A study of cognitive function, quality of sleep, and Stroop effect among adolescent girls with premenstrual syndrome
Bibliographic record
Abstract
Background: Premenstrual syndrome (PMS) involves various somatic and psychological symptoms related to the luteal phase of the menstrual cycle, ranging from mild discomfort to disability and impacting daily life. Objective: To compare cognitive function, sleep quality, and the Stroop effect between adolescent girls with PMS and healthy controls. Materials and Methods: This cross-sectional study included 60 adolescent girls (30 with PMS and 30 controls) at the Department of Physiology, Government Thiruvarur Medical College. The participants were selected using the Premenstrual Symptoms Screening Tool (PSST). Cognitive function was assessed using the Montreal Cognitive Assessment (MoCA), sleep quality using the Pittsburgh Sleep Quality Index (PSQI), and attention processing using the Stroop effect. Measurements were taken three days before menstruation. Results: The mean age was similar in both groups (PMS: 18.97 ± 0.81; controls: 18.93 ± 0.78). MoCA scores were significantly lower in the PMS group (23.9 ± 2.97) than the controls (25.93 ± 1.76, P < 0.05). PSQI scores were higher in the PMS group (6.67 ± 1.65 vs. 5.3 ± 1.3, P < 0.05), indicating poorer sleep quality. The Stroop effect duration was significantly shorter in the PMS group (48.67 ± 15.18) than in controls (66.7 ± 19.13, P < 0.05). Conclusion: PMS significantly impairs cognitive function, sleep quality, and Stroop task performance in adolescent girls. Early recognition and intervention are crucial to mitigate these impacts on academic and daily activities.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".