The Influence of the Menstrual Cycle on Electrical Thresholds for Sensory and Pain Perception: Implications for Exercise and Rehabilitation in Women With and Without Primary Dysmenorrhea—A Pilot Study
Bibliographic record
Abstract
Background: Hormonal fluctuations during the menstrual cycle (MC) influence pain perception, potentially affecting exercise performance and rehabilitation in women. This effect may be more pronounced in individuals with primary dysmenorrhea (PD), requiring tailored physiotherapeutic and exercise interventions. Objective: To analyze the influence of MC phases on sensory electrical threshold (SET) and pain electrical threshold (PET) in eumenorrheic women with and without PD, considering the potential implications for physical activity and rehabilitation. Methods: An observational longitudinal study was conducted with 34 physically active women, divided into a control group (CG) and a PD group. SET and PET were measured using transcutaneous electrical nerve stimulation (TENS) at the forearm (peripheral site) and lower abdomen (pain-referred site) across five MC phases. Pain intensity was assessed using a Visual Analog Scale (VAS). Results: SET and PET were significantly lower in the premenstrual phase (p < 0.001), suggesting increased pain sensitivity. VAS scores were higher in the PD group during all phases, except for the follicular phase (p < 0.033), with the highest pain levels recorded in the menstrual and premenstrual phases. While no significant differences in SET and PET were found between groups across most phases, the PD group exhibited a significantly higher SET in the forearm during the premenstrual phase (p = 0.005), potentially indicating altered central pain modulation. Conclusions: MC-related hormonal fluctuations affect pain sensitivity, particularly in women with PD. These findings underscore the need for phase-specific exercise adaptations and rehabilitation strategies to improve performance, pain management, and recovery in physically active women.
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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 | 0.001 | 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".