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date: 22 August 2017

Immersive Virtual Environments, Avatars, and Agents for Health

Summary and Keywords

Immersive virtual environments (IVEs) are systems comprised of digital devices that simulate multiple layers of sensory information so that users experience sight, sound, and even touch like they do in the physical world. Users are typically represented in these environments in the form of virtual humans and may interact with other virtual representations such as health-care providers, coaches, future selves, or treatment stimuli (e.g., phobia triggers, such as crowds of people or spiders). These virtual representations can be controlled by humans (avatars) or computers algorithms (agents). Embodying avatars and interacting with agents, patients can experience sensory-rich simulations in the virtual world that may be difficult or even impossible to experience in the physical world but are sufficiently real to influence health attitudes and behaviors. Avatars and agents are infinitely customizable to tailor virtual experiences at the individual level, and IVEs are able to transcend the spatial and temporal boundaries of the physical world. Although still preliminary, a growing number of studies demonstrate IVEs’ potential as a health promotion and therapy tool, complementing and enhancing current treatment regimens. Attempts to incorporate IVEs into treatments and intervention programs have been made in a number of areas, including physical activity, nutrition, rehabilitation, exposure therapy, and autism spectrum disorders. Although further development and research is necessary, the increasing availability of consumer-grade IVE systems may allow clinicians and patients to consider IVE treatment as a routine part of their regimen in the near future.

Keywords: avatars, agents, immersive virtual environments, health interventions, virtual reality, virtual reality exposure therapy

Surpassing three trillion US dollars in 2014, health-care spending is at almost $10,000 per person (Centers for Medicare & Medicaid Services), and this trend is projected to accelerate in the coming decade (Keehan et al., 2015). Labor involved in health care accounts for the largest proportion of expenditures in many health systems, and scholars believe that unlocking innovation to reduce the labor-intensive nature of health care might be key to slowing this spending growth (Macdonnell & Darzi, 2013). The search for creative and effective solutions to reduce health-care expenditure is a timely task. Healthcare technology, such as m-health and e-health, aims to offer cost- and labor-effective solutions to health-care professionals through incorporating digital devices and infrastructures. For instance, a large-scale study suggested that web-based interventions for adults using computer-tailored health guidance might be more cost effective for health outcomes than traditional means of health care (Schulz et al., 2014).

There has been much anticipation of recent regarding the potential of immersive virtual environments, popularly referred to as “virtual reality,” as a viable technology to be applied in everyday clinical settings and a source of self-guided health care for patients. In the 1990s, researchers and clinicians began to recognize the utility of these computer-generated environments to provide health treatment. Since then, the application of virtual environments in health care has expanded greatly, ranging from interventions to training programs. Immersive virtual environments are being actively researched for a myriad of health-care applications, including doctor training, therapy, rehabilitation, and patient education. Building on the earlier efforts to develop efficient and effective health-care technology, this chapter introduces immersive virtual environments as another potential innovation to the existing array of health-care technology by discussing how these virtual worlds may offer a cost- and labor-effective approach to improving health care while retaining much of the advantages of traditional health-care practices. In the coming sections, this article provides an introduction to immersive virtual environments and explains their distinctive structural affordances. This article also discusses how users and other humans are represented in virtual environments and what characteristics of these representations are meaningful for health applications. Then, various health applications of virtual environments in both research and clinical settings will be reviewed. Finally, the literature will be synthesized to discuss the advantages and limitations of virtual environments for health practitioners now and in the future.

An Introduction to Immersive Virtual Environments

Immersive virtual environments (IVEs) are digital systems comprised of devices that simulate multiple layers of sensory information so that users are able to see, hear, and feel as if they are in the real world (Blascovich & Bailenson, 2011; Loomis, Blascovich, & Beall, 1999). IVEs are distinguished from other virtual environments by their ability to track users’ natural physical movements and use this information to render the digital setting accordingly. A growing collection of literature demonstrates that digitally mediated multisensory experiences in IVEs can influence attitudes and behaviors that transfer into the non-mediated, physical world (see Ahn & Fox, 2016; Blascovich & Bailenson, 2011; Fox, Christy, & Vang, 2014; Yee, 2014). Novel affordances of advanced digital media such as IVEs allow individuals to go beyond passive consumption experiences provided by traditional media such as television and books. Instead, people become active participants in the mediated context.

Personal and direct experiences have greater impact on attitude and behavior change than indirect experiences (Hertwig et al., 2004; Rajecki, 1982). Direct experiences provide detailed sensory cues, which become associated and stored with existing schemas or mental models. These schemas are later activated and recalled when the individual encounters or thinks about similar stimuli (Barsalou, 2009). When direct experiences are mimicked with sufficient realism, schemas may also be constructed following mediated experiences (Bandura, 2001). Because the rich layers of simulated sensory information in IVEs mimic direct experiences better than traditional media or imagination (Ahn, in press; Ahn, Bailenson, & Park, 2014), virtual experiences in IVEs are likely to have a stronger impact on attitude and behavior formation than simulations where the person is less embodied and presented with environments less similar to direct experiences.

As the name implies, immersion is a main feature of IVEs and refers to users being surrounded or enveloped by sensory information simulated with digital devices (Heeter, 1992; Steuer, 1992). Virtual environments can differ in the level of immersion that they offer. IVEs can provide stereoscopic visual input, spatialized aural input, and tactile input, yielding a sense of perceptual depth and vivid realism. In comparison, virtual environments with lower levels of immersion, such as desktop computers, offer monoscopic visual, simple audio, and limited tactile inputs. The effect of having differing intensity of immersiveness is still being debated (Ahn et al., 2016; Fox et al., 2014; Price & Anderson, 2007; Price, Anderson, & Rothbaum, 2008). For example, a meta-analysis (Cummings & Bailenson, 2016) reported that levels of immersion yield moderate size effects on users’ perceptions of “being there” in the virtual world, and a systematic review suggested that more immersive virtual simulations may be more conducive to positive treatment outcomes for autism spectrum disorders (Miller & Bugnariu, 2016). However, because the perception of presence in virtual worlds is subjective, and not necessarily dependent on technological features, the degree of immersiveness may not be the sole driver of user experience, but rather, individual differences (Galloso, Palacios, Feijóo, & Santamaría, 2016) such as cognitive abilities (Sacau, Laarni, & Hartmann, 2008), capacity for imagination (Sas & O’Hare, 2003), and even personality (Sacau et al., 2008; Sas & O’Hare, 2003). Thus, if the individual does not or is not able to perceive differences between high versus low immersive systems, user experience may not be influenced.

Interactivity is another characteristic of IVEs that distinguishes them from traditional media—the technological capacity of the digital system to actually respond in a two-way exchange, immediately, in real-time (Rafaeli, 1988; Rice & Williams, 1984; Steuer, 1992). Although interactivity is not unique to IVEs, they tend to provide users with the most engaging and responsive stimuli that respond in real time to user actions. Interactivity allows the user to be both an observer and a participant in mediated environments, possibly leading to more potent media effects (Rafaeli, 1988; Steuer, 1992). IVEs offer interactivity in several ways that encourage greater user control, participation, and engagement by eliciting user interaction with the interface through system features (Sundar, Xu, & Bellur, 2010).

These features present a wide range of opportunities for health communication researchers and practitioners to incorporate IVEs into their health-care or health intervention programs, which will be discussed in further detail in following sections. In the past, access to IVE systems were often restricted to sophisticated laboratory and research establishments. In the early 21st century, however, the applicability of IVEs in clinical settings has become much more feasible with the rapid development of consumer-grade headsets that would allow users to experience IVEs in the comfort of their own living rooms, such as the Google Cardboard, Samsung Gear VR, Oculus Rift, and HTC Vive. As of 2016, 2.3 million US households with broadband currently own at least one such headset, and the rate of adoption is expected to increase rapidly (Parks Associates, 2016). The adoption of this novel technology has the potential to transform existing paradigms of human interaction in both mediated and non-mediated environments. The past two decades of research has also demonstrated the potential of IVEs for changing health-related attitudes and behaviors.

Representing Interactions in Immersive Virtual Environments with Avatars and Agents

Virtual representations include both people and objects rendered in virtual environments. Representations can vary on both their physical realism, which is how much they appear similar to their manifestation in the real world, and their behavioral realism, or to what extent they act in ways consistent with the real world (Blascovich, 2002). For example, a virtual pizza high in physical realism may look good enough to eat, down to the glisten of grease atop a meaty pepperoni slice. If the pizza suddenly spoke and informed you that you would be consuming 298 calories and 12 grams of fat per slice, however, it would be low in behavioral realism.

Conceptually speaking, any form of representation that symbolizes a person can be considered an avatar, whether digital or not (Ahn et al., 2011). A name, a voice, a photo, or a top hat used in a game of Monopoly: these can all serve as a user’s avatar. In digital environments, an avatar is a representation controlled by a human user. If a representation is controlled by a computer or algorithm, it is an agent. This distinction is an important one; avatars have been shown to be more persuasive than agents (see meta-analysis by Fox, Ahn, Janssen, Yeykelis, Segovia, & Bailenson, 2015). The model of social influence in virtual environments, however, suggests this effect may be moderated by the perceived behavioral realism of virtual representations (Blascovich, 2002). Fox and colleagues (2015) also discovered that who is actually controlling a representation is less important than who people perceive to be controlling the representation. That is, if a user thinks another human is controlling a representation, then it is more persuasive—regardless of whether it is actually controlled by a human or a computer. This perception may be important for researchers or clinicians who are trying to persuade users to make health behavior changes, for example. If agents that are programmed to carry out the role of health-care professionals, such as nurses or therapists, are designed to behave just as realistically as their human counterparts, they may become as impactful as humans.

