Do alcohol interventions affect peers who do not receive the intervention? Modeling treatment contagion effects via simulations of adolescent social networks.

OBJECTIVE: Adolescents' drinking is influenced by their friends' drinking. However, it is unclear whether individually-targeted alcohol interventions reduce drinking in the friends of individuals who receive the intervention. This study used simulations of drinking in simulated longitudinal social networks to test whether individually-targeted alcohol interventions may be expected to spread to non-targeted individuals. METHOD: Stochastic actor-based models simulated longitudinal social networks where changes in drinking and friendships were modeled using parameters from a meta-analysis of high school 10th grade social networks. Social influence (i.e., how much one's friends' drinking affects their own drinking) and social selection (i.e., how much one's drinking affects who they select as friends) were manipulated at several levels. At the midpoint of each simulation, a randomly-selected heavy-drinking individual was experimentally assigned to an intervention (changing their drinking status to non-drinking) or a control condition (no change in drinking status) and the drinking statuses of that individual's friends were recorded at the end of the simulation. RESULTS: Friends of individuals who received the intervention significantly reduced their drinking, with higher reductions occurring in networks with greater social influence. However, all effect sizes were small (e.g., average per-friend reduction of .07 on a 5-point drinking scale). CONCLUSIONS: Individually-targeted alcohol interventions may have small effects on reducing the drinking of non-targeted adolescents, with social influence being a mechanism that drives such effects. Due to small effect sizes, many adolescents may need to receive alcohol interventions to produce measurable effects on drinking outcomes for non-targeted individuals. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Episodic memory: A hierarchy of spatiotemporal concepts.

We propose a new model of episodic memory. It consists of a hierarchy of partial sequences of events, blended for consistency across space and time by feedforward/feedback links to concepts expressing their shared information. This blended concept hierarchy is acquired and represented incrementally through synaptic or connection-weighted adaptation in a neural network with episodic memory capability. We derive this model through argumentation, explain its derivation within a category-theoretic model of representation, and discuss the capabilities we propose for this model.

Simulating drinking in social networks to inform alcohol prevention and treatment efforts.

Adolescent drinking influences, and is influenced by, peer alcohol use. Several efficacious adolescent alcohol interventions include elements aimed at reducing susceptibility to peer influence. Modeling these interventions within dynamically changing social networks may improve our understanding of how such interventions work and for whom they work best. We used stochastic actor-based models to simulate longitudinal drinking and friendship formation within social networks using parameters obtained from a meta-analysis of real-world 10th grade adolescent social networks. Levels of social influence (i.e., friends affecting changes in one's drinking) and social selection (i.e., drinking affecting changes in one's friendships) were manipulated at several levels, which directly impacted the degree of clustering in friendships based on similarity in drinking behavior. Midway through each simulation, one randomly selected heavy-drinking actor from each network received an "intervention" that either (a) reduced their susceptibility to social influence, (b) reduced their susceptibility to social selection, (c) eliminated a friendship with a heavy drinker, or (d) initiated a friendship with a nondrinker. Only the intervention that eliminated targeted actors' susceptibility to social influence consistently reduced that actor's drinking. Moreover, this was only effective in networks with social influence and social selection that were at higher levels than what was found in the real-world reference study. Social influence and social selection are dynamic processes that can lead to complex systems that may moderate the effectiveness of network-based interventions. Interventions that reduce susceptibility to social influence may be most effective among adolescents with high susceptibility to social influence and heavier-drinking friends. (PsycINFO Database Record

The use of virtual reality simulation of head trauma in a surgical boot camp.

Surgical "boot camps" provide excellent opportunities to enhance orientation, learning, and preparation of new surgery interns as they enter the clinical arena. This paper describes the utilization of an interactive virtual reality (VR) simulation and associated virtual patient (VP) as an additional tool for surgical boot camps. Complementing other forms of simulation, virtual patients (VPs) require less specialized equipment and can also provide a wide variety of medical scenarios. In this paper we discuss a study that measured the learning effectiveness of a real-world VP simulation used by a class of new surgery interns who operated it with a standard computer interface. The usability of the simulator as a learning tool has been demonstrated and measured. This study brings the use of VR simulation with VPs closer to wider application and integration into a training curriculum, such as a surgery intern boot camp.

Medical students learn over distance using virtual reality simulation.

