Measured Emotion and Exercise
Bibliographic record
Abstract
The Borg Scale of ratings of perceived exertion (RPE) is widely used to determine subjective exercise difficulty. However, RPE does not indicate emotional state of exercising humans. Consequently, the Self-Assessment Mannikin (SAM) of emotional states was used in conjunction with the Borg Scale to determine valence, arousal and dominance feelings during exercise of 3 different intensities in men and women. PURPOSE: To determine human emotional responses to exercise at various intensities. METHODS: Participants (n=28; female =18, male = 10) reported SAM and RPE prior to and at 17.5 minutes during steady state cycle ergometer exercise designed to elicit 40% (LOW), 60% (MOD), or 80% (HIGH) of maximal oxygen consumption. Data were analyzed using a 2 factor (3: intensity x 2: sex) repeated measures ANOVA and presented as mean (SD). RESULTS: RPE was significantly greater at each exercise intensity (9.2 (1.9), 11.3 (2.0) vs 13.9 (1.8) for the LOW, MOD and HIGH intensities, respectively; p<0.001). In each of the dimensions of emotion as measured by the SAM, there was a significant main effect for intensity such that participants in the HIGH intensity group reported significantly less positive scores than participants in the LOW and MOD intensity groups during exercise. Sam results are as follows: valence (1 = pleasant, 9 = unpleasant) mean ratings were 3.9 (0.8) for HIGH versus 2.7 (1.0) and 2.9 (1.1) for LOW and MOD, respectively (p<0.001); arousal (1 = excited, 9 = calm) mean ratings were 5.1 (0.7) for HIGH versus 6.8 (0.7) and 6.1 (0.8) for LOW and MOD, respectively (p<0.001); dominance (1 = dominated, 9 = dominant) mean ratings were 5.3 (0.9) for HIGH versus 6.4 (1.4) and 6.6 (1.0) for LOW and MOD, respectively (p<0.05). There was no significant effect of sex. CONCLUSION: At the highest intensity, participants reported significantly different emotional states as measured by SAM. These observations have implications for exercise prescription, adherence and mood.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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".