Critical Interventions, Real Conversations: Discursive Design for Culturally Tailored Smoking Cessation

This exploratory study examines how discursive design—using provocative, speculative artifacts to spark reflection and discussion—might expand public health experts’ problematization of approaches to tailoring and targeting interventions. Cultural tailoring and targeting (CTT) refers to adapting interventions for specific sociocultural populations. Because LGBTQ+ communities experience disproportionately high rates of tobacco use, this study applies discursive intervention concepts within this context to explore how they might help experts critically engage with CTT strategies for reaching LGBTQ+ populations more effectively. To investigate this, two pairs of discursive intervention concepts were designed and presented to three focus groups of public health experts. Each pair juxtaposed a conventional intervention approach with a more provocative, unfamiliar one—for example, deepfake-driven behavior disruption. The goal was to document the type of conversation discursive design could stimulate around CTT considerations and generate insights relevant to the value of design methodologies to foster new ways to problematize public health matters. Findings indicate that the concepts prompted critical conversations about CTT, although the depth and focus of engagement varied. Those with greater expertise in LGBTQ+ issues engaged more with CTT mechanisms and implications, while others focused on implementation and feasibility concerns—essential to intervention development but outside the study’s focus. These patterns highlight who should be included in such efforts and how they should be engaged from a facilitation perspective, raising important considerations for methodological refinements and future research. Overall, this initial exploration aims to uncover the potential of discursive design to deepen understanding of CTT interventions and inform more responsive, innovative approaches to addressing tobacco use among priority populations.