographic and occupational characteristics, as well as their attitudes toward AI. The second part contained the "Artificial Intelligence Anxiety Scale." Data were analyzed using SPSS 30.0. Normal distribution was assessed with the Kolmogorov–Smirnov test. Independent sample t-tests were used for binary group comparisons, One-way ANOVA (with Tukey HSD post-hoc) for comparisons involving three or more groups, and Chi-square with Z-Test for Proportions (with Bonferroni Correction) for categorical variables. Statistical significance was set at p < 0.05. Results: A total of 164 healthcare professionals working in Family Health Centers (FHCs) participated in this study. The majority of participants were family physicians, women, and married individuals, with most holding a bachelor's degree. Although only 24.4% (n=40) reported using AI applications or tools, a significantly higher proportion—70.7% (n=116)—expressed interest in developments related to AI. Additionally, 67.7% (n=111) believed that medical AI would have positive impacts in FHCs. Male healthcare professionals, those with postgraduate education, and family physicians showed significantly higher levels of both AI tool usage and interest in AI developments. While overall AI anxiety levels were measured as moderate, the highest anxiety was observed in the "sociotechnical blindness" subdimension. Compared to family physicians, midwives and emergency medical technicians reported significantly higher anxiety levels in the "job displacement" subdimension (p=0.034). Participants who were not interested in AI developments exhibited significantly higher total AI anxiety and learning anxiety scores than those who were interested (p=0.016 and p<0.001, respectively). Furthermore, individuals who held negative views regarding the implementation of medical AI in FHCs had significantly higher scores across both the total anxiety scale and all its subdimensions compared to those with neutral or positive views. Conclusion: The results indicate that beyond demographic background and professional experience, individuals' attitudes toward AI play a decisive role in shaping their anxiety levels. These findings suggest that for the successful integration of AI in primary healthcare, training programs should not only focus on technical competence and information dissemination but also include psychological and cultural interventions aimed at fostering positive perceptions and attitudes toward AI among healthcare workers. Such approaches may reduce practitioners' AI-related anxiety and maximize the benefits of technology for the quality and efficiency of patient care. Keywords: Artificial intelligence anxiety, primary healthcare services, family medicine.