Kan Kaying, Jörg Frederike, Wardenaar Klaas J, Blaauw Frank J, Brilman Maarten F, Visser Ellen, Raven Dennis, Meijnckens Dwayne, Buskens Erik, Cath Danielle C, Doornbos Bennard, Schoevers Robert A, Feenstra Talitha L
University Center for Psychiatry, Rob Giel Research Center, Interdisciplinary Center for Psychopathology and Emotion Regulation, University Medical Center Groningen, University of Groningen, PO Box 30001, Groningen, 9700 RB, The Netherlands, 31 5036161008, 31 655257786.
Department of Research, GGZ Friesland, Leeuwarden, The Netherlands.
J Particip Med. 2025 Jul 21;17:e67170. doi: 10.2196/67170.
Major depressive disorders significantly impact the lives of individuals, with varied treatment responses necessitating personalized approaches. Shared decision-making (SDM) enhances patient-centered care by involving patients in treatment choices. To date, instruments facilitating SDM in depression treatment are limited, particularly those that incorporate personalized information alongside general patient data and in cocreation with patients.
This study outlines the development of an instrument designed to provide patients with depression and their clinicians with (1) systematic information in a digital report regarding symptoms, medical history, situational factors, and potentially successful treatment strategies and (2) objective treatment information to guide decision-making.
The study was co-led by researchers and patient representatives, ensuring that all decisions regarding the development of the instrument were made collaboratively. Data collection, analyses, and tool development occurred between 2017 and 2021 using a mixed methods approach. Qualitative research provided insight into the needs and preferences of end users. A scoping review summarized the available literature on identified predictors of treatment response. K-means cluster analysis was applied to suggest potentially successful treatment options based on the outcomes of similar patients in the past. These data were integrated into a digital report. Patient advocacy groups developed treatment option grids to provide objective information on evidence-based treatment options.
The Instrument for shared decision-making in depression (I-SHARED) was developed, incorporating individual characteristics and preferences. Qualitative analysis and the scoping review identified 4 categories of predictors of treatment response. The cluster analysis revealed 5 distinct clusters based on symptoms, functioning, and age. The cocreated I-SHARED report combined all findings and was integrated into an existing electronic health record system, ready for piloting, along with the treatment option grids.
The collaboratively developed I-SHARED tool, which facilitates informed and patient-centered treatment decisions, marks a significant advancement in personalized treatment and SDM for patients with major depressive disorders.
重度抑郁症严重影响个人生活，不同的治疗反应需要个性化的治疗方法。共同决策（SDM）通过让患者参与治疗选择来加强以患者为中心的护理。迄今为止，促进抑郁症治疗中共同决策的工具有限，特别是那些将个性化信息与一般患者数据相结合并与患者共同创建的工具。
本研究概述了一种工具的开发，该工具旨在为抑郁症患者及其临床医生提供：（1）数字报告中的系统信息，包括症状、病史、情境因素和潜在成功的治疗策略；（2）客观的治疗信息以指导决策。
该研究由研究人员和患者代表共同领导，确保关于该工具开发的所有决策都是共同做出的。2017年至2021年期间采用混合方法进行数据收集、分析和工具开发。定性研究深入了解了最终用户的需求和偏好。范围综述总结了关于已确定的治疗反应预测因素的现有文献。应用K均值聚类分析根据过去类似患者的结果提出潜在成功的治疗选择。这些数据被整合到一份数字报告中。患者倡导团体制定了治疗选择网格，以提供基于证据的治疗选择的客观信息。
开发了抑郁症共同决策工具（I-SHARED），纳入了个体特征和偏好。定性分析和范围综述确定了4类治疗反应预测因素。聚类分析根据症状、功能和年龄揭示了5个不同的聚类。共同创建的I-SHARED报告结合了所有研究结果，并与治疗选择网格一起集成到现有的电子健康记录系统中，准备进行试点。
共同开发的I-SHARED工具促进了明智的、以患者为中心的治疗决策，标志着重度抑郁症患者个性化治疗和共同决策方面的重大进展。
