Exploring Artificial Intelligence in Respiratory Therapy: Insights on Knowledge, Perception, and Practices

Abstract

Background: AI is revolutionizing healthcare by leveraging big data to enhance medical diagnosis, treatment planning, and patient monitoring, notably in respiratory care. Understanding respiratory care professionals’ perspectives is crucial for successful AI integration. This cross-sectional study evaluates the knowledge, perceptions, and practices of respiratory care professionals in Saudi Arabia regarding AI use in their field. Methods: An online survey, distributed via email, professional associations, and online platforms, collected data from 448 participants, including respiratory therapists, educators, students, and specialists. The questionnaire covered socio-demographics, knowledge, perception, and current AI-related practices. Results: Indicated that 51% of respondents were female, predominantly aged 20-25 (54%), holding bachelor’s degrees (69%), and with 0-5 years of experience (73%). While 28% were familiar with AI, only 8.5% had practical experience. Gender-based disparities in knowledge were significant (P < .001). Perceptions of AI varied: 26% expressed enthusiasm, 25% acknowledged challenges, and 59% supported incorporating AI fundamentals into the curriculum. Self-learning was a key knowledge source for 34% of participants. A majority (51%) believed AI would be pivotal in respiratory care, with 55% foreseeing significant impacts. Organizational readiness was highlighted, with 41% reporting dedicated AI personnel. Key obstacles included knowledge gaps (23%) and skill development (23%), followed by inadequate university training (17%) and access to quality education (15%). AI applications were deemed essential in research (19%), critical care (18%), image interpretation (17%), and quality control (15%). Conclusions: This study observed varying degrees of knowledge and perception towards AI in respiratory therapy. It highlights the recognition of AI’s importance among professionals, while also pointing out significant challenges like knowledge gaps and organizational readiness. AI application varies by gender and experience, suggesting the need for tailored education and training. Addressing these issues through comprehensive AI education and strategic planning can enhance respiratory care delivery and outcomes. Bridging these gaps is crucial to fully realize AI’s potential in advancing respiratory care practice.Perception toward integrating AI into RC practiceResponsible for AI in Education, Research, Innovation and Research

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