A correction has been applied to this article in:
Corrigendum: Design guidelines for limiting and eliminating virtual reality-induced symptoms and effects at work: a comprehensive, factor-oriented review
Alexis D. Souchet
Domitile Lourdeaux1
Peter A. Hancock- 1Heudiasyc UMR 7253, Alliance Sorbonne Université, Université de Technologie de Compiègne, CNRS, Compiègne, France
- 2Institute for Creative Technologies, University of Southern California, Los Angeles, CA, United States
- 3IFSTTAR, University Gustave Eiffel and University of Paris, Paris, France
- 4Department of Psychology, University of Central Florida, Orlando, FL, United States
Virtual reality (VR) can induce side effects known as virtual reality-induced symptoms and effects (VRISE). To address this concern, we identify a literature-based listing of these factors thought to influence VRISE with a focus on office work use. Using those, we recommend guidelines for VRISE amelioration intended for virtual environment creators and users. We identify five VRISE risks, focusing on short-term symptoms with their short-term effects. Three overall factor categories are considered: individual, hardware, and software. Over 90 factors may influence VRISE frequency and severity. We identify guidelines for each factor to help reduce VR side effects. To better reflect our confidence in those guidelines, we graded each with a level of evidence rating. Common factors occasionally influence different forms of VRISE. This can lead to confusion in the literature. General guidelines for using VR at work involve worker adaptation, such as limiting immersion times to between 20 and 30 min. These regimens involve taking regular breaks. Extra care is required for workers with special needs, neurodiversity, and gerontechnological concerns. In addition to following our guidelines, stakeholders should be aware that current head-mounted displays and virtual environments can continue to induce VRISE. While no single existing method fully alleviates VRISE, workers' health and safety must be monitored and safeguarded when VR is used at work.
1. Introduction
The COVID-19 pandemic conditions have accelerated the democratization of itinerant and remote work (Gajendran et al., 2021), making virtual reality (VR) an attractive alternative to support remote and collaborative office work (Ofek et al., 2020) and fostering the potential for its mass adoption (Grubert et al., 2018; Fereydooni and Walker, 2020; Knierim and Schmidt, 2020). While the potential benefits of VR have been widely reported in the literature, several authors (Keller and Colucci, 1998; Stanney et al., 1998; Sharples et al., 2008; Melzer et al., 2009; Fuchs, 2017, 2018; Souchet, 2020; Anses, 2021; Grassini and Laumann, 2021; Souchet et al., 2022) have stressed the necessity to address potential health and safety-related side effects of VR exposure. We focus specifically on office work use of VR.
Many terms have referred to such adversarial effects in the literature, most notably “cybersickness,” “VR sickness,” or “Simulator sickness.” In this study, we adopt the terms virtual reality-induced symptoms and effects (VRISE) introduced by Cobb et al. (1999) as it elicits a complete picture of the variety of VR side effects. VRISE initially encompasses cybersickness, postural instability, and other effects on psychomotor control, perceptual judgment, concentration, stress, and physical ergonomics (Cobb et al., 1999; Nichols, 1999; Nichols and Patel, 2002). Besides cybersickness, which is the most documented VRISE, the literature highlights four other undesired deleterious effects: visual fatigue, muscle fatigue, musculoskeletal discomfort, acute Stress, and mental overload. We propose to distinguish between cybersickness and visual fatigue. Indeed, cybersickness mostly refers to visually induced motion sickness that negatively impacts oculomotor function (Wang Y. et al., 2019). However, visual fatigue can occur without visually induced motion sickness (Souchet et al., 2022). Additionally, to health and safety concerns, the occurrence of VRISE can also induce a negative user experience (Somrak et al., 2019; Lavoie et al., 2020) and drastically impair performance in the task. For recent reviews of and in-depth discussions of VRISE, see, e.g., Ref Stanney et al. (2020b, 2021b), Howard and Van Zandt (2021), and Souchet et al. (2022).
Despite continuous improvements in the related technologies and the most recent innovations, the literature still provides evidence of VRISE with simulators and virtual environments. For example, Saredakis et al. (2020) found a mean dropout rate of 15.6% (min = 0%, max. = 100%) based on data reported in 44 empirical studies from the 55 selected for their systematic review of cybersickness and VR content impact with a head-mounted display (HMD). More generally, according to Stanney et al. (2021a) some side effects could be experienced even by more than 80% of VR users.
