Physical activity level in women with primary dysmenorrhea: A cross-sectional observational study
Bibliographic record
Abstract
BACKGROUND: Primary dysmenorrhea (PD), menstrual pain in the absence of pathology, is the main cause of gynecological consultation in young women. There are many studies that suggest a possible relationship between a low level of physical activity (PA) and a greater intensity of menstrual pain, and others that find no relationship between these variables. OBJECTIVES: To identify the level of PA and menstrual pain intensity among women with PD, as well as the relationship between these variables. DESIGN: An observational, cross-sectional study was carried out on a cohort of adult population. METHODS: Data collection instrument was an online self-administered questionnaire. Main variables were pain intensity (Numeric Rating Scale; McGill Pain Questionnaire, short version) and PA level (International Physical Activity Questionnaire). RESULTS: A total number of 216 responses from the total responses obtained were considered PD cases. A 38% of women did not perform any intense PA during the last 7 days, and a 32.4% did not perform any moderate PA. No significant differences were found in menstrual pain intensity during the three last menstruations among women who performed PA, moderate, or intense. Nor were significant differences found between women who performed PA less than 3 days a week, compared with those ones who did it at least three times a week, or more. CONCLUSION: Menstrual pain intensity does not differ between the types of PA. A large number of participants did not perform any PA in the last 7 days.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".