Bond Zoe, Scanlon Tanya, Judah Gaby
Department of Surgery & Cancer, Institute of Global Health Innovation, Imperial College London, London W2 1NY, UK.
Healthcare (Basel). 2021 Sep 28;9(10):1282. doi: 10.3390/healthcare9101282.
Statin non-adherence is a common problem in the management of cardiovascular disease (CVD), increasing patient morbidity and mortality. Mobile health (mHealth) interventions may be a scalable way to improve medication adherence. The objectives of this review were to assess the literature testing mHealth interventions for statin adherence and to identify the Behaviour-Change Techniques (BCTs) employed by effective and ineffective interventions. A systematic search was conducted of randomised controlled trials (RCTs) measuring the effectiveness of mHealth interventions to improve statin adherence against standard of care in those who had been prescribed statins for the primary or secondary prevention of CVD, published in English (1 January 2000-17 July 2020). For included studies, relevant data were extracted, the BCTs used in the trial arms were coded, and a quality assessment made using the Risk of Bias 2 (RoB2) questionnaire. The search identified 17 relevant studies. Twelve studies demonstrated a significant improvement in adherence in the mHealth intervention trial arm, and five reported no impact on adherence. Automated phone messages were the mHealth delivery method most frequently used in effective interventions. Studies including more BCTs were more effective. The BCTs most frequently associated with effective interventions were "Goal setting (behaviour)", "Instruction on how to perform a behaviour", and "Credible source". Other effective techniques were "Information about health consequences", "Feedback on behaviour", and "Social support (unspecified)". This review found moderate, positive evidence of the effect of mHealth interventions on statin adherence. There are four primary recommendations for practitioners using mHealth interventions to improve statin adherence: use multifaceted interventions using multiple BCTs, consider automated messages as a digital delivery method from a credible source, provide instructions on taking statins, and set adherence goals with patients. Further research should assess the optimal frequency of intervention delivery and investigate the generalisability of these interventions across settings and demographics.
他汀类药物治疗依从性不佳是心血管疾病(CVD)管理中的常见问题,会增加患者的发病率和死亡率。移动健康(mHealth)干预措施可能是提高药物治疗依从性的一种可扩展方法。本综述的目的是评估测试mHealth干预措施对他汀类药物治疗依从性影响的文献,并确定有效和无效干预措施所采用的行为改变技术(BCT)。我们对随机对照试验(RCT)进行了系统检索,这些试验测量了mHealth干预措施在改善他汀类药物治疗依从性方面相对于标准治疗的有效性,研究对象为因CVD一级或二级预防而开具他汀类药物处方的患者,文献发表语言为英文(2000年1月1日至2020年7月17日)。对于纳入的研究,提取相关数据,对试验组中使用的BCT进行编码,并使用偏倚风险2(RoB2)问卷进行质量评估。检索确定了17项相关研究。12项研究表明,mHealth干预试验组的依从性有显著改善,5项研究报告对依从性无影响。自动语音信息是有效干预措施中最常用的mHealth传递方式。包含更多BCT的研究更有效。与有效干预措施最常相关的BCT是“目标设定(行为)”、“如何执行行为的指导”和“可靠来源”。其他有效技术包括“健康后果信息”、“行为反馈”和“社会支持(未明确说明)”。本综述发现,有适度的积极证据表明mHealth干预措施对他汀类药物治疗依从性有效果。对于使用mHealth干预措施来提高他汀类药物治疗依从性的从业者,有四项主要建议:使用采用多种BCT的多方面干预措施,将自动信息视为来自可靠来源的数字传递方式,提供服用他汀类药物的指导,并与患者设定依从性目标。进一步的研究应评估干预措施的最佳实施频率,并调查这些干预措施在不同环境和人群中的可推广性。