Both avatars and agents frequently manifest in human form within health IVEs. Over time, virtual representations of people have become significantly more complex, rendered in three dimensional forms with an extensive range of dynamic movements, photorealistic appearances, naturalistic language, and even the ability to mimic empathy when interacting with users (Blascovich & Bailenson, 2011). These virtual humans are designed to be high in both physical and behavioral realism. Such similarity to real people is conducive to natural interactions in the IVE, such as consulting with a virtual patient or interacting with a virtual fitness coach (Fox, 2012). Virtual humans have been used to impact a wide range of behaviors in the physical world, ranging from health monitoring (Skalski & Tamborini, 2007), helping behavior (Eastwich & Gardner, 2009), and to brand preference (Ahn & Bailenson, 2011; Fox et al., 2014). As Bandura (1977) noted, persuasive messages from interpersonal sources can have a direct impact on self-efficacy; using virtual humans to convey these messages may maximize the impact of health messages because they evoke many of the same or similar feelings as interpersonal interactions.

Advantages and Disadvantages of Using Avatars and Agents in Health Interventions

Both agents and avatars are viable options for incorporation in health prevention and intervention programs; the choice to use one over the other should be made after careful consideration of the benefits and costs. Avatars that are controlled by humans are likely to have stronger impacts on health behavior change in the physical world than agents that are controlled by machines. Rather than an agent providing a heavily scripted health intervention, an avatar delivering naturalistic interactions is likely to be much more effective in influencing health behaviors. Having an actual person control a virtual human may be useful in a variety of health contexts.

Avatars present many other advantages to health communication, particularly between doctors and patients. On a basic level, avatars allow users to interact with the doctor at a distance via virtual worlds, while minimizing issues or inconveniences of remote communication. For example, communicating via phone, e-mail, or text chat can strip out some nonverbal aspects. Although webcams can be useful, they are limited in that they can only portray the current physical state of the patient. Avatars allow patients to project more information than just their current state by graphically portraying descriptions and occurrences of their symptoms’ evolution over time to provide a doctor with more granular details. A doctor could map a patient’s history of complaints onto the patient’s avatar to get a holistic, head-to-toe view of medical issues. Having all of this information visible might facilitate diagnoses. This visibility might also be useful for doctors to explain the complex interrelations among the patient’s symptoms (e.g., how a person’s excess weight is causing back and knee pain) and show how these conditions might change the entire body over time.

Avatars also present users with the opportunity for an experience beyond mere exposure to mediated imagery. Users embody avatars, controlling the movements and interactions of the representation; thus, the avatar becomes a proxy for the physical self in the virtual world (Ahn, Fox, & Bailenson, 2011). As Biocca (1997) noted, during avatar embodiment “the mental model of the user’s body (body schema or body image) may be influenced by the mapping of the physical body to the geometry and topology of the virtual body.”

Although avatars are more persuasive than agents, there may be situations in which computer-controlled agents are a more viable option. Having human controllers positioned for each and every avatar would be effortful and costly; thus, employing a human controller may be prohibitive in a large-scale program. Although the initial development and setup of the agent might be costly, once the infrastructure is established, agents can continue to work at the same speed and efficiency without the need to eat or rest. These agents may be infinitely replicable, which would allow patients to receive equal and uniform care across all health-care facilities. Relational agents can express appropriate affect and empathy to patients (Bickmore, 2015). Recent research also indicates a potential benefit of using agents over avatars: when interacting with a virtual human during a health screening, participants were more comfortable disclosing to an agent than a human-controlled avatar (Lucas, Gratch, King, & Morency, 2014). For sensitive topics of discussion (e.g., sexual history, substance abuse), patients may prefer to interact with a computer-controlled agent rather than a human-controlled avatar for greater perceived privacy.

Individuals often judge others based on nonverbal cues such as physical appearance or behavior (Rosenberg & McCafferty, 1987; Sigelman, Sigleman, & Fowler, 1987; Todorov et al., 2005). Indeed, people are often drawn to others perceived as similar to themselves (Bailenson et al., 2008; Baumeister, 1998), or simply familiar (e.g., celebrities; Tanner & Maeng, 2012; Zajonc, 2001). Even with the knowledge from these findings, it would be difficult to apply these findings in clinical settings in the physical world because people have limited capacity to manipulate their appearances. In comparison, manipulating the appearance of a virtual human is much simpler: at the click of a button, a virtual human may be transformed into a multitude of permutations, bound only by the software’s limitations.

Because virtual humans afford labor- and cost-effective means of adopting almost a limitless option of physical appearances and behaviors, they may flexibly tailor and personalize their appearance and interaction patterns for each respective patient at a fraction of the cost it would take to hire and train health-care professionals (Ahn, 2017). For example, clinicians may interact with patients in virtual worlds and create virtual humans that match the traits of each individual patient, such as ethnicity or gender. Alternatively, the virtual human could take on the physical appearance of a well-known celebrity to deliver health messages, and the perceived familiarity triggered by the virtual human may favorably impact persuasion as demonstrated in earlier studies (Tanner & Maeng, 2012).

One particularly useful form of virtual human that maximizes this flexibility is the virtual doppelgänger that is created with digital photographs of the user so that they bear photorealistic resemblance to the self (Ahn, Fox, & Hahm, 2014; Fox & Bailenson, 2010). Because these virtual humans bear such striking similarities to the self, they lead to novel situations wherein the physical self may view the virtual self as a third person, much like looking into a mirror. The virtual doppelgänger can be programmed to behave independently of the physical self so that a virtual human that looks like the physical self may be controlled by a third party or an algorithm (Ahn, 2015, in press; Fox & Bailenson, 2009), creating unique situations for persuasion and behavior change wherein the virtual self is used to persuade the physical self (Ahn & Bailenson, 2011; Ahn, Phua, & Shan, 2017).

Another promising form of virtual representation would be an optimal hybrid of avatars and agents that combine the advantages of both forms of virtual humans (Fan, McNeese, & Yen, 2010). For instance, Chase and colleagues (2009) discuss using a hybrid virtual representative that blends the properties of avatars and agents to serve as a teaching agent. If avatars can exert greater social influence on individuals compared to agents as confirmed by our current study, and agents offer greater controllability and are cheaper to operate and manage, hybrids may be able implement the best of both worlds.

The use of avatars and agents allow users to maximize the benefits of the novel features that IVEs have to offer in the context of health interventions. The next few sections will discuss the interplay between these novel IVE features and embodied experiences or interactions with agents in the virtual worlds and the impact they have on health related outcomes. Because desired health behaviors and outcomes can vary widely depending on the relevant health issue, each section will discuss a specific health issue and how IVEs may be applied in the context of that particular issue.

Promoting Physical Activity

Identification, or feelings of being similar to another, increases the likelihood that an individual will model and follow the behaviors of the entity he or she identifies with (Bandura, 1977, 2001). One known motivator of physical activity is modeling a person with whom they identify with, for instance, parents (Bois, Sarrazin, Brustad, Rouilloud, & Cury, 2005; Brustad, 1996). These findings suggest that creating a virtual human that is sufficiently similar to the users to elicit identification is likely to be successful in encouraging physical activity via modeling.

An earlier study provided empirical support by investigating the use of virtual doppelgängers to promote physical activity (Fox & Bailenson, 2009). In this study, participants were randomly assigned to three groups: one group saw a virtual doppelgänger running on a treadmill in the virtual world, another group saw a virtual human of an unfamiliar person running on a treadmill, and the final group saw a virtual doppelgänger loitering. Twenty-four hours following exposure, participants who saw a virtual doppelgänger running engaged in greater levels of physical activity during the day than those in other conditions. These results suggest that using a virtual doppelgänger is more effective than a generic virtual human in encouraging modeling behaviors, wherein the physical self is persuaded to model and follow the behaviors of the virtual self.

In the past, such studies had to be conducted in a highly controlled laboratory setting because the experimental set up required state-of-the-art digital devices. In the early 21st century, videogame consoles with tracking capabilities have gradually increased the accessibility and affordability of IVE applications that require players to use body movements to progress through the game (Biddiss & Irwin, 2010). Some studies have demonstrated that interacting with virtual humans in these exergames results in increased physical activity (Peng & Crouse, 2013) and weight reduction (Staino, Abraham, & Calvert, 2013). Although findings are mixed and the physical activity outcomes of exergames remain small to moderate (Baranowski et al., 2012; Peng, Crouse, & Lin, 2013), they demonstrate the possibilities of health applications within low-grade, commercially available IVEs.

The bulk of studies looking at agents and avatars have investigated the influence of virtual humans, but not all virtual representations are required to take on human forms. Earlier, a small pilot study tested the feasibility of a desktop computer game of a virtual agent in the shape of a fish, which grew in size and sported different facial expressions depending on whether participants met physical activity goals (Lin et al., 2006). Although formal scientific designs were not incorporated in the study, all fourteen participants expressed engagement in the game over the span of 14 weeks.

More recently, researchers investigated the potential of using a computer agent linked to a physical activity monitor to promote physical activity in children (Ahn et al., 2015; Johnsen et al., 2014). Guided by the framework of social cognitive theory (Bandura, 1977, 2001), the virtual agent was a dog designed to systematically promote physical activity in children through goal setting, vicarious experiences, and positive reinforcement. Children’s physical activity was measured with an activity monitor that was synchronized with each virtual dog so that each child was paired with a unique pet displayed on a television screen mounted on a kiosk. The activity monitor worn by each child updated the virtual pet automatically with physical activity data when the child stepped up to the kiosk. As children engaged in physical activity and met more physical activity goals, the virtual dog displayed the health benefits through a leaner appearance, faster response times, and more enthusiastic body movements (e.g., wagging tail, playful gestures). When compared with children in the control group who were given an identical computer system with the same goal-setting and feedback functionalities but without the virtual dog, children who interacted with the virtual dog engaged in approximately 1.09 more hours of physical activity daily than the children in the control group. Interacting with the virtual dog led children to feel confident about their abilities to set and meet physical activity goals, which strengthened their beliefs that physical activity is good for them and subsequently led to an increase in physical activity.

Healthy Dietary Choices

Promoting food consumption presents unique challenges in children. When they are given extrinsic, rather than intrinsic, goals for healthy food consumption, children suddenly consider the healthy food item to be less preferable (Birch, Birch, Marlin, & Kramer, 1982). For example, when children were told that crackers would make them healthy, they ate fewer crackers and thought the crackers were less tasty compared to children who were given the same crackers without an extrinsic goal (Maimaran & Fishbach, 2014). This suggests that children may initially increase consumption of healthy foods to obtain extrinsic rewards but fail to continue the healthy behavior because of their decreased preference for the food items.

