The Role of Immersion and Presence in Virtual Reality Cue-reactivity Assessment
A Study into:
Cue-exposure on Subjective Craving Among Smokers and Ex-smokers
Joost de Vries 6075983
Joost899@gmail.com Master’s Thesis
Graduate School of Communication Persuasive Communication
dr. G.J. de Bruijn 1 February 2018
Abstract
Objectives: Cue-reactivity has been used to assess subjective craving among nicotine dependent individuals by exposing them to smoking cues. Craving has been associated with failure to successfully quit smoking and is a prime factor of relapse. Studies into virtual reality (VR) based cue-reactivity assessment has shown promise in eliciting cravings. VR can be incorporated into cue exposure treatment (CET), which involves repeated exposure to smoking cues to extinguish craving responses. This study investigates the role of immersion and presence of VR (natural movement and 3D) in provoking changes in craving among smokers and ex-smokers. Methods: 88 smokers and ex-smokers were divided into a 2D 360-video condition and a 3D VR 360-video condition to study the effects of immersion and presence on subjective craving after exposure to smoking cues (environment and external). Effects on changes in craving were studied using a 2 (time: pre- and posttest) x 2 (realism: low vs. high) x 2 (smoking status: smoker vs. ex-smoker) Results: The 3D VR condition reported significantly higher levels of immersion (p = .004) and presence (p = .008) than the 2D condition, but no significant differences in subjective craving between conditions were found (p = .751). Subjective craving increased significantly between pre- and posttest across conditions (p < .001). Smokers reported significant higher levels of cravings between pre- and posttest than ex-smokers, F(1, 84) = 7.98, p = .006. Results showed a significant interaction between time, condition and smoking status F(84) = 10.36, p = .002. Smokers in the 2D condition reported significantly higher cravings (M = 58.96) than in the 3D VR condition (M = 42.42). This effect was reversed for ex-smokers, who reported significantly higher cravings in the 3D VR condition (M = 44.19), than in the 2D condition (M = 22.00). 3D VR was effective for both smokers and ex-smokers, whereas 2D was only effective for smokers. Unexpectedly, cravings were strongest for smokers in the 2D condition. Conclusion: Immersion and presence (natural movement and 3D), unique to VR, have different effects for both smokers and ex-smokers that should be considered with regards to cue-reactivity studies and VR CET.
Introduction
Anno 2018, the smoking of tobacco products is still a widespread problem of
worldwide proportions. Globally, more than 1 billion people smoke regularly (World Health Organisation [WHO], 2018). Tobacco use is the single largest preventable cause of cancer in the world and is responsible for about 22 percent of all cancer related deaths (WHO, 2017). Tobacco use is also one of the main risk factors for a number of other (chronic) diseases such as lung diseases, cardiovascular diseases, diabetes and blindness (American Lung
Association, n.d.). Most smokers indicate that they would like to quit smoking, and almost half indicate that they tried to quit smoking in the last 12 months. Even though the motivation to quit smoking seems prevalent in smokers, most attempts to quit fail and relapse is common. Studies in clinical samples show that relapse curves often have a hyperbolic shape, meaning that the possibility of relapse is most common shortly after quitting and decreases over time (García-Rodríguez et al., 2013).
Craving, understood as an intense, urgent desire or longing, has been associated as one of the primary factors of relapse after smoking cessation (Shiffman et al., 1997; Bagot,
Heishman & Moolchan, 2007; Killen & Fortmann, 1997; Piasecki, 2006; Abrams et al., 1988). Two types of craving have been identified in relation to smoking: background and cue-induced craving. Whereas background craving is characterized by the steady experience of craving over time, cue-induced craving is characterized by moments of acute spikes of intense craving that are triggered by external cues associated with smoking (Pericot-Valverde et al., 2014). External cues can be environments that are associated with smoking (e.g. bar, bus stop), or contextual smoking-related cues in said environments (e.g. ashtray, cigarette lighter), but these go hand in hand most of the time (Paris et al, 2011). The reaction to these
Craving and cue-reactivity are conceptualized as classically conditioned implicit responses to smoking cues (Park et al., 2014).
Because cue-induced craving is a significant contributor to the high relapse rates, it’s important that interventions aimed at getting people to give up smoking acknowledge cue-reactivity (Bedi et al., 2011; Drummond, 2000; Ferguson & Shiffman, 2009; Schiffman et al., 1997). Cue exposure therapy (CET) is a form of therapy aimed at extinguishing the
association of a response (in this case smoking) to a stimulus (smoking relevant cues), by repeatedly exposing smokers to smoking cues, using pictures, photographs, videos or their imagination (Park et al., 2014). The prolonged and repeated nonreinforced presentation of these smoking cues (the conditioned stimuli), results in a decline of craving (conditioned response) by severing the implicit associations (Giovancarli et al., 2016).
