The effect of psychoeducation on anxiety and pain in patients with mastalgia
Bibliographic record
Abstract
BACKGROUND: Mastalgia is a debilitating disorder, which has serious effects on one's daily life and causes significant medical costs. AIM: Mastalgia patients determine the overall approach and improve the quality of life of patients. METHODS: In this study, the outcomes of psychoeducation on anxiety and pain in a group of patients with mastalgia without an organic etiology have been investigated. 88 patients were included in this study. The socio-demographic data form, the Symptom Checklist 90 (SCL-90), the Toronto Alexithymia Scale-20 (TAS-20), the Hamilton Anxiety Scorer (HAM-A), the State-Trait Anxiety Inventory (STAI-I, STAI-2) and the Visual Analogue Scale (VAS) were all applied to the patients. 64 randomly selected patients (Group 1) were given psychoeducation while the remaining 24 (Group 2) were not. All patients were called back after 1 month for repeats of the HAM-A, STAI-I, STAI-2 and VAS tests. RESULTS: The results of this study demonstrated that psychoeducation has positive impacts on the perception of pain besides stationary, contemporary and total anxiety scores. CONCLUSIONS: It is concluded that the administration of psychoeducation is a good choice in the degradation of anxiety symptoms and pain.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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".