Taking this challenge into consideration, the virtual dog was tested again in the context of promoting fruit and vegetable consumption in children (Ahn et al., 2016). Using similar goal setting, feedback, and reinforcement features, children between the ages 7 and 13 were randomly assigned to three experimental conditions: virtual dog, computer system with similar features without the virtual dog, and no intervention control. Fruit and vegetable consumption, as well as changes in food preferences for the fruit and vegetable items were assessed over a three day period. Results indicated that children in the virtual dog condition chose to be served significantly more fruit and vegetables than those in the computer only or control conditions. Moreover, food preferences did not differ significantly across the three conditions before and after experimental treatments, suggesting that interacting with the virtual dog may have subverted children’s attention on the fact that they were given extrinsic goals to consume healthy food items. Many participants indicated enjoyment regarding their interaction experience with the dog (e.g., “Fun to play with!”).

Another novel affordance of avatars and agents within IVEs is that they can be used to accurately portray past, current, and potential future health conditions. In the virtual world, time becomes a more fluid concept than in the physical world; once created, an agent or an avatar may be digitally manipulated to dynamically shift their appearances. Rather than having to exert cognitive effort to imagine oneself in a specific state, or personally experiencing the negative future health consequence, a user can experience and observe conditions on his or her own virtual body to simulate negative health consequences of unhealthy dietary choices without incurring harm to the physical body. Traditional media, such as static photos or television, are often limited to portraying only “before” and “after” scenarios, whereas the IVEs can be used to dynamically depict incremental levels of change or alternate realities depending on what health choices are made. These affordances allow virtual humans to be more potent and effective models than those used in traditional health behavior change efforts.

Individuals are likely to hold an unrealistic level of optimism in conceptualizing distant future events (Weinstein, 1980). People tend to think of the future as an isolated event, independent of past and present events, and base their forecasts of the future on plans and scenarios of success rather than on accurate past results (Kahneman & Lovallo, 1993). This biased thinking is particularly applicable to future health risks. Because negative health consequences may take some time to manifest following present behaviors, the large temporal distance is likely to encourage unrealistic and inaccurate levels of optimism in thinking about the health issue. For instance, consuming unhealthy snacks today will not immediately lead to weight gain and obesity-related issues the next day; rather, the detrimental effect of unhealthy snacking may require years to manifest. The temporal distance between the cause (unhealthy snacking) and effect (weight gain and obesity-related problems) renders this relationship abstract and opaque, leading individuals to assume an optimistic outlook for their health in the future. Consequently, this positivity bias is one major barrier to successfully communicating health risks and changing present health behaviors. Using agents and avatars in IVEs to digitally render future negative health consequences allows individuals to clearly understand the causal relationship between their present actions as well as the seriousness of the negative consequences to occur in the future.

One early study demonstrated the extent to which participants felt that the simulation of such future negative consequences using avatars in IVEs was vivid and believable. In this study (Fox, Bailenson, & Binney, 2009), participants were exposed to their self avatar eating. Afterward, they responded to some questionnaire items while seated at a computer with a bowl of chocolate candy placed on the table. For participants who experienced presence (i.e., they felt the environment was realistic and involving), social facilitation of eating behaviors occurred, wherein men ate more and women ate less in the presence of another person (Harrison, Taylor, & Marske, 2006; Herman, Roth, & Polivy, 2003). That is, the same social eating patterns that are observed in the physical world were replicated when participants encountered a virtual person: high-presence men ate more candy, whereas high-presence women suppressed their appetites.

Another study further explored the underlying mechanisms of virtual doppelgängers demonstrating accelerated passing of time to display the future negative health consequences of soft drink consumption (Ahn, Fox, & Hahm, 2014). Participants were exposed to an IVE showing either virtual doppelgängers or an unfamiliar agent gaining weight as a result of consuming soft drinks regularly for two years, depicted in two minutes in the virtual world. Results indicated that virtual doppelgängers were more effective than unfamiliar agents in increasing the perception of presence (i.e., participants felt as if they were in the virtual world, consuming a soft drink) as well as self-relevant thoughts. Watching an agent that looks like the self consume soft drinks and become obese made participants feel as if he or she were truly undergoing the experience and encouraged them to think about themselves in the context of soft drink consumption. Heightened presence and self-relevant thoughts, in turn, led to increased personal relevance to the issue of soft drink consumption and obesity.

Building on these preliminary findings, a recent set of studies investigated the effect of agents in eliciting perceptions of risk imminence (i.e., “The health risk could happen very soon”) and personal relevance toward the health risk (i.e., “The health risk could happen to me”) in the context of soft drink consumption (Ahn, 2015). Findings suggested that when such virtual simulations are coupled with traditional platforms of health communication, such as pamphlets, this combination could yield potent effects that persist over time, even without the use of virtual doppelgängers. Participants who were exposed to health risk information on soft drink consumption through both a pamphlet and an IVE simulation of a virtual agent gaining weight as a result of regularly consuming soft drinks over time exhibited an increase in perceived risk imminence, which led to a reduction in the consumption of soft drinks, one week following exposure to experimental treatments. A follow up study then demonstrated that such virtual simulations led to greater levels of risk perceptions on soft drink consumption than strictly statistical information or static “before” and “after” pictures (Ahn, in press).

IVEs may also be used to simulate and measure eating scenarios. Accurate measurement of food choice and consumption is extremely difficult to obtain in field studies and researchers often rely on self-reports such as food diaries that have often been criticized for inaccuracy and reporting-biases (Cook, Pryer, & Shetty, 2000). Creating eating environments in IVEs allow researchers to observe food selection in a highly controlled environment, while retaining ecological validity by constructing a realistic eating environment. For instance, McBride and colleagues (2013) constructed a virtual buffet where participants could select a variety of food items in varying amounts to place on their virtual plates, following individually tailored nutrition education. Using this experimental setup, researchers were able to accurately gauge the total caloric content of the foods selected without the interference of uncontrolled variables that may have been present if they had conducted the behavioral measure at a buffet in the physical world.

Using IVEs for Therapeutic Interventions

IVEs have also been used to complement traditional counseling and behavioral therapy. Scholars have noted that IVEs present the best of both worlds for therapy because the virtual simulation is perceived as a safer environment where patients can explore new grounds without incurring physical harm, yet retains sufficient experiential realism through vivid sensory information (Perpiña, Botella, & Baños, 2003). In addition, compared to traditional in vivo techniques that expose patients to real life situations, IVEs allow clinicians to control and tailor the exposure to the threat appropriate for each patient.

Virtual reality exposure therapy. One of the most common applications of IVEs is virtual reality exposure therapy (VRET; Parsons & Rizzo, 2008; Powers & Emmelkamp, 2008; Riva, 2005; Rothbaum, Hodges, & Kooper, 1997). Psychiatric researchers realized that IVEs could be used to treat patients who suffer from a specific anxiety or phobia (Opriş, Pintea, García-Palacios, Botella, Szamosközi, & David, 2012; Wiederhold & Bouchard, 2014). In the virtual environment, patients are gradually introduced to the negative stimulus in a virtual setting until they become desensitized or are able to cope with their fear or anxiety. Using IVEs allows the therapist to have maximal control over the introduction and intensity of the fear-inducing stimulus. VRET has been used to treat a number of fears, including acrophobia, the fear of heights (Coelho, Santos, Silvério, & Silva, 2006); agoraphobia, the fear of open spaces (Botella et al., 2007); fear of animals, such as arachnophobia, the fear of spiders (Cote & Bouchard, 2005); aviophobia, the fear of flying (Rothbaum, Hodges, Smith, Lee, & Price, 2000); and claustrophobia, the fear of enclosed spaces (Botella, Baños, Villa, Perpiñá, & García-Palacios, 2000). Phobia treatments may be particularly useful with sensitive populations for whom in vivo therapy (i.e., in which they experience their source of fear in the physical world) is risky, such as children with autism spectrum disorders (Maskey, Lowry, Rodgers, McConachie, & Parr, 2014). Another notable benefit of VRET is that, when considering treatment, individuals suffering from phobias are far less likely to refuse VR-based therapy compared to in vivo forms of therapy (Garcia-Palacios, Botella, Hoffman, & Fabregat, 2007). The ability to generate realistic virtual humans has also driven the use of virtual reality to address social anxiety and related phobias, such as public speaking anxiety (Harris, Kemmerling, & North, 2002), and social anxiety (Anderson et al., 2013; Roy, Klinger, Legeron, Lauer, Chemin, & Nugues, 2003).

One of the earliest clinical applications of VRET was to treat patients with body dysmorphia and eating disorders (Ferrer-García & Guitiérrez-Maldonado, 2012). Body image disturbances, wherein patients fail to accept their body as their own, lie at the core of many eating disorders, such as anorexia or bulimia (Stice & Shaw, 2002). This disturbance arises from the disconnect between the body image that the patients appraise and perceive of their body, and their actual physical appearance. Traditional therapy struggles to counter such cognitive biases, because the biased processing of information occurs almost automatically and as a result is real for patients (Williamson, 1990). Attempts to convince patients that their judgment of their body is biased are likely to produce strong psychological reactance (Dillard & Shen, 2005; Vitousek, Watson, & Wilson, 1998). Avatars and agents in IVEs allow patients to have complete control of their virtual body while clinicians guide them toward closing the gap between their perceived, virtual, and physical bodies (Perpiña, Botella, & Baños, 2002). Through creating and interacting with their avatars, patients are also able to view their body consciously as a third person. One study found that adding an IVE component to traditional behavioral treatments for body image disturbances better improved patient outcomes in their attitudes, thoughts, emotions, and behavior related to their body and physical appearance than the traditional behavioral treatment alone, both at post-treatment and at a one-year follow-up (Marco, Perpiña, & Botella, 2013).