CET has been proven to be an effective form of therapy for several psychological disorders, such as different forms of anxiety, phobias and obsessive-compulsive disorder (Aboujaoude & Starcevic, 2015; Abramowitz, Deacon & Whiteside, 2011). Literature reviews of CET trials for the treatment of addictions (including smoking) showed little efficacy of CET as part of addiction treatment (Conklin & Tiffany, 2002; Martin, LaRowe & Malcolm, 2010, Niaura et al., 1999). Nonetheless, Martin, LaRowe and Malcolm (2010) point out several promising methodological innovations, including the use of Virtual Reality (VR). In recent studies about the efficacy of cue-reactivity and CET, VR has shown advantages over traditional techniques of exposure in eliciting craving and as a treatment for addiction
(Pericot-Valverde et al., 2014; Choi et al., 2011; Culbertson et al., 2012; Moon & Lee, 2009). The Cambridge dictionary defines VR as: “a set of images and sounds, produced by a computer, that seem to represent a place or a situation that a person can take part in” (2018). This last part characterizes and distinguishes VR from other media. The ability of VR to immerse people in virtual environments and simulate a sense of presence (commonly referred
to as “being there”) is unique for the medium (Aboujaoude & Starcevic, 2015; Fox, Arena & Bailenson, 2009). Whereas VR shows much promise and advantages over traditional cue-reactivity paradigms, little is known about how immersion and presence influences craving in cue-reactivity. The overarching research question that this study addresses is as follows: “Does the difference in immersive qualities (natural movement and 3D) and sense of presence
between 2D and 3D VR influence the self-reported craving of cigarettes or tobacco products when participants are exposed to smoking related cues in three virtual environments showed in a 360-video?” Furthermore, an explorative research question is added that investigates the
difference of this interaction between smokers and ex-smokers (who quit three months ago or less), to investigate the effects of smoking status on cue-reactivity. “How does the difference
in immersive qualities (natural movement and 3D) and sense of presence between 2D and 3D VR affects the self-reported craving of smokers and ex-smokers?”
Theoretical background
VR, immersion & presence
VR has the possibility to expand the breadth and complexity of cue presentation
compared to other media, by integrating computer graphics in a head-mounted display (HMD) and incorporating different tracking technologies. Through VR, participants can be exposed to a combination of complex cues (environmental and contextual), which simulate real-world settings (Kaganoff, Bordnick & Carter, 2012). Several studies have examined the differences in cue-reactivity of smokers between neutral and smoking related cues, when these cues were imagined, presented as static pictures, in a video, and in real-life scenarios (García-Rodríguez et al., 2011; Carter & Tiffany, 1999, Conklin et al., 2008; Dunbar, Scharf, Kirchner &
Shiffman, 2010; Tong, Bovbjerg & Erblich, 2007). The use of VR to provoke craving via cue-reactivity has advantages over traditional methods. It can expose participants to very specific and diverse smoking cues and combine both external and contextual cues (García-Rodríguez
et al., 2011; Acker & MacKillop, 2013). Lee et al. (2003), found that cue exposure via VR elicits more craving than via classical devices (pictures). More recent studies consistently reported increased subjective craving after exposure in VR to smoking cues as compared to neutral cues (Acker & MacKillop, 2013; Bordnick et al., 2005; Paris et al., 2011; Bordnick, Yoon, Kaganoff & Carter, 2013; Traylor, Bordnick & Carter, 2008; Traylor, Bordnick & Carter, 2009; Lee, Lim, Wiederhold & Graham, 2005).
It’s important to make a theoretical distinction between immersion and presence. Whereas immersion is understood as an objective variable of VR technology, the
psychological sense of presence that the technology invokes in users is a subjective variable of their experience (Igroup, n.d.). Immersion refers to the physical stimulation of VR
technology that affects the users sensory (the processing of sensory information) and motor systems (involved with movement). The level of immersion depends on the amount and range of sensory and motor systems that are connected to the virtual environments. More
stimulation of the sensory and motor systems can therefore increase the level of immersion. This can be achieved by increasing the field of view and number of visual stimuli, using three-dimensional sound or video, or by matching the sensory and motor systems to respond naturally to changes in body movements. For example, turning your head in real life coincides with changes in perspective in the virtual environment in a real and lifelike way (Bohil, Alicea & Biocca, 2011). The ability to navigate freely and naturally within virtual
environments is known as natural movement and is often incorporated in HMD’s to make sure that changes in viewing directing in the virtual world mimics real-world head
movements. This is also known as head-coupled viewing and is commonly used in HMD’s by tracking the movements of the head. This allows users to naturally move their head in the virtual world and look in any direction in a 360-degree fashion (Stanney & Hale, 2015).
Another unique characteristic of VR, and HMD’s especially, is its ability to render three-dimensional (3D) scenes by showing separate images to each eye and subsequently fusing them together using special lenses to create the perception of depth. Consequently, this creates an extra layer of added realism to virtual environments, since they mimic real life environments more closely (Stanney & Hale, 2015). 3D VR using HMD’s immerses
participants in multisensory realistic environments that allows participants to feel present and react the same way to stimuli in the virtual world as they would in the real world (Baumann & Sayette, 2006). This way, 3D VR engages both the sensory and the motor systems more fully than traditional formats, increasing the potential to elicit more realistic psychological and behavioural responses from users (Bohil, Alicea & Biocca, 2011). 3D VR immerses the user’s senses and body, who in turn create a mental model of the body in the virtual environment by which the user experiences a sense of presence (Igroup, n.d.).
