Trial reportJMIR formative research2026
Using a Wearable-Based Animated Patient Avatar to Improve Patients' Perception of Vital Signs: Multicenter Computer-Based Study.
Trial report in JMIR formative research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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.
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.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
11 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundVisual patient avatars are an innovative patient monitoring technology that can be used to translate numerical and waveform data into intuitive, avatar-based representations of patient conditions. Previous research indicates that this technology improves health care providers' situational awareness compared to conventional monitoring methods. As patient-worn continuous vital sign monitoring continues to evolve, we introduce the Visual Patient Wearable device to provide avatar-based visualization tailored to this application.
objectiveThis study aimed to evaluate whether a wearable-based animated patient avatar can improve patients' perception and recall of simulated vital sign deviations compared to conventional monitoring methods, and to assess the usability and acceptance of this avatar-based visualization.
methodsThis computer-based study included 67 patients from 3 academic hospitals in Central Europe. Participants were randomly assigned to a Visual Patient Wearable group or a conventional monitoring group and viewed a standardized instructional video for their allocated method. They then completed 4 randomized clinical scenarios, each displayed for 6 seconds to simulate glance-based assessment. Accuracy in recalling vital sign deviations was measured, and Visual Patient Wearable participants additionally gave user feedback on Likert scales.
resultsThe Visual Patient Wearable system was associated with higher detection accuracy of vital sign deviations compared with standard monitoring layouts, increasing from a median correctness of 46% (IQR 33%-63%) with conventional monitoring to a median of 67% (IQR 49%-79%) with the Visual Patient Wearable system (P<.001). This corresponded to a risk ratio of 1.34 (95% CI 1.23%-1.47%). The magnitude of this association varied across signals, with the largest relative improvement observed for heart rhythm (137% improvement, 95% CI 85%-209%), followed by oxygen saturation (SpO
conclusionsThis computer-based study suggests that Visual Patient Wearable visualizations enhance patients' ability to detect and recall simulated vital sign deviations. Participants found the system intuitive, easy to learn, and reassuring. The Visual Patient Wearable system provides an at-a-glance interface that may support patients' understanding of their vital signs and could facilitate communication of relevant information to clinical staff, thereby potentially contributing to informed patient engagement. The next step is to develop a software prototype for wearable devices and test it in a clinical study.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.