Towards Culturally Sensitive Shared Decision-Making in Oncology A Study Protocol Integrating Bioethical Qualitative Research on Shared Decision-Making Among Ethnic Minorities With Ethical Reflection

Abstract

Background: Shared decision-making (SDM) is often considered the ideal for decision-making in oncology. Views of specific groups such as ethnic minorities have seldom been considered in its development. Aim: In this study we seek to assess in oncology if there is a need for adaptation of the current SDM model to ethnic minorities and to formulate possible adjustments. Design: This study is embedded in empirical bioethics, an interdisciplinary approach integrating empirical data with ethical reasoning to formulate normative conclusions regarding a practice. For the empirical social scientific part, a cross-sectional qualitative study will be conducted; for the ethical reflection the Reflective Equilibrium will be used to develop a coherent view on the application of SDM among ethnic minorities in oncology. Method: Semi-structured interviews combined with visual methods (timelines and relational maps) will be held with healthcare professionals (HCPs), ethnic minority patients, and their relatives to identify values steering the behavior of these actors in SDM. In addition, focus groups (FGs) will be held with ethnic minority community members to identify value structures at the group level. Respondents will be recruited through organizations with access to ethnic minorities and collaborating hospitals. Data will be analyzed using a reflexive thematic analysis through the lens of Schwartz’s value theory. The results of the empirical phase will be included in the RE to formulate possible adjustments of the SDM model, if needed. Discussion: The integration of empirical data with ethical reflection is an innovative method in decision-making. This method enables a systematic and profound assessment of the need for adaptation of SDM and the formulation of theoretically and empirically based suggestions for adaptations of the model. Findings of this study may enrich the SDM model.