Research Paper VRET (2018) MediaLAB Amsterdam, The Netherlands

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VIRTUAL REALITY EXPOSURE THERAPY (VRET)

Abstract We sought to develop a virtual reality exposure therapy (VRET) environment that is adaptable to the biofeedback of the user. Our prototype is built in Unity and integrates the sensory data from Mio Link heart rate monitor transferring it through a computational model that individually adapts to the VR environment. Our final concept is a user case located in an underwater VR environment focused on the specific phobia of sharks; galeophobia. Our research follows a multidisciplinary approach, combining fields of design thinking, psychology, cognitive neuroscience, human-computer interaction (HCI) and affective computing. Author Keywords Virtual reality; affective computing; exposure therapy; biofeedback; emotion detection; sensor technology ACM Classification Keywords H.5. Human-Centered Computing (e.g. HCC): Human-Computer Interaction (HCI) Introduction We were assigned a task on how to track emotions and transform it to a Virtual Reality (VR) environment. The ability of VR to simulate real-life situations that elicit similar subjective and physiological body reactions has made its way into psychological research [1]. The immersive nature of VR is seen capable of activating “real” emotions and therefore, it offers new possibilities

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Agnetha Mortensen MediaLAB Amsterdam, HvA Wibautstraat 2-4, Amsterdam The Netherlands agnetha.mortensen@gmail.com Christiaan van Leeuwen Hoegschool van Rotterdam The Netherlands leeuwen12@gmail.com

Janina Saarnio University of Turku Finland janina.saarnio@gmail.com Yujie Shan Kyushu University, Japan syj94326@163.com

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to easily investigate human behaviors in a controlled environment. The premise of VRET is relying on triggering the perceptual cues that activate our emotional experiences and create the sense of feeling in a VR environment - which we will from now on call as presence. We know high presence is especially crucial for emotional involvement during the initial phase of VRET to ensure the immersion of the user. [1] The opportunities of using virtual reality as a medium for exposure therapy has already been investigated. In contrast to in vivo exposure therapy, VRET provides some advantages, such as higher acceptance among patients, lower costs and higher accessibility [2]. Also, nowadays technology by itself is shown to create an emotional presence that may become useful when designing mental health applications directly aiming to modify problematic emotions. [1] Our prototype follows a basic and the most common method of exposure therapy relying on “fear habituation” [3], but the individual biofeedback will automatically control the steps of a graded exposure. We believe that our design based on triggering the fearful stimulus up to a point before the activation of maladaptive behavioral responses (i.e., avoidance or panicking) is an effective way to treat specific phobias. Emotions and Behavior Until today there is no universally accepted theory about emotions. We decided to follow the famous Russell’s circumplex model of affect (1980) that divides all emotions into a two-scale diagram according to their intensity of arousal and valence. Commonly, emotions can be measured from physiological changes (i.e., heart rate), behavioral responses (i.e., facial expression) and/or cognitive interpretation (i.e., self-reporting) (see Figure 1) [8]. The most important in the study of emotions is to use ROIs (regions of interests) to extract information from our affective nature [4]. However, even though we could be able to extract all

physiological responses from our body, it is highly possible that the self-reflection of the subject does not correlate with the “emotional” data. Due to this simple fact, emotions appear and remain somehow unfamiliar and unresolved for us. As Marvin Minsky [5] states, human emotions come under the category of ‘suitcase like’ definitions we use only to conceal “...the complexity of extensive ranges of different things whose relationships we do not yet comprehend.”. Therefore, it is only possible to make estimates of emotions. Physiologically our emotions are seen to be processed through a limbic system, which is situated behind the neocortex part of our brain. The neocortex parts deal with conscious thoughts and decision making. On the contrary, the very nature of the limbic system and our emotions are illogical, irrational and unreasonable [6]. In cognitive neuroscience, emotions are strongly linked to our decision making as whenever exposed to a particular stimulus we construct and store a somatic marker between the stimulus and our affective state. Then these somatic markers are stored in our memory and later used for decision making in similar or different context [7]. In fact, at the psychological level emotions are regarded as tacit appraisals of different situations regarding personal goals, concerns or needs [8]. According to the emotion-focused therapy approach as well as having emotions we also live in a constant process of making sense of our emotions [9]. The dialectical-constructivist view of human functioning helps to explain the process. The circular process of making sense of experience is run through bodily-felt sensations connected to our awareness and memory and later articulated in language. Therefore, emotions are an adaptive form of information-processing and action readiness that guides people in their interactions with other people and the surrounding environments [9].

