Dataset Information

The impact of self-avatars on trust and collaboration in shared virtual environments.

ABSTRACT: A self-avatar is known to have a potentially significant impact on the user's experience of the immersive content but it can also affect how users interact with each other in a shared virtual environment (SVE). We implemented an SVE for a consumer virtual reality system where each user's body could be represented by a jointed self-avatar that was dynamically controlled by head and hand controllers. We investigated the impact of a self-avatar on collaborative outcomes such as completion time and trust formation during competitive and cooperative tasks. We used two different embodiment levels: no self-avatar and self-avatar, and compared these to an in-person face to face version of the tasks. We found that participants could finish the task more quickly when they cooperated than when they competed, for both the self-avatar condition and the face to face condition, but not for the no self-avatar condition. In terms of trust formation, both the self-avatar condition and the face to face condition led to higher scores than the no self-avatar condition; however, collaboration style had no significant effect on trust built between partners. The results are further evidence of the importance of a self-avatar representation in immersive virtual reality.

SUBMITTER: Pan Y

PROVIDER: S-EPMC5730128 | biostudies-literature | 2017

REPOSITORIES: biostudies-literature

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The impact of self-avatars on trust and collaboration in shared virtual environments.

Pan Ye Y Steed Anthony A

PloS one 20171214 12

A self-avatar is known to have a potentially significant impact on the user's experience of the immersive content but it can also affect how users interact with each other in a shared virtual environment (SVE). We implemented an SVE for a consumer virtual reality system where each user's body could be represented by a jointed self-avatar that was dynamically controlled by head and hand controllers. We investigated the impact of a self-avatar on collaborative outcomes such as completion time and ...[more]

PMID: 29240837

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Project description:Ongoing self-management improves outcomes for those with Type 2 diabetes (T2D); however, there are many barriers to patients receiving assistance in this from the healthcare system and peers. Findings from our pilot study showed that a virtual diabetes community on the Internet with real-time interaction among peers with T2D-and with healthcare professionals-is feasible and has the potential to influence clinical and psychosocial outcomes.The purpose of this article is to present the protocol for the Diabetes Learning in Virtual Environments (LIVE) trial.Diabetes LIVE is a two-group, randomized controlled trial to compare effects of a virtual environment and traditional Web site on diet and physical activity. Our secondary aims will determine the effects on metabolic outcomes; effects of level of engagement and social network formation in LIVE on behavioral outcomes; potential mediating effects of changes in self-efficacy; and diabetes knowledge, diabetes-related distress, and social support on behavior change and metabolic outcomes. We will enroll 300 subjects at two sites (Duke University/Raleigh-Durham, NC and New York University/New York, NY) who have T2D and do not have serious complications or comorbidities. Those randomly assigned to the intervention group have access to the LIVE site where they can find information, synchronous classes with diabetes educators, and peer support to enhance self-management. Those in the control group have access to the same informational and educational content in a traditional asynchronous Web format. Measures of self-management, clinical outcomes, and psychosocial outcomes are assessed at baseline and 3, 6, 12, and 18 months.Should LIVE prove effective in improved self-management of diabetes, similar interventions could be applied to other prevalent chronic diseases. Innovative programs such as LIVE have potential for improving healthcare access in an easily disseminated alternative model of care that potentially improves the reach of self-management training and support.

Project description:BackgroundThere is a natural assumption that quality and efficiency are optimized when providers consistently work together and share patients. Diversity in composition and recurrence of groups that provide face-to-face care to the same patients has not previously been studied.ObjectiveClaims data enable identification of the constellation of providers caring for a single patient. To indirectly measure teamwork and provider collaboration, we measure recurrence of provider constellations and cohesion among providers.DesignRetrospective analysis of commercial healthcare claims from a single insurer.ParticipantsPatients with claims for office visits and their outpatient providers. To maximize capture of provider panels, the cohort was drawn from the four regions with the highest plan coverage. Regional outpatient provider networks were constructed with providers as nodes and number of shared patients as links.Main measuresMeasures of cohesion and stability of provider constellations derived from the networks of providers to quantify patient sharing.ResultsFor 10,325 providers and their 521,145 patients, there were 2,641,933 collaborative provider pairs sharing at least one patient. Fifty-four percent only shared a single patient, and 19 % shared two. Of 15,449,835 unique collaborative triads, 92 % shared one patient, 5 % shared two, and 0.2 % shared ten or more. Patient constellations had a median of four providers. Any precise constellation recurred rarely-89 % with exactly two providers shared just one patient and only 4 % shared over two; 97 % of constellations with exactly three providers shared just one patient. Four percent of constellations with 2+ providers were not at all cohesive, sharing only the hub patient. In the remaining constellations, a median of 93 % of provider pairs shared at least one additional patient beyond the hub patient.ConclusionStunning variability in the constellations of providers caring for patients may challenge underlying assumptions about the current state of teamwork in healthcare.

Project description:The efficient coding hypothesis posits that sensory systems are tuned to the regularities of their natural input. The statistics of natural image databases have been the topic of many studies, which have revealed biases in the distribution of orientations that are related to neural representations as well as behavior in psychophysical tasks. However, commonly used natural image databases contain images taken with a camera with a planar image sensor and limited field of view. Thus, these images do not incorporate the physical properties of the visual system and its active use reflecting body and eye movements. Here, we investigate quantitatively, whether the active use of the visual system influences image statistics across the visual field by simulating visual behaviors in an avatar in a naturalistic virtual environment. Images with a field of view of 120° were generated during exploration of a virtual forest environment both for a human and cat avatar. The physical properties of the visual system were taken into account by projecting the images onto idealized retinas according to models of the eyes' geometrical optics. Crucially, different active gaze behaviors were simulated to obtain image ensembles that allow investigating the consequences of active visual behaviors on the statistics of the input to the visual system. In the central visual field, the statistics of the virtual images matched photographic images regarding their power spectra and a bias in edge orientations toward cardinal directions. At larger eccentricities, the cardinal bias was superimposed with a gradually increasing radial bias. The strength of this effect depends on the active visual behavior and the physical properties of the eye. There were also significant differences between the upper and lower visual field, which became stronger depending on how the environment was actively sampled. Taken together, the results show that quantitatively relating natural image statistics to neural representations and psychophysical behavior requires not only to take the structure of the environment into account, but also the physical properties of the visual system, and its active use in behavior.

Dataset Information

The impact of self-avatars on trust and collaboration in shared virtual environments.

Publications

The impact of self-avatars on trust and collaboration in shared virtual environments.

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