The Correlation between Menstrual Symptoms and College Academic Activities [University of West Florida]

Abstract

Sleep and the menstrual cycle are greatly intertwined, Both sleep and menstruation can affect each other: sleep quality can be related to the regularity and symptoms of the menstrual cycle. Women have poorer sleep quality during menstruation, including difficulties in falling asleep and maintaining sleep. Few studies have looked directly at the correlation between menstrual symptoms, sleep quality, stress, and college academic activities. The purpose of this study is to determine whether there is a correlation between female students’ menstrual cycle symptoms, stress levels, sleep quality, and academic activities. We are also investigating whether the students compensate for the negative effects of menstruation, how they compensate, and how much they compensate. For example, “Do you compensate for sub-optimal conditions caused by your menstrual symptoms and their severity? If yes, how so?” A preliminary survey will be given to qualify participants for the longitudinal study. Data for this longitudinal study will be gathered through a daily self-reported survey with semi-structured Likert-scale and open-ended questions, about severity of menstrual symptoms; sleep quality, study habits, stress levels, and academic activities both during and not during menstruation. In order to avoid recall error and ensure consistency, we will conduct a naturalistic observational and longitudinal study wherein participants will answer questions nightly over the course of two months. A regression statistical analysis will be conducted. To compare performance and academic habits, participants will be separated into three academic groups according to GPA: 2.5-2.9, 3.0-3.4, and 3.5+. We expect to find that, during menstruation, relative to non-menstruation, participants experience higher stress levels, poorer sleep quality, a difference in academic activities, and compensation for deficiencies, with students with higher GPAs having higher rates of compensation. Data collection will be conducted in March and data analysis will be completed by April 2019.