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Record W4413029947 · doi:10.3389/frvir.2025.1553318

Virtual reality for older people: effectiveness of a training program for accident prevention

2025· article· en· W4413029947 on OpenAlex
Alina Napetschnig, Wolfgang Deiters, Klara Brixius

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueFrontiers in Virtual Reality · 2025
Typearticle
Languageen
FieldHealth Professions
TopicOlder Adults Driving Studies
Canadian institutionsnot available
Fundersnot available
KeywordsTraining (meteorology)Virtual realityAccident (philosophy)PsychologyApplied psychologyMedical educationPhysical medicine and rehabilitationComputer scienceMedicineHuman–computer interactionGeography

Abstract

fetched live from OpenAlex

Background As people age, physical and cognitive limitations increasingly affect the daily mobility of older adults. Virtual reality (VR) applications offer novel opportunities for senior citizens to enhance their functional abilities. Routine activities, like crossing a street, can be simulated and practiced within a virtual environment. Objective This intervention study investigated the impact of a VR training application (‘Wegfest’) on physical function, fall-related confidence, and cognitive status in senior citizens. It was hypothesized that participation in the VR-based training program would lead to improvements in functional mobility, fall-related self-confidence, and cognitive performance. Method For this study, the VR application ‘Wegfest’ was developed to simulate various road scenarios. Over a 4-week training period, senior citizens practiced navigating diverse road-crossing situations. The effectiveness of the application was evaluated through measures of physical and cognitive performance, including the Timed Up and Go (TUG) Test, the Falls Efficacy Scale-International (FES-I), and the Montreal Cognitive Assessment (MoCA). In total, 29 senior citizens ( M = 74.95 years) were recruited, with 20 participants included in the final analysis. Data collection and statistical analyses were performed using a database specifically created for Wegfest. Results The VR application “Wegfest” received positive feedback from participants. Significant improvements were found between pre- and post-intervention measurements for TUG, t (19) = 3.50, p = 0.002, and for FES-I, z = −2.82, p = 0.005. No significant differences were observed in MoCA scores, z = 0.58, p = 0.564. Conclusion Virtual reality (VR) shows promise as an effective tool for supporting older adults in their daily activities. As a pilot (exploratory) study with a small sample size and a relatively high dropout rate, the results should be interpreted as preliminary and indicative rather than conclusive. The lack of behavioral outcome measures further underscores the exploratory nature of this investigation. Further research with larger samples and more comprehensive outcome measures is needed to evaluate the effectiveness and generalizability of ‘Wegfest’ and similar VR applications for enhancing everyday mobility.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.006
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.678
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.058
GPT teacher head0.446
Teacher spread0.388 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it