Evidence map›Paper›PMID 39127806›Full record

ArticleArchives of orthopaedic and trauma surgery2024

Attitude of aspiring orthopaedic surgeons towards artificial intelligence: a multinational cross-sectional survey study.

Johannes Pawelczyk, Moritz Kraus, Larissa Eckl, Stefan Nehrer, Matthias Aurich, Kaywan Izadpanah, Sebastian Siebenlist, Marco-Christopher Rupp

Abstract read
In one paragraph

Article in Archives of orthopaedic and trauma surgery, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
–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.

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

11 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. Article
  5. Review
  6. Review
  7. Review
  8. Article
  9. Article
  10. Article
  11. Article
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

8 authors.

Johannes PawelczykKlinikum rechts der Isar, Sektion Sportorthopädie, Technische Universität München, Haus 524, Ismaninger Str. 22, 81675, Munich, Germany.
Moritz KrausSchulthess Klinik, Abteilung für Schulter- und Ellenbogenchirurgie, Zurich, Switzerland.
Larissa EcklSchulthess Klinik, Abteilung für Schulter- und Ellenbogenchirurgie, Zurich, Switzerland.
Stefan NehrerKlinische Abteilung für Orthopädie und Traumatologie, Universitätsklinikum Krems, Krems an der Donau, Austria.
Matthias AurichUniversitätsklinikum Halle (Saale), Halle, Germany.
Kaywan IzadpanahKlinik für Orthopädie und Unfallchirurgie, Universitätsklinikum Freiburg, Medizinische Fakultät, Albert-Ludwigs-Universität Freiburg, Freiburg, Germany.
Sebastian SiebenlistKlinikum rechts der Isar, Sektion Sportorthopädie, Technische Universität München, Haus 524, Ismaninger Str. 22, 81675, Munich, Germany. sebastian.siebenlist@mri.tum.de.
Marco-Christopher RuppKlinikum rechts der Isar, Sektion Sportorthopädie, Technische Universität München, Haus 524, Ismaninger Str. 22, 81675, Munich, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionThe purpose of this study was to evaluate the perspectives of aspiring orthopaedic surgeons on artificial intelligence (AI), analysing how gender, AI knowledge, and technical inclination influence views on AI. Additionally, the extent to which recent AI advancements sway career decisions was assessed. MATERIALS AND

methodsA digital survey was distributed to student members of orthopaedic societies across Germany, Switzerland, and Austria. Subgroup analyses explored how gender, AI knowledge, and technical inclination shape attitudes towards AI.

resultsOf 174 total respondents, 86.2% (n = 150) intended to pursue a career in orthopaedic surgery and were included in the analysis. The majority (74.5%) reported 'basic' or 'no' knowledge about AI. Approximately 29.3% believed AI would significantly impact orthopaedics within 5 years, with another 35.3% projecting 5-10 years. AI was predominantly seen as an assistive tool (77.8%), without significant fear of job displacement. The most valued AI applications were identified as preoperative implant planning (85.3%), administrative tasks (84%), and image analysis (81.3%). Concerns arose regarding skill atrophy due to overreliance (69.3%), liability (68%), and diminished patient interaction (56%). The majority maintained a 'neutral' view on AI (53%), though 32.9% were 'enthusiastic'. A stronger focus on AI in medical education was requested by 81.9%. Most participants (72.8%) felt recent AI advancements did not alter their career decisions towards or away from the orthopaedic specialty. Statistical analysis revealed a significant association between AI literacy (p = 0.015) and technical inclination (p = 0.003). AI literacy did not increase significantly during medical education (p = 0.091).

conclusionsFuture orthopaedic surgeons exhibit a favourable outlook on AI, foreseeing its significant influence in the near future. AI literacy remains relatively low and showed no improvement during medical school. There is notable demand for improved AI-related education. The choice of orthopaedics as a specialty appears to be robust against the sway of recent AI advancements. LEVEL OF EVIDENCE: Cross-sectional survey study; level IV.

Indexed as

Artificial IntelligenceAttitude of Health PersonnelOrthopedic SurgeonsAdultAustriaCareer ChoiceCross-Sectional StudiesFemaleGermanyHumansMaleOrthopedicsSurveys and QuestionnairesSwitzerlandArtificial intelligenceDigital healthMachine learningOrthopaedic surgerySurvey

Identifiers

PMID39127806
PMCPMC11417067

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.