Figure 1; Generic model of emotion detection.

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Fear as an Emotion Fear is defined as one of the basic emotions by consensus [8, 10]. From a physiological perspective, fear is sympathetic arousal and an aversive subjective threat. Our sympathetic nervous system (SNS) is activated through the amygdala and involves alterations in blood pressure (BP) that can be physiologically measured from the changes in heart rate or skin conductance, for example [11, 21]. From an evolutionary point of view, negative emotions are often useful and even necessary for our survival. In fact, anxiety, anger, and fear would not exist if they were not useful. However, the risk is that unpleasant emotions can turn dysfunctional when they also endure in the circumstances where they are not needed [9]. People who have a particular kind of phobia share a standard feature of amygdala hyper-responsiveness over the hippocampus and medial prefrontal cortex (mPFC) that are responsible for cognitive interpretation [13]. Relevant for our concept is that usually, people try to push down the unpleasant emotions such as pain, fear or anxiety. However, all of these so-called “escape methods” will only cause harm in the long term. Avoidance of emotion often creates a long-term feeling of suffering and prevents us to live life to its fullest [9]. In order, not to let the negative emotions take over one’s actions and behavior one needs to be aware of, to tolerate and to regulate negative emotionality as well as enjoy positive emotionality [14]. Scientifically we often refer to this regarding emotion regulation or emotional intelligence. Emotional intelligence means that the individual can use emotions as a guide, instead of being a slave or a victim of emotions [22]. The primary challenge of detecting fear is its close relation to anxiety and the oppression of our parasympathetic nervous system. From the

philosophical point of view, the difference between fear and anxiety lies in their relation to an object, as Sara Ahmed [12] states. According to Ahmed, fear has an object whereas anxiety has not. The temporal dimension in fear only appears when we are affronted to a threat. The fearful moment “projects us from the present into a future” which is felt as an intense bodily experience of the present. Sweating, increased heart rate, and unpleasant intensity through the whole body push us to either flight-freeze-or-fight. Ahmed concludes that we fear when an object approaches us and we anticipate it to hurt us [12]. Practically this means that even though the amygdala is central to emotional learning and memory, it is not critical to the expression and regulation of emotion. The amygdala only serves as a “smoke detector”, pre-consciously interpreting whether the incoming sensory information is a threat or not [9]. Therefore, the activation of our conscious interpretation is needed to help us overwrite the maladaptive fear memories (see Figure 2). However, the change can only occur by first activating the emotional memory with a fearful stimulus which we will simulate in VR. Overcoming Fear through Exposure Therapy Exposure therapy has shown to be the most effective treatment for phobias. Most commonly it is practiced by using one of the two scientifically proven methods; flooding or graded-exposure. Research indicates that gradual and prolonged exposure is the most optimal. Exposure therapy is rooted in classical conditioning where every exposure trial starts by activating the maladaptive experience and making the patients contact with the feared, conditioned stimulus (CS). The condition is maintained until the anxiety is lowered down. This process is often referred to as habituation and can only lead to successful outcomes if the patients are prevented to avoid the phobic stimuli in their sight [15]. The traditional exposure therapy methodology relies on the assumption that performance during

Figure 2; A basic model showing the link between the physical world relying on perceptual cues and their references to the different layers in our mental world.

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training and fear reduction within an exposure trial (also referred to as within-session habituation WSH) is “commensurate with learning” [16]. Exposure therapy can also follow a method of single massed exposure or a trial composed of multiple short exposures. Some evidence supports a single massed exposure to be more efficient than a series of short exposures having the same total duration. Different techniques of distraction during the exposure therapy cause a disrupted exposure [16]. However, these findings are not in line with some studies state that distraction during the exposure therapy may facilitate the fear reduction [17, 18]. Therefore, more than trying to generate one method for exposure therapy the fear

memory should be taken into account when designing the exposure trial in VR. Methods To come up with our concept we used different research methods from the MediaLAB Amsterdam Design Method Toolkit, such as a survey, in-depth interview and research collage together with our own methods and expert consultations. Along with the insights we generated several good ideas and concepts, finally resulting into a VRET concept with an underwater user case. However, the computational model is designed to adapt to an object so it can be easily applied to different types of specific phobias in different contexts.

