Tsoli Stergiani, Sutton Stephen, Kassavou Aikaterini
Department of Public Health and Primary Care, School of Clinical Medicine, University of Cambridge, Cambridge, UK.
Primary Care Unit, Behavioural Science Group, Institute of Public Health, School of Clinical Medicine, University of Cambridge, Cambridge, UK.
BMJ Open. 2018 Feb 24;8(2):e018974. doi: 10.1136/bmjopen-2017-018974.
A number of promising automated behaviour change interventions have been developed using advanced phone technology. This paper reviewed the effectiveness of interactive voice response (IVR)-based interventions designed to promote changes in specific health behaviours.
A systematic literature review of papers published between January 1990 and September 2017 in MEDLINE, CINAHL, Embase, PsycINFO, SCOPUS and the Cochrane Central Register of Controlled Trials (CENTRAL) was conducted. From the total of 2546 papers identified, 15 randomised control trials (RCTs) met the eligibility criteria and were included in a random effects meta-analysis. Meta-regression analysis was used to explore whether behaviour change techniques (BCTs) that were used in the interventions were associated with intervention effectiveness.
Meta-analysis of 15 RCTs showed that IVR-based interventions had small but significant effects on promoting medication adherence (OR=1.527, 95% CI 1.207 to 1.932, k=9, p=0.000) and physical activity (Hedges' g=0.254, 95% CI 0.068 to 0.439, k=3, p=0.007). No effects were found for alcohol (Hedges' g=-0.077, 95% CI -0.162 to 0.007, k=4, p=0.073) or diet (Hedges' g=0.130, 95% CI -0.088 to 0.347, k=2, p=0.242). In the medication adherence studies, multivariable meta-regression including six BCTs explained 100% of the observed variance in effect size, but only the BCT 'information about health consequences' was significantly associated with effect size (β=0.690, SE=0.199, 95% CI 0.29 to 1.08, p=0.000).
IVR-based interventions appear promising in changing specific health behaviours, such as medication adherence and physical activity. However, more studies are needed to elucidate further the combination of active components of IVR interventions that make them effective and test their feasibility and effectiveness using robust designs and objective outcome measures.
利用先进的电话技术开发了许多有前景的自动化行为改变干预措施。本文回顾了旨在促进特定健康行为改变的基于交互式语音应答（IVR）的干预措施的有效性。
对1990年1月至2017年9月期间发表在MEDLINE、CINAHL、Embase、PsycINFO、SCOPUS和Cochrane对照试验中央注册库（CENTRAL）上的论文进行系统的文献综述。在总共识别出的2546篇论文中，15项随机对照试验（RCT）符合纳入标准，并被纳入随机效应荟萃分析。采用荟萃回归分析探讨干预措施中使用的行为改变技术（BCT）是否与干预效果相关。
对15项RCT的荟萃分析表明，基于IVR的干预措施在促进药物依从性方面有小但显著的效果（OR = 1.527，95%CI 1.207至1.932，k = 9，p = 0.000）和身体活动方面（Hedges' g = 0.254，95%CI 0.068至0.439，k = 3，p = 0.007）。在饮酒（Hedges' g = -0.077，95%CI -0.162至0.007，k = 4，p = 0.073）或饮食（Hedges' g = 0.130，95%CI -0.088至0.347，k = 2，p = 0.242）方面未发现效果。在药物依从性研究中，包括六种BCT的多变量荟萃回归解释了效应大小观察变异的100%，但只有BCT“健康后果信息”与效应大小显著相关（β = 0.690，SE = 0.199，95%CI 0.29至1.08，p = 0.000）。
基于IVR的干预措施在改变特定健康行为（如药物依从性和身体活动）方面似乎很有前景。然而，需要更多的研究来进一步阐明使IVR干预措施有效的活性成分组合，并使用稳健的设计和客观的结局指标来测试其可行性和有效性。
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