The research on VRISE has revealed that deleterious responses of users to virtual environment (VE) exposure vary widely depending on several factors, among which are the characteristics and capabilities of the users, the system (hardware/software) characteristics, and the implemented tasks to be performed with the VE. Unfortunately, no complete and holistic approaches to these different VRISE-related factors to be considered at the design and evaluation stages of VE development have been provided as far as we know. The literature provides some lists of factors specific to one single VRISE [e.g., for cybersickness, see Davis et al. (2014), LaViola et al. (2017)] or reports on a specific subset of factors that can influence VRISE. The latter include, for example, the visual fatigue caused by stereoscopy (Bando et al., 2012), cybersickness (Mittelstaedt, 2020; Howard and Van Zandt, 2021; Rebenitsch and Owen, 2021), and a panoply of other VRISE issues that could arise with VR usage (Chen et al., 2021). Factors are described, however, at various degrees of detail and completeness with no systematic wording consistency. Further limitations include that it is not always clear whether the claimed factors are grounded on empirical evidence, nor if they were identified in a VR context (Stanney et al., 2020b, 2021b; Howard and Van Zandt, 2021; Souchet et al., 2022). Further shortcomings in the current literature are related to the confounding effects of VRISE on other psychophysiological effects or among them, as recently emphasized (Kourtesis et al., 2019). One VRISE could influence another, but very few direct experimental proofs allow us to appreciate the magnitude of those influences (Alsuraykh et al., 2019; Mittelstaedt, 2020; Sepich et al., 2022; Souchet et al., 2022).
Developing the use of VR at work can result in increased exposure of the population to these multiple side effects and their impact on workers' health and safety (LaViola et al., 2017; Fuchs, 2018; Khakurel et al., 2018; Çöltekin et al., 2020; Olson et al., 2020; Anses, 2021; Ens et al., 2021). Such risks were featured in the European Agency for Safety and Health at Work warning (EU-OSHA, 2019). Thus, it is critical to examine and organize the current knowledge on the whole set of potential VRISE relevant to using VR in a work context. This knowledge includes evidence associated with the various factors involved in VRISE occurrence (e.g., individual, contextual, or technological) and design resources and solutions susceptible to avoiding these effects or at least decreasing their impact and likelihood. In particular, design guidelines and principles provide essential resources. They can be combined with and integrated with all user-centered design processes. Design guidelines and principles have an extended history in human–computer interaction to support user interface decisions, e.g., Smith and Mosier (1986). Design decisions take advantage of extant practical experiences, results from user studies, and applicable experimental findings to promote application consistency. As technology develops, such guidelines have been adapted for or explicitly defined in VR (Gabbard et al., 1999; Stanney et al., 2003b, 2021a; Burkhardt et al., 2006). Particular devices and/or their components have driven guidelines regarding VR dimensions such as haptics (Hale and Stanney, 2004), 3D interaction (LaViola et al., 2017), or HMD's application in general (Vi et al., 2019). Guidelines for domain-specific applications or user profiles such as a therapist user interface (Brinkman et al., 2010), VR games (Desurvire and Kreminski, 2018), VR in human neuroscience (Kourtesis et al., 2019, 2020), and psychology (Vasser and Aru, 2020) or assessments of elderly users (Shamsuddin et al., 2011) have also been proposed. However, existing works provide only a limited and restricted consideration of VRISE directly (Souchet et al., 2022).
In a previous contribution (Souchet et al., 2022), we focused on defining the current state of the art regarding VRISE, emphasizing theoretical aspects and merging existing literature to provide a list of factors believed to influence VRISE. Following this previous publication, this study aimed to report on and organize a comprehensive review of published design guidelines associated with the five short-term VRISE cybersickness (CYB), visual fatigue (VF), muscular fatigue (MF), acute stress (S), and mental overload (MO), focusing on workers and vocational contexts. To assure that our guidelines are practical, we sought to consider typical tasks that office workers would usually undertake using a PC, but in our case using VR. In addition, we want to organize this review so that it is easy to use and apply by researchers, designers, and work professionals. For that purpose, we have ordered existing knowledge by VRISE, type of factors, and potential factors that may impact VRISE. Assessing VRISE factors can further help identify and establish how users, apparatus, and virtual environments each contribute to VRISE occurrence.
