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在多阶段优化策略框架中实现准备阶段目标的以人为本的设计方法。

Human-centered design methods to achieve preparation phase goals in the multiphase optimization strategy framework.

作者信息

O'Hara Karey L, Knowles Lindsey M, Guastaferro Kate, Lyon Aaron R

机构信息

Arizona State University, Tempe, AZ, USA.

VA Puget Sound Health Care System, Seattle, WA, USA.

出版信息

Implement Res Pract. 2022 Oct 22;3:26334895221131052. doi: 10.1177/26334895221131052. eCollection 2022 Jan-Dec.

Abstract

BACKGROUND

The public health impact of behavioral and biobehavioral interventions to prevent and treat mental health and substance use problems hinges on developing methods to strategically maximize their effectiveness, affordability, scalability, and efficiency.

METHODS

The multiphase optimization strategy (MOST) is an innovative, principled framework that guides the development of multicomponent interventions. Each phase of MOST (, , ) has explicit goals and a range of appropriate research methods to achieve them. Methods for attaining and phase goals are well-developed. However, methods used in the phase are often highly researcher-specific, and concrete ways to achieve phase goals are a priority area for further development.

RESULTS

We propose that the discover, design, build, and test (DDBT) framework provides a theory-driven and methods-rich roadmap for achieving the goals of the phase of MOST, including specifying the conceptual model, identifying and testing candidate intervention components, and defining the optimization objective. The DDBT framework capitalizes on strategies from the field of human-centered design and implementation science to drive its data collection methods.

CONCLUSIONS

MOST and DDBT share many conceptual features, including an explicit focus on implementation determinants, being iterative and flexible, and designing interventions for the greatest public health impact. The proposed synthesized DDBT/MOST approach integrates DDBT into the phase of MOST thereby providing a framework for rigorous and efficient intervention development research to bolster the success of intervention optimization.

PLAIN LANGUAGE SUMMARY

1.  Optimizing behavioral interventions to balance effectiveness with affordability, scalability, and efficiency requires a significant investment in intervention development.2.  This paper provides a structured approach to integrating human-centered design principles into the phase of the multiphase optimization strategy (MOST).3.  The proposed synthesized model provides a framework for rigorous and efficient intervention development research in the phase of MOST that will ensure the success of intervention optimization and contribute to improving public health impact of mental health and substance use interventions.

摘要

背景

行为和生物行为干预措施对预防和治疗心理健康及物质使用问题的公共卫生影响,取决于开发出能从战略上最大限度提高其有效性、可承受性、可扩展性和效率的方法。

方法

多阶段优化策略(MOST)是一个创新的、有原则的框架,用于指导多成分干预措施的开发。MOST的每个阶段(发现、设计、构建和测试)都有明确的目标以及一系列实现这些目标的适当研究方法。实现发现和设计阶段目标的方法已经很成熟。然而,构建阶段所使用的方法通常高度依赖研究者个人,实现测试阶段目标的具体方法是有待进一步发展的优先领域。

结果

我们提出,发现、设计、构建和测试(DDBT)框架为实现MOST的构建阶段目标提供了一个理论驱动且方法丰富的路线图,包括明确概念模型、识别和测试候选干预成分,以及定义优化目标。DDBT框架利用了以人为本的设计和实施科学领域的策略来推动其数据收集方法。

结论

MOST和DDBT有许多概念上的共同特征,包括明确关注实施决定因素、具有迭代性和灵活性,以及设计对公共卫生影响最大的干预措施。所提出的综合DDBT/MOST方法将DDBT整合到MOST的构建阶段,从而为严格且高效的干预开发研究提供一个框架,以提高干预优化的成功率。

通俗易懂的总结

  1. 优化行为干预措施以平衡有效性与可承受性、可扩展性和效率,需要在干预开发方面投入大量精力。2. 本文提供了一种结构化方法,将以人为本的设计原则整合到多阶段优化策略(MOST)的构建阶段。3. 所提出的综合模型为MOST的构建阶段严格且高效的干预开发研究提供了一个框架,这将确保干预优化的成功,并有助于提高心理健康和物质使用干预措施对公共卫生的影响。
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/999f/9924242/8cf6adbe7457/10.1177_26334895221131052-fig1.jpg

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