Evidence map›Paper›PMID 35983102›Full record

ArticleDigital health

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

Sebastian J Fritsch, Andrea Blankenheim, Alina Wahl, Petra Hetfeld, Oliver Maassen, Saskia Deffge, Julian Kunze, Rolf Rossaint, Morris Riedel, Gernot Marx and 1 more

Registry-linked trialAbstract read
In one paragraph

Article in Digital health. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT07600541 (Perceptions of Kidney Transplant Recipients Regarding the Role of Artificial Intelligence in Medicine), which is not on this map. Cited by 116 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
116citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

NCT07600541 recruitingnot on this map

Perceptions of Kidney Transplant Recipients Regarding the Role of Artificial Intelligence in Medicine

TypeobservationalSponsorParis Translational Research Center for Organ TransplantationRan2026 to 2026Enrolled1,000ConditionsKidney Transplant
3 · Its place in the literature

Who cites it

116 citing papers in PubMed, 1 synthesis or guideline pooled it.

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56 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors.

Sebastian J FritschDepartment of Intensive Care Medicine, University Hospital RWTH Aachen, Germany.ORCID https://orcid.org/0000-0002-8350-8584
Andrea BlankenheimDepartment of Intensive Care Medicine, University Hospital RWTH Aachen, Germany.
Alina WahlDepartment of Intensive Care Medicine, University Hospital RWTH Aachen, Germany.
Petra HetfeldDepartment of Intensive Care Medicine, University Hospital RWTH Aachen, Germany.
Oliver MaassenDepartment of Intensive Care Medicine, University Hospital RWTH Aachen, Germany.ORCID https://orcid.org/0000-0002-0437-9295
Saskia DeffgeDepartment of Intensive Care Medicine, University Hospital RWTH Aachen, Germany.ORCID https://orcid.org/0000-0003-0937-4327
Julian KunzeSMITH Consortium of the German Medical Informatics Initiative, Germany.
Rolf RossaintDepartment of Anesthesiology, University Hospital RWTH Aachen, Germany.
Morris RiedelSMITH Consortium of the German Medical Informatics Initiative, Germany.
Gernot MarxDepartment of Intensive Care Medicine, University Hospital RWTH Aachen, Germany.
Johannes BickenbachDepartment of Intensive Care Medicine, University Hospital RWTH Aachen, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: The 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. Methods: We 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. Results: From 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. Conclusions: German 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.

Indexed as

algorithmsArtificial intelligenceattitudeclinical decision support systemsdigital dividedigital technologypatientsperceptionsurveys and questionnaires

Identifiers

PMID35983102
PMCPMC9380417

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.