McCabe Catherine, McCann Margaret, Brady Anne Marie
School of Nursing and Midwifery, Trinity College Dublin, Dublin, Ireland.
Cochrane Database Syst Rev. 2017 May 23;5(5):CD011425. doi: 10.1002/14651858.CD011425.pub2.
BACKGROUND: Chronic obstructive pulmonary disease (COPD) is characterised by airflow obstruction due to an abnormal inflammatory response of the lungs to noxious particles or gases, for example, cigarette smoke. The pattern of care for people with moderate to very severe COPD often involves regular lengthy hospital admissions, which result in high healthcare costs and an undesirable effect on quality of life. Research over the past decade has focused on innovative methods for developing enabling and assistive technologies that facilitate patient self-management. OBJECTIVES: To evaluate the effectiveness of interventions delivered by computer and by mobile technology versus face-to-face or hard copy/digital documentary-delivered interventions, or both, in facilitating, supporting, and sustaining self-management among people with COPD. SEARCH METHODS: In November 2016, we searched the Cochrane Airways Group Specialised Register (CAGR), which contains trial reports identified through systematic searches of bibliographic databases including the Cochrane Central Register of Controlled Trials (CENTRAL), MEDLINE, Embase, CINAHL, AMED, and PsycINFO, and we handsearched respiratory journals and meeting abstracts. SELECTION CRITERIA: We included randomised controlled trials that measured effects of remote and Web 2.0-based interventions defined as technologies including personal computers (PCs) and applications (apps) for mobile technology, such as iPad, Android tablets, smart phones, and Skype, on behavioural change towards self-management of COPD. Comparator interventions included face-to-face and/or hard copy/digital documentary educational/self-management support. DATA COLLECTION AND ANALYSIS: Two review authors (CMcC and MMcC) independently screened titles, abstracts, and full-text study reports for inclusion. Two review authors (CMcC and AMB) independently assessed study quality and extracted data. We expressed continuous data as mean differences (MDs) and standardised mean differences (SMDs) for studies using different outcome measurement scales. MAIN RESULTS: We included in our review three studies (Moy 2015; Tabak 2013; Voncken-Brewster 2015) with a total of 1580 randomised participants. From Voncken-Brewster 2015, we included the subgroup of individuals with a diagnosis of COPD (284 participants) and excluded those at risk of COPD who had not received a diagnosis (1023 participants). As a result, the total population available for analysis included 557 participants; 319 received smart technology to support self-management and 238 received face-to-face verbal/written or digital information and education about self-management. The average age of participants was 64 years. We included more men than women because the sample from one of the studies consisted of war veterans, most of whom were men. These studies measured five of our nine defined outcomes. None of these studies included outcomes such as self-efficacy, cost-effectiveness, functional capacity, lung function, or anxiety and depression.All three studies included our primary outcome - health-related quality of life (HRQoL) as measured by the Clinical COPD Questionnaire (CCQ) or St George's Respiratory Questionnaire (SGRQ). One study reported our other primary outcomes - hospital admissions and acute exacerbations. Two studies included our secondary outcome of physical activity as measured by daily step counts. One study addressed smoking by providing a narrative analysis. Only one study reported adverse events and noted significant differences between groups, with 43 events noted in the intervention group and eight events in the control group (P = 0.001). For studies that measured outcomes at week four, month four, and month six, the effect of smart technology on self-management and subsequent HRQoL in terms of symptoms and health status was significantly better than when participants received face-to-face/digital and/or written support for self-management of COPD (SMD -0.22, 95% confidence interval (CI) -0.40 to -0.03; P = 0.02). The single study that reported HRQoL at 12 months described no significant between-group differences (MD 1.1, 95% CI -2.2 to 4.5; P = 0.50). Also, hospitalisations (logistic regression odds ratio (OR) 1.6, 95% CI 0.8 to 3.2; P = 0.19) and exacerbations (logistic regression OR 1.4, 95% CI 0.7 to 2.8; P = 0.33) did not differ between groups in the single study that reported these outcomes at 12 months. The activity level of people with COPD at week four, month four, and month six was significantly higher when smart technology was used than when face-to-face/digital and/or written support was provided (MD 864.06 daily steps between groups, 95% CI 369.66 to 1358.46; P = 0.0006). The only study that measured activity levels at 12 months reported no significant differences between groups (mean -108, 95% CI -720 to 505; P = 0.73). Participant engagement in this study was not sustained between four and 12 months. The only study that included smoking cessation found no significant treatment effect (OR 1.06, 95%CI 0.43 to 2.66; P = 0.895). Meta-analyses showed no significant heterogeneity between studies (Chi² = 0.39, P = 0.82; I² = 0% and Chi² = 0.01, P = 0.91; I² = 0%, respectively). AUTHORS' CONCLUSIONS: Although our review suggests that interventions aimed at facilitating, supporting, and sustaining self-managment in people with COPD and delivered via smart technology significantly improved HRQoL and levels of activity up to six months compared with interventions given through face-to-face/digital and/or written support, no firm conclusions can be drawn. This improvement may not be sustained over a long duration. The only included study that measured outcomes up to 12 months highlighted the need to ensure sustained engagement with the technology over time. Limited evidence suggests that using computer and mobile technology for self-management for people with COPD is not harmful and may be more beneficial for some people than for others, for example, those with an interest in using technology may derive greater benefit.The evidence, provided by three studies at high risk of bias, is of poor quality and is insufficient for advising healthcare professionals, service providers, and members of the public with COPD about the health benefits of using smart technology as an effective means of supporting, encouraging, and sustaining self-management. Further research that focuses on outcomes relevant to different stages of COPD is needed. Researchers should provide clear information on how self-management is assessed and should include longitudinal measures that allow comment on behavioural change.
