Work autonomy mediates associations between medical AI readiness and well being in a three wave nurse study.

内容摘要

This three-wave longitudinal study aimed to examine how medical artificial intelligence (AI) readiness impacts general well-being among nurses, focusing on the mediating role of work autonomy. The study further investigated potential reciprocal relationships among psychological readiness, motivational control, and well-being over time. A three-wave panel survey was administered at one-month intervals using validated instruments to measure medical AI readiness, perceived work autonomy, and general well-being. Data were collected from both clinical and educational departments of a major teaching hospital affiliated with a medical university in southwestern China, where smart healthcare systems and AI-powered technologies have been widely adopted. The final sample comprised 230 full-time registered nurses, each with at least one year of clinical experience and full participation across all three time points. Structural equation modeling (SEM) was conducted using AMOS 24.0 to test a full longitudinal mediation model. Measurement invariance and cross-lagged panel modeling were applied to assess autoregressive and reciprocal pathways. Indirect effects were examined via bootstrapping with 5,000 resamples and bias-corrected confidence intervals. Medical AI readiness significantly predicted general well-being both directly and indirectly through work autonomy, supporting a partial longitudinal mediation model. Specifically, higher readiness was associated with higher perceived autonomy over time, which in turn predicted higher well-being. Reciprocal pathways also emerged: general well-being predicted subsequent autonomy, and autonomy predicted later changes in AI readiness, indicating a dynamic feedback loop. All model fit indices met accepted thresholds, supporting the proposed structure. This study offers novel longitudinal evidence of a sequential and bidirectional mechanism linking technological readiness, workplace control, and well-being among nurses. Efforts to enhance nurses' readiness for AI integration should consider how perceptions of autonomy affect well-being outcomes and, conversely, how psychological well-being feeds back into motivational orientations and adaptation to innovation. Supportive leadership, inclusive technology design, and autonomy-enhancing strategies may interrupt maladaptive cycles and improve the human experience of digital transformation in healthcare.