Aim To determine differences in kinesiophobia levels among COPD patients at different time points 6 months after discharge;To identify potential subgroups of COPD patients who perceived different levels of kinesiophobia over time;and to evaluate differences in identified subgroups based on demographic and disease‐related characteristics Design An observational longitudinal study. Methods OPD patients hospitalized in respiratory department of a grade A hospital in Huzhou city from October 2021 to May 2022 were selected as the research objects. TSK scale was used to evaluate the level of kinesiophobia at discharge (T1), 1 month after discharge (T2), 4 months after discharge (T3) and 6 months after discharge (T4). The kinesiophobia level scores at different time points were compared using latent class growth modelling. ANOVA and Fisher's exact tests were used to test differences in demographic characteristics,and univariate analysis and multinomial logistic regression analysis were used to explore the influencing factors. Results During the first 6 months after discharge, kinesiophobia levels decreased significantly in the entire sample of COPD patients. The best‐fitting group‐based trajectory model described three distinctive trajectories: Low kinesiophobia group (31.4% of sample); Medium kinesiophobia group (43.4% of sample);and High kinesiophobia group (25.2% of sample). Logistic regression results showed that sex, age, course of disease, pulmonary function, education level, BMI, the level of pain, MCFS and mMRC were influencing factors of kinesiophobia trajectory in COPD patients ( p < 0.05).
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.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.