Development and Content Validation of Clinical Vignettes to Measure Decision-making Preferences along the Cancer Continuum in Adult Patients (Adaptation of the Autonomy Preferences Index)

Abstract

Abstract Background: We developed and validated clinical vignettes to assess decision-making preferences (DMP) among adults with cancer across the cancer care continuum. We aimed to adapt the Autonomy Preferences Index (API) to better reflect the complexities of cancer care, incorporating scenarios that span from prevention to end-of-life care. Existing tools often focus on acute conditions and short-term decisions, leaving a gap in addressing long-term cancer-related decision-making. Methods: Using a mixed-methods approach and following COSMIN methodology, we designed clinical vignettes around the cancer care continuum (CV-Ca) to represent real-life cancer care decisions. We then evaluated their content validity by having ten experts rate their relevance and clarity to obtain a Content Validity Index (CVI). Additionally, we conducted semi-structured interviews to gather qualitative insights. Based on this expert feedback, we revised the CV-Ca to ensure they aligned with current clinical practice and effectively captured the complexities of cancer decision-making. Results: The final CV-Ca demonstrated strong content validity, with improved CVI ratings after revisions. By using both quantitative and qualitative methods, we comprehensively assessed the vignettes and ensured their relevance and clarity. This study is the first to create vignettes that measure DMP across the entire cancer continuum, addressing a significant gap in existing tools. Conclusions: The validated CV-Ca can potentially provide healthcare providers with a reliable instrument to assess DMP in patients with cancer throughout their care journey. This tool supports shared decision-making, helping clinicians ensure that care aligns with patients' values and preferences. It has significant implications for improving patient-centered care in oncology, potentially enhancing treatment adherence, satisfaction, and outcomes. Future steps will involve piloting the tool in clinical settings and further assessing its reliability and construct validity.