Association between premenstrual syndrome and alexithymia among Turkish University students
Bibliographic record
Abstract
Premenstrual syndrome (PMS) is a heterogeneous disorder, which includes physical, cognitive, affective and behavioral symptoms. The aim of this study was to determine the factors affecting PMS and the relationship between PMS and alexithymia. The research was performed with 308 students. Data were collected using a demographic questionnaire, the Toronto alexithymia scale (TAS-20) and a premenstrual assessment form (PAF). The prevalence of PMS in our sample was 66.6%. The contributing factors to PMS were having a history of psychiatric treatment and having a smoking habit (p < 0.05). The PMS group showed higher scores than the non-PMS group on all the items of the TAS-20 which includes the three factors: difficulty in identifying feelings, difficulty in describing feelings and externally oriented thinking (p < 0.05). The alexithymic students showed higher scores on all PAF subscales (p ≤ 0.001). Further studies are needed to determine the probable role of alexithymia in the pathogenesis of PMS.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".