You're Making Me Sick: A Systematic Review of How Virtual Reality Research Considers Gender & Cybersickness

Title of the Paper

You’re Making Me Sick: A Systematic Review of How Virtual Reality Research Considers Gender & Cybersickness

Paper Information

• Subject Area: Gender factors and cybersickness research in virtual reality (VR)
• Keywords: Gender, gender differences, cybersickness, simulation sickness, virtual reality, virtual environments, systematic review

Research Background and Issues

• Problems and Challenges: Female users are more likely to experience cybersickness when using virtual reality devices, yet existing research lacks a systematic exploration of its causes and impacts. Many studies fail to adequately report participants' gender data, and inconsistencies exist in research design and data collection methods.
• Research Significance: As VR technology becomes more widespread, understanding the impact of cybersickness on different user groups is increasingly important, particularly regarding how gender may influence the occurrence and experience of cybersickness. Ignoring such gender differences could undermine the inclusivity and fairness of VR technology.
• Motivation and Related Work: The authors highlight that many VR studies have not thoroughly examined the influence of gender on cybersickness, leading to limited understanding of the experiences of certain groups (e.g., women). This research gap significantly affects the goal of designing VR systems "for everyone."

Solution

• Research Methods:
  • Conducted a systematic review, screening 71 VR-related papers focused on gender and cybersickness (including 59 experimental studies and 12 survey reviews).
  • Used the PRISMA framework to screen and analyze these papers, identifying multiple variables influencing cybersickness and its gender-related factors.
• Innovations:
  • Systematically evaluated the impact of gender on cybersickness and the reporting practices in VR research.
  • Proposed clear data reporting standards and explored ways to improve inclusive research design.
• Implementation Steps:
  • Screened literature from major databases (including ACM DL, IEEE, PubMed, etc.).
  • Extracted detailed information from the literature, such as research design, technical parameters, sample characteristics, gender-related data, and cybersickness measurement methods.
  • Conducted qualitative and quantitative analyses to uncover existing issues and knowledge gaps.

Research Findings

• Key Findings:
  • Female participants are more likely to experience cybersickness and exhibit different symptom distributions, such as a higher likelihood of disorientation and oculomotor disturbances, while male participants report more nausea.
  • Significant variability exists in research methods and cybersickness measurement tools (e.g., SSQ, MSSQ), making it difficult to draw consistent conclusions.
  • Gender considerations in VR research are often treated as supplementary analyses rather than primary factors, with little exploration of non-binary or transgender participants.
  • Data reporting (e.g., participant gender, reasons for dropout, exclusion criteria) is often incomplete, with unclear confounding factors and a lack of standardization.
• Research Value/Advantages:
  • Systematically revealed the underestimated impact of gender in VR research and provided directions for systematic improvement in future studies.
  • Highlighted the interdisciplinary importance of cybersickness and emphasized the need to improve inclusive design in VR systems.
• Recommendations:
  • Provide clearer reporting of participant demographics (gender, race, age, etc.).
  • Focus on exploring and sampling diverse gender identities rather than limiting to biological gender.
  • Record and analyze detailed information about participants who drop out due to cybersickness.
  • Develop and refine research designs to ensure greater inclusivity in terms of session duration, task settings, and technology choices.
• Limitations and Future Directions:
  • Limitations: The literature review focused on gender and cybersickness, potentially overlooking related studies that did not explicitly mention gender; search results may be biased depending on the database; factors such as age, race, and disability diversity were not considered.
  • Future directions include refining the interaction analysis between gender and other demographic characteristics, as well as incorporating interdisciplinary perspectives to improve data collection methods and experimental designs.