Barn Ruins Virtual Reality-Based Serious Game as a Rehabilitation Tool for Older Adults with Mild and Moderate Cognitive Impairment: A Pilot Study
Bibliographic record
Abstract
This study evaluates the potential of a serious game, called Barn Ruins, as a spatial learning rehabilitation tool for older adults with mild to moderate cognitive impairment (MCI). The game's user navigates a maze environment on a laptop screen using a gaming controller (a joystick). It progresses through easy, medium, and hard routes, and has an error-based spatial learning score. The intervention spanned eight weeks, during which participants played the game for 30 minutes, three times a week. Pre-and post-intervention assessments were conducted using two independent and validated spatial orientation measures: VRNHouse as the primary and the Clock Orientation Test as the secondary outcome.Seven participants (86.3 ± 4.9 years, 2 males) completed the study. Although no statistically significant changes were observed in VRNHouse or Clock Orientation Test scores, 71.4% of participants improved or maintained their performance in the primary outcome measure, while 66.7% demonstrated improvement or stability in the secondary measure. Analysis of spatial learning scores within the Barn Ruins game revealed significant improvements over time (p = 0.0046, Kendall's W = 0.42), particularly in easy (p = 0.023) and hard (p = 0.01) routes. Performance on medium routes fluctuated, suggesting greater difficulty with these trials.Post-hoc comparisons revealed that by Weeks 7 and 8, participants' overall spatial learning scores were significantly higher compared to those in Week 1. Notably, easy routes exhibited a ceiling effect after Week 4, while harder routes showed consistent improvement after Week 5.Despite modest results in independent outcome measures, the game's significant performance gains suggest its utility in improving spatial skills. Future research with larger samples is needed to validate these findings.Clinical Relevance- These findings highlight the potential of the Barn Ruins game as a novel rehabilitation tool for enhancing spatial learning in older adults with MCI.
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.
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 | 0.000 | 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".