Our study is organized as follows. First, we describe the general method we employed to select articles or written descriptions of each identified factor. Second, a concise definition, symptomology, and prevalence description are distilled for each VRISE. We have based these on existing reviews, systematic syntheses, and meta-analyses. Third, within each VRISE presentation, we point to Tables describing each factor, and guideline, distinguished by three characteristics: (1) individual, (2) hardware, and (3) software. Fourth, within each VRISE presentation, we promulgate general guidelines according to our presented synthesis of existing knowledge. Fifth, we discuss our summated results and explore their advantages and limitations. Sixth, tables that assemble and present descriptions and guidelines by factors regarding each short-term VRISE are displayed.
2. Methods
We conducted a literature search on journal and conference papers related to the five VRISE and published between January 2016 and mid-2021 partially (Primary Elements 5, 6, and 7 are not applied) applying the comprehensive review methodology stated in Ref (Stratton, 2016). The start date was selected because it corresponds to Oculus CV1's commercial release, delineating the moment when HMDs become more widely accessible for laboratories and other facilities and the public. Thus, it allows a targeted overview of contributions incorporating new-generation HMDs. HMDs are not the only devices allowing access to VR content (e.g., cave automatic virtual environment), but we focus on HMDs in the current review.
The review included the following search terms: (“Virtual Reality”) AND (“cybersickness” OR “visually induced motion sickness” OR “visual fatigue” OR “eyestrain” OR “muscle fatigue” OR “musculoskeletal discomfort” OR “stress” OR “acute stress” OR “cognitive load” OR “mental workload”) AND work AND (“meta-analysis” OR “systematic” OR “review”). This search was carried out on August 2021 on Scopus and Google Scholar.1
A first selection occurred based on titles and abstracts: We excluded those that did not refer to any of the five VRISE. Journal, conferences articles, and book chapters were included in this review if they were complete (i.e., includes a full paper, not just an abstract); the text was in English or French; the data were obtained from adults participants; the experimental tasks mainly were matching office-like tasks (text entry, document editing, reading, proofreading, gathering and processing data, creating graphs and data visualization (e.g., maps, plots), exploring and visually analyzing data, viewing several media (texts, images, videos, 3D objects), creating presentation materials, conducting meetings (public speaking), collaborating with other users in a shared VR environment. Additional papers anterior to 2016 were manually searched when no available review or meta-analysis was found regarding a VRISE or its related factors.
For each VRISE, we identified factors reported as associated with their occurrence and the proposed guidelines when provided. The definition and summary of the theories underlying the occurrence of each VRISE were made based on the most recent reviews or meta-analyses. Within each VRISE, we classified factors and guidelines into three (1) individual, (2) hardware, and (3) software, following LaViola (2000).
To better reflect our confidence in those guidelines, we graded each with a level of evidence based on Ackley et al. (2008) initially developed to assess nursing care evidences. Common factors occasionally influence different forms of VRISE. Hence, in those cases, crossing all VRISE can be important to envision what should be done to mitigate them.
As all empirical studies did not necessarily report guidelines, we translated the reported results as guidelines when it was the case. Hence, those guidelines are interpretations by the authors.
3. Results
3.1. Cybersickness
3.1.1. Definition
Cybersickness has been defined as “an uncomfortable side effect experienced by users of immersive interfaces commonly used for Virtual Reality. It is associated with symptoms such as nausea, postural instability, disorientation, headaches, eyestrain, and tiredness” (Lavoie et al., 2020).
3.1.2. Prevalence
Stanney et al. (2020b) have reported that at least one-third of users will experience cybersickness, with 5% of these participants presenting severe symptoms while using current HMDs generation, prevalence being almost necessarily contingent upon the technological state of the art (Somrak et al., 2019).
3.1.3. Theoretical grounding
The sensory cue conflict proposition is widely accepted compared with competing theories (Lee and Choo, 2013; Stanney et al., 2020b). According to sensory cue conflict, cybersickness appears to occur because of visual–vestibular–proprioceptive conflicts (Roesler and McGaugh, 2019; Staresina and Wimber, 2019; Wong et al., 2019; Hirschle et al., 2020; Klier et al., 2020; Saredakis et al., 2020; Stanney et al., 2020b; Grassini and Laumann, 2021; Howard and Van Zandt, 2021). These inconsistencies are also called sensorimotor conflicts. However, the ecological theory (postural instability) also relies on extensive experimental results (Theorell et al., 2015; Aronsson et al., 2017; Stanney et al., 2020b). According to the ecological theory, humans primarily try to maintain postural stability. Hence, motion sickness expands with postural instability due to the novel environment and motion cues (Stanney et al., 2020b). Therefore, the cue conflict theory defends inconsistencies between perception systems, while the ecological theory defends postural instability, provoking motion sickness.