Because traditionally HMD’s are cumbersome, expensive and difficult to use pieces of technology, and designing virtual environments is an expensive and time-consuming unique skill, this study uses mobile VR HMD’s and a 3D VR camera. The rapid growth in mobile VR with the Samsung Gear VR, Google Cardboard and YouTube VR, combined with the fact that most people nowadays own VR-ready smartphones, makes it relevant to investigate the effectiveness of these new technological breakthroughs in eliciting cravings. Modern mobile VR headsets are accessible, easy to use and cheap, making them potentially useful for researchers and health professionals, and even promises treatments that may be presented in an individual’s home (Bordnick, Yoon, Kaganoff & Carter, 2013). As of late, big steps have been made in the technology to easily and affordably capture 3D VR 360-videos. This circumvents the expensive and time-consuming modelling of virtual environments and contextual cues, while increasing the ecological validity by capturing real-life situations and people. Another added advantage of capturing real-life 3D VR videos, is that health
professionals can then easily and cheaply tailor or adjust treatment to focus on an individual’s specific triggers (cues) to decrease the risk of relapse (Kaganoff, Bordnick & Carter, 2012). Cue-reactivity
Studies into cue-reactivity consistently report significant increases in subjective craving after exposure in VR to smoking cues compared to neutral cues. It is therefore
expected that participants in the 3D VR 360-video condition will mimic this trend and show a significant increase in subjective craving. Less is known, however, about the reactivity to smoking cues for the 2D 360-video condition. Baumann and Sayette (2006) studied the effects of smoking cues in a virtual world on craving between neutral and smoking cues but did so without the use of an HMD to display the VR stimuli. Instead, they designed a VR simulation that could be displayed on a computer monitor. Participants were able to navigate the virtual world and look around in a 360-degree fashion by using a joystick. Participants were either placed in a neutral control group or in a group where they were exposed to both external and environmental cues that were proven to elicit craving. They were then asked to rate their urge to smoke on a 0-100 scale. Results showed that craving ratings were
significantly higher in the cue-exposure environment than in the control environment. This indicates that a 2D interactive virtual environment with smoking cues can also be effective in provoking cravings via cue exposure (Baumann & Sayette, 2006).
It’s expected that the level of self-reported immersion and presence will be significantly higher for the 3D VR condition than for the 2D condition, grounded on the unique immersive qualities of 3D VR over 2D in natural movement and depth perception via 3D. Whereas Baumann and Sayette (2006) proved that a virtual environment presented in 2D can also elicit significant cravings via cue exposure, it stands to reason that a virtual
environment presented in 3D VR will elicit significantly more cravings than in 2D. However, little research has been done into the specific effects of immersion and presence on craving.
Ferrer-García et al. (2010) found a strong direct relation between immersion in the VR environments and the level of craving to smoke, but only looked at these effects for former smokers, and did not compare these effects between different conditions. The heightened sense of presence and immersion that VR evokes is expected to translate in a higher level of subjective craving. It is therefore hypothesized that: “The self-reported craving between pre-
and posttest is significantly higher for the 3D VR condition than for the 2D condition”.
In general, studies into cue-reactivity found significant increases in craving after exposure in VR. However, a big portion of these studies only looked at the effects of VR on cue-reactivity for active regular smokers who were not necessarily looking to stop smoking (Paris et al., 2011; Acker & MacKillop, 2013; Bordnick et al., 2005; Baumann & Sayette, 2006; García-Rodríguez et al., 2011; García-Rodríguez et al., 2012; Bordnick et al., 2004; Lee et al., 2003). Ferrer-Garcia et al. (2010) studied the effects of VR cue exposure on former smokers and found significant increases in craving after cue exposure but did not differentiate between different conditions. Kaganoff, Bordnick and Carter (2012) specifically studied the effects of VR to assess cue-reactivity on treatment-seeking smokers and supported the use of VR in cue-reactivity assessment during treatment. Bordnick, Yoon, Kaganoff and Carter (2013) compared the results of two former studies that studied cue-reactivity in non-treatment smokers with their own follow-up study that studied cue-reactivity in treatment-seeking smokers (Bordnick et al., 2004; Bordnick et al., 2005). They found that VR cues elicited similar levels of craving for both treatment- and non-treatment seeking smokers, but only looked at active smokers. Because VR-CET can be applied to treatment seeking smokers
and/or ex-smokers, it’s relevant to study how the use of VR cue exposure differs for both
groups. Considering the lack of research into how 2D and 3D VR by which participants are exposed to smoking cues differs for smokers and ex-smokers in subjective craving, a final explorative research questions is added: “How does the difference in immersive qualities
(natural movement and 3D) and sense of presence between 2D and 3D VR affects the self-reported craving of smokers and ex-smokers?”
Methods
Participants
Participants were current smokers or ex-smokers who quit smoking in the past three months or earlier. Inclusion criteria for the study were to be older than 18 and to have smoked at least one cigarette a day in the past six months (on average). Participants were excluded if they were non-smokers, smoked less than one cigarette per day, or quit smoking outside of the pre-defined maximum period of three months. Participants were recruited via flyers
distributed at the University of Amsterdam Roeterseiland Campus and via www.lab.uva.nl. LAB is the website of the official research laboratory of the faculty of social and behavioural sciences, comprising the research institutes of (among others) Psychology, Communication Science and Anthropology.
