Evidence map›Paper›PMID 38206666›Full record

ArticleJMIR human factors2024

User Perceptions of Visual Clot in a High-Fidelity Simulation Study: Mixed Qualitative-Quantitative Study.

Greta Gasciauskaite, Clara Castellucci, Amos Malorgio, Alexandra D Budowski, Giovanna Schweiger, Michaela Kolbe, Daniel Fries, Bastian Grande, Christoph B Nöthiger, Donat R Spahn and 3 more

Abstract read
In one paragraph

Article in JMIR human factors, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

13 authors.

Greta GasciauskaiteInstitute of Anesthesiology, University Hospital Zurich, Zurich, Switzerland.ORCID 0000-0003-4963-8489
Clara CastellucciInstitute of Anesthesiology, University Hospital Zurich, Zurich, Switzerland.ORCID 0000-0002-0517-6609
Amos MalorgioInstitute of Anesthesiology, University Hospital Zurich, Zurich, Switzerland.ORCID 0000-0002-1355-6804
Alexandra D BudowskiInstitute of Anesthesiology, University Hospital Zurich, Zurich, Switzerland.ORCID 0000-0002-9721-3461
Giovanna SchweigerInstitute of Anesthesiology, University Hospital Zurich, Zurich, Switzerland.ORCID 0000-0002-9284-896X
Michaela KolbeSimulation Centre, University Hospital Zurich, Zurich, Switzerland.ORCID 0000-0001-6654-6370
Daniel FriesInstitute of Anesthesiology, University Hospital Zurich, Zurich, Switzerland.ORCID 0009-0005-1361-1200
Bastian GrandeInstitute of Anesthesiology, University Hospital Zurich, Zurich, Switzerland.ORCID 0000-0003-2935-1317
Christoph B NöthigerInstitute of Anesthesiology, University Hospital Zurich, Zurich, Switzerland.ORCID 0000-0002-0336-1421
Donat R SpahnInstitute of Anesthesiology, University Hospital Zurich, Zurich, Switzerland.ORCID 0000-0002-4782-183X
Tadzio R RocheInstitute of Anesthesiology, University Hospital Zurich, Zurich, Switzerland.ORCID 0000-0002-1072-5748
David W TschollInstitute of Anesthesiology, University Hospital Zurich, Zurich, Switzerland.ORCID 0000-0002-3677-3705
Samira AkbasInstitute of Anesthesiology, University Hospital Zurich, Zurich, Switzerland.ORCID 0000-0001-7692-4718

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundViscoelastic hemostatic assays, such as rotational thromboelastometry (ROTEM) or thromboelastography, enable prompt diagnosis and accelerate targeted treatment. However, the complex interpretation of the results remains challenging. Visual Clot-a situation awareness-based visualization technology-was developed to assist clinicians in interpreting viscoelastic tests.

objectiveFollowing a previous high-fidelity simulation study, we analyzed users' perceptions of the technology, to identify its strengths and limitations from clinicians' perspectives.

methodsThis is a mixed qualitative-quantitative study consisting of interviews and a survey. After solving coagulation scenarios using Visual Clot in high-fidelity simulations, we interviewed anesthesia personnel about the perceived advantages and disadvantages of the new tool. We used a template approach to identify dominant themes in interview responses. From these themes, we defined 5 statements, which were then rated on Likert scales in a questionnaire.

resultsWe interviewed 77 participants and 23 completed the survey. We identified 9 frequently mentioned topics by analyzing the interview responses. The most common themes were "positive design features," "intuitive and easy to learn," and "lack of a quantitative component." In the survey, 21 respondents agreed that Visual Clot is easy to learn and 16 respondents stated that a combination of Visual Clot and ROTEM would help them manage complex hemostatic situations.

conclusionsA group of anesthesia care providers found Visual Clot well-designed, intuitive, and easy to learn. Participants highlighted its usefulness in emergencies, especially for clinicians inexperienced in coagulation management. However, the lack of quantitative information is an area for improvement.

Indexed as

AnesthesiaHemostaticsHigh Fidelity Simulation TrainingThrombosisBlood CoagulationClotrimazoleHumansClotrimazoleHemostaticsblood coagulationblood coagulation testcoagulationhemostasisinterpretationperceptionquantitative informationrotational thromboelastometrysituation awarenesstechnologythromboelastographyuseruser-centered designviscoelastic hemostaticVisual Clotvisualization

Identifiers

PMID38206666
PMCPMC10811569

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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 OpenQuestion graph.