PDF(Pubmed)
Abstract：
Enhancing the arsenal of methods available to shape implementation strategies and bolster knowledge translation is imperative. Stated preference methods, including discrete choice experiments (DCE) and best-worst scaling (BWS), rooted in economics, emerge as robust, theory-driven tools for understanding and influencing the behaviors of both recipients and providers of innovation. This commentary outlines the wide-ranging application of stated preference methods across the implementation continuum, ushering in effective knowledge translation. The prospects for utilizing these methods within implementation science encompass (1) refining and tailoring intervention and implementation strategies, (2) exploring the relative importance of implementation determinants, (3) identifying critical outcomes for key decision-makers, and 4) informing policy prioritization. Operationalizing findings from stated preference research holds the potential to precisely align health products and services with the requisites of patients, providers, communities, and policymakers, thereby realizing equitable impact.
摘要：
必须增强可用于制定实施策略和支持知识翻译的方法库。陈述的首选项方法，包括离散选择实验(DCE)和最佳-最差缩放(BWS)，植根于经济学，表现得很健壮，理论驱动的工具，用于理解和影响创新的接受者和提供者的行为。本评论概述了既定偏好方法在实施连续体中的广泛应用，迎来有效的知识翻译。在实施科学中利用这些方法的前景包括（1）完善和定制干预和实施策略，(2)探索实施决定因素的相对重要性，(3)确定关键决策者的关键成果，和4)告知政策优先次序。实施既定偏好研究的结果具有使健康产品和服务与患者需求精确保持一致的潜力，提供者,社区,和政策制定者，从而实现公平的影响。
