Nurse-led self-care interventions for older adults with multiple chronic conditions: A protocol for a systematic review and network meta-analysis

被引:1
|
作者
Choi, Heejung [1 ,2 ]
Seomun, Gyeongae [1 ,2 ]
机构
[1] Korea Univ, Coll Nursing, Seoul, South Korea
[2] Korea Univ, Grad Sch, Transdisciplinary Major Learning Hlth Syst, Seoul, South Korea
来源
PLOS ONE | 2024年 / 19卷 / 01期
关键词
MANAGEMENT; DISEASE; PEOPLE;
D O I
10.1371/journal.pone.0298082
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
The importance of self-care interventions is progressively recognized, marked by a rapidly aging population that results in growing demands on costly tertiary and institutional care services, placing substantial pressure on health and social care systems. Against this background, in this study, we will provide evidence for the impact of self-care interventions on health-related quality of life by focusing on interventions led by nurses who can employ integrated approaches. Several databases, including Ovid MEDLINE, Cochrane, CINAHL, Embase, and PubMed, will be searched along with gray literature to prevent biased results. There will be no time restrictions, and all literature with English abstracts will be included. Using the Template for Intervention Description and Replication framework, we will evaluate intervention characteristics. The primary outcome will be health-related quality of life, and the secondary outcomes will be symptom burden, physical function, and cost-effectiveness. Pairwise and network meta-analyses will be performed, and network geometry and the surface under the cumulative ranking curve will be used to determine which type of nurse-led self-care intervention is best for health-related quality of life for older adults with multiple chronic conditions. We will secure study quality through PRISMA, AMSTAR 2, RoB 2.0, and the GRADE checklist. To ensure the quality of network meta-analysis, similarity will be checked based on the PICO framework. The consistency of the network meta-analysis results will be checked to ensure transitivity by using the Bayesian hierarchical framework. The study protocol is registered with PROSPERO (CRD42022365467).
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页数:12
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