During the three weeks that the study ran, a total of 112 people signed up for the study. After accounting for cancellations and no-shows, 94 people finished the study. The participants were randomly assigned to the conditions, which resulted in 46 people in the 2D condition and 48 people in the 3D VR condition. Five participants in the 2D condition had to be excluded from the study since they did not meet the pre-defined inclusion criteria of being active smokers or quit smoking a maximum of three months ago (3 participants) or smoking less than the minimum of one cigarette a day in the past six months (2 participants). One participant had to be excluded in the 3D VR condition because he or she did not declare how many cigarettes were smoked on average in the past six months. This left the study with a total of 88 participants distributed into 41 in the 2D condition and 47 in the 3D VR condition.
There were no differences in smoking status across the two conditions, as assessed by a chi-square test, p = .992.
The final sample consisted of 26 male participants (29.5%) and 62 female participants (70.5%) with a mean age of 21.1 (SD = 3.85), ranging from 18 to 47 years old. The
participants originated primarily from European countries (73.9%) and almost all of them labelled themselves as full-time students (93.2%). Almost half of the participants (45.5%) finished their secondary education as their highest educational level completed, whereas 17.3 percent completed a higher educational education and 17.3 percent completed an academic education. 58 participants (65.9%) were active smokers and 30 participants (34.1%) recently tried to quit smoking. On average, participants smoked 6.1 cigarettes per day in the past six months (SD = 7.95), ranging from 1 to 48 cigarettes or tobacco products. The Cigarette
Dependence Scale (CDS-12) was used to assess the nicotine dependency of the smokers in the sample (Etter, Houezec & Perneger, 2003). On a 7-point scale, the smokers in the sample (N = 58) reported an average addiction of 3.59 (SD = 1.17), indicating that the smokers in the sample were moderately addicted to cigarettes/tobacco products.
Seven questions assessed the attention of the participants for the relevant cues in the videos. Most participants attended to the relevant parts of the videos, namely the surroundings (89.7%) and the actors (95.4%). See Appendix A for a full report. Self-reported attention was subsequently tested using three control questions that measured item colour recall. Appendix B shows the colour recall for the different options in percentages. Most participants correctly recalled the colour of the items. We can conclude that the participants attended to the desired aspects of the video, and that a colour recall test confirmed this.
Instruments
To elicit cravings, three different 360-video scenes were filmed using an Insta 360 Pro VR camera (Insta 360 Pro, n.d.). The three scenes depicted in the video are, in order, having your coffee or tea in the morning, waiting for public transport to arrive, and having drinks at a bar or on a terrace (see Appendix C). The real environments depicted in the three scenes were validated in previous studies to elicit significant cravings (García-Rodríguez et al., 2011; Pericot-Valverde et al., 2014; García-Rodríguez et al., 2012; Baumann & Sayette, 2006). The Insta 360 Pro is a professional dedicated virtual reality camera that can shoot 360-video material in three-dimensional virtual reality up to an 8K resolution using six high definition lenses. The three videos used in this study were shot in a 4K resolution running at 60 frames per second and a 240 bitrate. The resulting videos were subsequently cut and edited into one 360-video with a runtime of 7:40 minutes. Each video lasted for exactly 2:30 minutes and had a five second fade-in and fade-out edited in to increase the comfort for the participants. A one-minute neutral test video preceded the three videos to give participants time to get accustomed with the technology (see Appendix D). In total, the video lasted for 8:47 minutes and was formatted to be watched in the YouTube VR format in a 2560x1440 resolution (Vries, 2018). To further increase the immersive qualities of the videos, stock sound effects were added to the three respective videos that matched the environments of the scenes.
A mobile VR HMD in combination with a mobile phone was used in the 3D VR condition, whereas the 2D condition used a mobile phone in combination with a set of earphones. Both conditions watched the exact same 360-video. However, participants in the 2D condition could look around in the scenes by tilting and turning the smartphone to view the virtual environments in a 360-degree fashion, whereas participants in the 3D VR condition used their head and body to naturally look around in the scenes (natural movement) and had the perception of depth (3D). To further enhance the comparability between the two
conditions, and to rule out any confounding factors other than the manipulation of natural movement and 3D, identical VR-headsets, smartphones and earphones were used. Two OnePlus One smartphones were used to show participants the 360-videos. The OnePlus One is a fairly representative smartphone of the general smartphone being used today, sporting a 5.5-inch full HD screen and a fast internal processor (OnePlus One, n.d.). The VR headset used in the study was a BOBO VR Z5. With a clear, natural and 120 degree viewing angle, the BOBO VR Z5 offers an immersive and true to life perspective of the three scenes. Any smartphone with a screen larger than 4.7 inches can be inserted in the headset to create a mobile VR experience. The headset is easily customizable for the different physical
characteristics of the participants, due to a built in diopter adjustment system for changing the focal lengths and a system to modify the headset for your own personal pupillary distance (BOBOVR Z5, n.d.). This made it easy for participants to get the most comfortable and clear experience possible, while still being affordable.