3.1.4. Guidelines considering cybersickness factors
Rebenitsch and Owen (2021) have proposed 50 factors influencing cybersickness occurrence in VR. Unfortunately, in doing so, they do not limit to this relevant literature. However, they reuse Davis et al.'s (2014) list and align with the factors that Howard and Van Zandt (2021) noted. Mittelstaedt (2020) also proposed a synthesis. We selected Rebenitsch and Owen's (2014) factors list because it postulates more factors than other comparable publications. Each table lists one type or subtype of factor that could influence cybersickness:
- Individual factors related to experience with virtual environments and users' physical attributes are given in Table 1; general demographic factors and mental attributes are listed in Table 2.
- Hardware factors relating to screen are provided in Table 3, tracking in Table 4, rendering in Table 5, and non-visual feedback in Table 6.
- Software factors relating to movement in Table 7 and appearance and stabilizing information in Table 8.
TABLE 1
Table 1. Guidelines for possible individual factors relating to experience with virtual environments (CYB_1 to 4) and users' physical attributes (CYB_5 to 9) influencing cybersickness.
TABLE 2
Table 2. Guidelines for possible general demographic factors (CYB_10 to 14) and mental attributes (CYB_15 to 17) influencing cybersickness.
TABLE 3
Table 3. Guidelines for possible hardware factors relating to screen influencing cybersickness.
TABLE 4
Table 4. Guidelines for possible hardware factors relating to tracking influencing cybersickness.
TABLE 5
Table 5. Guidelines for possible hardware factors relating to rendering influencing cybersickness.
TABLE 6
Table 6. Guidelines for possible hardware factors relating to non-visual feedback influencing cybersickness.
TABLE 7
Table 7. Guidelines for possible software factors relating to movement influencing cybersickness.
TABLE 8
Table 8. Guidelines for possible software factors relating to appearance (CYB_41 to 46) and stabilizing information (CYB_47 to 50) influencing cybersickness.
3.2. Visual fatigue
3.2.1. Definition
Visual fatigue can be defined as: “physiological strain or stress resulting from excessive exertion of the visual system” (Somrak et al., 2019). Sheppard and Wolffsohn (2018) reference the list of symptoms identified by the American Optometric Association. These include eyestrain, headache, blurred vision, dry eyes, and pain in the neck and shoulders.
3.2.2. Prevalence
Visual fatigue is already a significant issue in everyday work, with a large population at risk estimated at around 50% (Nesbitt and Nalivaiko, 2018). Close-up work on computer screens is an issue regarding dry eyes, ametropia, and accommodation or vergence mechanisms (Lackner, 2014). New-generation HMDs still continue to cause visual fatigue (Koohestani et al., 2019; Wang Y. et al., 2019; Descheneaux et al., 2020; Kemeny et al., 2020; Caserman et al., 2021; MacArthur et al., 2021) alongside visual discomfort (Lambooij and IJsselsteijn, 2009; Sheppard and Wolffsohn, 2018; Ang and Quarles, 2020; Descheneaux et al., 2020; Yildirim, 2020). HMDs seem to create higher visual fatigue than PC, tablets, or smartphones (Souchet et al., 2018; Hirota et al., 2019; Descheneaux et al., 2020; Hirzle et al., 2020). However, as HMDs could summate with other screen usages, more prolonged exposure to screens, in general, leads to increasingly negative symptoms on the visual system (Souchet et al., 2019).
3.2.3. Guidelines considering visual fatigue factors
Fourteen factors influence visual fatigue occurrence based on our update (Souchet et al., 2022) of Bando et al. (2012)'s list. Each table lists one type or subtype of factor that could influence visual fatigue:
- Individual and hardware factors influencing visual fatigue are shown in Table 9.
- Software factors influencing visual fatigue are provided in Table 10.
TABLE 9
Table 9. Guidelines for possible individual (VF_1 to 3) and hardware (VF_4 to 7) factors influencing visual fatigue.
TABLE 10
Table 10. Guidelines for possible software factors influencing visual fatigue.
Factors inducing visual fatigue are not, in most cases, the central focus of peers for reducing VRISE. Therefore, further research is recommended in order to draw more precise and quantified guidelines.
