Evidence map›Paper›PMID 31768924›Full record

ArticleJournal of clinical monitoring and computing2020

Effects of a standardized distraction on caregivers' perceptive performance with avatar-based and conventional patient monitoring: a multicenter comparative study.

Juliane Pfarr, Michael T Ganter, Donat R Spahn, Christoph B Noethiger, David W Tscholl

Abstract readMulticenter Study
PubMed Publisher
In one paragraph

Article in Journal of clinical monitoring and computing, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing 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

16 citing papers in PubMed.

  1. Observational
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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

5 authors.

Juliane PfarrInstitute of Anesthesiology, University and University Hospital Zurich, Raemistrasse 100, 8091, Zurich, Switzerland.
Michael T GanterInstitute of Anesthesiology and Pain Therapy, Cantonal Hospital Winterthur, Brauerstrasse 15, 8400, Winterthur, Switzerland.
Donat R SpahnInstitute of Anesthesiology, University and University Hospital Zurich, Raemistrasse 100, 8091, Zurich, Switzerland.
Christoph B NoethigerInstitute of Anesthesiology, University and University Hospital Zurich, Raemistrasse 100, 8091, Zurich, Switzerland.
David W TschollInstitute of Anesthesiology, University and University Hospital Zurich, Raemistrasse 100, 8091, Zurich, Switzerland. david.tscholl@usz.ch.ORCID http://orcid.org/0000-0002-3677-3705

Funding

University of Zurich Filling-the-Gap Career Development GrantUniversity of Zurich UZ16/288POC
6 · The paper itself

Abstract

Patient monitoring requires constant attention and may be particularly vulnerable to distractions, which frequently occur during perioperative work. In this study, we compared anesthesia providers' perceptive performance and perceived workload under distraction for conventional and avatar-based monitoring, a situation awareness-based technology that displays patient status as an animated patient model. In this prospective, multicenter study with a within-subject design, 38 participants evaluated scenarios of 3- and 10-s durations using conventional and avatar-based monitoring, under standardized distraction in the form of a simple calculation task. We quantified perceptual performance as the number of vital signs correctly remembered out of the total of 11 vital signs shown. We quantified perceived workload using the National Aeronautics and Space Administration Task Load Index score. Anesthesia providers remembered more vital signs under distraction using the avatar monitoring technology in the 3-s scenario: 6 (interquartile range [IQR] 5-7) vs. 3 (IQR 2-4), p < 0.001, mean of differences (MoD): 3 (95% confidence interval [95% CI] 1 to 4), and in the 10-s monitoring task: 6 (IQR 5-8) vs. 4 (IQR 2-7), p = 0.028, MoD: 1 (95% CI 0.2 to 3). Participants rated perceived workload lower under distraction with the avatar in the 3-s scenario: 65 (IQR 40-79) vs. 75 (IQR 51-88), p = 0.007, MoD: 9 (95% CI 3 to 15), and in the 10-s scenario: 68 (IQR 50-80) vs. 75 (IQR 65-86), p = 0.019, MoD: 10 (95% CI 2 to 18). Avatar-based monitoring improved anesthesia providers' perceptive performance under distraction and reduced perceived workload. This technology could help to improve caregivers' situation awareness, especially in high-workload situations.

Indexed as

CaregiversVital SignsHumansMonitoring, PhysiologicProspective StudiesWorkloadComputer-assisted diagnosisPatient monitoringSituation awarenessVisual patient

Identifiers

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Registered trials

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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.