Natural Sciences

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https://hdl.handle.net/20.500.11888/18293

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Browsing Natural Sciences by Author "Abdullahو Nour Eddine Adeeb Muhammad"

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    FACTORS INFLUENCING THE ADOPTION OF ARTIFICIAL INTELLIGENCE TOOLS IN PALESTINIAN HEALTHCARE SECTOR: AN EMPIRICAL STUDY
    (An-Najah National University, 2025-08-26) Abdullahو Nour Eddine Adeeb Muhammad
    Recent years have witnessed rapid growth in the application of artificial intelligence (AI) in the healthcare sector. However, some developing countries, such as Palestine, have not seen significant interest in this field. This study aims to explore the key factors and barriers affecting the adoption of AI technologies in the Palestinian healthcare sector, focusing on the levels of trust and ethical concerns faced by healthcare workers. The Technology Acceptance Model (TAM) was adopted as the primary framework for explaining behaviors, given its ability to analyze the impact of perceived ease of use (PE) and perceived usefulness (PU) on intentions to use. To gain a deeper understanding of technology adoption behavior, a mixed-methods approach was adopted, combining qualitative and quantitative methods (Venkatesh et al., 2016). The qualitative phase included semi-structured interviews with a group of physicians and healthcare professionals. The transcripts were analyzed using NVivo 14 software, employing coding and thematic analysis to identify key themes related to awareness, biases, and ethical barriers. The quantitative phase used a structured questionnaire distributed to a random sample of 186 participants from Palestinian hospitals, clinics, and healthcare institutions. The questionnaire was designed based on validated and reliable measures, and the data were analyzed using partial least squares structural equation modeling (PLS-SEM). The results showed that AI adoption is primarily influenced by organizational and ethical factors. In enhancing overall performance through PE, institutional pressure (IP), legal compliance, and ethical concern (EA) played a significant role, while financial readiness (FR) and top management support (TMS) had no significant impact. The results indicate that the availability of resources or management support, while important, are not sufficient on their own to boost trust or improve adoption intentions. The study also revealed that practical experience, quality of training, and external incentives play a crucial role in shaping healthcare professionals' perceptions of AI systems. This study helps bridge the knowledge gap by examining the Palestinian reality, which faces resource and institutional challenges and is unique in this regard. It offers practical insights for enhancing self-awareness, reducing biases, and improving ethical decision-making regarding AI applications in the healthcare sector. Its findings offer valuable recommendations for policymakers, clinicians, and technology developers on how to accelerate the adoption of these technologies and optimize their use in similar resource-limited settings.