检查表
观察研究
比例(比率)
质量(理念)
心理学
描述性统计
感知
护理部
医学
家庭医学
地理
哲学
统计
地图学
数学
认识论
病理
神经科学
认知心理学
作者
Zhangyi Wang,Yang Yang,Yue Zhu,Mengru Liu,Xiqun Zhao,Luwei Xiao,Yajun Zhang,Facun Liang,Xiaoli Pang,Zhihua Yang,Huiying Weng
出处
期刊:Palliative & Supportive Care
[Cambridge University Press]
日期:2022-10-18
卷期号:21 (1): 108-117
被引量:4
标识
DOI:10.1017/s1478951522001237
摘要
Abstract Objectives To investigate the spiritual care needs and their attributes among Chinese elders hospitalized for severe chronic heart failure (CHF) based on the Kano model, in order to provide a reference for improving the quality and satisfaction of spiritual care. Methods An observational design was implemented, and the STROBE Checklist was used to ensure quality reporting of the study. The demographic characteristics questionnaire, the Nurse Spiritual Therapeutics Scale, and the Kano model–based Nurse Spiritual Therapeutics Attributes Scale were used. A convenience sample of 451 patients were selected from 2 hospitals. Descriptive statistics, and Kano model were used to analyze the data. Results The total score of spiritual care needs was 29.95 ± 7.51. Among the 12 items, 3 items were attractive attributes, all of which were located in Reserving Zone IV; 5 items were one-dimensional attributes, of which 3 were located in Predominance Zone I and 2 were located in Improving Zone II; 2 items were must-be attributes, all of which were located in Improving Zone II; and 2 items were indifference attributes, all of which were located in Secondary Improving Zone III. Significance of results The spiritual care needs among Chinese elders hospitalized for severe CHF were moderate. The must-be and one-dimensional attributes mainly focus on “creating a good atmosphere” and “sharing self-perception” dimensions, while attractive attributes mainly focus on “sharing self-perception” and “helping thinking” dimensions. It is suggested that hospital authority should develop and innovate attractive attributes on the basis of maintaining and perfecting must-be and one-dimensional attributes, and objectively analyze and optimize indifference attributes.
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