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Background Lung cancer screening (LCS) uptake remains low with substantial racial, ethnic, socioeconomic, and geographic disparities in screening. Insufficient shared decision-making (SDM), a key component of LCS, is a barrier to screening uptake, and identification of strategies to implement high-quality SDM is a priority. Research Question How can a patient decision aid (PDA) to improve equitable SDM on LCS be codeveloped with high-risk and underrepresented veterans, and what are important components to consider in the design and implementation of an equity-focused PDA? Study Design and Methods Human-centered design (HCD) was used to complete a landscape analysis of existing LCS PDAs, design a PDA prototype, and then refine the tool and strategies for its implementation. A design team consisting of LCS providers and screening-eligible veterans from marginalized groups participated in an HCD workshop to codesign and iteratively refine the web-based LCS PDA and streamlined referral tool. A qualitative thematic analysis of workshop notes and observations was performed using an a priori coding schema. Results The landscape analysis revealed few PDAs tailored toward marginalized higher-risk populations and gaps in the optimal strategies to integrate these tools into the clinical workflow. Ten veteran patients and 5 LCS staff participated in the HCD workshop. Key themes from the workshop which guided subsequent modifications to the PDA include the following: (1) address technologic needs and barriers in LCS SDM implementation; (2) acknowledge emotions and mental health and mitigate fears; (3) tailor, personalize, and repeat content; (4) use veteran-centered language and images; and (5) foster human connections. Interpretation We developed an equity-focused, patient-facing decision aid with direct input from underrepresented high-risk veterans which can be implemented outside of a primary care visit. Our tool serves as a strategy to enhance high-quality SDM without overburdening an already time-constrained provider visit and can be tested via future hybrid implementation-effectiveness trials.
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Lamberton et al. (2026) studied this question.
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