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000298181 245__ $$aAI-generated cancer prevention influencers can target risk groups on social media at low cost.
000298181 260__ $$aAmsterdam [u.a.]$$bElsevier$$c2025
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000298181 520__ $$aThis study explores the potential of Artificial Intelligence (AI)-generated social media influencers to disseminate cancer prevention messages. Utilizing a Generative AI (GenAI) application, we created a virtual persona, 'Wanda', to promote cancer awareness on Instagram.We created five posts, addressing the five most modifiable risk factors for cancer: tobacco consumption, unhealthy diet, sun exposure, alcohol consumption, and Human Papillomavirus (HPV) infection. To amplify the campaign's reach, posts were boosted using a custom-targeted as well as an automated advertisement algorithm. An overall budget of €100 was equally distributed between the two algorithms. Campaign performance was assessed based on the number of users reached and the age distribution of the audience.The campaign achieved a total of 9902 recognitions, with a cost-efficiency analysis revealing an average expenditure of €0.013 per reach. The most economical intervention achieved a cost of only €0.006 per reach. In comparing the two advertisement strategies, we observed similar overall reach but noted differences in the age demographics of the audience.Our findings underscore the potential of combining generative AI with strategically targeted advertisement to promote cancer prevention messages effectively, with minimal time and financial investment. We discuss chances presented by GenAI applications in health communication, their implication, and the impact of parasocial relationships on content perception. This study highlights the potential of AI-driven influencers as scalable tools for digital health communication.
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000298181 650_7 $$2Other$$aAI-generated influencers
000298181 650_7 $$2Other$$aCancer prevention
000298181 650_7 $$2Other$$aDigital health campaigns
000298181 650_7 $$2Other$$aGenAI
000298181 650_7 $$2Other$$aHealth communication
000298181 650_7 $$2Other$$aRisk groups
000298181 650_7 $$2Other$$aSocial media
000298181 650_7 $$2Other$$aTargeted prevention
000298181 7001_ $$0P:(DE-He78)6ff1d8cd02e50566a935419daf3d6a93$$aAbels, Julia$$b1$$udkfz
000298181 7001_ $$0P:(DE-HGF)0$$aKuehn, Arlene$$b2
000298181 7001_ $$0P:(DE-He78)c249ca85d4d8ef90f462ccccf7d02865$$aCarl, Nicolas$$b3$$udkfz
000298181 7001_ $$0P:(DE-He78)3c4243de81f11e32405a8ad3bd617e2f$$aWies, Christoph$$b4$$udkfz
000298181 7001_ $$0P:(DE-He78)1e33961c8780aca9b76d776d1fdc1ebb$$aBrinker, Titus$$b5$$eLast author$$udkfz
000298181 773__ $$0PERI:(DE-600)1468190-0$$a10.1016/j.ejca.2025.115251$$gVol. 217, p. 115251 -$$p115251$$tEuropean journal of cancer$$v217$$x0959-8049$$y2025
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