基于Kales概念模型的护理干预对痴呆患者激越行为的影响
Impact of nursing interventions based on Kales conceptual model on agitated behaviours of dementia patients
杜红娣 1王薇 1何志娟 1薄琳1
作者信息
- 1. 中国医学科学院北京协和医院保健医疗部,北京,100730
- 折叠
摘要
目的 探讨基于Kales概念模型的护理干预对痴呆患者激越行为的影响.方法 选取 2021 年 12 月至 2022 年12 月在北京市某三级甲等综合医院老年科住院的 80 例痴呆患者作为研究对象.采用随机数字表法将患者分为对照组和观察组.对照组(n=40)接受常规护理,观察组(n=40)在常规护理的基础上实施基于Kales概念模型的护理干预,分别比较干预前、干预 2w后、干预 4w后两组患者激越行为及生活质量.结果 重复测量方差分析显示,两组患者干预 3 个时间点激越行为得分和生活质量得分的时间效应、组间效应和交互效应比较,差异具有统计学意义(均P<0.05).干预后观察组患者激越行为得分均低于对照组,两组比较,差异具有统计学意义(P<0.001).干预后观察组患者生活质量得分均高于对照组,两组比较,差异有统计学意义(P<0.01).结论 基于Kales概念模型的护理干预有助于改善痴呆患者激越行为,提高痴呆患者生活质量.
Abstract
Objective To investigate the impact of nursing interventions based on Kales conceptual model on agitated behaviours of dementia patients.Methods A total of 80 dementia patients were randomly divided into two groups using a random number table.Patients in the control group(n=40)received routine care,while those in the observation group(n=40)received the nursing interventions based on Kales concept model on top of the routine care.The agitated behaviours and quality of life of the two groups were compared before,2 weeks and 4 weeks after the intervention.Results The repeated measures ANOVA showed statistically significant differences in three time points in terms of the time effect,inter-group effect and interactive effects on the scores of agitations and quality of life(all P<0.05).After the intervention,the score of agitations in the observation group was significantly lower than that of the control group(P<0.05),and the score of quality of life in the observation group was significantly higher than that in the control group(P<0.05).Conclusion The nursing interventions based on Kales conceptual model is effective in reducing agitations of dementia patients and improving the quality of life.
关键词
Kales概念模型/痴呆/精神行为症状/激越行为Key words
Kales conceptual model/dementia/behavioural and psychological symptoms/agitation引用本文复制引用
基金项目
中国医学科学院医学与健康科技创新工程项目(2020-I2M-C&T-B-008)
中央保健科研课题(2020YB22)
北京协和医院护理科研课题(XHHLKY202116)
出版年
2024
NETL
NSTL
万方数据