Evidence map›Paper›PMID 41725702›Full record

ArticleFrontiers in health services2025

Attitude and perception toward artificial intelligence among German physicians with intensive care experience: a survey study.

G D Giebel, P Raszke, M Tokic, L Palmowski, N Timmesfeld, H Nowak, M Adamzik, P Heinz, S Mreyen, F M Brunkhorst and 3 more

Abstract read
In one paragraph

Article in Frontiers in health services, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

13 authors.

G D GiebelInstitute for Health Care Management and Research, University of Duisburg-Essen, Essen, Germany.
P RaszkeInstitute for Health Care Management and Research, University of Duisburg-Essen, Essen, Germany.
M TokicDepartment of Medical Informatics, Biometry and Epidemiology, Ruhr University Bochum, Bochum, Germany.
L PalmowskiDepartment of Anesthesiology, Intensive Care Medicine and Pain Therapy, Knappschaft Kliniken University Hospital Bochum, Ruhr-University Bochum, Bochum, Germany.
N TimmesfeldDepartment of Medical Informatics, Biometry and Epidemiology, Ruhr University Bochum, Bochum, Germany.
H NowakDepartment of Anesthesiology, Intensive Care Medicine and Pain Therapy, Center for Artificial Intelligence, Medical Informatics and Data Science, Knappschaft Kliniken University Hospital Bochum, Ruhr-University Bochum, Bochum, Germany.
M AdamzikDepartment of Anesthesiology, Intensive Care Medicine and Pain Therapy, Knappschaft Kliniken University Hospital Bochum, Ruhr-University Bochum, Bochum, Germany.
P HeinzKnappschaft Kliniken GmbH, Recklinghausen, Germany.
S MreyenKnappschaft Kliniken GmbH, Recklinghausen, Germany.
F M BrunkhorstInstitute of Infectious Diseases and Infection Control, Jena University Hospital, Jena, Germany.
J WasemInstitute for Health Care Management and Research, University of Duisburg-Essen, Essen, Germany.
F BuchnerInstitute for Health Care Management and Research, University of Duisburg-Essen, Essen, Germany.
N BlaseInstitute for Health Care Management and Research, University of Duisburg-Essen, Essen, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: The applications of artificial intelligence (AI) in healthcare are very diverse. AI-based systems can assist with diagnosis and decision-making, particularly in intensive care medicine. However, physicians must accept these systems to fully exploit their potential. We investigated attitude and perception toward AI among physicians with intensive care experience. Methods: A cross-sectional questionnaire survey was conducted between August and October 2024 among 7,475 physicians with intensive care experience. Participants were recruited via the hospital operator Knappschaftskliniken GmbH, the German Sepsis Society and via an address register. The questionnaire collected background information on the participants as well as their attitude toward and perception to AI. Their general attitudes toward AI were assessed using the validated Attari-12 tool. Questions specifically addressing attitude and perception of AI in healthcare were developed independently. Descriptive statistics and subgroup analysis were conducted. Results: Of the 7,475 physicians initially contacted, 620 returned the questionnaire. Of these, 445 questionnaires were included in the evaluation. Most were male (81.8%) aged over 50 years in leadership positions (92.1%). In both cases, general and health care specific, the attitude toward AI was rather positive. The majority of physicians asked for AI applications that are comprehensible to the treating physicians (87.1%) and agreed that objective values alone are not always sufficient for making medical decisions (87.3%). Furthermore, physicians faced problems in finding reliable information about AI in healthcare (52.6%) and only 21.6% considered communication about AI in the medical community as appropriate. Subgroup analysis revealed few differences for age and gender. The correlation between conscious use of AI in a professional context and attitude toward it was notable. Discussion: Physicians with intensive care experience generally hold a positive attitude toward AI, particularly in healthcare. However, the sample was predominantly male, older, and in leadership positions, so these findings may not fully reflect the attitudes of younger or female physicians. Several considerations were highlighted: AI outputs should be interpretable, clinical decisions cannot rely solely on objective data, and physicians need reliable information and guidance for further AI education. Leveraging the positive attitude could help make healthcare systems more efficient, effective, and sustainable.

Indexed as

artificial intelligence—AIdigital healthintensive care medicinemedical decision-makingphysician attitudessurvey study

Identifiers

PMID41725702
PMCPMC12916590

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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 Socratic graph.