Discomfort Responses To Repeated Bouts Of Isometric Handgrip Exercise With And Without Blood Flow Restriction
Bibliographic record
Abstract
Subjective perceptions influence the participant's attitude towards training and, ultimately, affect motivation and adherence. PURPOSE: To examine perceptions of blood flow restricted (BFR) exercise and determine if it differs from exercise performed without BFR. METHODS: 135 participants (18-35 yrs) were randomly assigned to one of three training conditions: (1) low-intensity (LI, n = 47); (2) high-intensity (HI, n = 47) or (3) low-intensity with BFR (LI-BFR, n = 41). All groups completed 18 training sessions across 6 weeks. LI and LI-BFR training consisted of 4 sets of two-minute isometric handgrip exercise at 30% of their max. In the LI-BFR training group, a cuff was inflated to 50% of the participant's arterial occlusion pressure. The HI group performed 4 sets of max contractions. Participants gave their discomfort ratings (0-10+ scale) at first, mid and final training session. Bayesian repeated measures ANOVA was used to analyze between-group changes in discomfort ratings. A 4 contingency table tested whether participants would continue with the same type of exercise they had been doing or switch if training continued. Results are presented as means (SD). RESULTS: Discomfort changed differently (Group*Time: BF10: 11378). From the first to mid-session, both the LI [-1.2 (1.8) units] and LI-BFR [-0.7 (1.5) units] groups saw greater reductions in their rating of discomfort compared to the HI group [0.2 (1.5) units]. From the first session to the final session both the LI [-1.7 (1.7) units] and LI-BFR [-1.5 (1.9) units] groups saw greater reductions in discomfort compared to the HI group [0.04 (1.5) units]. There were no differences between mid-final session (BF10: 0.25). There were also main effects of group and time. The LI (~5 units) and LI-BFR (~5.1 units) group had greater discomfort than the HI group (~2.8 units). Discomfort also decreased across time (First > Mid > Final). When asked if they would continue the type of training if it were to be shown to benefit health, 66%, 68%, and 80% of those in the LI, LI-BFR, and HI groups, respectively said they would (no difference between groups: BF10: 0.2). CONCLUSION: Although HI training had the lowest discomfort throughout, the willingness to continue the current form of training in the future was not different. Discomfort may not be the sole factor used for exercise selection.
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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 | 0.002 |
| 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) | 0.002 | 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".