Willingness to pay among individuals from the Dutch general population for artificial intelligence based apps for skin cancer detection: a survey-based mixed-methods study

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• Picked for Dermatology (top studies of the week, 9 August 2026): Willingness to pay for AI skin cancer detection apps

Abstract

BACKGROUND: Rising skin cancer incidence increases pressure on the healthcare system. Artificial intelligence (AI)-based mobile health applications (mHealth apps) are being offered to laypersons from the general population to be used on their own initiative. It is unclear if, and how much, they are willing to pay (WTP) for these apps and how they decide on their valuation. OBJECTIVES: The primary objective was to investigate individuals' relative WTP for AI-based mHealth apps for skin cancer risk detection. Secondary objectives were to explore the reasons underlying WTP using a mixed-methods approach. METHODS: This survey-based study embedded in a randomized controlled trial, invited 11,621 participants in the Netherlands between 29-08-2022 and 23-02-2023. Participants were offered a questionnaire about their experiences with an mHealth app, their WTP in three hypothetical scenarios (AI alone, AI with teledermatologist involvement, and physical dermatologist consultation), and could provide open-text explanations. Associations between participant characteristics and WTP were assessed using regression analyses, and qualitative analysis was applied to open-text responses to capture underlying reasoning. RESULTS: A total of 1,953 participants completed the questionnaire (16.8% complete response rate; mean age 58.4 years [SD 13.1]; 57.6% female; 95.4% self-reported light skin type; 49.7% high educational level; 79.4% prior app use). Median WTP was significantly higher for AI combined with a teledermatologist compared to AI alone (€20 [IQR 0-45] vs €5 [IQR 0-20], p < 0.001), but lower than for a physical dermatologist consultation (€50 [IQR 22-75], p < 0.001). Increasing age was the only participant characteristic positively associated with WTP across all scenarios. Qualitative analyses revealed that similar valuations could range from pragmatic to fundamental and reflect different rationales, namely low WTP could indicate lack of trust or a perceived lack of added value, but also the belief that services should be freely accessible. CONCLUSIONS: Individuals place the highest monetary value on dermatologist involvement compared to AI-based apps alone. However, this study suggests that WTP does not always reflect perceived importance, as similar valuations could arise from different underlying rationales. Future studies could explore which features of these apps users value most and how to improve engagement.

Abstract as published, via PubMed.