Pre and Post Menstruation Cognitive Functioning in Women with Premenstrual Dysphoric Disorder, Premenstrual Syndrome and Controls: A Quasi Experimental Study
Bibliographic record
Abstract
BACKGROUND: Inconsistent findings regarding the cognitive impact of Premenstrual Syndrome (PMS) and Premenstrual Dysphoric Disorder (PMDD) limit understanding of their effects on women's daily lives. These inconsistencies may arise from neglecting menstrual phase in cognitive assessments. Considering the significant impact of PMS/PMDD on work, academics, and relationships, clarifying their cognitive effects is essential for targeted interventions and improved quality of life. This study investigates the cognitive impacts of these conditions, focusing on the influence of menstrual phase. METHODS: Using a Google Form for initial data collection, 60 participants (mean age 24.47) were categorized into Control, PMS, and PMDD groups based on their responses. Cognitive performance was gauged using the Montreal Cognitive Assessment (MoCA), administered during two distinct menstrual phases: luteal and follicular. RESULTS: Key findings revealed pronounced cognitive differences across these phases, with the most significant disparities observed in the PMDD group, suggesting a gradient effect where PMDD individuals exhibited the most considerable cognitive shifts (p < .001, η²p = .25). The study's overarching results highlighted a significant divergence in cognitive functioning during the luteal phase, a time historically linked with heightened symptomology in women with PMS and PMDD. Notably, specific cognitive functions, especially language (p < .000) and abstraction (p < .001), showed significant improvement during the follicular phase across all groups (η²p = .25) - a novel finding not assessed in earlier studies. CONCLUSIONS: This study reveals significant cognitive fluctuations across the menstrual cycle, particularly in women with PMDD, and novel improvements in language and abstraction during the follicular phase. Despite limitations, these findings emphasize the importance of considering menstrual phase in assessing and treating women with PMS/PMDD. Further rigorous research is needed to elucidate the neural mechanisms driving these cognitive changes, enabling targeted interventions to improve well-being and functional capacity. The research had its limitations, including a limited sample size, the non-random nature of the sampling method, and potential issues with the tools used for assessments. Despite these constraints, the study provides a foundation for future research, emphasizing the need for a deeper understanding of the neural mechanisms influenced by menstrual phases and offering insights to better support affected women.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".