Premenstrual Syndrome and Its Impact on the Quality of Life of Female Medical Students at Bisha University, Saudi Arabia
Bibliographic record
Abstract
Objective: The severity and chronicity of PMS can lead to the impairment of studies, and it can also affect relationships, activities, quality of life (QoL), and academic performance. This study aimed to determine PMS frequency and its associated factors in order to assess the quality of life (QoL) among female medical students at Bisha University, Saudi Arabia. Methods: This study was cross-sectional and included 388 female medical students in the Faculty of Medical Applied Sciences and the Faculty of Medicine at Bisha University. The participants all filled in a self-administered questionnaire. The Premenstrual Syndrome Scale (PSS) was used based on the diagnostic and statistical criteria for PMS assessment. PMS was diagnosed after the presence of five or more severe premenstrual symptoms had been resolved following menstruation (adapted from American Psychiatric Association). Data Analysis: The data obtained were analyzed using SPSS 25.0. A chi-square test was used to test the associations between the study variables. A logistic regression analysis technique was used to select the group of variables. Participants were asked to provide consent to participate in the study. IRB was obtained from the University of Bisha, College of Medicine. Results: The participants were aged 19.5 ± 4.9 years, and the prevalence of PMS was 64.9%. Most of the female students were of extroverted personality types (35%). In addition, 13.4% were obese or overweight, and 19.5% of the 50% with PMS exercised regularly ( p < 0.05). Menstruation significantly influenced the related quality of life subscales ( p < 0.05). Conclusion: PMS significantly influenced daily activities related to quality of life and homework. Moreover, almost half of the female students experienced the effects of menstruation in their learning environment. Therefore, among female students, the modification of risk factors should be considered a critical intervention point. Keywords: PMS, medical students, quality of life, University of Bisha, Saudi Arabia
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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 | 0.000 | 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".