3.3. Muscle fatigue and musculoskeletal discomfort
3.3.1. Definition
Muscle fatigue has been defined as an: “exercise-induced reduction in the ability of a muscle or muscle group to generate maximal force or power” (Yoon et al., 2020). Muscle fatigue frequently arises with screen work (Souchet et al., 2021).
3.3.2. Prevalence
Repetitions of excessive muscular loads can lead to musculoskeletal disorders and are the most common (almost 24% of EU workers) work-related problem in Europe (Cho et al., 2017). Neck, shoulder, forearm, and hands pain as well as upper and low back pain, prove to be the primary disorders associated with office work (Guo et al., 2017, 2019; Han J. et al., 2017; Bracq et al., 2019). Sitting while performing computer work can be associated with short-term adverse effects, such as physical discomfort (Yu X. et al., 2018). Symptoms associated with prolonged use of computers are neck and wrist pain as well as backache (Zhang et al., 2020c). Such symptoms are likely to also arise in VR. However, the majority of the associated literature concerns sports activity and is relatively less concerning office work tasks. Many experiments on muscle fatigue and/or musculoskeletal discomfort are assessed primarily using smartphones, tablets, and computer screens. Rarely do these employ HMDs, although the trend is changing.
3.3.3. Guidelines considering muscle fatigue and musculoskeletal discomfort factors
Fifteen factors have been identified (Souchet et al., 2022) as influencing muscle fatigue and musculoskeletal discomfort frequency of occurrence based on the current synthesis of existent work. Each table lists one type, or subtype, of factor that may influence muscle fatigue and musculoskeletal discomfort:
- Individual and Hardware factors influencing muscle fatigue and musculoskeletal discomfort are provided in Table 11.
- Software factors influencing muscle fatigue and musculoskeletal discomfort are described in Table 12.
TABLE 11
Table 11. Guidelines for individual (MF_1 and 2) and hardware (MF_3 to 7) factors influencing muscle fatigue.
TABLE 12
Table 12. Guidelines for software factors influencing muscle fatigue.
Clear information about muscle fatigue and musculoskeletal discomfort associated with VR exposure remains problematically scarce. Only a few works using PC or smartphone provide coherent findings for HMDs. However, the body part mobilized here, the tension experienced with HMDs and the interaction device use might not be equivalent. Therefore, we sought to extrapolate information from screen uses to provide guidelines. Muscle fatigue and musculoskeletal discomfort depend on specific task characteristics (Alabdulkader, 2021), making generalization challenging to validate.
3.4. Acute stress
3.4.1. Definition
Stress can be defined as a: “condition in which an individual is aroused and made anxious by an uncontrollable aversive challenge” (Gandevia, 2001). Acute stress represents a sudden or short time exposure incident (trauma, perceived threat, death of a loved one, job loss, etc.). Acute stresses are often juxtaposed with chronic stress, the latter being long-term effects (European Agency for Safety Health at Work, 2007; Coenen et al., 2019).
3.4.2. Prevalence
Current knowledge does not allow us to define acute stress prevalence induced by VR use specifically outside of wild task-specific aspects and technostress. Introducing VR at work without the proper training could trigger techno-complexity (see S_3 in Table 13) and add up to all the other apparatus workers already use, which might trigger techno-overload (see S_4 in Table 13). One wide use of VR is remote meetings. Public speaking is stress-inducing, but it seems higher with VR (Helminen et al., 2019; Zimmer et al., 2019). Acute stress, in general, impairs executive functioning (Calik et al., 2022). According to LeBlanc (Eltayeb et al., 2009), stress diminishes the efficiency of selective attention (Heidarimoghadam et al., 2020; Frutiger and Borotkanics, 2021). Stress can also impair working memory and has been suggested to enhance memory consolidation (Baker et al., 2018). Stress has been observed to impair memory recall/retrieval (Borhany et al., 2018; Shannon et al., 2019). Therefore, we can assert that stress can act to impair work performance when fulfilling tasks in VR. And, of course, these effects are dependent on task typologies. At the occupational level, stress impacts workers' health, performance, and wellbeing (Sesboüé and Guincestre, 2006; Fink, 2016). It can lead to depressive symptoms (Fink, 2007), burnout symptoms (Shields et al., 2016), hypertension (LeBlanc, 2009), and/or type 2 diabetes mellitus (Bater and Jordan, 2020). Stressors can therefore impact VR adoption as they affect task completion novelty and the spectrum of tasks' typology.