INTRODUCTION: This article presents the results of a demonstration project that was designed with the goal to determine the feasibility and acceptability of medical students in using distance technology and virtual reality (VR) simulation within a problem-based learning (PBL). METHODS: This pilot project involved students from the Universities of New Mexico and Hawaii and compared (1) control groups consisting of medical students in a tutor-guided PBL session using a text-based case, (2) distance groups using the same text-based case but interacting over distance from multiple sites, (3) groups using a VR simulation scenario integrated into the case without interaction over distance, and (4) combination groups interacting over distance from multiple sites with integration of a VR simulation scenario. RESULTS: The study results suggest that it is possible to successfully conduct a PBL tutorial with medical students from two institutions with the integration VR and distributed distance interaction in combination or independently. The addition of these modalities did not interfere with learning dynamics when compared with traditional tutorial sessions. CONCLUSIONS: These findings suggest the feasibility and acceptability by students in the use of VR simulation integrated into a PBL learning session, as well as multipoint distance technologies that allowed interaction between students and tutors in different locations. The authors believe that these modalities can be applied where students and tutors from different institutions are in separate locations and can be used to support interactive experiential learning in a distributed network or on site and suggest areas for additional research.

The effect of degree of immersion upon learning performance in virtual reality simulations for medical education.

Simulations are being used in education and training to enhance understanding, improve performance, and assess competence. However, it is important to measure the performance of these simulations as learning and training tools. This study examined and compared knowledge acquisition using a knowledge structure design. The subjects were first-year medical students at The University of New Mexico School of Medicine. One group used a fully immersed virtual reality (VR) environment using a head mounted display (HMD) and another group used a partially immersed (computer screen) VR environment. The study aims were to determine whether there were significant differences between the two groups as measured by changes in knowledge structure before and after the VR simulation experience. The results showed that both groups benefited from the VR simulation training as measured by the significant increased similarity to the expert knowledge network after the training experience. However, the immersed group showed a significantly higher gain than the partially immersed group. This study demonstrated a positive effect of VR simulation on learning as reflected by improvements in knowledge structure but an enhanced effect of full-immersion using a HMD vs. a screen-based VR system.

Towards an immersive virtual environment for medical team training.

Many computer based medical simulators focus on individual skills training. However, medical care is frequently rendered by teams. In addition, the conditions under which care is provided can be a crucial factor in training. For example, mass-casualty events can involve the management and triage of large numbers of victims under austere environments. Learning to care for the injured warfighter during combat requires realistic simulation of battlefield conditions. Current simulation systems do not adequately address team training requirements within lifelike environments. This paper describes our work toward the development of an immersive virtual environment that meets these needs.

Reification of abstract concepts to improve comprehension using interactive virtual environments and a knowledge-based design: a renal physiology model.

Several abstract concepts in medical education are difficult to teach and comprehend. In order to address this challenge, we have been applying the approach of reification of abstract concepts using interactive virtual environments and a knowledge-based design. Reification is the process of making abstract concepts and events, beyond the realm of direct human experience, concrete and accessible to teachers and learners. Entering virtual worlds and simulations not otherwise easily accessible provides an opportunity to create, study, and evaluate the emergence of knowledge and comprehension from the direct interaction of learners with otherwise complex abstract ideas and principles by bringing them to life. Using a knowledge-based design process and appropriate subject matter experts, knowledge structure methods are applied in order to prioritize, characterize important relationships, and create a concept map that can be integrated into the reified models that are subsequently developed. Applying these principles, our interdisciplinary team has been developing a reified model of the nephron into which important physiologic functions can be integrated and rendered into a three dimensional virtual environment called Flatland, a virtual environments development software tool, within which a learners can interact using off-the-shelf hardware. The nephron model can be driven dynamically by a rules-based artificial intelligence engine, applying the rules and concepts developed in conjunction with the subject matter experts. In the future, the nephron model can be used to interactively demonstrate a number of physiologic principles or a variety of pathological processes that may be difficult to teach and understand. In addition, this approach to reification can be applied to a host of other physiologic and pathological concepts in other systems. These methods will require further evaluation to determine their impact and role in learning.

Algorithmically generated music enhances VR nephron simulation.

While sonification has enjoyed much attention in VR simulation studies, music has generally been incorporated as ambiance. This is partially due to difficulties with manipulating it interactively in real-time while maintaining a sensible musicality. This paper discusses how algorithmically generated music is used to provide ambiance, characterize the visual representation of molecular particle flow, provide orientation cues to the user, and enhance recognition of chemical gradient balances in a reified model of the kidney nephron. The technical obstacles related to the use of music in this context are also addressed.

Virtual reality training improves students' knowledge structures of medical concepts.

