Examining the Effects of an Interspersed Biofeedback Training Intervention on Physiological Indices
Bibliographic record
Abstract
The study aimed to determine whether athletes who practice biofeedback are able to self-regulate by reaching resonance frequency and gaining physiological control quicker than if practice time integrates imagery or a rest period. Intervention effectiveness (e.g., intervention length, time spent training) was also explored. Twenty-seven university athletes were assigned to one of three groups: (a) biofeedback (i.e., continuous training), (b) biofeedback/imagery (i.e., interspersed with imagery), and (c) biofeedback/rest (i.e., interspersed with a rest period). Five biofeedback sessions training respiration rate, heart rate variability, and skin conductance were conducted. A repeated-measure analysis of variance showed a significant interaction between groups over time ( p ≤ .05) for respiration rate, heart rate variability, and skin conductance, indicating that resonance frequency and physiological control was regained following imagery or a rest period. Postmanipulation check data found intervention length and training time to be sufficient. Combining imagery with biofeedback may optimize management of psychophysiological processes.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".