DOES MUSIC ALTER PERFORMANCE AND CHANGE PERCEPTION OF EFFORT DURING EXERCISE?
Bibliographic record
Abstract
Listening to music during exercise can produce ergogenic effects. Some studies have reported improved motor performance and increased aerobic endurance. Music can also enhance the exercise experience. One can attribute the psychophysical benefits of music during exercise to a narrowed attention and decreased awareness of internal cues of fatigue. This narrowed attention could lead to lower ratings of perceived exertion. Perception of effort could play a key role in performance or in adherence to a training program. PURPOSE To investigate the role of music on physiological and biomechanical variables and perception of effort in females running at submaximal and maximal intensities on a treadmill. METHODS 9 active females were recruited (22.1±2.4 years; mean±SD). For each participant, pre-tests consisted of anthropometric measures and measurement of VO2peak using the Bruce treadmill protocol (62.5±5.0 kg, 47.9±4.8 ml/kg/min). In a repeated measures counter balanced design, subjects were then assigned to each of the two test conditions: 1) control (no music); 2) music (continuous, 150 beats per minute). Ventilation, oxygen consumption, respiratory exchange ratio, heart rate, blood glucose, blood lactate, stride length, stride frequency and perceived exertion were measured during a 6 min submaximal running test and during a subsequent run to exhaustion. RESULTS Submaximal performance, physiological, biomechanical and psychological variables were not affected by music. However, time to exhaustion was significantly longer in the music condition. Furthermore, during maximal effort, stride length increased while stride frequency decreased with music, thus improving running economy. Respiratory exchange ratio was lower during the music condition. Ratings of perceived exertion were also significantly lower at the end of the run during the music condition. CONCLUSION These data suggest that music can have positive effects on physiological, psychological and biomechanical variables during vigorous exercise in young women. Supported by the Nova Scotia Health Research Foundation and the AUFA25.55 fund.
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.
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 | 0.001 | 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".