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Article

Improving Visual-Patient-Avatar Design Prior to Its Clinical Release: A Mixed Qualitative and Quantitative Study

Institute of Anaesthesiology, University Hospital Zurich, Raemistrasse 100, 8091 Zurich, Switzerland
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Author to whom correspondence should be addressed.
Diagnostics 2022, 12(2), 555; https://doi.org/10.3390/diagnostics12020555
Submission received: 28 December 2021 / Revised: 15 February 2022 / Accepted: 18 February 2022 / Published: 21 February 2022
(This article belongs to the Section Machine Learning and Artificial Intelligence in Diagnostics)

Abstract

Visual-Patient-avatar, an avatar-based visualisation of patient monitoring, is a newly developed technology aiming to promote situation awareness through user-centred design. Before the technology’s introduction into clinical practice, the initial design used to validate the concept had to undergo thorough examination and adjustments where necessary. This mixed qualitative and quantitative study, consisting of three different study parts, aimed to create a design with high user acceptance regarding perceived professionalism and potential for identification while maintaining its original functionality. The first qualitative part was based on structured interviews and explored anaesthesia personnel’s first impressions regarding the original design. Recurrent topics were identified using inductive coding, participants’ interpretations of the vital sign visualisations analysed and design modifications derived. The second study part consisted of a redesign process, in which the visualisations were adapted according to the results of the first part. In a third, quantitative study part, participants rated Likert scales about Visual-Patient-avatar’s appearance and interpreted displayed vital signs in a computer-based survey. The first, qualitative study part included 51 structured interviews. Twenty-eight of 51 (55%) participants mentioned the appearance of Visual-Patient-avatar. In 23 of 51 (45%) interviews, 26 statements about the general impression were identified with a balanced count of positive (14 of 26) and negative (12 of 26) comments. The analysis of vital sign visualisations showed deficits in several vital sign visualisations, especially central venous pressure. These findings were incorporated into part two, the redesign of Visual-Patient-avatar. In the subsequent quantitative analysis of study for part three, 20 of 30 (67%) new participants agreed that the avatar looks professional enough for medical use. Finally, the participants identified 73% (435 of 600 cases) of all vital sign visualisations intuitively correctly without prior instruction. This study succeeded in improving the original design with good user acceptance and a reasonable degree of intuitiveness of the new, revised design. Furthermore, the study identified aspects relevant for the release of Visual-Patient-avatar, such as the requirement for providing at least some training, despite the design’s intuitiveness. The results of this study will guide further research and improvement of the technology. The study provides a link between Visual-Patient-avatar as a scientific concept and as an actual product from a cognitive engineering point of view, and may serve as an example of methods to study the designs of technologies in similar contexts.
Keywords: avatar technology; intuitiveness; patient monitoring; situation awareness; user-centred design; Visual-Patient-avatar avatar technology; intuitiveness; patient monitoring; situation awareness; user-centred design; Visual-Patient-avatar

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MDPI and ACS Style

Wetli, D.J.; Bergauer, L.; Nöthiger, C.B.; Roche, T.R.; Spahn, D.R.; Tscholl, D.W.; Said, S. Improving Visual-Patient-Avatar Design Prior to Its Clinical Release: A Mixed Qualitative and Quantitative Study. Diagnostics 2022, 12, 555. https://doi.org/10.3390/diagnostics12020555

AMA Style

Wetli DJ, Bergauer L, Nöthiger CB, Roche TR, Spahn DR, Tscholl DW, Said S. Improving Visual-Patient-Avatar Design Prior to Its Clinical Release: A Mixed Qualitative and Quantitative Study. Diagnostics. 2022; 12(2):555. https://doi.org/10.3390/diagnostics12020555

Chicago/Turabian Style

Wetli, Doreen J., Lisa Bergauer, Christoph B. Nöthiger, Tadzio R. Roche, Donat R. Spahn, David W. Tscholl, and Sadiq Said. 2022. "Improving Visual-Patient-Avatar Design Prior to Its Clinical Release: A Mixed Qualitative and Quantitative Study" Diagnostics 12, no. 2: 555. https://doi.org/10.3390/diagnostics12020555

APA Style

Wetli, D. J., Bergauer, L., Nöthiger, C. B., Roche, T. R., Spahn, D. R., Tscholl, D. W., & Said, S. (2022). Improving Visual-Patient-Avatar Design Prior to Its Clinical Release: A Mixed Qualitative and Quantitative Study. Diagnostics, 12(2), 555. https://doi.org/10.3390/diagnostics12020555

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