医学
护理部
护理人员
三级护理
人口
压力伤
家庭医学
第三层次
环境卫生
数学教育
数学
作者
Li Zhang,Shu-Nan Hu,Xu-Mei Yan,Yan Zhang,Wei Shen,Ye-Fen Han
出处
期刊:British journal of hospital medicine
[Mark Allen Group]
日期:2024-09-09
卷期号:: 1-16
标识
DOI:10.12968/hmed.2024.0226
摘要
Aims/Background The prevalence of pressure injuries (PIs) is a widely used clinical indicator of patient safety and quality of care. Nurses' understanding of pressure injury (PI) can significantly impact the treatment outcomes for patients. This study, based on latent profile analysis (LPA), reveals the characteristics associated with PI knowledge levels among clinical nurses in district and county tertiary medical institutions. We aim to help nursing managers formulate training plans accurately so that clinical nurses can provide high-level skin care services for patients. Method In June 2023, 1482 nurse staff from 4 tertiary general hospitals at the district and county level in Chengdu were chosen as research subjects using the convenience sampling method. Responses to the general information questionnaire, the Chinese Version of Pressure Ulcer Knowledge Assessment Tool (C-PUKAT), and the Chinese Version of Attitude towards Pressure ulcer Prevention (C-APuP) were used to compare the population's characteristics based on LPA. Results Three latent profiles of nurses’ PI knowledge were identified: weak foundation type (46.3%), strengthening foundation type (42.7%), and special improvement type (11.0%). Subjects’ departments, administrative positions, highest degrees and PI prevention attitude scores, as well as whether they have participated in the training, all differed significantly between latent profile groups (p < 0.05). Conclusion The PI knowledge level of nursing staff at the district and county tertiary general hospitals requires urgent improvement. Nursing managers should prioritize the management level and quality of PI training among clinical nursing staff. Precise training programs can be developed based on different categories of nursing staff to enhance their PI knowledge, thereby effectively improving the quality of healthcare for inpatients.
科研通智能强力驱动
Strongly Powered by AbleSci AI