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Restorative Effects of Virtual Nature Settings

2010· article· en· 354 citations· W2087865581 on OpenAlex· 10.1089/cyber.2009.0308

Why is this work in the frame?

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

Canadian affiliationAn author listed a Canadian institution. This is the only route the usual frame has.

Full frame distilled prediction

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.

Candidate categories
none
Consensus categories
none
Domain
Candidate signal: noneConsensus signal: none
Study design
Candidate signal: ObservationalConsensus signal: Observational
Genre
Candidate signal: EmpiricalConsensus signal: Empirical
Teacher disagreement score
0.077
Threshold uncertainty score
0.472
Validation status
machine_predicted_unvalidated · codex-gemma-dda1882f352a

Codex and Gemma teacher scores by category

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

Machine scores (provisional)

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

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.

Opus teacher head0.007
GPT teacher head0.284
Teacher spread
0.277 · how far apart the two teachers sit on this one work
Validation status
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

Abstract

Previous research regarding the potential benefits of exposing individuals to surrogate nature (photographs and videos) has found that such immersion results in restorative effects such as increased positive affect, decreased negative affect, and decreased stress. In the current experiment, we examined whether immersion in a virtual computer-generated nature setting could produce restorative effects. Twenty-two participants were equally divided between two conditions, while controlling for gender. In each condition, participants performed a stress-induction task, and were then immersed in virtual reality (VR) for 10 minutes. The control condition featured a slide show in VR, and the nature experimental condition featured an active exploration of a virtual forest. Participants in the nature condition were found to exhibit increased positive affect and decreased stress after immersion in VR when compared to those in the control condition. The results suggest that immersion in virtual nature settings has similar beneficial effects as exposure to surrogate nature. These results also suggest that VR can be used as a tool to study and understand restorative effects.

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.

The record

Venue
Cyberpsychology Behavior and Social Networking
Topic
Urban Green Space and Health
Field
Environmental Science
Canadian institutions
University of Waterloo
Funders
not available
Keywords
Immersion (mathematics)Virtual realityAffect (linguistics)PsychologyVirtual machineSimulationSocial psychologyCognitive psychologyHuman–computer interactionComputer scienceMathematicsCommunication
Has abstract in OpenAlex
yes