主管:国家卫生健康委员会
主办:国家卫生计生委医院管理研究所
中国科学引文数据库(CSCD)来源期刊
中国科技论文统计源期刊 中国科技核心期刊
《中文核心期刊要目总览》入选期刊

Chinese Nursing Management ›› 2022, Vol. 22 ›› Issue (2): 196-200.doi: 10.3969/j.issn.1672-1756.2022.02.007

• Research Papers • Previous Articles     Next Articles

Construction of predictive model of Inattentional Blindness in nursing

YANG Jing, FANG Qian, LENG Anming, LUO Meimei, MENG Tingting, LI Dejie, ZOU Min   

  1. Nursing Department, Guizhou Provincial People's Hospital, Guiyang, 550002, China
  • Online:2022-02-15 Published:2022-02-15
  • Contact: E-mail:969824080@qq.com

Abstract: Objective: To analyze the relationship between perceptual load, attentional set, negative emotion and nursing Inattentional Blindness (IB) by establishing a predictive model of the influencing factors of IB in nursing. Methods: From June to July 2020, 976 nurses from three tertiary general hospitals in Guiyang were selected by convenience sampling method. The status and the influencing factors of nurses' IB were investigated. The structural equation model was used to analyze the roles of nurses' perceptual load, attentional set and negative emotions in the emerging of nursing IB. Results: Attentional set, perceptual load, and negative emotions positively affected IB, with an interpretation rate of 70.2%. The total effect of perceptual load on IB was 0.435, the direct effect was 0.196, and mediation effect was 0.239, accounting for 54.9%. The total effect of attentional set on IB was 0.434, direct effect was 0.234, and mediation effect was 0.200, accounting for 46.1%. Conclusion: Perceptual load, attentional set and negative emotions are the direct influencing factors of nursing IB, while negative emotions play an intermediary effect between perceptual load, attentional set and the occurrence of IB in nursing, and have a positive correlation predictive effect. The results of this study provide a theoretical basis for the targeted prevention of the occurrence of nursing IB in the future.

Key words: Inattentional Blindness; nursing; structural equation model; predictive model

CLC Number: R47