IVEs are also being actively tested as a therapy tool to complement traditional counseling and behavioral therapy for eating disorders. Scholars have noted that IVEs present the best of both worlds for therapy because the virtual simulation is perceived as a “safe” environment where patients can confidently explore new grounds without incurring physical harm, yet retains sufficient experiential realism through vivid sensory information (Perpiña, Botella, & Baños, 2003; Riva, 2005). A randomized controlled trial of morbidly obese patients who underwent IVE treatment in addition to traditional treatments based on cognitive-behavioral approaches yielded greater likelihood of maintenance of the results of treatment at the 12-month follow-up, compared to patients who did not receive the IVE component (Cesa et al., 2013).

Due to the nascence of the field, and the complexity of the problem, further research is still needed to develop a standardized form of treatment that incorporates virtual experiences as a part of the formal treatment process for eating disorders and body image disturbances. Riva and his team have made substantial contributions to this effort by creating a protocol for body image rescripting, which includes 14 one-hour sessions led by a therapist (Riva, Gaggioli, & Dakanalis, 2013) to present patients with a comprehensive treatment plan that includes therapist-guided virtual simulations of critical situations that patients can experience from both a first-person and a third-person perspective. This encouraged patients to interpret and discuss their problems from both subjective and objective standpoints.

VRET has also been employed in the treatment of post-traumatic stress disorder (PTSD; McLay et al., 2014; Rothbaum, Ruef, Litz, Han, & Hodges, 2003; Rizzo, Rger, Gahm, Difede, & Rothbaum, 2009). For example, in the treatment of combat-related PTSD, VEs are used to simulate battle environments, including the sights (e.g., jungle clearings, desert scenes, or inside helicopters), sounds (including gunfire, bombs, planes, others’ voices), and even haptic experiences (such as vibrations from an explosion). Veterans are gradually exposed to more vivid and stressful cues in the virtual environment over time, which can be used to facilitate desensitization or to evoke suppressed memories. Coping mechanisms can be practiced during or following the experience. In this way, veterans can learn to manage stressful triggers, such as loud noises, in the safety of a clinical setting. A meta-analysis of VRET also revealed another possible advantage, finding that veterans in treatment for PTSD seem less resistant to VRET compared to other forms of therapy (Gonçalves, Pedrozo, Coutinho, Figueira, & Ventura, 2012).

Another area of treatment that virtual environments researchers are currently exploring is addiction. Virtual reality has been used to test how relevant cues stimulate cravings for substances such as alcohol and tobacco (Baumann & Sayette, 2006; Cho et al., 2008). Cognitive behavioral therapy techniques are then incorporated alongside the cue exposure therapy so that individuals learn to cope with their cravings in a variety of contexts to maximize self-efficacy. These cue exposure techniques have been used to address problematic behaviors such as smoking (Pericot-Valverde, Secades-Villa, Gutiérrez-Maldonado, & García-Rodríguez, 2014) and gambling (Giroux, Faucher-Gravel, St-Hilaire, Boudreault, Jacques, & Bouchard, 2013).

Physical Therapy, Rehabilitation, and Applications

Another increasingly common application is the use of virtual reality therapy in physical rehabilitation (Riva, 2014; Schultheis & Rizzo, 2001; Sveistrup et al., 2003; Weiss, Keshner, & Levin, 2014). Virtual environments have two features that uniquely facilitate physical rehabilitation: the ability to capture and review one’s physical behavior three-dimensionally, thus enabling examination of one’s progress and failures and the ability to see one’s own avatar rendered in real time from a third-person point of view (Bailenson, Patel, Nielsen, Bajscy, Jung, & Kurillo, 2008). Additionally, virtual environments can be used to safely re-create real environments that might be challenges for those who have suffered an injury (e.g., crossing a busy intersection). VEs have been used to help stroke victims regain a sense of balance while walking (Deutsch & Mirelman, 2007) and help children with cerebral palsy develop muscular coordination (Bryanton, Bossé, Brien, McLean, McCormick, & Sveistrup, 2006).

Avatars and agents may provide assistance to populations with various disabilities who need rehabilitation work but find it difficult to regularly visit clinical settings. Preliminary evidence points to the potential of using IVE or videogame systems to aid rehabilitation programs, for example, patients recovering after knee surgery (Lee et al., 2016) and stroke patients (Corbetta, Imeri, & Gatti, 2015). Although these studies are preliminary, scholars commend the ease of use with virtual environments that allow patients to engage in highly repetitive rehabilitation sessions in the comfort of their own homes without the burden of personal trainers. Furthermore, Corbetta, Imeri, and Gatti (2015) note that because virtual environments mimic physical interactions better than more traditional media channels, they are more effective in encouraging rehabilitation exercises than television or video format training.

Treatment for Autistic Spectrum Disorders

Because IVEs are able to reproduce sensory-rich experiences, individuals likely expend less cognitive energy to construct mental imageries during a virtual experience. This digital assistance in mental imagery construction would be helpful in instances where individuals lack the schema to base their mental imagery on. For example, earlier research suggested that participants who are inherently less likely to engage in mentally taking the perspective of another person may receive greater assistance in understanding the other person by virtually experiencing that person’s perspective through IVEs than participants who are inherently more likely to engage in perspective taking (Ahn, Le, & Bailenson, 2013).

Similarly, scholars and practitioners who work with individuals on the autism spectrum disorder have begun to test IVE experiences that may help their patients (Irish, 2013; Lorenzo, Pomares, & Lledó, 2013). Exposure to virtual experiences is particularly relevant for these individuals because difficulty in taking the perspective of another person and using imagination to construct mental imageries are major characteristics of individuals with autistic spectrum disorders (Jordan, 2003; Wing & Gould, 1979). Because IVEs allow individuals to “step into the shoes” of another person through avatar embodiment from the first-person perspective, so that he or she may see, hear, and feel as the other person would, this offers a wide range of training and therapeutic opportunities to hone social cognitive skills, such as reading social cues or understanding different perspectives (Ahn et al., 2013). The fact that social situations constructed in IVEs may be repeated an infinite number of times for the patient without incurring training and personnel costs is another advantage for clinicians. In addition, the virtual environment is a safe place for patients to experiment and readjust their responses, allowing patients to be bolder in their level of engagement and exploration in IVEs than in real life situations (Standen & Brown, 2005).

A growing number of small-scale pilot studies confirm IVEs’ potential as a cost- and labor-effective tool for training social skills in individuals with autistic spectrum disorders in both children (Herrera et al., 2008; Ke & Im, 2013; Lorenzo et al., 2016) and high-functioning adults (Kandalaft et al., 2013; Parsons & Mitchell, 2002). A pilot study also demonstrated potential long-term benefits of IVE training by showing that participants with high-functioning autistic spectrum disorder who received job interview training via virtual simulations secured more competitive job positions six months following treatment than participants who did not receive this training (Smith et al., 2015).

IVEs as Health Teaching and Training Environments

Due to their high levels of realism and interactivity, IVEs have been incorporated in medical training for many years (Mantovani, Castelnuovo, Gaggioli, & Riva, 2003; Riva, 2014). Virtual three-dimensional models of the human body have become popular interactive tools for teaching medical students, nurses, and doctors elements of anatomy and physiology. Rather than put patients at risk, medical students and doctors can practice new techniques using virtual environments (de Ribaupierre, Kapralos, Haji, Stroulia, Dubrowski, & Eagleson, 2014; Riva, 2014). Not only are IVEs safer, they can also be used to simulate challenging conditions that are infrequently encountered in regular practice: the surgeon is then prepared for even the rarest complexities.

IVEs have also been used to teach medical personnel communication and decision-making skills. Traditional training techniques often involved actors and physical setups, which can be inconvenient or limiting. Several IVEs have been built for practitioners to develop and practice patient-provider interaction skills with diverse populations (Johnsen et al., 2006; Kenny, Rizzo, Parsons, Gratch, & Swartout, 2007). IVEs are capable of rendering a wide variety of scenarios and contexts to practice efficient decision making in highly stressful situations, including complex injuries; triage in an overflowing ER; and on-site management at a large-scale disaster, like a highway pileup (de Leo et al., 2003; Freeman, Thompson, Allely, Sobel, & Stansfield, 2000).

IVEs may also be a helpful tool in educating the public about abstract scientific concepts (Persky & McBride, 2009). For example, Kaphingst and colleagues (2009) created an educational virtual world where participants learned about genomic concepts such as preventative steps for increased genetic risk for health problems or diseases. To learn these concepts, participants could either actively search for the knowledge or passively listen to a lecture on genomic concepts. Interestingly, although participants who were active in the IVE simulation were more motivated to engage in learning, comprehension of the information provided was higher for participants who passively listened to the lecture. Although this was a small-scale pilot study, these findings suggest that interactivity in IVEs may not always lead to positive outcomes in the education context.

Discussion of the Literature

By producing simulations that closely mimic non-mediated sensory experiences, IVEs offer novel opportunities for health researchers and practitioners. Although IVEs may not completely replace current treatment regimens, these highly immersive and interactive platforms have the potential to complement and enhance traditional health intervention programs. Embodying avatars and interacting with computer agents, patients are able to freely experiment with a variety of simulated scenarios that are sufficiently real, without incurring social and physical costs. Traditional in vivo treatments are often rejected by patients because they can be overbearing; however, patients may explore virtual environments at their own pace, while still comforted by the fact that they are physically located at the clinician’s office. The confidence that patients gain within a virtual world is likely to facilitate the progress of treatment.

Because the physical and behavioral characteristics of virtual humans can be easily manipulated, virtual doppelgängers may be created to create simulations wherein the virtual self is employed to persuade the physical self. The simulations can be a straightforward replica of a real world event or a fantastical situation, which transcends the temporal and spatial boundaries of the physical world. Because time and space are relatively fluid concepts in the virtual space, negative future health consequences may be vividly depicted on the self’s virtual doppelgänger to demonstrate that health risks are personally relevant and can be imminent. Not only can these simulations be minutely tailored to meet each individual user’s needs, but patients can also repeat the simulations infinitely without expending further resources. Optimally, patients should be actively involved in the creation of the simulations to maximize the benefits of hyper-tailored health interventions using IVEs.

