AI Technology Acceptance, Decent Work Perception, and Job Crafting Among Nurses: A Three-Wave Cross-Lagged Study

IF 3.7 3区医学 Q1 NURSING

International Nursing Review Pub Date : 2026-01-13 DOI:10.1111/inr.70150

Juntong Jing, Yongkang Fu, Dongrun Liu, Zhengyi Ma, Hangna Qiu, Huanhuan Zhang, Jie Liu, Chaoran Chen

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引用次数: 0

Abstract

Aim

To examine how nurses’ acceptance of artificial intelligence influences job crafting over time and to explore the longitudinal mediating role of decent work perception in this relationship.

Background

The integration of artificial intelligence into clinical settings is accelerating, yet its impact on nurses’ proactive work behaviors remains underexplored. Understanding the mechanisms through which artificial intelligence acceptance affects job crafting is critical for optimizing workforce adaptation.

Methods

This longitudinal study employed a three-wave cross-lagged panel design. A total of 598 nurses from six tertiary hospitals in China completed surveys on artificial intelligence acceptance, decent work perception, and job crafting over a six-month period. Structural equation modeling and bootstrap analysis were used to test longitudinal mediation.

Results

Artificial intelligence acceptance showed declining stability over time, while decent work perception increased, and job crafting stabilized. Cross-lagged analyses revealed that artificial intelligence acceptance positively predicted job crafting both directly and indirectly via enhanced decent work perception. The mediating effect accounted for over one-quarter of the total effect.

Discussion

These findings challenge static views of technology adoption, suggesting that artificial intelligence implementation triggers dynamic psychological and behavioral responses among nurses.

Conclusion

Early acceptance of artificial intelligence technology significantly predicts subsequent job crafting, both directly and through the mediating role of decent work perception.

Implications for nursing

Enhancing nurses’ early acceptance of artificial intelligence and strengthening their perception of decent work may foster more proactive job crafting behaviors.

Implications for Nursing Policy

Nurse managers and policymakers should incorporate psychological support and dignity-enhancing strategies into artificial intelligence integration plans. By adopting these approaches, nursing leaders can foster nurses’ adaptive behaviors, improve job satisfaction, and ultimately enhance patient care outcomes, thereby promoting long-term workforce sustainability.

查看原文本刊更多论文

护士对人工智能技术的接受、体面工作的感知和工作的塑造：一项三波交叉滞后研究。

目的：研究护士对人工智能的接受程度如何随着时间的推移影响工作制作，并探讨体面工作感知在这种关系中的纵向中介作用。背景：人工智能与临床环境的融合正在加速，但其对护士主动工作行为的影响仍未得到充分探讨。了解人工智能接受度影响工作制定的机制对于优化劳动力适应至关重要。方法：本研究采用三波交叉滞后面板设计。在六个月的时间里，来自中国六家三级医院的598名护士完成了关于人工智能接受度、体面工作感知和工作塑造的调查。采用结构方程模型和自举分析对纵向中介效应进行检验。结果：随着时间的推移，人工智能的接受度呈现出下降的稳定性，而体面工作的认可度上升，工作制作趋于稳定。交叉滞后分析显示，人工智能的接受程度直接或间接地通过提高体面工作的认可度来积极预测工作的形成。中介效应占总效应的四分之一以上。讨论：这些发现挑战了技术采用的静态观点，表明人工智能的实施引发了护士的动态心理和行为反应。结论：早期接受人工智能技术可以直接或通过体面工作感知的中介作用显著预测随后的工作塑造。对护理的影响：提高护士对人工智能的早期接受程度，加强他们对体面工作的看法，可能会促进更积极主动的工作创造行为。对护理政策的影响：护士管理者和政策制定者应将心理支持和尊严提升策略纳入人工智能整合计划。通过采用这些方法，护理领导者可以培养护士的适应行为，提高工作满意度，最终提高患者护理效果，从而促进长期的劳动力可持续性。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

International Nursing Review 医学-护理

CiteScore

7.90

自引率

7.30%

发文量

审稿时长

6-12 weeks

期刊介绍： International Nursing Review is a key resource for nurses world-wide. Articles are encouraged that reflect the ICN"s five key values: flexibility, inclusiveness, partnership, achievement and visionary leadership. Authors are encouraged to identify the relevance of local issues for the global community and to describe their work and to document their experience.