Effect of individual counseling on pain quality in the women with cyclic mastalgia: a clinical trial
Bibliographic record
Abstract
Background: Despite the high prevalence of cyclic mastalgia and disagreement about its therapeutic methods, there is a lot of ambiguity about breast pain yet.Objective: This study aimed to investigate the effect of individual counseling on the quality of pain in the women with cyclic mastalgia.Methods: This randomized-controlled trial study was conducted in 2017 on eighty eligible women with cyclic mastalgia that had referred to Health Centers in Karaj, Iran.The subjects were randomly assigned to two groups; intervention and control.Four individual counseling sessions were held for intervention group.With a special visual analog scale for pain and Cardiff's breast pain chart, cyclic mastalgia was diagnosed.Pain was assessed before and after consultation with McGill pain quality questionnaire.T-test and ANCOVA were used to examine the means of pain quality before and after the intervention.Findings: Demographic results including, marital status, educational level, occupation, spouse's education and the husband's job were not significant.Also, the history of lactation, surgery, breast sampling, benign breast disease, nipple discharge and breast injury were no significant between two groups as the chi-square test.But, after the intervention, the McGill mean score test in all of pain dimensions showed a significant difference between two groups (P= 0.001).Conclusion: This study showed that counseling can lead improvement of pain quality indices in affecting women.As the result, counseling can be suggested as a suitable treatment for mild to moderate pain.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 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".