Academic and Social Impact of Menstrual Disturbances in Female Medical Students: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
BACKGROUND: The stressful academic schedule of medical students poses an obvious challenge to their daily lifestyle. Psychosomatic discomfort poses a significant risk for inaccurate self-medication for ameliorating menstrual complications and feeling better, thus directly impacting personal and academic wellbeing. OBJECTIVE: The impact of menstrual disturbances on academic life is not extensively explored. Therefore, the primary objective of this research was to probe the prevalence of menstrual disturbances and assess the academic and social impact. Finally, the authors provide an overview of pharmacological and other interventions students adopt to reduce clinical symptoms. METHODS: A database search was conducted from the year 2016 till September 2021 for the studies reporting the prevalence of menstrual disorders in all geographic locations of the world. Keywords used for searching databases included "menstrual disturbances" and "medical students," "prevalence" OR "symptoms" of "Premenstrual syndrome" OR "Premenstrual dysphoric disorder" OR "Dysmenorrhea" in medical students. Prospero Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) and Meta-Analysis of Observational Studies in Epidemiology (MOOSE) protocols were followed. The protocol was registered in the International prospective register of systematic reviews (PROSPERO), the Center for Reviews and Dissemination, University of York (CRD42021277962). The quality of the methodologies used in selected studies was evaluated by a modified version of Newcastle Ottawa Scale (NOS). RESULTS: Initially, 1527 articles were available. After a review, 26 papers were selected for analysis. A total of 25 citations were identified for quantitative analyses, out of which 16 studies reported Pre-menstrual syndrome, 7 reported Pre-menstrual dysphoric disorder, and 13 articles reported dysmenorrhea. The pooled prevalence of Pre-menstrual syndrome was 51.30%, Pre-menstrual dysphoric disorder was 17.7%, and dysmenorrhea was 72.70%. Most common associated lifestyle factors were stress, excessive caffeine intake and lack of exercise. Painkillers, hot packs and hot beverages were amongst the common measures taken by the students to relieve their symptoms. CONCLUSIONS: The current situation calls for action to accommodate students' needs and bridge the social gap regarding menstrual health. Proactive measures by medical educators and stakeholders are required for an inclusive, accommodating educational environment which will minimize the gender discrepancy in academic satisfaction and professional life.
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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 | 0.011 | 0.029 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.015 | 0.030 |
| Bibliometrics | 0.008 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".