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Comparing preferences for skin cancer screening: AI-enabled app vs dermatologist

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  • Gaube, Susanne
  • Biebl, Isabell
  • Engelmann, Magdalena Karin Maria
  • Kleine, Anne-Kathrin
  • Lermer, Eva

Abstract

Skin cancer is a major public health issue. While self-examinations and professional screenings are recommended, they are rarely performed. Mobile health (mHealth) apps utilising artificial intelligence (AI) for skin cancer screening offer a potential solution to aid self-examinations; however, their uptake is low. Therefore, the aim of this research was to examine provider and user characteristics influencing people's decisions to seek skin cancer screening performed by a mHealth app or a dermatologist.

Suggested Citation

  • Gaube, Susanne & Biebl, Isabell & Engelmann, Magdalena Karin Maria & Kleine, Anne-Kathrin & Lermer, Eva, 2024. "Comparing preferences for skin cancer screening: AI-enabled app vs dermatologist," Social Science & Medicine, Elsevier, vol. 349(C).
  • Handle: RePEc:eee:socmed:v:349:y:2024:i:c:s0277953624003150
    DOI: 10.1016/j.socscimed.2024.116871
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    References listed on IDEAS

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    1. Chiara Longoni & Andrea Bonezzi & Carey K Morewedge, 2019. "Resistance to Medical Artificial Intelligence," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 46(4), pages 629-650.
    2. Jussupow, Ekaterina & Benbasat, Izak & Heinzl, Armin, 2020. "Why Are We Averse Towards Algorithms? A Comprehensive Literature Review on Algorithm Aversion," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 138565, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    3. Hainmueller, Jens & Hopkins, Daniel J. & Yamamoto, Teppei, 2014. "Causal Inference in Conjoint Analysis: Understanding Multidimensional Choices via Stated Preference Experiments," Political Analysis, Cambridge University Press, vol. 22(1), pages 1-30, January.
    4. Paul E. Green & Abba M. Krieger & Yoram Wind, 2001. "Thirty Years of Conjoint Analysis: Reflections and Prospects," Interfaces, INFORMS, vol. 31(3_supplem), pages 56-73, June.
    5. Erickson, Gary M & Johansson, Johny K, 1985. "The Role of Price in Multi-attribute Product Evaluations," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 12(2), pages 195-199, September.
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