Mental imagery and musical performance: Development of the Musician’s Arousal Regulation Imagery Scale
Bibliographic record
Abstract
Arousal imagery has been used to help performers regulate performance anxiety in order to perform well. Music performance anxiety research has been dominated by relaxation imagery and despite positive results, methodological limitations prevent causal conclusions regarding its efficacy. Further, arousal imagery strategies incorporating high arousal have helped performers in closely related performance domains, and these strategies might benefit musicians. In addition, emotion regulation models raise concerns about the efficacy of relaxation imagery. In light of these issues, understanding whether and how musicians use arousal imagery in their own practice is an important, yet understudied area. Building on earlier work, we developed the Musician’s Arousal Regulation Imagery Scale (MARIS) to measure musicians’ intentional use of different arousal imagery strategies in three samples of musicians with varying levels of expertise, who reported performing different musical genres and instruments from different musical families. Participants completed the MARIS and a musical background questionnaire. Results suggest that the MARIS has excellent psychometric properties and that it captures two broad classes of arousal imagery. Further, findings suggest that musicians use arousal imagery containing varying levels of arousal. Implications of the present study, limitations, and suggestions for future research are discussed.
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How this classification was reachedexpand
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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 teacher head, 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".