Furthermore, patients are able to enter these simulations from the first-person perspective and step into the virtual shoes of another person, seeing, hearing, and feeling as that person would. The sensory-rich experience that mimics direct experiences yields greater impact on attitudes and behaviors than indirect experiences (e.g., print message, mental imagery) and presents the potential of IVEs in treating mental impairments that make it difficult for patients to understand others’ perspectives. The enhanced ability to take the perspective of another person through IVEs would also be useful in training healthy persons to better understand and empathize with the problems and issues that patients go through on a daily basis.

Based on such novel features, a growing number of studies point to the utility of IVEs in a variety of health contexts for both children and adults, including the promotion of physical activity, healthy food choices, exposure therapy, physical therapy for rehabilitation, and autistic spectrum disorder. Although the findings are mostly preliminary and the generalizability of the findings is limited at this point, these are efforts to supplement current health practices with creative approaches to treat and maintain individual health. In addition, much work needs to be done to develop appropriate content to match the rapid development of consumer-grade IVE systems. Nevertheless, IVE technologies are advancing at an unprecedented speed, and we may soon witness virtual experiences and interactions with avatars and agents becoming a new norm of clinical treatments.

Although IVEs offer many advantages for health researchers and practitioners, like any method, they have drawbacks. First, despite rapidly decreasing costs of IVE systems and the media attention on the development of affordable and accessible consumer-grade IVE devices, quality virtual content can take considerable financial and human resources to design, develop, and implement. As with any other communication platform, a sophisticated device (hardware) would be meaningless without access to appropriate content (software). Thus, a clinician or health practitioners may be unpleasantly surprised to find that purchasing the state-of-the-art IVE device may be as useful as a computer without any software installed on it.

Researchers and clinicians must also keep in mind that individual use in the home or other uncontrolled environments are likely to feature any number of contextual issues, from spatial constraints to limited system processing to distractions. It is possible that these factors constrain or interfere with users’ experiences, thus limiting users’ attention, immersion, or perceptions of realism within the IVE. Very few research studies have examined whether treatments that have been effective in controlled virtual reality lab environments are as effective with lower-quality versions or in natural or uncontrolled settings.

Second, developing an effective IVE simulation requires specific expertise. One downside to the rapid diffusion of technologies and lowered barriers of adoption is that many people assume that simply having ideas for content and then hiring programmers who can generate the content is sufficient. Researchers and practitioners rarely consider the necessity of hiring experts in usability and user experience (UX) design in addition to programmers. Given the complexity of IVEs, this is an essential developmental role. Another error is that users themselves are conspicuously missing from the design process. Researchers map out content, have someone build said content, and then test said content without involving users earlier in the process. As a result, many health-oriented apps and video games are poorly designed, and low-quality IVE simulations are similarly inevitable. It is important for practitioners to assess potential users’ needs and requirements, develop multiple alternatives, generate prototypes, and evaluate these prototypes before the first line of code is even written. User-centered and evidence-centered design is necessary for virtual applications to be engaging and effective.

Third, like most technologies, IVEs have some accessibility issues that may limit the individuals who can use certain setups. Currently, most virtual experiences heavily rely on visual stimuli. Those with vision difficulties or impairments, such as colorblindness or blurred vision, may have difficulties. Stereoblindness is a vision issue that is often undetected but may have a significant impact on whether or not a user perceives a virtual environment as three dimensional. Some studies indicate that even users with healthy vision may experience visual fatigue if immersed too long.

Another problem is cybersickness or simulator sickness. Some users, particularly those susceptible to light-based stimuli, may experience dizziness, light-headedness, and nausea after spending time in VEs, particularly if they are fully immersive (Keshavarz, Hecht, & Lawson, 2014). Several studies have demonstrated that beyond individual sensitivities (e.g., susceptibility to motion sickness, history of migraines), the type of technology, its level of sophistication, and the time spent immersed may also play a role in whether users experience cybersickness while immersed (Keshavarz et al., 2014; Stanney, Hale, Nahmens, & Kennedy, 2003). For example, lag, or the time delay between the user’s actual motions and the updating of the visual scene, may cause illness in VR users. One longitudinal study, however, has demonstrated that cybersickness tends to decrease over time as participants become more familiar with the experience of immersion (Bailenson & Yee, 2006).

Finally, the findings from many of the studies reported in this chapter should be interpreted with caution for several reasons. The bulk of the research on IVEs, avatars, and agents present preliminary data with small sample sizes using convenience samples, tested in a highly controlled environment. Many IVE studies also lack sound methodological practices, such as randomization, blind assessment, and true controls (McCann et al., 2014). Furthermore, few studies have assessed limited longitudinal effects, so there is little known about the change in effects over time or following repeated exposure. Also, partly due to the nascence of the field, replication efforts both within and across reported studies are difficult to find. Thus, despite the promise and potential that IVEs hold for the future of health campaigns and treatments, further research and development will be imperative in the development of effective communication strategies and treatment plans that incorporate IVEs. Ethical issues are underexplored as well, despite potential problems that could arise with the blurred boundary between the virtual and the physical identities, when both may either look or behave in similar ways.

Further Reading

Ahn, S. J. (2016). Using avatars and agents to promote real world health behavior changes. In C. D. Combs, J. A. Sokolowski, & C. M. Banks (Eds.), The digital patient: Advancing healthcare, research, and education (pp. 167–178). Hoboken, NJ: John Wiley.Find this resource:

Ahn, S. J. (2017). Face & hair: Looks that change behaviors. In J. Banks (Ed.), Avatars, assembled (Chapter 5). Peter Lang.Find this resource:

Ahn, S. J., & Fox, J. (2016). Persuasive avatars: Extending the self through new media advertising. In R. E. Brown, V. K. Jones, & M. Wang (Eds.), The new advertising: Branding, content, and consumer relationships in the data-driven social media era (Vols. 2). Santa Barbara, CA: Praeger.Find this resource:

Ahn, S. J., Fox, J., & Bailenson, J. N. (2011). Avatars. In W. S. Bainbridge (Ed.), Leadership in science and technology: A reference handbook (pp. 695–702). Thousand Oaks, CA: SAGE.Find this resource:

Blascovich, J., & Bailenson, J. N. (2011). Infinite reality: Avatars, eternal life, new worlds, and the dawn of the virtual revolution. New York: William Morrow.Find this resource:

Cowdery, J. E., & Ahn, S. J. (2015). The use of virtual worlds in health promotion. In C. Parvanta, D. E. Nelson, S. A. Parvanta, & R. N. Harner (Eds.), Essentials of public health communication. Sudbury, MA: Jones & Bartlett Learning.Find this resource:

Fox, J. (2012). Avatars in health communication contexts. In S. M. Noar & N. G. Harrington (Eds.), eHealth applications: Promising strategies for behavior change (pp. 96–109). New York: Routledge.Find this resource:

Fox, J., & Ahn, S. J. (2013). Avatars: Portraying, exploring, and changing online and offline identities. In R. Luppicini (Ed.), Handbook of research on technoself: Identity in a technological society (pp. 255–271). Hershey, PA: Idea Group Global.Find this resource:

Fox, J., Arena, D., & Bailenson, J. N. (2009). Virtual reality: A survival guide for the social scientist. Journal of Media Psychology, 21(3), 95–113.Find this resource:

Jerald, J. (2015). The VR book: Human-centered design for virtual reality. San Rafael, CA: Morgan & Claypool.Find this resource:

Wiederhold, B. K., & Bouchard, S. (2014). Advances in virtual reality and anxiety disorders. New York: Springer.Find this resource:


Ahn, S. J. (2015). Incorporating immersive virtual environments in health promotion campaigns: A construal-level theory approach. Health Communication, 30, 545–556.Find this resource:

Ahn, S. J. (2017). Face & hair: Looks that change behaviors. In J. Banks (Ed.), Avatars, assembled (Chapter 5). Peter Lang.Find this resource:

Ahn, S. J. (in press). Virtual exemplars in health promotion campaigns: Heightening perceived risk and involvement to reduce soft drink consumption in young adults. Journal of Media Psychology.Find this resource:

Ahn, S. J., & Bailenson, J. N. (2011). Self-endorsing versus other-endorsing in virtual environments: The effect on brand attitude and purchase intention. Journal of Advertising, 40, 93–106.Find this resource:

Ahn, S. J., Bailenson, J. N., & Park, D. (2014). Short- and long-term effects of embodied experiences in immersive virtual environments on environmental locus of control and behavior. Computers in Human Behavior, 39, 235–245.Find this resource:

Ahn, S. J., Bostick, J., Ogle, E., Nowak, K., McGillicuddy, K., & Bailenson, J. N. (2016). Experiencing nature: Embodying animals in immersive virtual environments increases inclusion of nature in self and involvement with nature. Journal of Computer-Mediated Communication, 21(6), 399–419.Find this resource:

Ahn, S. J., & Fox, J. (2016). Persuasive avatars: Extending the self through new media advertising. In R. E. Brown, V. K. Jones, & M. Wang (Eds.), The new advertising: Branding, content, and consumer relationships in the data-driven social media era (Vol. 2). Santa Barbara, CA: Praeger.Find this resource:

Ahn, S. J., Fox, J., & Bailenson, J. N. (2011). Avatars. In W. S. Bainbridge (Ed.), Leadership in science and technology: A reference handbook (pp. 695–702). Berkeley, CA: SAGE.Find this resource:

Ahn, S. J., Fox, J., & Hahm, J. M. (2014). Using virtual doppelgangers to increase personal relevance of health risk communication. Lecture Notes in Computer Science, 8637, 1–12.Find this resource:

Ahn, S. J., Johnsen, K., Moore, J., Brown, S., Biersmith, M., & Ball, C. (2016). Using virtual pets to increase fruit and vegetable consumption in children: A technology-assisted social cognitive theory approach. Cyberpsychology, Behavior, and Social Networking, 19(2), 86–92.Find this resource:

