 Navigating AI unpredictability: Exploring technostress in AI-powered healthcare systemsHelmi Issa, Jad Jaber and Hussein Lakkis Technological Forecasting and Social Change, 2024, vol. 202, issue C Abstract: The adoption of AI-powered systems in healthcare has revolutionized the field by introducing autonomous diagnostics and predictions, though it remains a source of debate due to its disruptive nature. This research utilizes the holistic model of stress to empirically examine the effects of six techno-stressors on both techno-eustress and techno-distress among users in the healthcare sector. Data for this research was collected from 224 participants through an e-survey distributed across diverse sources. The findings reveal intriguing insights, highlighting the emergence of techno-unpredictability as a potential new techno-stressor within the context of AI-powered systems in healthcare. With this newfound understanding, healthcare specialists and organizations can stay one step ahead, better equipped to address and navigate the complexities of emerging stressors for enhanced well-being, patient care and safety. Keywords: AI-powered systems; Healthcare; Techno-stressors; Techno-unpredictability (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:eee:tefoso:v:202:y:2024:i:c:s0040162524001070 DOI: 10.1016/j.techfore.2024.123311 Access Statistics for this article Technological Forecasting and Social Change is currently edited by Fred Phillips More articles in Technological Forecasting and Social Change from Elsevier |
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