Figure 3; Overview of most creative methods used in our project throughout the different sprints

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Online Survey To learn more from a target audience that is not that social or open about their problems we decided to do a survey together with a follow-up interview to get Schwartz values and guidelines for the design. We combined open phobia/anxiety questions [30] and closed phobia questions [31] to create an extensive survey. We also used open questions which showed up

to be harder to interpret and categorized. The survey was also translated into Dutch and shared on Facebook through our profiles as well as in a variety of relevant Facebook groups for young women. Results from the survey revealed some interesting insights on the most common phobias among our target group. Based on our findings from the online survey as well as desktop research we developed three unique concepts that

Fear / Phobia No.Ppl.

Total %

A burglar breaking into the house / sclerophobia 31 56,36%

Spiders or scorpions / arachnophobia 28 50,91%

Making mistakes / erratophobia 25 45,45%

Bees (apiphobia) / wasps (spheksophobia) 24 43,64%

Looking foolish in front of people / gelotophobia 24 43,64%

Not being able to breathe / asphyxiphobia 24 43,64%

Deep water or ocean / thalassophobia 21 38,18%

Sharks / galeophobia 20 36,36% Death or dying / thanatophobia 20 36,36%

Being alone / monophobia 15 27,27%

Dark spaces / nyctophobia 15 27,27%

Jellyfish / scyphophobia 8 14,55%

Table 1; Results from International and Dutch survey on closed questions about specific phobias and fears. Blue color are phobias that could be adapted to an underwater environment.

Figure 4; Results from Online Survey with open questions about fear, phobia and anxiety

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could be alternated in a VR environment. We found that almost none of the participants suffer from severe forms of phobia or anxiety but almost all of them suffered from them in some amount. In-Depth Interviews and Collage Session Based on the Schwartz values (2006) we conducted in-depth interviews with eight young women from 3 different countries in the hope of getting a better understanding of our target group and how they relate to fear. We saw some overall similarities with high levels of ambitions, fear of judgment and/or not being good enough and being left out of a social circle/being alone. We also applied the Five Factor Model (FFM) into our question to get a better understanding of the young women's gaming habits, and by doing this, we could get scientifically correct and unambiguous answers. The central insight from the in-depth interviews was that although the target audience differs in kind of phobia, age, origin, and intensity of the phobia, gradually facing the phobia helps them to overcome their fears. A few weeks later in the project, we learned that unknowingly and unwillingly this was the first moment that exposure therapy started to play a role in the project. Fear Research Collage Session To narrow down which phobias would be interesting to use for the first exposure therapy concepts, we wanted to try the research collage method. This method from the Design Method Toolkit (MediaLAB Amsterdam) was perfect for people to visually explain their phobias and the situations and memories associated with them. We did the session with five people from MediaLAB Amsterdam and one person whom we got in contact with via the survey we did. Pictures of different kind of phobias were cut out to match together on colored paper sheets, and we let people work on their sheet

until most people were done and then they had to present their collage. The central insight from this session was that most phobias revolve around a memory or situation. This entails that those phobias could not as easily be triggered in a controlled environment because they are very individual experiences for each person. Developing our Target Group and our Personas From the beginning of the project, we all agreed that we wanted to create something meaningful that would help people. We discussed a lot back and forth about issues and problems the society is facing today. During our desktop research, we came across several interesting news articles on how anxiety is on the rise among young women, especially in the westernized countries like the UK and the US, but also in Asian countries like Japan and South Korea. We wanted to understand better what exactly was troubling young girls and women, and wanted to create something that could help and prevent mental health issues that could potentially arise. We defined our target group to be young women between the age of 15-25. Not only because of the troublesome inner struggles some of them might face, but also because statistics do show that VR is more exciting and appealing to young people (tweens, teens, and Millennials) [33]. We also chose to keep a primary focus on women because they are more sensitive to physiological changes towards fearful stimuli [32]. Women are also twice as likely as men to experience different types of anxieties [19]. To narrow down our concept we chose to focus on a specific phobia as this is easier to treat, as well as most of the anxieties revolve around a particular situation strongly relying on a context-dependent memory, but specific phobias can be more generalized.