Measurements
To control for possible significant differences between the two conditions in their respective average level of addiction, the Cigarette Dependency Scale (CDS) was used to rule out any differences in addiction. The CDS is a 12-item self-administered measure of cigarette dependence that covers the main components of the DSM-IV definitions of dependency including compulsion, withdrawal symptoms, loss of control, time allocation, neglect of other activities, and persistence despite harm. The CDS-12 was found to be a reliable measure of cigarette/tobacco dependence and scored high in content validity and construct validity (Etter, Houezec & Perneger, 2003). Comparative research into the validity and predictive power of the CDS-12 with the older standard Fagerström Test for Nicotine Dependence (FTND), found that the CDS-12 outperformed the FTND on tests of predictive power, construct validity and reported a higher internal consistency (Etter, 2005; Etter, 2008). The CDS-12 was modified
from a 5-point answering scale to a 7-point answering scale ranging from 1 (strongly
disagree) to 7 (strongly agree) for more nuance (see Appendix E). Questions 1 through 4 were recoded. As expected, the scale had a high overall reliability, Cronbach's α = .91.
To assess the subjective individual cravings for cigarettes/tobacco, a Short Form of the Tobacco Craving Questionnaire (SF-TCQ) was used. The TCQ has been proven to be a valid and reliable 47-item self-report measure that assesses the craving for tobacco (Heishman, Singleton & Moolchan, 2003). Heishman, Singleton and Pickworth constructed a short form of the TCQ that consisted of 12 items for more practical use in research and clinical settings (2008). Follow-up research into the reliability and validity of the SF-TCQ compared to the 47-item TCQ, revealed that the SF-TCQ is as valid and reliable as the 47-item TCQ in measuring craving (Heishman, Singleton & Pickworth, 2008; Berlin, Singleton & Heishman, 2010; Singleton, Anderson & Heisman 2003). The 12 items were rated on a 7-point Likert-scale ranging from 1 (strongly disagree) to 7 (strongly agree). The four reverse keyed items that were included to reduce variance due to acquiescence were recoded. See Appendix F for the full SF-TCQ. As expected, the scale had a high overall reliability, Cronbach's α = .93. The ability to evoke a sense of presence in the two conditions was tested as a randomisation check using a modified version of the 14-item self-report Igroup Presence Questionnaire (IPQ). The modified IPQ consists of 13 subjective rating scales that are scored on a 7-point Likert-scale ranging from 1 (strongly disagree) to 7 (strongly agree), with higher scores indicating a greater sense of presence (Igroup, n.d.). One item measuring the
interactivity of the virtual world was left out of the questionnaire because of the
incompatibility with the static nature of the videos. The items were customized for the study and reverse coded where necessary before further analysis. The IPQ has been found to be a reliable and valid measure to assess presence in virtual environments (Vasconcelos-Raposo et
al, 2016; Schubert, Friedmann & Regenbrecht, 2001). Appendix G shows the modified IPQ. As expected, the scale had a high overall reliability, Cronbach's α = .89.
Finally, both the craving for cigarettes or other tobacco products and the level of immersion was assessed separately from the validated scales using a slider that ranged from 0 (no cravings at all/totally not immersed) to a 100 (extreme cravings/completely immersed). The average level of immersion was composed of the level of immersion in each of the three depicted scenes (coffee/tea, public transport, bar). Four questions were added to assess the attention of the participants for the different elements in the scenes. On top of that, three control questions measured if the participants paid attention to the actors and what they were doing. They were asked what colour the sweater of the actor who was drinking a cup of coffee in the morning after waking up was, what colour the coats of the actors who were waiting for public transport to arrive were, and what colour the cigarette lighter used in the video where the actors were having a drink on a terrace was. Four options (including the correct one) were given for each scene, plus an open answer and don’t know option. Open answers were
considered correct if they were an extension or variation of the correct colour (e.g. maroon or dark red).
Procedure
Participants were randomly assigned to either the 2D condition or the 3D VR condition using a research randomiser. This randomiser is developed by the Social
Psychology Network and is specifically designed for the random assignment of participants into experimental conditions (Research randomizer, n.d.). A set of 120 numbers was
randomly generated and assigned either a zero (2D) or a one (3D VR) to realise random assignment into the two experimental conditions.
Upon arrival, participants were invited to take a seat into one of the two laboratory rooms reserved for the experiment. Participants were asked to carefully read an information leaflet detailing the study’s procedures, after which an informed consent was obtained from each participant if they agreed to the drawn-up terms and conditions. After this, participants were asked to start the questionnaire wherein they answered socio-demographic questions relevant to the study, as well as questions about their current smoking behaviour and nicotine dependency using the CDS-12. The baseline of participants’ current craving for cigarettes or tobacco products was assessed using the SF-TCQ.
After the first part of the study, the VR cue exposure procedure commenced. Participants were asked to read a short instruction leaflet that explained the next part of the study and were implored to mainly focus on what the actors in the videos were doing. The researcher brought in the headset and helped set it up to each participants’ personal
preferences, in case of the 3D VR condition. In the 2D condition participants were given a mobile phone with a set of headphones. Participants in both conditions were shown how to navigate the virtual environments in a one-minute acclimation video featuring a 360-video of a nature trail following a river, after which the three scenes were shown as explained in the instruments section of the study. Participants were asked to place the study materials in front of them when the video was completed and finish the final part of the questionnaire.
