An online evidence-based dictionary of common adverse events of antidepressants: a new tool to empower patients and clinicians in their shared decision-making process - Hong, JSW; Ostinelli, EG; Kamvar, R; Smith, KA; Walsh, AEL; Kabir, T; Tomlinson, A; Cipriani, A (BioMed Central, 2024)
Background: 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. Methods: 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. Results: 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. Conclusions: 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.