Virtual Reality Exposure Training for Musicians: Its Effect on Performance Anxiety and Quality
Bibliographic record
Abstract
Music performance anxiety affects numerous musicians, with many of them reporting impairment of performance due to this problem. This exploratory study investigated the effects of virtual reality exposure training on students with music performance anxiety. Seventeen music students were randomly assigned to a control group (n=8) or a virtual training group (n=9). Participants were asked to play a musical piece by memory in two separate recitals within a 3-week interval. Anxiety was then measured with the Personal Report of Confidence as a Performer Scale and the S-Anxiety scale from the State-Trait Anxiety Inventory (STAI-Y). Between pre- and post-tests, the virtual training group took part in virtual reality exposure training consisting of six 1-hour long sessions of virtual exposure. The results indicate a significant decrease in performance anxiety for musicians in the treatment group for those with a high level of state anxiety, for those with a high level of trait anxiety, for women, and for musicians with high immersive tendencies. Finally, between the pre- and post-tests, we observed a significant increase in performance quality for the experimental group, but not for the control group.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| 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) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".