Figure 5; The above personas are based on basic research about phobias and assumptions about personality and emotions. These personas helped to take the target audience into account when we set up the experiments.

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Final Design Criteria 1. The design must be coherent to enhance the immersion for the user experience. When the environment and the rules within the fictional world are coherent, it has a better chance of enhancing the immersion and also the presence of the user in a VR environment [34,35]. 2. The computational model in the prototype must be able to interpret individual biofeedback and adjust the VR environment accordingly. As biofeedback is individual, it is essential that the computational model take this into account and adapts the experience according to different user’s needs. 3. The VR experience should help the users cope with their phobia/anxiety and not make it worse. It is essential to keep in mind the theories in exposure therapy and be aware of the user’s anxiety levels. The phobia or anxiety should be triggered to measure the biofeedback, but avoid overexposing them as that could end up traumatizing them even more. 4. The concept could give feedback to the user about their emotional state. We believe that self-awareness about one’s emotional state through visual feedback could help users overcome their fears easier. 5. The concept could benefit from music to enhance the immersive experience. Binaural sounds could be applied to calm the user before, during and after the exposure trial. 6. The prototype would be easily transferable to different phobia and environments. We want to make sure that the prototype applies to other user cases and are easily transferable to other phobias.

Pre-Experiment on Fear and Colors We conducted a small experimental pre-study on fear and aura (colors) to develop our computational model. The primary goal of this experiment was to test a change in the heart rate when the users are exposed to something fearful in a virtual environment. We decided to focus on HR as the monitors are less invasive for the users as well as it is more easily available and cheap compared to other sensors on the market. The sensors tested in this experiment include Mio Link and Garmin Forerunner 35. We aimed to test if Mio Link is accurate enough to be used in our concept in virtual reality environment. The sub-goal of this experiment was to gain some insights about the surrounding colors around the user (which are different from the environment

Total: 35-45 minutes per person they are supposed to feel immersed in) while they are exposed to something fearful. This is related to our idea of having an aura around the user in VRET.

Table 2; Fear and Color (AURA) Experiment Setup

Time (min) What Tools

5 Introduction and instructions

Personal talk

5 Pre-survey and consent form

The survey + pen

5-10 Baseline trial: Watching a calm video

Soothing movie/ soothing experience

10-20 Experiment session: Playing scary game to get physiological data

Mio Link + RGB light with remote + recording equipment

5 Post-survey The survey + pen

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We got a total amount of 12 people to participate in the experiment, 4 males, and 8 females. However, the final number of valid data we took into account for building the computational model is 10 (M=4, F=6) of 5 for both control groups (darkness/colors). The age of the participants was between 22-30 years old. The baseline trial and the experiment session was recorded using GoPro HERO4 as well as Canon 80D with live recording through EOS Utility on Apple Mac. We decided to base the computational model relying on the baseline and the self-reported fear level. The benefits of using baseline as one variable are that it takes into account the daily variations in the heart rate – such as stress, the amount of sleep and the intake of caffeine. We also acknowledged that the self-reported fear level should play a role in the computational model. Based on the pre-experiment we gained many insights that we could implement into our final version of the computational model. Final Prototype We sought to design a realistic and coherent underwater VR environment to enhance the immersion of the user. The phobic stimulus is following a graded exposure methodology, and the gaze is programmed to prevent the avoidance behavior of the user. Visual Design To make the user aware of her own emotions we designed an Aura that can be adapted to our concept of VRET. The colorful lights around the user could aim to visualize their emotional state and depending on the design either working as a feature to enhance the immersion or create an additional layer in the VR environment. However, research shows that colors are differently interpreted in every culture which potentially can create difficulties for the outcome of the design, but by

