Effects of Heat Treatment On Dysmenorrhea and Its Mental Health Outcomes: A Randomized Clinical Trial
Bibliographic record
Abstract
This randomized controlled prospective experimental trial was conducted with 46 students with dysmenorrhea who were randomized in a 1:1 ratio to the heat treatment group (HTG) ( n = 23) and control group (CG) ( n = 23). To HTG, dry heat was applied for 20 minutes to the lower abdominal region of the subjects when their dysmenorrhea was most severe. Visual Analogue Scale (VAS), the Short Form McGill Pain Questionnaire (SF-MPQ), the Menstrual Attitude Questionnaire (MAQ), and the Depression Anxiety and Stress Scale (DASS) were used in this study. At the first menstrual cycle, both groups received the questionnaires, and no treatment was applied. At the second, third, and fourth menstrual cycles, VAS and SF-MPQ were applied before the treatment (T1), right after the treatment (T2), and 2 hours after the treatment (T3). MAQ and DASS were applied right after the treatment. Seven subjects from HTG and four subjects from CG were excluded from the study on account of their analgesic medicine usage, inability to menstruate, or by their own requests. When HTG and CG were compared, the decrease in the dysmenorrhea pain after the heat treatment in each of the three menstrual cycles was found to be statistically significant ( P < 0.05). In each of the four menstrual cycles, depression, anxiety, and stress were detected in each subject in both groups. However, the effectiveness of the treatment was not determined ( P > 0.05). In HTG, awareness of the changes during menstruation was diminished with time. [ Psychiatr Ann . 2023;53(6):270–281.]
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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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".