Published on in Vol 6, No 3 (2022): March

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/28750, first published .
Identity Threats as a Reason for Resistance to Artificial Intelligence: Survey Study With Medical Students and Professionals

Identity Threats as a Reason for Resistance to Artificial Intelligence: Survey Study With Medical Students and Professionals

Identity Threats as a Reason for Resistance to Artificial Intelligence: Survey Study With Medical Students and Professionals

Authors of this article:

Ekaterina Jussupow1 Author Orcid Image ;   Kai Spohrer2 Author Orcid Image ;   Armin Heinzl1 Author Orcid Image

Journals

  1. Kedar S, Khazanchi D. Neurology education in the era of artificial intelligence. Current Opinion in Neurology 2022 View
  2. Mousavi Baigi S, Sarbaz M, Ghaddaripouri K, Ghaddaripouri M, Mousavi A, Kimiafar K. Attitudes, knowledge, and skills towards artificial intelligence among healthcare students: A systematic review. Health Science Reports 2023;6(3) View
  3. Alsaad A. The dual effect of anthropomorphism on customers’ decisions to use artificial intelligence devices in hotel services. Journal of Hospitality Marketing & Management 2023;32(8):1048 View
  4. Hofer B, Kittler M, Laukens K. How deep learning influences workflows and roles in virtual surgical planning. Discover Health Systems 2023;2(1) View
  5. Craig K, Grover V, Thatcher J. Integrating the perceptions that cause Resistance to IT: Expanding the nomological network of the IT identity Threat. Journal of Information Technology Case and Application Research 2024;26(1):35 View
  6. Ahmad M, Abdallah S, Abbasi S, Abdallah A. Student perspectives on the integration of artificial intelligence into healthcare services. DIGITAL HEALTH 2023;9 View
  7. Shinners L, Aggar C, Stephens A, Grace S. Healthcare professionals' experiences and perceptions of artificial intelligence in regional and rural health districts in Australia. Australian Journal of Rural Health 2023;31(6):1203 View
  8. Hesso I, Kayyali R, Dolton D, Joo K, Zacharias L, Charalambous A, Lavdaniti M, Stalika E, Ajami T, Acampa W, Boban J, Nabhani-Gebara S. Cancer care at the time of the fourth industrial revolution: an insight to healthcare professionals’ perspectives on cancer care and artificial intelligence. Radiation Oncology 2023;18(1) View
  9. Kumar R, Sood P, Nirala R, Ade R, Sonaji A. Uses of AI in Field of Radiology- What is State of Doctor & Pateints Communication in Different Disease for Diagnosis Purpose. Journal for Research in Applied Sciences and Biotechnology 2023;2(5):51 View
  10. Kumari P, Shankar A, Behl A, Pereira V, Yahiaoui D, Laker B, Gupta B, Arya V. Investigating the barriers towards adoption and implementation of open innovation in healthcare. Technological Forecasting and Social Change 2024;200:123100 View
  11. Ackerhans S, Huynh T, Kaiser C, Schultz C. Exploring the role of professional identity in the implementation of clinical decision support systems—a narrative review. Implementation Science 2024;19(1) View
  12. Fazakarley C, Breen M, Thompson B, Leeson P, Williamson V. Beliefs, experiences and concerns of using artificial intelligence in healthcare: A qualitative synthesis. DIGITAL HEALTH 2024;10 View
  13. Weber S, Wyszynski M, Godefroid M, Plattfaut R, Niehaves B. How do medical professionals make sense (or not) of AI? A social-media-based computational grounded theory study and an online survey. Computational and Structural Biotechnology Journal 2024;24:146 View
  14. Myslicka M, Kawala-Sterniuk A, Bryniarska A, Sudol A, Podpora M, Gasz R, Martinek R, Kahankova Vilimkova R, Vilimek D, Pelc M, Mikolajewski D. Review of the application of the most current sophisticated image processing methods for the skin cancer diagnostics purposes. Archives of Dermatological Research 2024;316(4) View
  15. Alessandro G, Dimitri O, Cristina B, Anna M. The emotional impact of generative AI: negative emotions and perception of threat. Behaviour & Information Technology 2024:1 View
  16. Mou Y, Gong Y, Ding Z. Complement or substitute? A study of the impact of artificial intelligence on consumers’ resistance. Marketing Intelligence & Planning 2024;42(4):647 View
  17. Hattori E, Yamakawa M, Miwa K. Human bias in evaluating AI product creativity. Journal of Creativity 2024;34(2):100087 View
  18. Zou X, Na Y, Lai K, Liu G. Unpacking public resistance to health Chatbots: a parallel mediation analysis. Frontiers in Psychology 2024;15 View
  19. Amiri H, Peiravi S, rezazadeh shojaee S, Rouhparvarzamin M, Nateghi M, Etemadi M, ShojaeiBaghini M, Musaie F, Anvari M, Asadi Anar M. Medical, dental, and nursing students’ attitudes and knowledge towards artificial intelligence: a systematic review and meta-analysis. BMC Medical Education 2024;24(1) View
  20. Fenwick A, Molnar G, Frangos P. The critical role of HRM in AI-driven digital transformation: a paradigm shift to enable firms to move from AI implementation to human-centric adoption. Discover Artificial Intelligence 2024;4(1) View
  21. Daniyal M, Qureshi M, Marzo R, Aljuaid M, Shahid D. Exploring clinical specialists’ perspectives on the future role of AI: evaluating replacement perceptions, benefits, and drawbacks. BMC Health Services Research 2024;24(1) View
  22. Wu M, Huang X, Jiang B, Li Z, Zhang Y, Gao B. AI in medical education: the moderating role of the chilling effect and STARA awareness. BMC Medical Education 2024;24(1) View
  23. Diller S, Stenzel L, Passmore J. The coach bots are coming: exploring global coaches’ attitudes and responses to the threat of AI coaching. Human Resource Development International 2024;27(4):597 View
  24. Pawelczyk J, Kraus M, Eckl L, Nehrer S, Aurich M, Izadpanah K, Siebenlist S, Rupp M. Attitude of aspiring orthopaedic surgeons towards artificial intelligence: a multinational cross-sectional survey study. Archives of Orthopaedic and Trauma Surgery 2024;144(8):3541 View
  25. Shen G, Mullen D, DePuccio M, Kerrissey M. The Human–Technology Continuum. Quality Management in Health Care 2024 View
  26. Lash M. HEX: Human-in-the-loop explainability via deep reinforcement learning. Decision Support Systems 2024;187:114304 View
  27. SimanTov-Nachlieli I. More to Lose: The Adverse Effect of High Performance Ranking on Employees’ Preimplementation Attitudes Toward the Integration of Powerful AI Aids. Organization Science 2024 View
  28. Alli S, Hossain S, Das S, Upshur R. The Potential of Artificial Intelligence Tools for Reducing Uncertainty in Medicine and Directions for Medical Education. JMIR Medical Education 2024;10:e51446 View