The final part of the questionnaire consisted of the control questions about the videos, as well as the immersion scales and the modified IPQ to measure the sense of immersion and presence in the virtual environment shown in the videos. Finally, a posttest assessed the participants’ craving after cue exposure, using the SF-TCQ that was also used for the baseline measurement, as well as the 0-100 scale measuring craving. Participants were subsequently thanked for their time and effort participating in the study, before they received their preferred reward (participation points or a financial compensation of 5 euros).
Data analysis
All data were analysed with the statistical package SPSS for Windows (version 24). The data were analysed using a combination of Independent T-Tests and repeated-measures ANOVA’s. Partial eta-squared (η2) values were computed as estimates of effect sizes for comparisons. Effect sizes were considered as small, η2 = .01, medium, η2 = .09, and large, η2 = .25. According to the guidelines by Cohen (1988), Cohen’s d was considered as small, d = .10, medium, d = .50, and large, d = .80. Statistical significance was defined as p < 0.05.
Results
Randomisation and manipulation checks
All randomisation checks were carried out using Independent T-Tests. No significant differences were found across conditions and between smoking status for baseline variables (all p’s > .05). See figure 1 for the full statistics. Randomisation was deemed successful. Figure 1
Randomisation checks of baseline variables
Baseline variables 2D (N = 41) 3D VR (N = 47) Sig. Smokers (N = 58) Ex-smokers (N = 30) Sig. Gender 1.71 1.70 .958 1.74 1.63 .298 Age 21.51 20.85 .424 20.79 21.87 .217 Addiction smokers (N = 58) 3.77 3.44 . 282 - - - Baseline craving 3.06 3.26 .403 3.26 2.97 .233 Attention 4.68 4.61 .581 4.63 4.65 .903
To test whether the self-reported level of immersion was significantly higher for the 3D VR condition than for the 2D condition, an Independent T-Test was carried out. For each situation the 3D VR condition had higher immersion scores than the 2D condition. However, only the first and the third situation were significant, p = .013, p = .004. See also figure 2. Figure 2
Immersion per situation and condition (2D – 3D VR)
Statistics M (2D) SD n M (3D) SD n 95% CI t df p Morning tea/coffee 50.46 27.31 41 64.38 24.41 47 [-24.88, -2.96] -2.51 86 .013* Public transport 46.9 27.44 41 56.26 22.36 47 [-19.91, 1.21] -1.76 86 .082 Drinks at a bar 53.81 25.88 41 68.85 21.36 47 [-25.06, -4.87] -2.99 86 .004*
Note: p values with an asterisk are significant at p < .05
To test if the manipulation between conditions (2D and 3D VR) in immersion and sense of presence was successful, Independent T-Tests were carried out. Figure 3 shows that for both immersion and presence there were significant differences between conditions. Both immersion (d = .58) and presence (d = .54) reported medium-sized effects.
Figure 3
Manipulation checks between conditions for immersion and presence
Statistics M (2D) SD n M (3D) SD n 95% CI t df p Immersion 0-100 scale 50.39 22.22 41 63.16 18.49 47 [-21.40, -4.15] -2.94 86 .004* Presence IPQ scale 4.67 1.01 41 4.13 .87 47 [-0.94, -0.14] -2.70 86 .008*
Hypothesis testing
There were no outliers in the data, as assessed by inspection of a boxplot for values greater than 1.5 box-lengths from the edge of the box. Cravings in the pre- and posttest were normally distributed, as assessed by a Normal Q-Q Plot. There was homogeneity of variances, as assessed by Levene's test of homogeneity of variance (p > .05). There was homogeneity of covariances, as assessed by Box's test of equality of covariance matrices (p = .851). There was a statistically significant effect of time, F(1, 84) = 48.06, p < .001, partial η2 = .36,
representing a large effect. Contrary to the hypothesis, no significant two-way interaction was found between condition (2D vs. 3D VR) and time (pre- and posttest), p = .751. Self-reported craving between pre- and posttest was not significantly higher for the 3D VR condition than for the 2D condition. The hypothesis was therefore rejected. A significant two-way interaction was found between time (pre- and posttest) and smoking status, F(1, 84) = 7.89, p = .006, partial η2 = .09. Smokers reported significantly higher cravings between pre- and posttest than ex-smokers. The three-way interaction between condition, smoking status and time was statistically significant, F(1, 84) = 10.63, p = .002, partial η2 = .11
Figure 4 shows the two-way interaction between time (pre- and posttest) and
conditions (2D vs. 3D VR), for both smokers and ex-smokers. Whereas ex-smokers reported the expected increase in craving in the 3D VR condition compared to the 2D condition between pre- and posttest (right), smokers showed an inverse trend wherein they reported increased craving in the 2D condition as opposed to the 3D VR condition between pre- and posttest (left). The significant higher level of immersion and presence of 3D VR 360-video compared to 2D 360-video did not translate in higher subjective cravings for smokers, whereas it did for ex-smokers. Figure 5 shows that, apart from ex-smokers in the 2D
Figure 4. Two-way interaction effects between time (pre- and posttest) and condition (2D vs. 3D VR), for both smokers and ex-smokers (in percentages)
Note: Asterisks show significant effects at p < .05
Figure 5
Average increase in craving (pre- and posttest) per condition for smokers and ex-smokers
Statistics M (Pre) SD M (Post) SD n 95% CI t df p Smokers 2D 31.63 24.40 58.96 24.49 27 [-35.07, -19.60] -7.26 26 .000* Smokers 3D VR 29.77 24.12 42.42 26.92 31 [-19.63, -5.66] -3.70 30 .001* Ex-smokers 2D 19.57 19.02 22.00 23.87 14 [-12.27, 7.41] -0.53 13 .603 Ex-smokers 3D VR 29.69 21.14 44.19 27.28 16 [-22.36, -6.64] -3.93 15 .001*
Note: p values with an asterisk are significant at p < .05
0 10 20 30 40 50 60 70 Pre-test Posttest Me an lev el o f cra vin g
Smokers (n =58)
