Effects of dyadic care interventions for heart failure on patients' and caregivers' outcomes: A systematic review, meta-analysis and meta-regression

被引:1
|
作者
Yu, Doris Sau-fung [1 ]
Qiu, Chen [1 ]
Li, Polly Wai Chi [1 ]
Lau, Jason [1 ]
Riegel, Barbara [2 ]
机构
[1] Univ Hong Kong, Li Ka Shing Fac Med, Sch Nursing, Hong Kong, Peoples R China
[2] Univ Penn, Sch Nursing, Philadelphia, PA USA
关键词
Heart failure; Dyadic care; Family caregivers; Self-care; Hospital admission; Mortality; RANDOMIZED CONTROLLED-TRIAL; QUALITY-OF-LIFE; SELF-CARE; EDUCATION INTERVENTIONS; HOSPITAL READMISSION; FAMILY PARTNERSHIP; CLINICAL-TRIAL; SUPPORT; BURDEN; MANAGEMENT;
D O I
10.1016/j.ijnurstu.2024.104829
中图分类号
R47 [护理学];
学科分类号
1011 ;
摘要
Background: The contemporary model for managing heart failure has been extended to a patient-family caregiver dyadic context. However, the key characteristics of the model that can optimise health outcomes for both patients and caregivers remain to be investigated. Objectives: This study aimed to identify the effects of dyadic care interventions on the behavioural, health, and health-service utilisation outcomes of patients with heart failure and their family caregivers and to explore how the intervention design characteristics influence these outcomes. Design: This study involved systematic review, meta-analysis, and meta-regression techniques. Methods: We performed a systematic review and meta-analysis, using 12 databases to identify randomised controlled trials or quasi-experimental studies published in English or Chinese between database inception and 31 December 2022. The considered interventions included those targeting patients with heart failure and their family caregivers to enhance disease management. Data synthesis was performed on various patient- and caregiver-related outcomes. The identified interventions were categorised according to their design characteristics for subgroup analysis. Meta-regression was performed to explore the relationship between care delivery methods and their effectiveness. Results: We identified 48 studies representing 9171 patient-caregiver dyads. Meta-analyses suggested the positive effects of dyadic care interventions on patients' health outcomes [Hedges' g (95 % confidence interval {CI}): heart failure knowledge = 1.0 (0.26, 1.75), p = 0.008; self-care confidence = 0.45 (0.08, 0.83), p = 0.02; selfcare maintenance = 1.12 (0.55, 1.70), p < 0.001; self-care management = 1.01 (0.54, 1.49), p < 0.001; anxiety = -0.18 (-0.34, -0.02), p = 0.03; health-related quality of life = 0.30 (0.08, 0.51), p < 0.001; hospital admission (risk ratio {95 % CI}: hospital admission = 0.79 (0.65, 0.97), p = 0.007; and mortality = 0.58 (0.36, 0.93), p = 0.02)]. Dyadic care interventions also improved the caregivers' outcomes [Hedges' g (95 % CI): social support = 0.67 (0.01, 1.32), p = 0.05; perceived burden = -1.43 (-2.27, -0.59), p < 0.001]. Although the design of the identified care interventions was heterogeneous, the core care components included enabling and motivational strategies to improve self-care, measures to promote collaborative coping within the care dyads, and nurse-caregiver collaborative practice. Incorporating the first two core components appeared to enhance the behavioural and health outcomes of the patients, and the addition of the last component reduced readmission. Interventions that engaged both patients and caregivers in care provision, offered access to nurses, and optimised continuity of care led to better patient outcomes. Conclusions: These findings demonstrate that dyadic care interventions can effectively improve disease management in a family context, resulting in better health outcomes for both patients and caregivers. Additionally, this study provides important insights into the more-effective design characteristics of these interventions. Registration number: The review protocol was registered in the PROSPERO International Prospective Register of Systematic Reviews (CRD42022322492). (c) 2024 Elsevier Ltd. All rights are reserved, including those for text and data mining, AI training, and similar technologies.
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页数:13
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