focusing only on colors, the intensity of the lights can show to be more beneficial and a safe solution for visual stimuli towards users. The aura is not adapted into our final prototype but could be taken into account in future research, primarily as a feature to enhance the immersion of the user. Auditory Beat Stimulation through Binaural Beats With the growth of technology, music has become an increasingly important facet of a game. It is, therefore, necessary to understand how it does affect our behavior, concentration and cognitive stimulation. Music activates the whole brain, and the perception of sound and its tones are processed through the auditory cortex which transfers information to the hippocampus. What moves us to get emotionally involved in a song or a movie is controlled by the amygdala. The amygdala is also responsible when we feel fear, and it is where we store traumatic experiences. Music is a unique tool that can repair brain damage and help to return lost memories [23], it can also help learning processes [24], as well as reduce stress levels and anxiety [25].

It was vital for us to take all these factors of music perception and behavior change into consideration when creating our VRET prototype. We wanted to make use of music that could potentially reduce anxiety and lower one's stress levels. Several studies on binaural beats show exciting results when it comes to improving cognition and reducing anxiety. One study using alpha-theta brainwave biofeedback as a relaxation therapy showed promising results in treating anxiety among alcohol addicts. The brainwave treatment appeared to counteract the increase in circulating beta-endorphin levels seen in the control group of alcoholics, making the subjects less reluctant to fall back into abuse of alcohol [28].

Binaural beats are created when two coherent sounds with nearly similar frequencies are presented to each

Figure 6; The Limbic System. Source: D.P. Lyle, MD (2013)

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ear respectively with stereo headphones, the brain integrates the two signals and produces a sensation of a third sound called binaural beat (BB) [26]. Binaural-beats signals (BBS’s) were first observed by the German scientists H.W. Dove in 1839. In its purest form BBS’s consists of two pure tones of a different pitch being presented to each ear [27]. Research on binaural beats also shows that we may enhance mood states, lower anxiety levels and improve vigilance by using auditory beat stimulation [29].

By stimulating the brainwaves through binaural beats, we wanted to empower the users and make them more at ease, gradually lower their stress levels as well as making the users less anxious about the phobia we wanted to treat. We chose to track the baseline of the users in a relaxing state while listening to a piece of binaural beats generated from Water Droplets and Water passing through a musical pipe that was tuned to 396Hz solfeggio frequency. Users would listen to this track for 5 - 10 minutes before entering the VRET. Within the VRET we had a second piece of underwater binaural beats tuned to 417Hz. We found this track suitable for the underwater theme of the specific phobia of sharks. This level of frequency may also help to facilitating behavior change according to the clinical psychologist Dr. Joseph Puleo research during the 70’s.

Computational Model The computational model takes into account two individual variables: baseline of the heart rate BPM (x) and self-reported fear level (y). Baseline setting takes approximately 5 minutes before the exposure trial and uses standard deviation. The individual maximum heart rate to stop the fearful stimulus is calculated from the baseline (x) as follows:

HR max = x + ((- 3.217 · y) + 53.417)1

1 This is a first iteration of the computational model that was built upon our experiment data where we found a small correlation between the

Gaze Implementation Gaze is the first form of input and is a primary form of targeting within mixed reality. Gaze tells you where the user is looking in the world and lets you determine their intent. In the real world, you'll typically look at an object that you intend to interact with. This is the same with the gaze. In our computational model, the gaze works as a tool for interactive feedback from fear stimuli towards the player. In such a sense, the player cannot avoid the fearful stimuli (phobia) that is exposed.

self-reported fear level and the heart rate changes when the users were asked to play a video game called Slenderman (2013) in a closed environment.

