The role of age and postural stability for visually induced motion sickness in a simulated driving task
Bibliographic record
Abstract
Background: Visually-induced motion sickness (VIMS) is a common sensation using driving simulators, typically characterized by pallor, cold sweat, fatigue, dizziness, and/or nausea. Postural instability resulting from visual motion inputs has been discussed as a potential cause of VIMS. Interestingly, older adults are not only known to have reduced postural stability compared to younger adults, they have also been shown to be more susceptible to VIMS. The present study aimed to evaluate whether VIMS can be reduced through passive restraint, whether age affects VIMS, and how these factors interact. Methods: Twenty-one younger and 16 older adults participated in two simulated driving sessions for up to 25 minutes each using a console video game. The participant’s upper body was either restrained or unrestrained. In the restrained condition, participants’ torso and head were fixed to the backrest of the seat using elastic straps. In the unrestrained condition, the backrest of the seat was removed and participants could move freely during driving. The order of sessions was counterbalanced. VIMS was measured using the Fast Motion Sickness Scale and the Simulator Sickness Questionnaire. Postural sway was measured for 60 s with eyes closed before and after driving using a force plate. Results: During the unrestrained condition, 44% of older and 57% of younger adults reported sickness. For these participants, passive restraint resulted in a significant reduction in VIMS ( p = .002), particularly in older adults. In general, older adults did not report more VIMS than younger adults. With respect to postural control, older participants showed significantly more sway than younger adults both before and after the driving task. No group differences in postural sway showed between sick and non-sick participants. However, we found moderate to high positive correlations between the severity of VIMS and the amount of postural sway, indicating that stronger VIMS was accompanied by more postural sway. Discussion: Our findings indicate that passive restraint can be an efficient method to reduce (but not fully eliminate) VIMS during a driving task in users who experience sickness. Specifically older adults appear to benefit from passive restraint to reduce VIMS. Positive correlations between VIMS and postural stability support the assumption that postural control is involved to some degree in the occurrence of VIMS. Conclusion: Our results indicate that supporting postural stability can help to reduce the occurrence of VIMS, particularly in older adults. These findings have implications for the design and use of driving simulators and other virtual environments that bear the potential to create VIMS.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".