2D 360-video* 3D VR 360-video* 0 5 10 15 20 25 30 35 40 45 50 Pre-test Posttest Me an lev le o f cra vin gEx-smokers (n = 30)
2D 360-video 3D VR 360-video*Discussion & Conclusion
The primary purpose of the current study was to investigate how unique immersive qualities of VR, in this case natural movement and depth perception via 3D, influenced cue-reactivity (measured as craving), when nicotine dependent participants were exposed to smoking related cues in three virtual environments. In addition, this study investigated how this interaction differs between smokers and ex-smokers. Results supported the idea that the 3D VR format is significantly more immersive than the 2D format and leads to a significant higher sense of presence. Although subjective cravings increased significantly across
conditions and for conditions respectively, the higher level of immersion and presence in the 3D VR condition, compared to the 2D condition, did not result in significantly higher levels of craving for the 3D VR condition compared to the 2D condition, refuting the hypothesis. The interaction between time and condition for both smokers and ex-smokers showed an unexpected inverse trend between smoking status. While ex-smokers reported significantly higher cravings in the 3D VR condition compared to the 2D condition, smokers reported significantly higher cravings in the 2D condition than in the 3D VR condition. Additionally, cue exposure in both the 2D and the 3D VR condition resulted in significant increases in subjective craving for smokers, whereas for ex-smokers only the 3D VR condition provoked significant increases in craving after cue exposure. The results show that there’s a distinct difference in how 2D and 3D VR elicit cravings in smokers and ex-smokers, and that smoking status must be considered for cue-reactivity assessment and CET. The increased sense of immersion and presence of 3D VR over 2D did not result in higher subjective cravings for smokers but did for ex-smokers.
These results, while surprising, show similarities with preceding studies into VR cue-reactivity, as delineated in the theoretical framework. Across the board, significant increases in subjective craving were found after exposure to smoking cues in VR for smokers (Paris et
al., 2011; Acker & MacKillop, 2013; Bordnick et al., 2005; García-Rodríguez et al., 2011; García-Rodríguez et al., 2012; Bordnick et al., 2004; Lee et al., 2003), as well as for former smokers (Ferrer-Garcia et al., 2010), and treatment seeking smokers (Kaganoff, Bordnick & Carters, 2012; Bordnick, Yoon, Kaganoff & Carter, 2013). These findings align with the results of the present study, which shows a significant increase in subjective craving for both smokers and ex-smokers in the 3D VR condition. Compared to the former studies, similar mean levels of craving at posttest for 3D VR were found in the present study, which revolve around the middle of the scale. Baumann and Sayette (2006), found significant increases in cue-reactivity among smokers using VR simulations in a 2D format on computer screens, which is in agreement with our findings for smokers in the 2D condition. However, to date, no studies were found that investigated the effectiveness of 2D 360-video cue exposure for ex-smokers. Although the 2D format resulted in significant increased cravings for smokers, in fact the smokers in the 2D condition reported the highest level of cravings of all conditions, 2D had no significant effect for ex-smokers.
There are a few limitations to bear in mind. First off, besides the unique qualities of immersion and presence that VR technologies can invoke, another distinctive characteristic of VR is the ability of people to interact in (and with) virtual environments (Gamito et al., 2010). This allows users to navigate in the virtual environments and interact with certain elements such as characters and objects as in a computer game. This provides participants with the opportunity to freely explore virtual environments and receive feedback from the virtual world (Baumann & Sayette, 2006). The present study, however, used static virtual
environments wherein participants assumed the role of spectators in the three scenes. A more interactive approach might have increased the immersion and sense of presence even further. Secondly, self-reported measures (e.g. how much you experience craving) are fallible and can be particularly subject to bias (Wilson & Dunn, 2004). Sayette et al., (2000) argue therefore
that psychophysiological responses might be a more objective and sensitive way of assessing craving and are less vulnerable to possible bias. These can include changes in heart rate, blood pressure, skin conductance, skin temperature or even fMRI. It was not possible to incorporate these potentially interesting alternative craving measures in the present study, but future research into the field might benefit from these alternative measures. Thirdly, even though the participants used in this study originated from a multitude of (primarily) European countries which increases generalizability of the results across origin, almost all of them identified as academic students in their early twenties. This impedes the generalizability of the findings to other nicotine dependent individuals with different ages and educational backgrounds. This is a common limitation in academic research, but it is important that this is addressed in future studies, since nicotine dependency and relapse are problematic in all walks of life and among different age groups. Finally, it wasn’t assessed if participants had smoked before coming in for the study. Therefore, the possibility exists that some participants smoked beforehand or, alternatively, came in smoke-deprived. This could have had an influence on their subjective level of craving. To combat this possible bias, it might be relevant to ask participants not to smoke for 12 hours before the experiment to level out baseline craving.