TABLE 13
Table 13. Guidelines for possible individual (S_1 and 2) and hardware (S_3 and 4) factors influencing acute stress.
3.4.3. Guidelines considering acute stress factors
Based upon our synthetic assessment of previous works, several factors are identified as influencing acute stress occurrence. We focused on nine of these (Souchet et al., 2022). They are couched in terms of office-like tasks. Each table lists one type of factor that influences acute stress:
- Individual and hardware factors influencing acute stress are shown in Table 13.
- Software factors influencing acute stress are given in Table 14.
TABLE 14
Table 14. Guidelines for possible software factors influencing acute stress.
Depending on the tasks at hand, the interactions, and the relevant interfaces, acute stress in VR can arise accordingly. Just considering the possibility of stress while using VR may already help create safe working conditions and promote more benevolent work conditions. VR allows for teleporting users to a stress-relieving environment [natural surrounds (e.g., trees, grass, indoor biophilic environment) as well as light conditions (Van den Berg et al., 2015; Liu M. Y. et al., 2017; Yin et al., 2018; Hedblom et al., 2019; Wang et al., 2019; Huang et al., 2020; Kerous et al., 2020; Li C. et al., 2020; Park et al., 2020; Shuda et al., 2020; Li et al., 2021), music (Sokhadze, 2007; Nakajima et al., 2016; Yu C. P. et al., 2018; Paszkiel et al., 2020; Yin et al., 2020)]; and could help alleviate the above-described symptoms via this capacity (Thoma et al., 2013).
3.5. Mental overload
3.5.1. Definition
Mental workload can be defined as “a subjectively experienced physiological processing state, revealing the interplay between one's limited and multidimensional cognitive resources and the cognitive work demands being exposed to” (Young et al., 2015; Ahmaniemi et al., 2017; de Witte et al., 2020) indicated that overload “occurs […] when the operator is faced with more stimuli than (s)he is able to handle while maintaining their own standards of performance.”
3.5.2. Prevalence
Current knowledge does not allow us to define mental overload prevalence induced by VR use specifically outside of wild task-specific aspects. But, mental fatigue appears to be higher in VR as compared to conducting the same tasks in real offices (Van Acker et al., 2018). Furthermore, VR induces a higher mental workload than PC (Lim et al., 2013; Zhang et al., 2017; Broucke and Deligiannis, 2019; Makransky et al., 2019). But, contradictory results regarding mental workload have been observed (Porcino et al., 2017). For example, VR presents a lower cognitive demand for geo-visualization and trajectory data exploration than PC usage (Collaboration, 2015; Kaplan et al., 2020; Szopa and Soares, 2021), and a higher mental workload does not always negatively impact task performance (Tian et al., 2021). As mental overload is especially contingent on task characteristics, relying only on a general model provides only general assertions. Examples exist in air traffic control (Young et al., 2015), driving (Paxion et al., 2014; Tobaruela et al., 2014), as well as work in nuclear power plants (Wickens, 2017). Therefore, we here consider primarily two factors (general enough to apply to a wide variety of tasks). However, (Wickens, 2017) have previously considered 26 factors that could influence mental workload. In VR, task characteristics impact mental workload, via interactions and interfaces. We thus focus especially on time pressure and task difficulty.
3.5.3. Guidelines considering mental overload factors
Based on our present synthesis of previous works, Table 15 features time pressure and task difficulty as these are the main factors influencing mental overload.
TABLE 15
Table 15. Guidelines for two possible factors influencing mental overload.
4. Discussion and limitations
We have provided a review featuring human factors and ergonomic approaches that have considered 90 factors that are proposed as impacting VRISE. More particularly, we considered 50 factors related to cybersickness in VR. Additionally, we examined fourteen factors involved with visual fatigue in VR and 15 related to muscle fatigue and musculoskeletal discomfort in VR. Finally, we identified nine factors for acute stress when working in VR, alongside two factors critical for mental overload assessment in VR.
General guidelines that designers should follow for a healthy, safe, and performant user experience at work:
- Design environments such that users can fulfill most of their tasks within 20-min interval to reduce cybersickness and visual fatigue occurrence.
- Provide an “exploration phase,” so that users can preview the fundamentals of their interactions, as well as experiencing local system feedback to reduce cybersickness and mental overload occurrence.
