Smith Kirsten A, Vennik Jane, Morrison Leanne, Hughes Stephanie, Steele Mary, Tiwari Riya, Bostock Jennifer, Howick Jeremy, Mallen Christian, Little Paul, Ratnapalan Mohana, Lyness Emily, Misurya Pranati, Leydon Geraldine M, Dambha-Miller Hajira, Everitt Hazel A, Bishop Felicity L
Primary Care Population Sciences and Medical Education, University of Southampton, Southampton, United Kingdom.
Centre for Clinical and Community Applications of Health Psychology, Department of Psychology, University of Southampton, Southampton, United Kingdom.
Front Pain Res (Lausanne). 2021 Aug 24;2:721222. doi: 10.3389/fpain.2021.721222. eCollection 2021.
Empathic communication and positive messages are important components of "placebo" effects and can improve patient outcomes, including pain. Communicating empathy and optimism to patients within consultations may also enhance the effects of verum, i.e., non-placebo, treatments. This is particularly relevant for osteoarthritis, which is common, costly and difficult to manage. Digital interventions can be effective tools for changing practitioner behavior. This paper describes the systematic planning, development and optimization of an online intervention-"Empathico"-to help primary healthcare practitioners enhance their communication of clinical empathy and realistic optimism during consultations. The Person-Based Approach to intervention development was used. This entailed integrating insights from placebo and behavior change theory and evidence, and conducting primary and secondary qualitative research. Systematic literature reviews identified barriers, facilitators, and promising methods for enhancing clinical empathy and realistic optimism. Qualitative studies explored practitioners' and patients' perspectives, initially on the communication of clinical empathy and realistic optimism and subsequently on different iterations of the Empathico intervention. Insights from the literature reviews, qualitative studies and public contributor input were integrated into a logic model, behavioral analysis and principles that guided intervention development and optimization. The Empathico intervention comprises 7 sections: Introduction, Empathy, Optimism, Application of Empathico for Osteoarthritis, Reflection on my Consultations, Setting Goals and Further Resources. Iterative refinement of Empathico, using feedback from patients and practitioners, resulted in highly positive feedback and helped to (1) contextualize evidence-based recommendations from placebo studies within the complexities of primary healthcare consultations and (2) ensure the intervention addressed practitioners' and patients' concerns and priorities. We have developed an evidence-based, theoretically-grounded intervention that should enable practitioners to better harness placebo effects of communication in consultations. The extensive use of qualitative research throughout the development and optimization process ensured that Empathico is highly acceptable and meaningful to practitioners. This means that practitioners are more likely to engage with Empathico and make changes to enhance their communication of clinical empathy and realistic optimism in clinical practice. Empathico is now ready to be evaluated in a large-scale randomized trial to explore its impact on patient outcomes.
共情沟通和积极信息是“安慰剂”效应的重要组成部分,能够改善患者的治疗效果,包括缓解疼痛。在诊疗过程中向患者传达共情和乐观情绪,也可能增强真实治疗(即非安慰剂治疗)的效果。这对于骨关节炎尤为重要,因为骨关节炎常见、治疗费用高且难以管理。数字干预可以成为改变从业者行为的有效工具。本文描述了一种在线干预措施——“Empathico”——的系统规划、开发和优化过程,该干预旨在帮助初级医疗从业者在诊疗过程中加强临床共情和现实乐观情绪的传达。采用了基于人的干预开发方法。这需要整合来自安慰剂和行为改变理论及证据的见解,并开展初级和二级定性研究。系统的文献综述确定了增强临床共情和现实乐观情绪的障碍、促进因素及有前景的方法。定性研究探讨了从业者和患者的观点,最初是关于临床共情和现实乐观情绪的传达,随后是关于Empathico干预的不同迭代版本。文献综述、定性研究和公众贡献者意见的见解被整合到一个逻辑模型、行为分析和原则中,以指导干预的开发和优化。Empathico干预包括7个部分:引言、共情、乐观、Empathico在骨关节炎中的应用、对我诊疗过程的反思、设定目标和更多资源。利用患者和从业者的反馈对Empathico进行迭代完善,得到了高度积极的反馈,并有助于:(1)在初级医疗诊疗的复杂性中,将安慰剂研究基于证据的建议置于具体情境中;(2)确保干预解决了从业者和患者的担忧及优先事项。我们开发了一种基于证据、理论基础扎实的干预措施,应能使从业者在诊疗过程中更好地利用沟通的安慰剂效应。在整个开发和优化过程中广泛使用定性研究,确保了Empathico对从业者具有高度的可接受性和意义。这意味着从业者更有可能参与Empathico,并做出改变,以在临床实践中加强临床共情和现实乐观情绪的传达。Empathico现已准备好在大规模随机试验中进行评估,以探索其对患者治疗效果的影响。