Suppr超能文献

基于互联网的支持性干预措施对痴呆患者家属的影响:系统评价和荟萃分析。

Internet-Based Supportive Interventions for Family Caregivers of People With Dementia: Systematic Review and Meta-Analysis.

机构信息

School of Nursing, Peking University, Beijing, China.

Peking University Health Science Centre for Evidence-Based Nursing: A Joanna Briggs Institute Affiliated Group, Beijing, China.

出版信息

J Med Internet Res. 2020 Sep 9;22(9):e19468. doi: 10.2196/19468.

Abstract

BACKGROUND

Caring for people with dementia is perceived as one of the most stressful and difficult forms of caring. Family caregivers always experience high levels of psychological burden and physical strain, so effective and practical support is essential. Internet-based supportive interventions can provide convenient and efficient support and education to potentially reduce the physical and psychological burden associated with providing care.

OBJECTIVE

This review aimed to (1) assess the efficacy of internet-based supportive interventions in ameliorating health outcomes for family caregivers of people with dementia, and (2) evaluate the potential effects of internet-based supportive intervention access by caregivers on their care recipients.

METHODS

An electronic literature search of the PubMed, EMBASE, Web of Science, CINAHL, Cochrane Library, and PsycINFO databases was conducted up to January 2020. Two reviewers (ML and YZ) worked independently to identify randomized controlled trials (RCTs) that met the inclusion criteria and independently extracted data. The quality of the included RCTs was evaluated using the approach recommended by the Cochrane Handbook for Systematic Reviews of Interventions. Standardized mean differences (SMDs) with 95% CIs were applied to calculate the pooled effect sizes.

RESULTS

In total, 17 RCTs met the eligibility criteria and were included in this systematic review. The meta-analysis showed that internet-based supportive interventions significantly ameliorated depressive symptoms (SMD=-0.21; 95% CI -0.31 to -0.10; P<.001), perceived stress (SMD=-0.40; 95% CI -0.55 to -0.24; P<.001), anxiety (SMD=-0.33; 95% CI -0.51 to -0.16; P<.001), and self-efficacy (SMD=0.19; 95% CI 0.05-0.33; P=.007) in dementia caregivers. No significant improvements were found in caregiver burden, coping competence, caregiver reactions to behavioral symptoms, or quality of life. Six studies assessed the unintended effects of internet-based supportive intervention access by caregivers on their care recipients. The results showed that internet-based supportive interventions had potential benefits on the quality of life and neuropsychiatric symptoms in care recipients.

CONCLUSIONS

Internet-based supportive interventions are generally effective at ameliorating depressive symptoms, perceived stress, anxiety, and self-efficacy in dementia caregivers and have potential benefits on care recipients. Future studies are encouraged to adopt personalized internet-based supportive interventions to improve the health of family caregivers and their care recipients.

TRIAL REGISTRATION

PROSPERO CRD42020162434; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=162434.

摘要

背景

照顾痴呆症患者被认为是压力最大和最困难的护理形式之一。家庭护理人员始终承受着较高的心理负担和身体压力,因此需要有效的实用支持。基于互联网的支持性干预措施可以为护理人员提供便捷有效的支持和教育,从而有可能减轻与提供护理相关的身体和心理负担。

目的

本综述旨在评估(1)基于互联网的支持性干预措施对改善痴呆症患者家庭护理人员健康结果的效果,以及(2)护理人员获得基于互联网的支持性干预措施对其护理对象的潜在影响。

方法

对 PubMed、EMBASE、Web of Science、CINAHL、Cochrane Library 和 PsycINFO 数据库进行了电子文献检索,检索截至 2020 年 1 月。两名审查员(ML 和 YZ)独立工作,以确定符合纳入标准的随机对照试验(RCT),并独立提取数据。使用 Cochrane 干预系统评价手册推荐的方法评估纳入 RCT 的质量。应用标准化均数差(SMD)和 95%置信区间(CI)计算汇总效应量。

结果

共有 17 项 RCT 符合纳入标准,并纳入本系统评价。荟萃分析表明,基于互联网的支持性干预措施可显著改善痴呆症护理人员的抑郁症状(SMD=-0.21;95%CI -0.31 至 -0.10;P<.001)、感知压力(SMD=-0.40;95%CI -0.55 至 -0.24;P<.001)、焦虑(SMD=-0.33;95%CI -0.51 至 -0.16;P<.001)和自我效能感(SMD=0.19;95%CI 0.05-0.33;P=.007)。护理人员负担、应对能力、对行为症状的反应或生活质量未见显著改善。有 6 项研究评估了护理人员获得基于互联网的支持性干预措施对其护理对象的意外影响。结果表明,基于互联网的支持性干预措施可能对护理对象的生活质量和神经精神症状有潜在益处。

结论

基于互联网的支持性干预措施通常可有效改善痴呆症护理人员的抑郁症状、感知压力、焦虑和自我效能感,并可能对护理对象有益。鼓励未来的研究采用个性化的基于互联网的支持性干预措施,以改善家庭护理人员及其护理对象的健康状况。

试验注册

PROSPERO CRD42020162434; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=162434。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/caac/7511858/02c0c4be32e5/jmir_v22i9e19468_fig1.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验