Department of Psychiatry, University of Oxford, Oxford, UK.
Oxford Precision Psychiatry Lab, NIHR Oxford Health Biomedical Research Centre, Oxford, UK.
BMC Psychiatry. 2024 Jul 25;24(1):532. doi: 10.1186/s12888-024-05950-6.
Adverse events (AEs) are commonly reported in clinical studies using the Medical Dictionary for Regulatory Activities (MedDRA), an international standard for drug safety monitoring. However, the technical language of MedDRA makes it challenging for patients and clinicians to share understanding and therefore to make shared decisions about medical interventions. In this project, people with lived experience of depression and antidepressant treatment worked with clinicians and researchers to co-design an online dictionary of AEs associated with antidepressants, taking into account its ease of use and applicability to real-world settings.
Through a pre-defined literature search, we identified MedDRA-coded AEs from randomised controlled trials of antidepressants used in the treatment of depression. In collaboration with the McPin Foundation, four co-design workshops with a lived experience advisory panel (LEAP) and one independent focus group (FG) were conducted to produce user-friendly translations of AE terms. Guiding principles for translation were co-designed with McPin/LEAP members and defined before the finalisation of Clinical Codes (CCs, or non-technical terms to represent specific AE concepts). FG results were thematically analysed using the Framework Method.
Starting from 522 trials identified by the search, 736 MedDRA-coded AE terms were translated into 187 CCs, which balanced key factors identified as important to the LEAP and FG (namely, breadth, specificity, generalisability, patient-understandability and acceptability). Work with the LEAP showed that a user-friendly language of AEs should aim to mitigate stigma, acknowledge the multiple levels of comprehension in 'lay' language and balance the need for semantic accuracy with user-friendliness. Guided by these principles, an online dictionary of AEs was co-designed and made freely available ( https://thesymptomglossary.com ). The digital tool was perceived by the LEAP and FG as a resource which could feasibly improve antidepressant treatment by facilitating the accurate, meaningful expression of preferences about potential harms through a shared decision-making process.
This dictionary was developed in English around AEs from antidepressants in depression but it can be adapted to different languages and cultural contexts, and can also become a model for other interventions and disorders (i.e., antipsychotics in schizophrenia). Co-designed digital resources may improve the patient experience by helping to deliver personalised information on potential benefits and harms in an evidence-based, preference-sensitive way.
在使用监管活动医学词典(MedDRA)进行的临床研究中,通常会报告不良事件(AEs),MedDRA 是药物安全监测的国际标准。然而,MedDRA 的技术语言使得患者和临床医生难以理解,因此难以就医疗干预措施做出共同决策。在这个项目中,有抑郁症治疗经验的患者与临床医生和研究人员合作,共同设计了一个与抗抑郁药相关不良事件的在线词典,考虑到其易用性和在现实环境中的适用性。
通过预先定义的文献检索,我们从用于治疗抑郁症的抗抑郁药随机对照试验中确定了 MedDRA 编码的不良事件。通过与 McPin 基金会合作,我们与一个有经验的患者咨询小组(LEAP)和一个独立的焦点小组(FG)进行了四次共同设计研讨会,以生成用户友好的不良事件术语翻译。翻译指南是与 McPin/LEAP 成员共同设计的,并在最终确定临床代码(CC,或代表特定不良事件概念的非技术术语)之前定义。使用框架方法对 FG 结果进行了主题分析。
从搜索中确定的 522 项试验开始,我们将 736 个 MedDRA 编码的不良事件术语翻译成 187 个 CC,这平衡了 LEAP 和 FG 认为重要的关键因素(即广度、特异性、通用性、患者可理解性和可接受性)。与 LEAP 的合作表明,不良事件的用户友好语言应该旨在减轻污名化,承认“非专业”语言中的多层次理解,并平衡语义准确性与用户友好性的需求。在这些原则的指导下,共同设计了一个不良事件在线词典,并免费提供(https://thesymptomglossary.com)。LEAP 和 FG 认为这个数字工具是一个资源,可以通过共同决策过程促进对潜在危害的准确、有意义的表达,从而改善抗抑郁治疗。
这个词典是围绕着抑郁症中抗抑郁药的不良事件在英语中开发的,但它可以适应不同的语言和文化背景,也可以成为其他干预措施和疾病(即精神分裂症中的抗精神病药)的模型。共同设计的数字资源可以通过以循证、偏好敏感的方式提供潜在益处和危害的个性化信息,帮助改善患者体验。