Anxiety Increases the Feeling of Presence in Virtual Reality
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
Given previous studies indicating a significant correlation between anxiety and presence, the purpose of this investigation was to explore the direction of the causal relationship between them. The sample consisted of 31 adults suffering from snake phobia. The study featured a randomized within-between design with two conditions and three counterbalanced immersions: (a) a baseline control immersion (BASELINE), (b) an immersion in a threatening and anxiety-inducing environment (ANX), and (c) an immersion in a nonthreatening environment that should not induce anxiety (NOANX). In the NOANX environment, participants were immersed for 5 min in a virtual Egyptian desert. They were told that the environment was safe and contained no snakes. The ANX immersion was identical, except that participants were led to believe that a multitude of hidden and dangerous snakes were lurking in the environment. A period of distraction (reading a text on relaxation) separated the ANX and NOANX immersions. Experimenters recorded presence and anxiety in the middle of and after each VR immersion. These brief measures of presence supported our hypothesis and were significantly higher in the anxious immersion than in the baseline or the nonanxious immersion. This finding was not corroborated by the presence questionnaire, where scores varied significantly in the opposite direction. The results from the brief one-item measures of presence support the significant contribution of emotions felt during the immersion on the subjective feeling of presence. The mixed results with the presence questionnaire are discussed, along with psychological factors potentially involved in presence.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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 it