In recent years, the increasing number of empty-nest elderly has become a significant global social problem, and the rapid development of medical technology and information technology has improved the feasibility of telenursing. However, few studies have been conducted on needs of telenursing among the empty-nest elderly. The aim of this study is to explore the needs of telenursing for community-dwelling empty-nest elderly who are completely independent in activities of daily living (ADL), or who are mildly disabled, and to provide a reference for improving the remote care quality. A questionnaire survey aiming to explore telenursing needs of the elderly was conducted among 268 community-dwelling empty-nest elderly who were selected using random sampling and then data were analyzed based on the Kano Model. Chi-square goodness-of-fit test showed that there were significant differences between actual and expected counts for each item of telenursing needs ( < 0.01 for all), indicating that the sample had specific individual preference for the Kano category. The desired degree of telenursing service ranged from 48.37% to 80.86%, the better values (satisfaction) were between 57.09% and 67.56%, and the worse values (dissatisfaction) were between 11.92% and 37.93%. The items, remote one-button emergency caller and remote emergency assistance arrangement, were considered to be one-dimensional qualities by empty nesters and the rest were attractive qualities. In the quadrant analysis diagram, all the remote care services were categorized as attractive qualities. The community-dwelling empty-nest elderly with ADL independence or mild impairment have positive attitudes toward telenursing services, especially the needs of remote first aid nursing. Medical policy makers and nursing managers can provide targeted telenursing services according to empty nesters' requirements, thus improving nursing care quality and satisfaction of the elderly.
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http://dx.doi.org/10.1089/tmj.2020.0037 | DOI Listing |
BMC Geriatr
December 2024
Department of Nursing, Daqing Campus, Harbin Medical University, 39 Xinyang Road, Daqing, 163319, China.
Objectives: This study aimed to examine Intrinsic Capacity (IC) subgroups and the association of IC subgroups with IC predictors in Chinese urban empty nesters.
Methods: A convenient sample of 385 older adults aged 60 and above in Community Health Service Center was recruited from Hei Longjiang Province, China, between June 2023 and December 2023. Latent class Analysis (LCA) was conducted to explore IC subgroups using the sensory, cognition, locomotion, psychological, and vitality domains of IC as input variables.
Front Public Health
December 2024
The Affiliated Wenzhou Kangning Hospital, Wenzhou Medical University, Wenzhou, Zhejiang, China.
BMC Public Health
November 2024
Center of Experimental Economics in Education, Shaanxi Normal University, No. 620 West Chang'an Street, Chang'an District, Xi'an, Shaanxi Province, 710119, China.
Background: With the intensification of aging, depression among the older adults has become a significant global health challenge, especially in developing countries where the problem is particularly severe. This study aims to explore the association between living arrangements and depression, with a specific focus on examining the mediating role of social support in rural northwest China.
Methods: Data were collected from 501 individuals aged 60 and above in rural Shaanxi Province, northwest China.
Adv Life Course Res
December 2024
University of Erlangen-Nuremberg, Findelgasse 7/9, 90402 Nuremberg Germany. Electronic address:
This article investigates the effect of adult children leaving the parental home on parental well-being. Adult children moving out is an important event in parents' lives. However, it is theoretically unclear whether parental well-being decreases or increases from children moving out.
View Article and Find Full Text PDFBMC Geriatr
October 2024
School of Economics and Management, Xidian University, No. 266 Xinglong Section of Xifeng Road, Chang'an District, Xi'an, 710126, China.
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