Selection of Behavior Change Techniques for Asthma Medication Adherence Apps: Evidence-Based Design Study.

IF 6.2 2区 医学 Q1 HEALTH CARE SCIENCES & SERVICES
Alison J Wright, Jeremy Holland, Iain Simpson, Samantha Walker, Naomi Bennett-Steele, John Weinman
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引用次数: 0

Abstract

Background: Poor medication adherence is a widespread issue that causes adverse patient outcomes and is expensive for all aspects of the health care system. Developing cost-effective and scalable interventions to promote medication adherence is a key goal. Mobile apps hold promise as a mode of delivery for adherence interventions, but app design rarely takes into account the behavioral influences on nonadherence with sufficient rigor. As a result, apps may not realize their full potential in enhancing adherence. Medication nonadherence is common among adults prescribed preventer inhalers for asthma and has a variety of influences, creating a need to identify what components behavior change technique (BCT) apps should include to effectively tackle each influence.

Objective: This study aimed to identify the most acceptable and practicable BCTs to include in a medication adherence app targeting factors that influence preventer inhaler adherence in adults with asthma.

Methods: Key influences on preventer inhaler adherence in adults with asthma were identified based on reviews of peer-reviewed and gray literature and domain expert knowledge. These influences were then mapped to a published set of 26 mechanisms of action (MoAs) of behavior change interventions. Next, candidate BCTs to change each MoA were identified using the Theory and Techniques tool, a web-based resource that reflects almost 100 expert behavioral scientists' consensus about which BCTs are most likely to change particular MoAs. Finally, candidate BCTs were filtered by considering their potential acceptability and practicability.

Results: A total of 31 influences on preventer inhaler adherence were identified and coded to 15/26 of the influences on behavior listed by the Theory and Techniques tool. The initial mapping of influences on behavior to candidate BCTs to change those influences identified 41 candidate BCTs. After considering the potential acceptability and practicability of the candidate BCTs, the number of BCTs suggested for inclusion was reduced to 24.

Conclusions: Using an evidence-based approach, this study identified 24 BCTs that may be particularly useful to include in apps promoting adherence to preventer inhalers in order to target particular influences on adherence. The list can be used by app developers to improve the quality of adherence behavior change support that their apps provide or by health care decision-makers to identify which apps contain elements addressing a range of adherence difficulties.

哮喘药物依从性应用程序的行为改变技术选择:循证设计研究。
背景:药物依从性差是一个普遍存在的问题,它会导致不良的患者结果,并且对卫生保健系统的各个方面都是昂贵的。制定具有成本效益和可扩展的干预措施以促进药物依从性是一个关键目标。手机应用有望成为一种提供依从性干预的模式,但应用设计很少足够严格地考虑到行为对不依从性的影响。因此,应用程序可能无法充分发挥其在提高依从性方面的潜力。用药不依从在成人哮喘预防剂吸入器中很常见,并且有多种影响,因此需要确定行为改变技术(BCT)应用程序应该包括哪些组件来有效地解决每种影响。目的:本研究旨在确定最可接受和可行的bct,将其纳入药物依从性应用程序,针对影响成人哮喘患者预防吸入器依从性的因素。方法:根据同行评审、灰色文献和领域专家知识,确定成人哮喘患者对预防剂吸入器依从性的关键影响因素。然后将这些影响映射到已发表的行为改变干预措施的26种作用机制(MoAs)。接下来,使用理论和技术工具确定改变每个MoA的候选bct,这是一个基于网络的资源,反映了近100名专家行为科学家对哪些bct最有可能改变特定MoA的共识。最后,考虑候选btc的潜在可接受性和实用性,对其进行筛选。结果:共识别出31种影响预防器吸入器依从性的因素,并将其编码为理论和技术工具列出的对行为影响的15/26。将对行为的影响初步映射到候选btc以改变这些影响,确定了41个候选btc。在考虑候选btc的潜在可接受性和实用性后,建议纳入的btc数量减少到24个。结论:采用循证方法,本研究确定了24个bct,这些bct可能特别有用,可纳入促进预防吸入器依从性的应用程序,以针对依从性的特定影响。应用程序开发人员可以使用该列表来提高其应用程序提供的依从性行为改变支持的质量,或者医疗保健决策者可以使用该列表来确定哪些应用程序包含解决一系列依从性困难的元素。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
JMIR mHealth and uHealth
JMIR mHealth and uHealth Medicine-Health Informatics
CiteScore
12.60
自引率
4.00%
发文量
159
审稿时长
10 weeks
期刊介绍: JMIR mHealth and uHealth (JMU, ISSN 2291-5222) is a spin-off journal of JMIR, the leading eHealth journal (Impact Factor 2016: 5.175). JMIR mHealth and uHealth is indexed in PubMed, PubMed Central, and Science Citation Index Expanded (SCIE), and in June 2017 received a stunning inaugural Impact Factor of 4.636. The journal focusses on health and biomedical applications in mobile and tablet computing, pervasive and ubiquitous computing, wearable computing and domotics. JMIR mHealth and uHealth publishes since 2013 and was the first mhealth journal in Pubmed. It publishes even faster and has a broader scope with including papers which are more technical or more formative/developmental than what would be published in the Journal of Medical Internet Research.
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