A Cross-sectional Study to Assess Knowledge and Attitude toward Artificial Intelligence among Healthcare Professionals

Abstract

INTRODUCTION: Artificial intelligence (AI) is crucial in the healthcare sector. It improves patient outcomes and service efficiency. Using machine learning, natural language processing, and computer vision, it helps clinicians personalize treatments. In addition, AI optimizes resources and addresses cost challenges. MATERIALS AND METHODS: A cross-sectional study was conducted to assess the knowledge and attitude toward AI among healthcare professionals. A convenience sampling technique was used to gather responses from healthcare professionals across various health settings in Punjab. Knowledge was assessed using a predesigned questionnaire comprising 30 multiple-choice questions, with correct responses awarded one mark and incorrect responses zero. Knowledge levels were categorized as good (21-30), average (11-20), and below average (≤10). Attitude was measured using a 20-item, five-point Likert scale, with reverse coding for negative items. Attitude scores ranged from 20 to 100 and were categorized as positive (81-100), neutral (51-80), or negative (20-50). RESULTS: Among healthcare professionals, 51.5% had below-average knowledge, 25.5% had average knowledge, and 23.0% had good knowledge. Regarding attitude, 56.4% were neutral, 24.2% were negative, and 19.4% were positive. The mean knowledge score was 13.36 ± 6.73, and the attitude score was 60.26 ± 17.60. Notably, a moderate positive correlation (P = 0.001) was found between knowledge and attitude. Furthermore, multinomial logistic regression analysis revealed that profession (P = 0.017) and education level (P = 0.020) were significant predictors of both knowledge and attitude levels. In addition, the most common use of AI and sex were significant predictors of attitude. CONCLUSION: The study highlights the need for improved AI education among healthcare professionals to enhance knowledge and positive attitudes.

Ähnliche Arbeiten