- Provide the user with a virtual assistant to adapt both interactions and interfaces to reduce mental overload occurrence.
- Limit movements within the virtual environment and display stereoscopy only when tasks require explicit depth cues to reduce cybersickness and visual fatigue occurrence.
- Create display features by considering user is sitting but allowing them to stand and walk on occasion to reduce muscular fatigue and musculoskeletal discomfort occurrence.
- Emphasize teleportation with guides for orientation if re-location within the virtual environment is necessary to reduce cybersickness.
- Allow users to customize their experience in the virtual environment (e.g., avatar, interface, and interactions) to reduce cybersickness, mental overload, and acute stress occurrence.
- Provide a monitoring toolkit that is based on questionnaires and psychophysiological measures, which allows to determine a user's susceptibility to side effects and to detect while they are immersed to reduce all VRISE occurrence.
- Provide stress-relieving procedures: these include, but are not limited to, nature (trees, grass, indoor biophilic environment), daylight, and relaxing music to reduce acute stress occurrence.
General guidelines that employers should follow for a healthy, safe, and effective use of virtual environments:
- Train workers to employ hardware and software effectively. This allows habituation and desensitization for the riskiest populations regarding cybersickness, reduces technostress that can provoke acute stress, and promotes an optimal degree of mental workload to reduce mental overload occurrence.
- Rethink and recast working tasks such that they can be readily adapted to virtual environments and their constraints to reduce acute stress and mental overload occurrence.
- Monitor workers' psychophysiological reactions in the virtual environment to record data to establish use benefit/risk ratios to reduce each VRISE occurrence.
- Have workers fill out anonymous questionnaires that inform about their individual susceptibility to VRISE.
General guidelines that workers would be informed of to sustain a healthy, safe, and effective use of virtual environments:
- Cease using virtual environments when symptoms of cybersickness, visual fatigue, muscle fatigue, and stress are experienced or task performance breakdowns occur.
- Take breaks following the use of virtual environments (take micro-naps, where possible walk beyond the bounds of the workplace, go drink water, seek “natural” spaces, listen to relaxing music or any and all combinations thereof) to reduce all VRISE symptoms.
- For those beyond 40 years of age, consider the individual to be might be more susceptible to elements of these side effects.
- Those with pathologies and/or particularities (e.g., eye diseases, overweight, neuroatypical, epilepsy, balance issues, muscle issues, and cognitive particularities), should be considered more susceptible to specific side effects of virtual environments.
Some prior guidelines have been suggested for discrete factors to promote healthier, safer, and more efficient work with virtual environments (Gabbard et al., 1999; Stanney et al., 2003b, 2021b; Burkhardt et al., 2006; Bando et al., 2012; Lanier et al., 2019; Muthukrishna and Henrich, 2019; Chen et al., 2021). However, most of these works concentrated on only one VRISE at a time. Frequently, they are not clear on the level of confidence associated with each guideline. However, to build on these previous works, we categorized factors into three types: individual, hardware, and software. With our tables, readers and stakeholders can easily refer to the present work as a guide for their design or use of virtual environments. Hence, the present offering is the most substantial and comprehensive assessment for the VR community. This is because it encompasses the greatest assemblage of information while providing the most practical and useful survey and recommendations.
The occurrence of acute stress and mental overload can be influenced by many further factors than those presented in our guidelines. Moreover, the factors and associated guidelines for all five VRISE are based on current knowledge. Further theoretical and experimental contributions are still needed to explain VRISE better by encompassing its inherent complexity. We must be aware that some factors are similar across VRISE (Souchet et al., 2022). We present them for each short-term VRISE to emphasize those similarities and better demonstrate confounding effects that remain to be addressed.
Some guidelines do not apply to all workers as we purposely selected only office-like tasks to contextualize our current contribution to the ergonomics of VR. However, very few existing works have been directed at tackling VRISE. Currently, the primary uses of VR lie in video games (entertainment in general) and training (see Cockburn et al., 2020). Consequently, our guidelines are sometimes based on observations, not directly on experiments using virtual environments for work or VR. Part of our guidelines still rests upon low evidence. Cybersickness is the VRISE with the most robust evidentiary basis. However, most meta-analyses, as well as systematic reviews, are founded upon questionnaire responses. Questionnaires appear to be the most utilized approach for all VRISE. Therefore, confidence in tested techniques to reduce VRISE relies, to the present time, less on objective measurements than might be preferred (Souchet et al., 2022).