背景:慢性阻塞性肺疾病(COPD)的特征是肺部对有害颗粒或气体(如香烟烟雾)产生异常炎症反应,进而导致气流阻塞。中重度COPD患者的护理模式通常涉及定期长时间住院,这会导致高昂的医疗费用,并对生活质量产生不良影响。过去十年的研究主要集中在开发促进和辅助技术的创新方法,以帮助患者进行自我管理。 目的:评估通过计算机和移动技术提供的干预措施与面对面或硬拷贝/数字文档提供的干预措施(或两者结合)相比,在促进、支持和维持COPD患者自我管理方面的有效性。 检索方法:2016年11月,我们检索了Cochrane气道组专业注册库(CAGR),其中包含通过对包括Cochrane对照试验中心注册库(CENTRAL)、MEDLINE、Embase、CINAHL、AMED和PsycINFO在内的书目数据库进行系统检索而识别出的试验报告,我们还手工检索了呼吸杂志和会议摘要。 入选标准:我们纳入了随机对照试验,这些试验测量了基于远程和Web 2.0的干预措施的效果,这些干预措施被定义为包括个人电脑(PC)和移动技术应用程序(app)(如iPad、安卓平板电脑、智能手机和Skype)等技术对COPD自我管理行为改变的影响。对照干预措施包括面对面和/或硬拷贝/数字文档教育/自我管理支持。 数据收集与分析:两位综述作者(CMcC和MMcC)独立筛选标题、摘要和全文研究报告以确定是否纳入。两位综述作者(CMcC和AMB)独立评估研究质量并提取数据。对于使用不同结局测量量表的研究,我们将连续数据表示为平均差(MDs)和标准化平均差(SMDs)。 主要结果:我们的综述纳入了三项研究(Moy 2015;Tabak 2013;Voncken-Brewster 2015),共有1580名随机参与者。从Voncken-Brewster 2015中,我们纳入了诊断为COPD的个体亚组(284名参与者),排除了有COPD风险但未确诊的个体(1023名参与者)。因此,可供分析的总人群包括557名参与者;319名接受智能技术支持自我管理,238名接受关于自我管理的面对面口头/书面或数字信息和教育。参与者的平均年龄为64岁。我们纳入的男性多于女性,因为其中一项研究的样本由退伍军人组成,其中大多数是男性。这些研究测量了我们定义的九个结局中的五个。这些研究均未包括自我效能、成本效益、功能能力、肺功能或焦虑和抑郁等结局。所有三项研究都纳入了我们的主要结局——通过临床COPD问卷(CCQ)或圣乔治呼吸问卷(SGRQ)测量的健康相关生活质量(HRQoL)。一项研究报告了我们的其他主要结局——住院和急性加重。两项研究纳入了我们通过每日步数测量的身体活动这一次要结局。一项研究通过提供叙述性分析探讨了吸烟问题。只有一项研究报告了不良事件,并指出两组之间存在显著差异,干预组记录了43起事件而对照组记录了8起事件(P = 0.001)。对于在第4周、第4个月和第6个月测量结局的研究,与接受面对面/数字和/或书面COPD自我管理支持的参与者相比,智能技术对自我管理及随后的HRQoL(在症状和健康状况方面)产生的效果显著更好(标准化平均差 -0.22,95%置信区间(CI) -0.40至 -0.03;P = 0.02)。唯一一项在12个月时报告HRQoL的研究描述两组之间无显著差异(平均差1.1,95% CI -2.2至4.5;P = 0.50)。同样,在12个月时报告这些结局的唯一一项研究中,两组之间的住院率(逻辑回归比值比(OR)1.6,95% CI 0.8至3.2;P = 0.19)和加重率(逻辑回归OR 1.4,95% CI 0.7至2.8;P = 0.33)没有差异。当使用智能技术时,COPD患者在第4周、第4个月和第6个月的活动水平显著高于提供面对面/数字和/或书面支持时(两组之间每日步数平均差864.06,95% CI 369.66至1358.46;P = 0.0006)。唯一一项在12个月时测量活动水平的研究报告两组之间无显著差异(平均差 -108,95% CI -720至505;P = 0.73)。本研究中参与者的参与度在4个月至12个月之间未持续。唯一一项包括戒烟内容的研究未发现显著治疗效果(OR 1.06,95% CI 0.43至2.66;P = 0.895)。荟萃分析显示各研究之间无显著异质性(卡方 = 0.39,P = 0.82;I² = 0%以及卡方 = 0.01,P = 0.91;I² = 0%)。 作者结论:尽管我们的综述表明,与通过面对面/数字和/或书面支持提供的干预措施相比,旨在促进、支持和维持COPD患者自我管理并通过智能技术提供的干预措施在长达六个月的时间内显著改善了HRQoL和活动水平,但无法得出确凿结论。这种改善可能无法长期持续。唯一一项测量长达12个月结局的纳入研究强调了随着时间推移确保持续使用该技术的必要性。有限的证据表明,使用计算机和移动技术对COPD患者进行自我管理无害,且对某些人可能比其他人更有益,例如,对使用技术感兴趣的人可能获益更大。由三项存在高偏倚风险的研究提供的证据质量较差,不足以就使用智能技术作为支持COPD患者自我管理的有效手段对健康的益处向医疗保健专业人员、服务提供者和公众提供建议。需要进一步开展关注与COPD不同阶段相关结局的研究。研究人员应提供关于如何评估自我管理的明确信息,并应纳入能够对行为改变进行评论的纵向测量方法。
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