Ahn, S. J., Johnsen, K., Robertson, T., Moore, J., Brown, S., Marable, A., & Basu, A. (2015). Using virtual pets to promote physical activity in children: An application of the youth physical activity promotion model. Journal of Health Communication, 20, 807–815.Find this resource:

Ahn, S. J., Le, A. M. T., & Bailenson, J. N. (2013). The effect of embodied experiences on self-other merging, attitude, and helping behavior. Media Psychology, 16, 7–38.Find this resource:

Ahn, S. J., Phua, J. J., & Shan, Y. (2017). Self-endorsing in digital advertisements: Using virtual selves to persuade physical selves. Computers in Human Behavior, 71, 110–121.Find this resource:

Anderson, P. L., Price, M., Edwards, S. M., Obasaju, M. A., Schmertz, S. K., Zimand, E., & Calamaras, M. R. (2013). Virtual reality exposure therapy for social anxiety disorder: A randomized controlled trial. Journal of Consulting & Clinical Psychology, 81, 751–760.Find this resource:

Bailenson, J. N., Patel, K., Nielsen, A., Bajscy, R., Jung, S.-H., & Kurillo, G. (2008). The effect of interactivity on learning physical actions in virtual reality. Media Psychology, 11, 354–376.Find this resource:

Bailenson, J. N., & Yee, N. (2006). A longitudinal study of task performance, head movements, subjective report, simulator sickness, and transformed social interaction in collaborative virtual environments. Presence: Teleoperators & Virtual Environments, 15, 699–716.Find this resource:

Bandura, A. (1977). Self-efficacy: Toward a unifying theory of behavioral change. Psychological Review, 84, 191–215.Find this resource:

Bandura, A. (2001). Social cognitive theory of mass communication. Media Psychology, 3, 265–298.Find this resource:

Baranowski, T., Abdelsamad, D., Baranowski, J., O’Connor, T. M., Thompson, D., Barnett, A., Cerin, E., & Chen, T-A. (2012). Impact of an active video game on healthy children’s physical activity. Pediatrics, 129, e636–e642.Find this resource:

Barsalou, L. W. (2009). Simulation, situated conceptualization, and prediction. Philosophical Transactions of the Royal Society B: Biological Sciences, 364, 1281–1289.Find this resource:

Baumann, S. B., & Sayette, M. A. (2006). Smoking cues in a virtual world provoke craving in cigarette smokers. Psychology of Addictive Behaviors, 20, 484–489.Find this resource:

Baumeister, R. (1998). The self. In D. T. Gilbert, S. T. Fiske, & G. Lindzey (Eds.), The handbook of social psychology (pp. 680–740). Boston: McGraw-Hill.Find this resource:

Bickmore, T. W. (2015). Relational agents in health applications: Leveraging affective computing to promote healing and wellness. In R. Calvo, S. D’Mello, J. Gratch, & A. Kappas (Eds.), The Oxford handbook of affective computing (pp. 537–546). New York: Oxford.Find this resource:

Biddiss, E., & Irwin, J. (2010). Active video games to promote physical activity in children and youth: A systematic review. Archives of Pediatrics and Adolescent Medicine, 164, 664–672.Find this resource:

Biocca, F. (1997). The cyborg’s dilemma: Progressive embodiment in virtual environments. Journal of Computer-Mediated Communication, 3.Find this resource:

Birch, L. L., Birch, D., Marlin, D. W., & Kramer, L. (1982). Effects of instrumental consumption on children’s food preference. Appetite, 3, 125–134.Find this resource:

Blascovich, J. (2002). Social influence within immersive virtual environments. In R. Schroeder (Ed.), The social life of avatars: Presence and interaction in shared virtual environments (pp. 127–145). London: Springer-Verlag.Find this resource:

Blascovich, J., & Bailenson, J. N. (2011). Infinite reality: Avatars, eternal life, new worlds, and the dawn of the virtual revolution. New York: William Morrow.Find this resource:

Bois, J. E., Sarrazin, P. G., Brustad, R. J., Rouilloud, D. O., & Cury, F. (2005). Elementary schoolchildren’s perceived competence and physical activity involvement: The influence of parents’ role modeling behaviours and perceptions of their child’s competence. Psychology of Sports and Exercise, 6, 381–397.Find this resource:

Botella, C., Baños, R. M., Villa, H., Perpiñá, C., & García-Palacios, A. (2000). Virtual reality in the treatment of claustrophobic fear: A controlled, multiple-baseline design. Behavior Therapy, 31, 583–595.Find this resource:

Botella, C., García-Palacios, A., Villa, H., Baños, R. M., Quero, S., Alcañiz, M., Riva, G. (2007). Virtual reality exposure in the treatment of panic disorder and agoraphobia: A controlled study. Clinical Psychology & Psychotherapy, 14, 164–175.Find this resource:

Brustad, R. J. (1996). Attraction to physical activity in urban schoolchildren: Parental socialization and gender influences. Research Quarterly for Exercise and Sport, 67, 316–323.Find this resource:

Bryanton, C., Bossé, J., Brien, M., Mclean, J., McCormick, A., & Sveistrup, H. (2006). Feasibility, motivation, and selective motor control: Virtual reality compared to conventional home exercise in children with cerebral palsy. Cyberpsychology & Behavior, 9, 123–128.Find this resource:

Cesa, G. L., Manzoni, G. M., Bacchetta, M., Castelnuovo, G., Conti, S., Gaggioli, A. et al. (2013). Virtual reality for enhancing the cognitive behavioral treatment of obesity with binge eating disorder: Randomized controlled study with one-year follow-up. Journal of Medical Internet Research, 15, e113.Find this resource:

Chase, C. C., Chin, D. B., Oppezzo, M. A., & Schwartz, D. L. (2009). Teachable agents and the protégé effect: Increasing the efforts towards learning. Journal of Science Education & Technology, 18, 334–352.Find this resource:

Cho, S., Ku, J., Park, J., Han, K., Lee, H., Choi, Y. K., et al. (2008). Development and verification of an alcohol-craving induction tool using virtual reality: Craving characteristics in a social pressure situation. CyberPsychology & Behavior, 11, 302–309.Find this resource:

Coelho, C. M., Santos, J. A., Silvério, J., & Silva, C. F. (2006). Virtual reality and acrophobia: One-year follow-up and case study. CyberPsychology & Behavior, 9, 336–341.Find this resource:

Cook, A., Pryer, J., & Shetty, P. (2000). The problem of accuracy in dietary surveys: Analysis of the over 65 UK National Diet and Nutrition Survey. Journal of Epidemiology & Community Health, 54, 611–616.Find this resource:

Corbetta, D., Imeri, F., & Gatti, R. (2015). Rehabilitation that incorporates virtual reality is more effective than standard rehabilitation for improving walking speed, balance and mobility after stroke: A systematic review. Journal of Physiotherapy, 61, 117–124.Find this resource:

Cote, S., & Bouchard, S. (2005). Documenting the efficacy of virtual reality exposure with psychophysiological and information processing measures. Applied Psychophysiology & Biofeedback, 30, 217–232.Find this resource:

Cummings, J. J., & Bailenson, J. N. (2016). How immersive is enough? A meta-analysis of the effect of immersive technology on user presence. Media Psychology, 19, 272–309.Find this resource:

De Leo, G., Ponder, M., Molet, T., Fato, M., Thalmann, D., Magnenat-Thalmann, N., … Beltrame, F. (2003). A virtual reality system for the training of volunteers involved in health emergency situations. CyberPsychology & Behavior, 6, 267–274.Find this resource:

De Ribaupierre, S., Kapralos, B., Haji, F., Stroulia, E., Dubrowski, A., & Eagleson, R. (2014). Healthcare Training Enhancement Through Virtual Reality and Serious Games. In M. Ma, L. C. Jain, & P. Anderson (Eds.), Virtual, augmented reality and serious games for healthcare (pp. 9–27). Berlin: Springer-Verlag.Find this resource:

Deutsch, J. E., & Mirelman, A. (2007). Virtual reality-based approaches to enable walking for people poststroke. Topics in Stroke Rehabilitation, 14, 45–53.Find this resource:

Dillard, J. P., & Shen, L. (2005). On the nature of reactance and its role in persuasive health communication. Communication Monographs, 72(2), 144–168.Find this resource:

Eastwich, P. W., & Gardner, W. L. (2009) Is it a game? Evidence for social influence in the virtual world. Social Influence, 4, 18–32.Find this resource:

Fan, X., McNeese, M., & Yen, J. (2010). NDM-based cognitive agents for supporting decision-making teams. Human-Computer Interaction, 25, 195–234.Find this resource:

Ferrer-García, M., & Guitiérrez-Maldonado, J. (2012). The use of virtual reality in the study, assessment, and treatment of body image in eating disorders and nonclinical samples: A review of the literature. Body Image, 9(1), 1–11.Find this resource:

Fox, J. (2012). Avatars in health communication contexts. In S. M. Noar & N. G. Harrington (Eds.), eHealth applications: Promising strategies for behavior change (pp. 96–109). New York: Routledge.Find this resource:

Fox, J., Ahn, S. J., Janssen, J. H., Yeykelis, L., Segovia, K. Y., & Bailenson, J. N. (2015). Avatars versus agents: A meta-analysis quantifying the effects of agency on social influence. Human-Computer Interaction, 30, 401–432.Find this resource:

Fox, J., & Bailenson, J. N. (2009). Virtual self-modeling: The effects of vicarious reinforcement and identification on exercise behaviors. Media Psychology, 12, 1–25.Find this resource:

Fox, J., & Bailenson, J. N. (2010). The use of doppelgängers to promote health and behavior change. Cybertherapy & Rehabilitation, 3(2), 16–17.Find this resource:

Fox, J., Bailenson, J. N., & Binney, J. (2009). Virtual experiences, physical behaviors: The effect of presence on imitation of an eating avatar. Presence: Teleoperators & Virtual Environments, 18, 294–303.Find this resource:

Fox, J., Christy, K. R., & Vang, M. H. (2014). The experience of presence in persuasive virtual environments. In G. Riva, J. Waterworth, & D. Murray (Eds.), Interacting with presence: HCI and the sense of presence in computer-mediated environments (pp. 164–178). Berlin: DeGruyter Open.Find this resource:

