Please use this identifier to cite or link to this item: https://www.um.edu.mt/library/oar/handle/123456789/145140
Title: Healthcare professionals' attitudes and perceptions of artificial intelligence use in critical care
Authors: Cilia, Robert (2026)
Keywords: Artificial intelligence
Critical care medicine
Medical personnel -- Malta -- Attitudes
Preparedness
Issue Date: 2026
Citation: Cilia, R. (2026). Healthcare professionals' attitudes and perceptions of artificial intelligence use in critical care (Master's dissertation).
Abstract: Background: Artificial intelligence (AI) is increasingly being applied in healthcare, including critical care settings. This study explored the perceptions, perceived benefits, challenges, attitudes, and readiness levels of critical care professionals in Malta regarding the integration of AI into clinical practice. Methodology: A convergent parallel mixed-methods design was adopted. Data was collected using the validated Shinners Artificial Intelligence Perception (SHAIP) questionnaire (n = 88) and eight semi-structured interviews with critical care professionals. Descriptive and inferential statistics were used to analyse demographic variables correlated with two factors; "Perceived Impact of AI", and "Preparedness for AI". Interview data was coded and thematically analysed. Findings Professionals expressed optimism about AI’s potential to enhance patient care, assistance in decision-making, and workload management, reflected in the Impact subscale mean score (M = 3.682). However, preparedness scores were lower (M = 3.267), with the lowest item (M = 1.64) being limited AI-specific training. Concerns centred on accountability, ethics, and data security, alongside infrastructural barriers such as handwritten documentation and underdeveloped digital systems. Mixed-methods analysis showed congruence on AI as an assistive tool and clinicians’ accountability, but mixed-methods analysis highlighted contrasting views on AI’s financial benefits and its potential to diminish the human touch in care. Conclusion: This research highlights that the integration of AI into critical care requires more than the adoption of new technologies. There is a necessity of sustained investment in training, education, institutional readiness, and clear ethical and legal guidance. This study highlights that successful AI adoption will depend on bridging the gap between perceived benefits and practical preparedness, ensuring that healthcare professionals are empowered and supported.
Description: M.Sc.(Melit.)
URI: https://www.um.edu.mt/library/oar/handle/123456789/145140
Appears in Collections:Dissertations - FacHSc - 2026
Dissertations - FacHScNur - 2026

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