Exploring the Suitability of Existing VR Locomotion Technique Applications for Older Adults - A Scoping Review
Bibliographic record
Abstract
Virtual reality (VR) locomotion techniques are commonly known as the ability to navigate or move in virtual spaces. With the increasing VR applications for older adults (OAs), locomotion techniques become increasingly important for their experience, especially since many VR applications aim to support healthy aging. Yet, we do not know whether the commonly used locomotion techniques in VR are suitably designed for OAs. As a first step toward understanding this, we conducted a scoping review of VR literature in two databases (ACM Library and IEEE Xplore). We employed the PRISMA method to identify papers that includes empirical studies and head mounted display (HMD) VR applications intended for OAs. The search returned 399 papers, and 47 papers were selected after 2 rounds of screening. The analysis of these papers shows that motion-based and room scale-based locomotion techniques are most common in VR applications for OAs. However, we also found a lack of formal evaluation of how suitable the common VR locomotion techniques are for OAs – a gap that needs addressing in order to improve the accessibility of VR for older users.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.027 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.015 | 0.012 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".