Freeman, K., Thompson, S., Allely, E., Sobel, A., & Stansfield, S. (2000). A virtual reality training system for the triage and stabilization of head trauma and multiple injury patients. San Diego, CA: Naval Health Research Center.Find this resource:

Galloso, I., Palacios, J. F., Feijóo, C., & Santamaría, A. (2016). On the influence of individual characteristics and personality traits on the user experience with multi-sensorial media: An experimental insight. Multimedia Tools and Applications, 75, 12365–12408.Find this resource:

Garcia-Palacios, A., Botella, C., Hoffman, H., & Fabregat, S. (2007). Comparing acceptance and refusal rates of virtual reality exposure vs. in vivo exposure by patients with specific phobias. Cyberpsychology and Behavior, 10(5), 722–724.Find this resource:

Giroux, I., Faucher-Gravel, A., St-Hilaire, A., Boudreault, C., Jacques, C., & Bouchard, S. (2013). Gambling exposure in virtual reality and modification of urge to gamble. Cyberpsychology, Behavior, & Social Networking, 16, 224–231.Find this resource:

Gonçalves, R., Pedrozo, A. L., Coutinho, E. S. F., Figueira, I., & Ventura, P. (2012). Efficacy of virtual reality exposure therapy in the treatment of PTSD: A systematic review. PLoS One, 7(12), e48469.Find this resource:

Gutiérrez-Maldonado, J., Ferrer-García, M., Caqueo-Urizar, A., & Letosa-Porta, A. (2006). Assessment of emotional reactivity produced by exposure to virtual environments in patients with eating disorders. CyberPsychology & Behavior, 9, 507–513.Find this resource:

Harris, S. R., Kemmerling, R. L., & North, M. M. (2002). Brief virtual reality therapy for public speaking anxiety. CyberPsychology & Behavior, 5, 543–550.Find this resource:

Harrison, K., Taylor, L. D., & Marske, A. L. (2006). Women’s and men’s eating behavior following exposure to ideal-body images and text. Communication Research, 33, 507–529.Find this resource:

Heeter, C. (1992). Being there: The subjective experience of presence. Presence: Teleoperators and Virtual Environments, 1, 262–271.Find this resource:

Herman, C. P., Roth, D. A., & Polivy, J. (2003). Effects of the presence of others on food intake: A normative interpretation. Psychological Bulletin, 129, 873–886.Find this resource:

Herrera, G., Alcantud, F., Jordan, R., Blanquer, A., Labajo, G., De Pablo, C. (2008). Development of symbolic play through the use of virtual reality tools in children with autistic spectrum disorders: Two case studies. Autism, 12, 143–157.Find this resource:

Hertwig, R., Barron, G., Weber, E. U., & Erev, I. (2004). Decisions from experience and the effect of rare events in risky choice. Psychological Science, 15, 534–539.Find this resource:

Irish, J. E. (2013). Can I sit here? A review of the literature supporting the use of single-user virtual environments to help adolescents with autism learn appropriate social communication skills. Computers in Human Behavior, 29, A17–A24.Find this resource:

Johnsen, K., Ahn, S. J., Robertson, T., Moore, J., Brown, S., Marable, A., & Basu, A. (2014). Mixed reality virtual pets to reduce childhood obesity. IEEE Transactions on Visualization and Computer Graphics, 20, 523–530.Find this resource:

Johnsen, K., Dickerson, R., Rajj, A., Harrison, C., Lok, B., Stevens, A., et al. (2006). Evolving an immersive medical communication skills trainer. Presence: Teleoperators & Virtual Environments, 15, 33–46.Find this resource:

Jordan, R. (2003). Social play and autistic spectrum disorders: A perspective on theory, implication and educational approaches. Autism, 7, 347–360.Find this resource:

Kahneman, D., & Lovallo, D. (1993). Timid choices and bold forecasts: A cognitive perspective on risk taking. Management Science, 39, 17–31.Find this resource:

Kandalaft, M. R., Didehbani, N., Krawczyk, D. C., Allen, T. T., & Chapman, S. B. (2013). Virtual reality social cognition training for young adults with high-functioning autism. Journal of Autism and Developmental Disorders, 43, 34–44.Find this resource:

Kaphingst, K. A., Persky, S., Lachance, C., McCall, C., Beall, A. C., & Blascovich, J. (2009). Conveying genomic concepts in virtual reality technology. Journal of Health Communication, 14, 384–399.Find this resource:

Ke, F., & Im, T. (2013). Virtual-reality-based social interaction training for children with high-functioning autism. Journal of Educational Research, 106, 441–461.Find this resource:

Keehan, S. P., Cuckler, G. A., Sisko, A. M., Madison, A. J., Smith, S. D., … Lizonitz, J. M. (2015). National health expenditure projections, 2014–24: Spending growth faster than recent trends. Health Affairs, 34, 1407–1417.Find this resource:

Keshavarz, B., Hecht, H., & Lawson, B. D. (2014). Visually induced motion sickness: Causes, characteristics, and countermeasures. In K. S. Hale & K. M. Stanney (Eds.), Handbook of virtual environments: Design, implementation, and applications (2d ed., pp. 647–698). New York: CRC Press.Find this resource:

Kenny, P., Rizzo, A. A., Parsons, T. D., Gratch, J., & Swartout, W. (2007). A virtual human agent for training novice therapists clinical interviewing skills. Annual Review of CyberTherapy & Telemedicine, 5, 77–83.Find this resource:

Lee, M., Suh, D., Son, J., Kim, J., Eun, S. D., & Yoon, B. (2016). Patient perspectives on virtual reality-based rehabilitation after knee surgery: Importance of level of difficulty. Journal of Rehabilitation Research & Development, 53, 239–252.Find this resource:

Lin, J. J., Mamykina, L., Lindtner, S., Delajoux, G., & Strub, H. B. (2006). Fish “n” Steps: Encouraging physical activity with an interactive computer game. Lecture Notes in Computer Science, 4206, 261–278.Find this resource:

Loomis, J. M., Blascovich, J., & Beall, A. C. (1999). Immersive virtual environment technology as a basic research tool in psychology. Behavior Research Methods, Instruments, & Computers, 31, 557–564.Find this resource:

Lorenzo, G., Lledó, A., Pomares, J., & Roig, R. (2016). Design and application of an immersive virtual reality system to enhance emotional skills for children with autism spectrum disorders. Computers & Education, 98, 192–205.Find this resource:

Lorenzo, G., Pomares, J., & Lledó, A. (2013). Inclusion of immersive virtual learning environments and visual control systems to support the learning of students with Asperger syndrome. Computers & Education, 62, 88–101.Find this resource:

Lucas, G. M., Gratch, J., King, A., & Morency, L. P. (2014). It’s only a computer: virtual humans increase willingness to disclose. Computers in Human Behavior, 37, 94–100.Find this resource:

Macdonnell, M., & Darzi, A. (2013). A key to slower health spending growth worldwide will be unlocking innovation to reduce the labor-intensity of care. Health Affairs, 32, 653–660.Find this resource:

Maimaran, M., & Fishbach, A. (2014). If it’s useful and you know it, do you eat? Preschoolers refrain from instrumental food. Journal of Consumer Research, 41, 642–655.Find this resource:

Mantovani, F., Castelnuovo, G., Gaggioli, A., & Riva, G. (2003). Virtual reality training for health-care professionals. CyberPsychology & Behavior, 6, 389–395.Find this resource:

Marco, J. H., Perpiña, C., & Botella, C. (2013). Effectiveness of cognitive behavioral therapy supported by virtual reality in the treatment of body image in eating disorders: One year follow-up. Psychiatry Research, 209, 619–625.Find this resource:

Maskey, M., Lowry, J., Rodgers, J., McConachie, H., & Parr, J. R. (2014). Reducing specific phobia/fear in young people with autism spectrum disorders (ASDs) through a virtual reality environment intervention. PLoS One, 9(7), e100374.Find this resource:

McBride, C. M., Persky, S., Wagner, L. K., Faith, M. S., & Ward, D. S. (2013). Effects of providing personalized feedback of child’s obesity risk on mothers’ food choices using a virtual reality buffet. International Journal of Obesity, 37, 1322–1327.Find this resource:

McCann, R. A., Armstrong, C. M., Skopp, N. A., Edwards-Stewart, A., Smolenski, D. J., June, J. D., … Reger, G. M. (2014). Virtual reality exposure therapy for the treatment of anxiety disorders: An evaluation of research quality. Journal of Anxiety Disorders, 28, 625–631.Find this resource:

McLay, R., Ram, V., Murphy, J., Spira, J., Wood, D. P., Wiederhold, M. D., Wiederhold, B. K., Johnston, C., & Reeves, D. (2014). Effect of virtual reality PTSD treatment on mood and neurocognitive outcomes. Cyberpsychology, Behavior, & Social Networking, 17, 439–446.Find this resource:

Miller, H. L., & Bugnariu, N. L. (2016). Level of immersion in virtual environments impacts the ability to assess and teach social skills in autism spectrum disorder. Cyberpsychology, Behavior, & Social Networking, 19, 246–256.Find this resource:

Opriş, D., Pintea, S., García-Palacios, A., Botella, C., Szamosközi, Ş., & David, D. (2012). Virtual reality exposure therapy in anxiety disorders: A quantitative meta‐analysis. Depression & Anxiety, 29, 85–93.Find this resource:

Parks Associates (2016). 2.3 million U.S. households own a virtual reality headset. Available at

Parsons, S., & Mitchell, P. (2002). The potential of virtual reality in social skills training for people with autistic spectrum disorders. Journal of Intellectual Disability Research, 46, 430–443.Find this resource:

Parsons, T. D., & Rizzo, A. A. (2008). Affective outcomes of virtual reality exposure therapy for anxiety and specific phobias: A meta-analysis. Journal of Behavior Therapy & Experimental Psychiatry, 39, 250–261.Find this resource:

