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Record W2471797326 · doi:10.21091/mppa.2015.3032

Virtual Reality Exposure Training for Musicians: Its Effect on Performance Anxiety and Quality

2015· article· en· W2471797326 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueMedical Problems of Performing Artists · 2015
Typearticle
Languageen
FieldArts and Humanities
TopicDiverse Music Education Insights
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsAnxietyPsychologyTrait anxietyVirtual realityClinical psychologyApplied psychologyAudiologyMedicinePsychiatryComputer science

Abstract

fetched live from OpenAlex

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.

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 imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.905
Threshold uncertainty score0.606

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
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 integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.141
GPT teacher head0.308
Teacher spread0.168 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it