Gain or Drain? A Qualitative Study on the Double-Edged Sword Effect of Artificial Intelligence Application in Clinical Nurses Based on the Job Demands-Resources Model
ABSTRACT
Background:
Artificial intelligence (AI) is rapidly transforming clinical nursing, promising administrative relief and decision support. However, the frontline reality presents a "double-edged sword" effect, where technological empowerment is frequently offset by novel occupational burdens and technostress.
Objective:
To theoretically deconstruct the bidirectional impacts of AI application among clinical nurses and identify moderating buffers, utilizing the Job Demands-Resources (JD-R) theoretical framework.
Methods:
A descriptive qualitative study was conducted across multiple general hospitals in mainland China. Using maximum variation and purposive sampling, semi-structured in-depth interviews were conducted with registered nurses who actively utilize clinical AI systems. Data were analyzed using Directed Qualitative Content Analysis guided by the predefined JD-R constructs.
Results:
The analysis revealed three overarching domains comprising 9 main themes and 24 sub-themes. On the gain path (job resources), AI empowered nurses through a workflow efficiency leap, clinical cognitive empowerment, and professional capital appreciation. Conversely, the drain path (job demands) exposed severe hidden costs, conceptualized as cognitive impediment, relational attrition, and digital involution driven by performance inflation and competitive perfectionism. The interplay between these pathways was significantly buffered by moderating mechanisms, specifically nurses' proactive coping strategies, professional boundary demarcation, and the provision of a cohesive organizational support architecture.
Conclusions:
The impact of AI integration in nursing is not technologically deterministic. While AI acts as a robust cognitive and operational resource, it concurrently generates intense digital demands. To prevent AI from devolving into an occupational hazard, healthcare administrators must transcend mere algorithmic deployment by establishing clear clinical governance, providing advanced AI literacy training, and fiercely protecting the irreplaceable humanistic core of clinical care. Clinical Trial: Not Applicable
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