Experiencing Immersive Virtual Nature for Well-Being, Restoration, Performance, and Nature Connectedness: A Scoping Review
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.
Bibliographic record
Abstract
This paper presents a scoping review of immersive virtual nature experiences delivered via head-mounted displays (HMDs) and their role in promoting well-being, psychological restoration, cognitive performance, and nature connectedness. As access to natural environments becomes increasingly constrained by urbanization, technological lifestyles, and environmental change, immersive technologies offer a scalable and accessible alternative for engaging with nature. Guided by three core research questions, this review explores how HMD-mediated immersive technologies have been used to promote nature connectedness and well-being, what trends and outcomes have been observed across applications, and what methodological gaps or limitations exist in this growing body of work. Fifty-five peer-reviewed studies were analyzed and categorized into six key implication areas: emotional well-being, stress reduction, cognitive performance, attention recovery, restorative benefits, and nature connectedness. The review identifies immersive virtual nature as a promising application of extended reality (XR) technologies, with potential across healthcare, education, and daily life, while also emphasizing the need for more consistent methodologies and long-term research.
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 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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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 it