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Navigating AI unpredictability: Exploring technostress in AI-powered healthcare systems

Author

Listed:
  • Helmi Issa

    (BSB - Burgundy School of Business (BSB) - ESC Dijon-Bourgogne, CEREN - Centre de Recherche sur les Entreprises - BSB - Burgundy School of Business (BSB) - ESC Dijon-Bourgogne)

  • Jad Jaber

    (LAU - Lebanese American University)

  • Hussein Lakkis

    (AU - Antonine University = Université Antonine)

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.

Suggested Citation

  • Helmi Issa & Jad Jaber & Hussein Lakkis, 2024. "Navigating AI unpredictability: Exploring technostress in AI-powered healthcare systems," Post-Print hal-05841861, HAL.
    • Handle: RePEc:hal:journl:hal-05841861
    DOI: 10.1016/j.techfore.2024.123311
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