Peng, W., & Crouse, J. (2013). Playing in parallel: The effects of multiplayer modes in active video game on motivation and physical exertion. Cyberpsychology, Behavior, and Social Networking, 16, 423–427.Find this resource:

Peng, W., Crouse, J., & Lin, J-H. (2013). Using active video games for physical activity promotion: A systematic review of the current state of research. Health Education & Behavior, 40, 171–192.Find this resource:

Pericot-Valverde, I., Secades-Villa, R., Gutiérrez-Maldonado, J., & García-Rodríguez, O. (2014). Effects of systematic cue exposure through virtual reality on cigarette craving. Nicotine & Tobacco Research, 16, 1470–1477.Find this resource:

Perpiña, C., Botella, C., & Baños, R. (2002). Body image in eating disorders: Virtual reality assessment and treatment. Promolibro: Valencia, Spain.Find this resource:

Perpiña, C., Botella, C., & Baños, R. (2003). Virtual reality in eating disorders. European Eating Disorders Review, 11, 261–278.Find this resource:

Persky, S., & McBride, C. M. (2009). Immersive virtual environment technology: a promising tool for future social and behavioral genomics research and practice. Health Communication, 24, 677–682.Find this resource:

Powers, M. B., & Emmelkamp, P. M. G. (2008). Virtual reality exposure therapy for anxiety disorders: A meta-analysis. Journal of Anxiety Disorders, 22, 561–569.Find this resource:

Price, M., & Anderson, P. (2007). The role of presence in virtual reality exposure therapy. Journal of Anxiety Disorders, 21, 742–751.Find this resource:

Price, M.Anderson, P., & Rothbaum, B. O. (2008). Virtual reality as treatment for fear of flying: A review of recent research. International Journal of Behavioral Consultation and Therapy, 4, 340–347.Find this resource:

Rafaeli, S. (1988). Interactivity: From new media to communication. In R. P. Hawkins, J. M. Wiemann, & S. Pingree (Eds.), Advancing Communication Science: Merging Mass and Interpersonal Processes (pp. 110–134). Beverly Hills: SAGE.Find this resource:

Rajecki, D. W. (1982). Attitudes: themes and advances. Sunderland, MA: Sinauer.Find this resource:

Read, S. J., Miller, L. C., Appleby, P. R., Nwosu, M. E., Reynaldo, S., Lauren, A., et al. (2006). Socially optimized learning in a virtual environment: Reducing risky sexual behavior among men who have sex with men. Human Communication Research, 32, 1–34.Find this resource:

Rice, R. E., & Williams, F. (1984). Theories old and new: The study of new media. In R. E. Rice (Ed.), The new media: Communication, research, and technology (pp. 33–54). Beverly Hills, CA: SAGE.Find this resource:

Riva, G. (2005). Virtual reality in psychotherapy: Review. CyberPsychology & Behavior, 8, 220–230.Find this resource:

Riva, G. (2014). Medical clinical uses of virtual worlds. In M. Grimshaw (Ed.), The Oxford handbook of virtuality (pp. 649–665). New York: Oxford.Find this resource:

Riva, G., Gaggioli, A., & Dakanalis, A. (2013). From body dissatisfaction to obesity: How virtual reality may improve obesity intervention and treatment in adolescents. Studies in Health Technology and Informatics, 184, 356–362.Find this resource:

Rizzo, A. A.Rger, G., Gahm, G., Difede, J., & Rothbaum, B. O. (2009). Virtual reality exposure therapy for combat related PTSD. In P. Shiromani, T. Keane, & J. LeDoux (Eds.), Post-traumatic stress disorder: Basic science and clinical practice (pp. 375–399). New York: Humana Press.Find this resource:

Rosenberg, S. W., & McCafferty, P. (1987). The image and the vote: Manipulating voter’s preferences. Public Opinion Quarterly, 51, 31–47.Find this resource:

Rothbaum, B. O., Hodges, L., Smith, S., Lee, J. H., & Price, L. (2000). A controlled study of virtual reality exposure therapy for the fear of flying. Journal of Consulting & Clinical Psychology, 68, 1020–1026.Find this resource:

Rothbaum, B. O., Hodges, L. F., & Kooper, R. (1997). Virtual reality exposure therapy. Journal of Psychotherapy Practice & Research, 6, 219–226.Find this resource:

Rothbaum, B. O., Ruef, A. M., Litz, B. T., Han, H., & Hodges, L. (2003). Virtual reality exposure therapy of combat-related PTSD: A case study using psychophysiological indicators of outcome. Journal of Cognitive Psychotherapy, 17, 163–177.Find this resource:

Roy, S., Klinger, E., Legeron, P., Lauer, F., Chemin, I., & Nugues, P. (2003). Definition of a VR-based protocol to treat social phobia. Cyerpsychology and Behavior, 6, 411–420.Find this resource:

Sacau, A., Laarni, J., & Hartmann (2008). Influence of individual factors on presence. Computers in Human Behavior, 24, 2255–2273.Find this resource:

Sas, C., & O’Hare, G. M. P. (2003). Presence equation: An investigation into cognitive factors underlying presence. Presence: Teleoperators & Virtual Environments, 12, 523–537.Find this resource:

Schultheis, M. T., & Rizzo, A. A. (2001). The application of virtual reality technology in rehabilitation. Rehabilitation Psychology, 46, 296–311.Find this resource:

Schultz, D. N., Smit, E. S., Stanczyk, N. E., Kremers, S. P. J., de Vries, H., & Evers, S. M. A. A. (2014). Economic evaluation of a web-based tailored lifestyle intervention for adults: Findings regarding cost-effectiveness and cost-utility from a randomized controlled trial. Journal of Medical Internet Research, 16, e91.Find this resource:

Sigelman, L., Sigleman, C. K., & Fowler, C. (1987). A bird of a different feather? An experimental investigation of physical attractiveness and the electability of female candidates. Social Psychology Quarterly, 50, 32–43.Find this resource:

Skalski, P., & Tamborini, R. (2007). The role of social presence in interactive agent-based persuasion. Media Psychology, 10, 385–413.Find this resource:

Smith, M. J., Fleming M. F., Wright, M. A., Losh, M., Humm, L. B., Olsen, D., & Bell, M. D. (2015). Vocational outcomes for young adults with autism spectrum disorders at six months after virtual reality job interview training. Journal of Autism & Developmental Disorders, 45, 3364–3369.Find this resource:

Staino, A. E., Abraham, A. A., & Calvert, S. L. (2013). Adolescent exergame play for weight loss and psychosocial improvement: A controlled physical activity intervention. Obesity, 21, 598–601.Find this resource:

Standen, P. J., & Brown, D. J. (2005). Virtual reality in the rehabilitation of people with intellectual disabilities: Review. Cyberpsychology & Behavior, 8, 272–282.Find this resource:

Stanney, K. M., Hale, K. S., Nahmens, I., Kennedy, R. S. (2003). What to expect from immersive virtual environment exposure: Influences of gender, body mass index, and past experience. Human Factors, 45(3), 504–520.Find this resource:

Stanney, K., & Salvendy, G. (1998). Aftereffects and sense of presence in virtual environment: Formulation of a research and development agenda. International Journal of Human-Computer Interaction, 10, 135–187.Find this resource:

Stanney, K. M., Mollaghasemi, M., Reeves, L., Breaux, R., & Graeber, D. A. (2003). Usability engineering of virtual environments (VEs): Identifying multiple criteria that drive effective VE system design. International Journal of Human-Computer Studies, 58, 447–481.Find this resource:

Steuer, J. (1992). Defining virtual reality: Dimensions determining telepresence. Journal of Communication, 42, 73–93.Find this resource:

Stice, E., & Shaw, H. E. (2002). Role of body dissatisfaction in the onset and maintenance of eating pathology: A synthesis of research findings. Journal of Psychosomatic Research, 53, 985–993.Find this resource:

Sundar, S. S., Xu, Q., & Bellur, S. (2010). Designing interactivity in media interfaces: A communications perspective. In Proceedings of CHI 2010: Perspectives on Design. Atlanta, Georgia.Find this resource:

Sveistrup, H., McComas, J., Thornton, M., Marshall, S., Finestone, H., McCormick, A., et al. (2003). Experimental studies of virtual reality-delivered compared to conventional exercise programs for rehabilitation. CyberPsychology & Behavior, 6, 245–249.Find this resource:

Tanner, R. J., & Maeng, A. (2012). A tiger and a president: Imperceptible celebrity facial cues influence trust and preference. Journal of Consumer Research, 39, 769–783.Find this resource:

Todorov, A., Mandisodza, A. N., Goren, A., & Hall, C. C. (2005). Inferences of competence from faces predict election outcomes. Science, 308, 1623–1626.Find this resource:

Vitousek, K., Watson, S., & Wilson, G. T. (1998). Enhancing motivation for change in treatment-resistant eating disorders. Clinical Psychology Review, 18(4), 391–420.Find this resource:

Weinstein, N. (1980). Unrealistic optimism about future life events. Journal of Personality and Social Psychology, 39, 806–820.Find this resource:

Weiss, P. L. T., Keshner, E. A., & Levin, M. F. (2014). Virtual reality for physical and motor rehabilitation. Springer-Verlag: New York.Find this resource:

Wiederhold, B. K., & Wiederhold, M. D. (2005). Virtual reality therapy for anxiety disorders: Advances in evaluation and treatment. Washington, DC: American Psychological Association.Find this resource:

Williamson, D. A. (1990). Assessment of eating disorders: Obesity, anoexia, and bulimia nervosa. New York: Pergamon.Find this resource:

Wing, L., & Gould, J. (1979). Severe impairments of social interaction and associated abnormalities in children: Epidemiology and classification. Journal of Autism and Developmental Disorders, 9, 11–29.Find this resource:

Yee, N. (2014). The Proteus paradox: How online games and virtual worlds change us—and how they don’t. New Haven, CT: Yale University Press.Find this resource:

Zajonc, R. B. (2001). Mere exposure: A gateway to the subliminal. Current Directions in Psychological Science, 10, 224–228.Find this resource: