Journal Article FZJ-2022-03000

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Attitudes and perception of artificial intelligence in healthcare: A cross-sectional survey among patients

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2022
Sage Thousand Oaks, Calif. [u.a.]

Digital health 8, 205520762211167 - () [10.1177/20552076221116772]

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Abstract: ObjectiveThe attitudes about the usage of artificial intelligence in healthcare are controversial. Unlike the perception of healthcare professionals, the attitudes of patients and their companions have been of less interest so far. In this study, we aimed to investigate the perception of artificial intelligence in healthcare among this highly relevant group along with the influence of digital affinity and sociodemographic factors.MethodsWe conducted a cross-sectional study using a paper-based questionnaire with patients and their companions at a German tertiary referral hospital from December 2019 to February 2020. The questionnaire consisted of three sections examining (a) the respondents’ technical affinity, (b) their perception of different aspects of artificial intelligence in healthcare and (c) sociodemographic characteristics.ResultsFrom a total of 452 participants, more than 90% already read or heard about artificial intelligence, but only 24% reported good or expert knowledge. Asked on their general perception, 53.18% of the respondents rated the use of artificial intelligence in medicine as positive or very positive, but only 4.77% negative or very negative. The respondents denied concerns about artificial intelligence, but strongly agreed that artificial intelligence must be controlled by a physician. Older patients, women, persons with lower education and technical affinity were more cautious on the healthcare-related artificial intelligence usage.ConclusionsGerman patients and their companions are open towards the usage of artificial intelligence in healthcare. Although showing only a mediocre knowledge about artificial intelligence, a majority rated artificial intelligence in healthcare as positive. Particularly, patients insist that a physician supervises the artificial intelligence and keeps ultimate responsibility for diagnosis and therapy.

Classification:

Contributing Institute(s):
  1. Jülich Supercomputing Center (JSC)
Research Program(s):
  1. 5112 - Cross-Domain Algorithms, Tools, Methods Labs (ATMLs) and Research Groups (POF4-511) (POF4-511)
  2. SMITH - Medizininformatik-Konsortium - Beitrag Forschungszentrum Jülich (01ZZ1803M) (01ZZ1803M)

Appears in the scientific report 2022
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Medline ; Creative Commons Attribution-NonCommercial CC BY-NC 4.0 ; DOAJ ; OpenAccess ; Clarivate Analytics Master Journal List ; Current Contents - Clinical Medicine ; Current Contents - Social and Behavioral Sciences ; DOAJ Seal ; IF < 5 ; JCR ; National-Konsortium ; SCOPUS ; Social Sciences Citation Index ; Web of Science Core Collection
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 Record created 2022-08-08, last modified 2023-01-23


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