Simulating the Benefits of Nature Exposure on Cognitive Performance in Virtual Reality: A Window into Possibilities for Education and Cognitive Health
Bibliographic record
Abstract
Purpose: This one-group pretest−posttest, designed within a subject study, looks to compare the effects of an outdoor nature walk (ONW) to those of a virtual nature walk (VRW) on memory and cognitive function. Implications are discussed for education as well as for the world of virtual reality. Methods: Sixty-four healthy university students were asked to complete an ONW and a VRW, which was created using 3D video of the same nature trail used for the ONW. The VRW condition involved a five-minute walk on a treadmill, while wearing a virtual reality mask (Oculus, San Francisco, USA) that projected a previously recorded three-dimensional capture of the same nature walk they experienced outdoors. Both experimental conditions lasted approximately 5 min and were counterbalanced between participants. A Digit Span Test (Digit) for working memory and a Trail Test (TMT) for executive function were administered to all study participants, immediately before and after each type of walk. Results: For executive function testing (Trail Making Test), our results demonstrate that both the ONW and VRW condition improved the TMT time, when compared to a baseline (ONW 37.06 ± 1.31 s vs. 31.75 ± 1.07 s, p < 0.01 and VRW 36.19 ± 1.18 s vs. 30.69 ± 1.11 s, p < 0.01). There was no significant difference between the ONW and VRW groups. Similarly, for the Digit memory task, both conditions improved compared to the baseline (ONW 54.30 ± 3.01 vs. 68.4 ± 2.66, p < 0.01 and VRW 58.1 ± 3.10 vs. 67.4 ± 2.72, p < 0.01). There was a difference at the baseline between the ONW and VRW conditions (54.3 ± 3.01 vs. 58.1 ± 3.10, p < 0.01), but this baseline difference in memory performance was no longer significant post exercise, between groups at follow-up (68.4 ± 2.66 vs. 67.4 ± 2.72, p < 0.08). Conclusions: Our results suggest that both a virtual reality protocol and a nature walk can have positive outcomes on memory and executive function in younger adults.
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 | 0.002 | 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 | 0.001 | 0.001 |
| 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".