Despite these limitations, the current study is one of the few that investigated how differences in immersive qualities (natural movement and 3D) and sense of presence between 2D and 3D VR influences self-reported craving when participants are exposed to smoking related cues in virtual environments, and how this subsequently affects both smokers and ex-smokers. A strength of the study is the relatively large sample size (n = 88), which makes it one of the largest studies into VR-based cue-reactivity. The increased power that comes with larger sample sizes allows for a greater ability to detect differences between conditions and their impact on subjective craving.
An additional strength lies in the practical implications of the VR technology that was used in this study for the day-to-day practice of health practitioners, researchers and
therapists. The mobile VR HMD’s used in this study are affordable, easy to use and
accessible, which makes them potentially useful tools to incorporate in their daily practice. This study showed that cue-reactivity assessment using mobile VR HMD’s in nicotine dependent individuals is comparable with previous studies that used professional expensive VR equipment, in terms of its effectiveness in eliciting cravings. Furthermore, mobile VR HMD’s can potentially be effectively deployed in other fields within VR CET such as the treatment of different psychological disorders (e.g. anxiety and phobias), drugs or alcohol dependency that have similar conditioned reactions to cues in the environment, or other academic research domains.
Another practical strength is the use of an affordable and easy to use 3D VR camera to record the stimulus material. This study proved that real-life situations filmed in a 360-degree format can successfully elicit increased cravings in smokers (2D and 3D VR) and ex-smokers (3D VR only), increasing the ecological validity. Designing virtual environments is
expensive, time-consuming and difficult, whereas using a 3D VR camera is as easy as operating any other normal camera. On top of that, the affordability and ease-of-use of capturing real-life 3D VR videos, is that health professionals can easily and cheaply tailor or adjust treatment to focus on an individual’s specific cues. These practical strengths are not be underestimated, since the effective application of technologies for evidence-based treatments is directly related to the ability of health professionals and patients to effectively and easily use these tools (Giovancarli et al., 2016).
To sum up, in accordance with previous studies into cue-reactivity, exposure to smoking cues in VR can be used to effectively elicit cravings in both smokers and
effective overall), no significant effects of 2D were found for ex-smokers, whereas 3D VR was effective for both smokers and ex-smokers. It’s reasoned that the higher levels of immersion via natural movement and depth perception of the 3D VR condition over the 2D condition are particularly important in eliciting cravings in ex-smokers, whereas this was not the case for smokers.
A possible explanation for this unexpected effect might be that the ex-smokers have adopted (self-taught) coping mechanisms to deal with cravings, invoked by environmental and contextual smoking cues, such as the ones used in this study to prevent relapse (Marlatt & Donovan, 2005). In contrast, it’s possible that most of the active smokers were content with their current smoking behaviour. The increased level of immersion (through natural
movement and depth perception via 3D) and sense of presence that the 3D VR condition invoked in the ex-smokers, led subsequently to significantly increased cravings over the 2D condition, as was originally expected based on previous research. The smokers might have been less reactive to the presented smoking cues since they are likely not (or less) motivated to stop smoking anytime soon. This, in turn, might be an explanation as to why the less immersive 2D condition was effective for smokers but not for ex-smokers, since the active smokers were less motivated to guard themselves (sub)consciously against these smoking cues, plus they could smoke a cigarette within five minutes after the end of the experiment. This does not explain why the 2D condition elicited significantly higher cravings in smokers than the 3D VR condition. However, these findings do indicate that the mode in which smoking cues are presented to nicotine dependent individuals, in either cue-reactivity assessment or VR CET to effectively elicit cravings, differs between smokers and ex-smokers. It’s important that subsequent research into cue-reactivity and CET using VR technologies take the immersive properties unique to VR on smoking status into account, since they can have real-life implications for both patients and health professionals.
Acknowledgements
Special thanks to Ruben Vroman and Luc Boesten from BoemanFX for their help filming, producing and editing the stimulus material used in this study.
Thanks to thesis supervisor dr. Gert-Jan de Bruijn for his contributions in setting up the experiment and the design of the questionnaire.
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Appendices
Appendix A: Self-reported attention
Attention in percentages (n =88) Scale Strongly disagree (1) 2 3 4 5 6 Strongly agree (7) Clothes 6.8 28.4 15.9 8 33 8 - Surroundings - 3.4 2.3 4.5 31.8 44.3 13.6 Non-relevant details - 14.8 19.3 4.5 37.5 17 6.8 Actors - 3.4 1.1 - 17 53.4 25
Appendix B: Colour recall
Colour recall in percentages (n = 88)
Colour Black White Red Blue Another
colour
Don’t Know
Sweater 2.3 1.1 69.3* 17 2.3 8
Green Red Black/Blue Brown Another
colour
Don’t know
Coats - 2.3 70.5* 10.2 2.3 14.8
Blue Red Black White Another
colour
Don’t know
Lighter 5.7 59.1* 3.4 3.4 3.4 25
Appendix C: Stills taken from the 360-video
While having your coffee or tea in the morning
While having drinks at a bar or on a terrace
