Conn Vicki S, Ruppar Todd M
S317 Sinclair Building, University of Missouri, Columbia, MO 65211, USA.
University of Missouri, Columbia, MO, USA.
Prev Med. 2017 Jun;99:269-276. doi: 10.1016/j.ypmed.2017.03.008. Epub 2017 Mar 16.
Excellent medication adherence contributes to decreases in morbidity, mortality, and health care costs. Although researchers have tested many interventions to increase adherence, results are sometimes conflicting and often unclear. This systematic review applied meta-analytic procedures to integrate primary research that tested medication adherence interventions. Comprehensive searching completed in 2015 located 771 published and unpublished intervention studies with adherence behavior outcomes. Random-effects model analysis calculated standardized mean difference effect sizes. Meta-analytic moderator analyses examined the association between adherence effect sizes and sample, design, and intervention characteristics. Analyses were conducted in 2016. A standardized mean difference effect size of 0.290 comparing treatment and control groups was calculated. Moderator analyses revealed larger effect sizes for habit-based and behavioral-targeted (vs. cognitive-focused) interventions. The most effective interventions were delivered face-to-face, by pharmacists, and administered directly to patients. Effect sizes were smaller in studies with older and homeless participants. Risks of bias were common; effect sizes were significantly lower among studies with masked data collectors and intention-to-treat analyses. The largest effect sizes were reported by studies using medication electronic event monitoring and pill count medication adherence measures. Publication bias was present. This most comprehensive review to date documented that, although interventions can increase adherence, much room remains for improvement. Findings suggest health care providers should focus intervention content on behavioral strategies, especially habit-based interventions, more so than cognitive strategies designed to change knowledge and beliefs.
良好的药物依从性有助于降低发病率、死亡率和医疗成本。尽管研究人员已经测试了许多提高依从性的干预措施,但结果有时相互矛盾,而且往往不明确。本系统评价应用荟萃分析程序整合了测试药物依从性干预措施的原始研究。2015年完成的全面检索找到了771项已发表和未发表的具有依从行为结果的干预研究。随机效应模型分析计算了标准化平均差效应大小。荟萃分析调节因素分析考察了依从性效应大小与样本、设计和干预特征之间的关联。分析于2016年进行。计算得出治疗组和对照组的标准化平均差效应大小为0.290。调节因素分析显示,基于习惯和行为目标(相对于认知聚焦)的干预措施的效应大小更大。最有效的干预措施是由药剂师面对面直接提供给患者。在有老年参与者和无家可归参与者的研究中,效应大小较小。偏倚风险很常见;在有数据收集者设盲和意向性分析的研究中,效应大小显著较低。使用药物电子事件监测和药丸计数药物依从性测量的研究报告的效应大小最大。存在发表偏倚。迄今为止,这项最全面的综述记录表明,尽管干预措施可以提高依从性,但仍有很大的改进空间。研究结果表明,医疗保健提供者应将干预内容更多地集中在行为策略上,尤其是基于习惯的干预措施,而不是旨在改变知识和信念的认知策略。