Virtual environments can provide training that is difficult to achieve under normal circumstances. Medical students can work on high-risk cases in a realistic, time-critical environment, where students practice skills in a cognitively demanding and emotionally compelling situation. Research from cognitive science has shown that as students acquire domain expertise, their semantic organization of core domain concepts become more similar to those of an expert's. In the current study, we hypothesized that students' knowledge structures would become more expert-like as a result of their diagnosing and treating a patient experiencing a hematoma within a virtual environment. Forty-eight medical students diagnosed and treated a hematoma case within a fully immersed virtual environment. Student's semantic organization of 25 case-related concepts was assessed prior to and after training. Students' knowledge structures became more integrated and similar to an expert knowledge structure of the concepts as a result of the learning experience. The methods used here for eliciting, representing, and evaluating knowledge structures offer a sensitive and objective means for evaluating student learning in virtual environments and medical simulations.

Distributed interactive virtual environments for collaborative experiential learning and training independent of distance over Internet2.

Medical knowledge and skills essential for tomorrow's healthcare professionals continue to change faster than ever before creating new demands in medical education. Project TOUCH (Telehealth Outreach for Unified Community Health) has been developing methods to enhance learning by coupling innovations in medical education with advanced technology in high performance computing and next generation Internet2 embedded in virtual reality environments (VRE), artificial intelligence and experiential active learning. Simulations have been used in education and training to allow learners to make mistakes safely in lieu of real-life situations, learn from those mistakes and ultimately improve performance by subsequent avoidance of those mistakes. Distributed virtual interactive environments are used over distance to enable learning and participation in dynamic, problem-based, clinical, artificial intelligence rules-based, virtual simulations. The virtual reality patient is programmed to dynamically change over time and respond to the manipulations by the learner. Participants are fully immersed within the VRE platform using a head-mounted display and tracker system. Navigation, locomotion and handling of objects are accomplished using a joy-wand. Distribution is managed via the Internet2 Access Grid using point-to-point or multi-casting connectivity through which the participants can interact. Medical students in Hawaii and New Mexico (NM) participated collaboratively in problem solving and managing of a simulated patient with a closed head injury in VRE; dividing tasks, handing off objects, and functioning as a team. Students stated that opportunities to make mistakes and repeat actions in the VRE were extremely helpful in learning specific principles. VRE created higher performance expectations and some anxiety among VRE users. VRE orientation was adequate but students needed time to adapt and practice in order to improve efficiency. This was also demonstrated successfully between Western Australia and UNM. We successfully demonstrated the ability to fully immerse participants in a distributed virtual environment independent of distance for collaborative team interaction in medical simulation designed for education and training. The ability to make mistakes in a safe environment is well received by students and has a positive impact on their understanding, as well as memory of the principles involved in correcting those mistakes. Bringing people together as virtual teams for interactive experiential learning and collaborative training, independent of distance, provides a platform for distributed "just-in-time" training, performance assessment and credentialing. Further validation is necessary to determine the potential value of the distributed VRE in knowledge transfer, improved future performance and should entail training participants to competence in using these tools.

eLoom and Flatland: specification, simulation and visualization engines for the study of arbitrary hierarchical neural architectures.

eLoom is an open source graph simulation software tool, developed at the University of New Mexico (UNM), that enables users to specify and simulate neural network models. Its specification language and libraries enables users to construct and simulate arbitrary, potentially hierarchical network structures on serial and parallel processing systems. In addition, eLoom is integrated with UNM's Flatland, an open source virtual environments development tool to provide real-time visualizations of the network structure and activity. Visualization is a useful method for understanding both learning and computation in artificial neural networks. Through 3D animated pictorially representations of the state and flow of information in the network, a better understanding of network functionality is achieved. ART-1, LAPART-II, MLP, and SOM neural networks are presented to illustrate eLoom and Flatland's capabilities.

Virtual patient simulator for distributed collaborative medical education.

Project TOUCH (Telehealth Outreach for Unified Community Health; http://hsc.unm.edu/touch) investigates the feasibility of using advanced technologies to enhance education in an innovative problem-based learning format currently being used in medical school curricula, applying specific clinical case models, and deploying to remote sites/workstations. The University of New Mexico's School of Medicine and the John A. Burns School of Medicine at the University of Hawai'i face similar health care challenges in providing and delivering services and training to remote and rural areas. Recognizing that health care needs are local and require local solutions, both states are committed to improving health care delivery to their unique populations by sharing information and experiences through emerging telehealth technologies by using high-performance computing and communications resources. The purpose of this study is to describe the deployment of a problem-based learning case distributed over the National Computational Science Alliance's Access Grid. Emphasis is placed on the underlying technical components of the TOUCH project, including the virtual reality development tool Flatland, the artificial intelligence-based simulation engine, the Access Grid, high-performance computing platforms, and the software that connects them all. In addition, educational and technical challenges for Project TOUCH are identified.