Moreover, experimental quality and reproducibility need improvement in the VR field, which is valid for psychology and human-computer interaction in general (Chang et al., 2020; Petri et al., 2020; Gilbert et al., 2021; Halbig and Latoschik, 2021; Biener et al., 2022). Therefore, designers, employers, and workers should be cognizant that some factors tackled here and the associated guidelines are sometimes a direct transposition from the scientific literature that has not directly tackled VRISE or the work context. Such literature might suffer from shortcomings. However, it also means that part of the guidelines can be generalized to other contexts than work: i.e., entertainment and skills training. The median evidence level crystallizes this: five for cybersickness, four for visual fatigue, six for muscular fatigue, five for stress, and six for mental overload. We applied a scale from the medical field which hasn't been created for ergonomics issues, and proof that it is entirely relevant in this very case is low. Mainly because most scientific experiments in VR very rarely follow a large multisite randomized controlled trial methodology.
One major limitation of this study is that we concentrated on short-term VRISE. However, working in VR implies daily use, and a pre-print (Biener et al., 2022) documented VR work for one week. VR appears to be worse than PC working. Cybersickness is a concern, and some participants even dropped out of the study. The advantages and disadvantages of VR's long-term use are yet to be drawn. Following the present guidelines might help foster advantages, but they cannot delete disadvantages.
Another major limitation of our contribution is the included papers. We stopped inclusion in the review with papers published in mid-2021. However, several relevant papers were published at the end of 2021, in 2022, and at the beginning of 2023. Those relevant publications include guidelines for each VRISE, side effects mitigation technics, prediction and detection of side effects. This fosters the need for the research community to critique and update these guidelines.
Future valuable contributions regarding VRISE factors and guidelines to reduce any such impacts include the following:
1) Increasing experimental contributions testing influences of each factor on VRISE with high-quality methods using within-subject, between-subject, and crossover designs,
2) Increasing considered VRISE to allow a better risk/benefit ratio consideration to use VR or not,
3) Increasing experimental contributions regarding tangles between VRISE,
4) Advancing automatic VRISE detection based on psychophysiological measurements,
5) Contributing to publications looking at the big picture of VR via systematic reviews and meta-analysis,
6) Updating the current guidelines with stronger evidence.
Although important to follow our guidelines, stakeholders should remain aware that current HMDs and virtual environments will most likely induce cybersickness, visual fatigue, muscle fatigue, acute stress, and mental overload. Currently, no existing method can fully alleviate these VR side effects. Therefore, detecting and adapting the virtual environment based on psychophysiological measurements (Smith and Du'Mont, 2009) could help better individualize and optimize the user experience. A better understanding of all VRISE risks will allow a benefit/risk ratio assessment to decide when to use virtual environments or not.
Author contributions
AS, DL, J-MB, and PH contributed to conception and design of the review. AS wrote the first draft of the manuscript. All authors contributed to manuscript revision, read, and approved the submitted version.
Funding
This study was funded by European Union's Horizon 2020 research and innovation program under grant agreement No. 883293—INFINITY project. AS received a Fulbright grant delivered by the Franco-American Fulbright Association to be a visiting scholar at USC Institute for Creative Technologies.
Conflict of interest
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
Publisher's note
All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.
Footnotes
1. ^Due to the current limitations to 32 words, two requests were done distributing between the Former and latter VRISE.
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Keywords: virtual reality, ergonomics, cybersickness, visual fatigue, muscle fatigue, acute stress, mental overload, work
Citation: Souchet AD, Lourdeaux D, Burkhardt J-M and Hancock PA (2023) Design guidelines for limiting and eliminating virtual reality-induced symptoms and effects at work: a comprehensive, factor-oriented review. Front. Psychol. 14:1161932. doi: 10.3389/fpsyg.2023.1161932
Received: 08 February 2023; Accepted: 16 May 2023;
Published: 09 June 2023.
Edited by:
Osvaldo Gervasi, University of Perugia, ItalyReviewed by:
Kazunori Miyata, Japan Advanced Institute of Science and Technology, JapanHai-Ning Liang, Xi'an Jiaotong-Liverpool University, China
Abele Michela, Radboud University, Netherlands
Copyright © 2023 Souchet, Lourdeaux, Burkhardt and Hancock. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
*Correspondence: Alexis D. Souchet, Y29udGFjdCYjeDAwMDQwO2FsZXhpc3NvdWNoZXQuY29t