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Conclusion Undeniably, the nature of our emotions is involuntary and unconscious, but the earlier view of seeing emotion as post-cognitive is inadequate. Emotion can precede cognition, but more importantly, it plays a vital role in the information processing [9]. Fear by itself is natural and vital for our survival, but the over-activation of our fear learning and memory can generate anxieties that prevent us to live life to its fullest. The interactive and immersive virtual reality environment can trigger real emotions, and help to modify our emotional learning and memory. Unfortunately, the more advanced technologies to track the activity of amygdala (such as infrared thermal imaging or EEG monitors) are not available on a global market nor yet compatible with VR headsets. In future, more accurate measurements will enable better estimates of the user’s emotions with a cost of a more

complex design. To validate the measured arousal level, we could design new techniques for self-reporting and tracking behavioral responses of the users in VR. The interactive environment also allows creating new designs for the illusion of competence and self-efficacy of the user that might help to enhance the successful outcome of VRET. Future Work Because of its sympathetic nature measuring fear arousal from a heart rate might become problematic. Only four studies show that heart rate can be used as an indicator of physiological response during the initial fear activation (IFA) [16]. This might be since heart rate indeed is “influenced by a myriad of factors other than sympathetic fear-based arousal”, and sometimes falls under the oppression of our parasympathetic nervous system.

Figure 7; Computational Model applied to Final Prototype

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As the healthy heart is not a metronome but a “mathematical chaos” [20] heart rate variability (HRV) indicating the changes of time between interbeat intervals might offer a better solution instead of the traditional BPMs recording. HRV is an index of neurocardiac function which is affected continuously by heart-brain interaction and the processes of our autonomic nervous system (ANS) [20]. HRV has been widely used as an indicator of stress since the 1960s. During the past two decades, various studies have shown its potential to indicate the individual capacity of emotion regulation [14]. As HRV, also our emotions are forced to continually change the environmental conditions reflecting “the status of one’s ongoing adjustment to constantly changing environmental demands” [14]. By measuring the resting HRV, we can predict the flexible, dynamic regulation of autonomic activity. Higher HRV signals “the availability of context- and goal-based control of emotions” whereas lower HRV can be linked to some degree of ‘laziness’ in the emotion regulation system [13]. Therefore, measuring HRV during the baseline trial might even predict the outcome of VRET. What needs to be taken into account for the computational model is that even though heart rate does not necessarily decline across the occasions of exposure the self-reported fear level does. As studies [3] show, declines in heart rate or skin conductance are not necessary for overall improvement. Therefore, and most importantly, the successful exposure therapy should be mediated mainly in the cognitive shifts if not directly in physiological changes [16]. We could highlight the importance of fear toleration instead of a fear reduction as an indicator of successful exposure therapy and take it into account in future research. When it comes to the binaural music implementation we could optimally get the users baseline by having them in relaxation therapy for 15 - 30 minutes as done in the Penistion and Kulkosky study [28]. By

stimulating their brainwaves over a long enough time, we could hopefully lower anxiety levels in patients and change their behavioral responses towards their phobia. We also imagine connecting the binaural music to colors that would represent the aura of the patients and give visual feedback to patients about their emotional state and fear/anxiety level. Acknowledgments We want to give big thanks to the MediaLAB Amsterdam and Amsterdam University of Applied Sciences for facilitating us with any necessary tools needed for this project. Special thanks to our coach Tamara Pinos Cisneros who guided us through from sprint to sprint. We also want to thank Triple for assigning us to a very challenging problem that helped us growing and learning as individuals as well as in a team. We also want to thank Radboud University GEMH-LAB and Behavioral Research Department for the personal feedback on our project that guided us in the right way of our final prototype. We also want to thank our fellow collaborators and creators at Kyushu University for all their guidance and feedback throughout this project. Thank you so much to Danny Dorstijn, our lead programmer, for cracking the code and hacking the Mio Link device so we could connect it directly with Unity and get live data from the biofeedback in the VRET. Much thanks to everybody else who helped us in one way or another and much love to our colleagues at MediaLAB Amsterdam. References 1. Peperkorn, Henrik M., Diemer, Julia, and Mühlberger, Andreas. 2015. Temporal dynamics in the relation between presence and fear in virtual reality. Computers in Human Behavior, 48 (July 2015) 542-547. DOI: https://doi.org/10.1016/j.chb.2015.02.028 2. Garcia-Palacios, A., Botella, C., Hoffman, H., and Fabregat, S. 2007. Comparing Acceptance and Refusal Rates of Virtual Reality Exposure vs. In Vivo Exposure by Patients with Specific Phobias. CyberPsychology & Behavior, 10(5). DOI: https://doi.org/10.1089/cpb.2007.9962

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